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Supra-glacial deposition and flux of catastrophic rock-slope failure debris, south-central Alaska
(2013)
The ongoing debate over the effects of global environmental change on Earth's cryosphere calls for detailed knowledge about process rates and their variability in cold environments. In this context, appraisals of the coupling between glacier dynamics and para-glacial erosion rates in tectonically active mountains remain rare. We contribute to filling this knowledge gap and present an unprecedented regional-scale inventory of supra-glacial sediment flux and hillslope erosion rates inferred from an analysis of 123 large (> 0 center dot 1km2) catastrophic bedrock landslides that fell onto glaciers in the Chugach Mountains, Alaska, as documented by satellite images obtained between 1972 to 2008. Assuming these supra-glacial landslide deposits to be passive strain markers we infer minimum decadal-scale sediment yields of 190 to 7400tkm-2yr-1 for a given glacier-surface cross-section impacted by episodic rock-slope failure. These rates compare to reported fluvial sediment yields in many mountain rivers, but are an order of magnitude below the extreme sediment yields measured at the snouts of Alaskan glaciers, indicating that the bulk of debris discharged derives from en-glacial, sub-glacial or ice-proximal sources. We estimate an average minimum para-glacial erosion rate by large, episodic rock-slope failures at 0 center dot 5-0 center dot 7mmyr-1 in the Chugach Mountains over a 50-yr period, with earthquakes likely being responsible for up to 73% of this rate. Though ranking amongst the highest decadal landslide erosion rates for this size of study area worldwide, our inferred rates of hillslope erosion in the Chugach Mountains remain an order of magnitude below the pace of extremely rapid glacial sediment export and glacio-isostatic surface uplift previously reported from the region.
Spatial analysis of the impacts of the Chaiten volcano eruption (Chile) in three fluvial systems
(2016)
The eruption of the Chaiten volcano in May 2008 generated morphological and ecological disturbances in adjacent river basins, and the magnitude of these disturbances depended on the type of dominant volcanic process affecting each of them. The aim of this study is to analyse the morphological changes in different periods in river segments of the Blanco, El Amarillo and Rayas river basins located near the Chaiten volcano. These basins suffered disturbances of different intensity and spatial distribution caused by tephra fall, dome collapses and pyroclastic density currents that damaged hillslope forests, widened channels and destroyed island and floodplain vegetation. Changes continued to occur in the fluvial systems in the years following the eruption, as a consequence of the geomorphic processes indirectly induced by the eruption. Channel changes were analyzed by comparing remote images of pre and post eruption conditions. Two periods were considered: the first from 2008 to 2009-2010 associated with the explosive and effusive phases of the eruption and the second that correspond to the post-eruption stage from 2009-2010 to 2013. Following the first phases channel segments widened 91% (38 m/yr), 6% (7 m/yr) and 7% (22 m/yr) for Blanco, Rayas and El Amarillo Rivers, respectively, compared to pre-eruption condition. In the second period, channel segments additionally widened 42% (8 m/yr), 2% (2 m/yr) and 5% (4 m/yr) for Blanco, Rayas and El Amarillo Rivers, respectively. In the Blanco River 62 and 82% of the islands disappeared in the first and second period, respectively, which is 6-8 times higher than in the El Amarillo approximately twice the Rayas. Sinuosity increased after the eruption only in the Blanco River but the three study channels showed a high braiding intensity mainly during the first post-eruption period. The major disturbances occurred during the eruptive and effusive phases of Chaiten volcano, and the intensity of these disturbances reflects the magnitude of the dominant volcanic processes affecting each basin. Inputs of sediment from dome collapses and pyroclastic density currents and not ash fall seem to explain morphologic channel change magnitudes in the study segments. The resulting knowledge can facilitate land use planning and design of river restoration projects in areas affected by volcanic eruptions disturbances. (C) 2016 Elsevier Ltd. All rights reserved.
The 2008 eruption of Chaiten volcano in southern Chile severely impacted several densely forested river catchments by supplying excess pyroclastic sediment to the channel networks. Our aim is to substantiate whether and how channel geometry and forest stands changed in the Rayas River following the sudden input of pyroclastic sediment. We measured the resulting changes to channel geometry and riparian forest stands along 17.6 km of the impacted gravel-bed Rayas River (294 km(2)) from multiple high-resolution satellite images, aerial photographs, and fieldwork to quantify yield volume characteristics of the forest stands. Limited channel changes during the last 60 years before the eruption reflect a dynamic equilibrium condition of the river corridor, despite the high annual precipitation and the sediment supply from Chaiten and Michinmahuida volcanoes in the headwaters. Images taken in 1945, 2004, and 2005 show that total size of the vegetated channel islands nearly doubled between 1945 and 2004 and remained unchanged between 2004 and 2005. Pyroclastic sediment entering the Rayas River after the 2008 eruption caused only minor average channel widening (7%), but killed all island vegetation in the study reach. Substantial shifts in the size distribution of in-channel vegetation patches reflect losses in total island area of 46% from 2005 to 2009 and an additional 34% from 2009 to 2012. The estimated pulsed release of organic carbon into the channel, mainly in the form of large wood from obliterated island and floodplain forests, was 78-400 tC/km/y and surpasses most documented yields from small mountainous catchments with similar rainfall, forest cover, and disturbance history, while making up between 20% and 60% of the annual carbon burial rate of fluvial sediments in the northern Patagonian fjords. We conclude that the carbon footprint of the 2008 Chaiten eruption on the Rayas River was more significant than the measured geomorphic impacts on channel geometry for the first five years following disturbance. The modest post-eruptive geomorphic response in this river is a poor indicator of its biogeochemical response. (C) 2015 Elsevier B.V. All rights reserved.
Breakup Without Borders
(2019)
Relative plate motions during continental rifting result from the interplay of local with far-field forces. Here we study the dynamics of rifting and breakup using large-scale numerical simulations of mantle convection with self-consistent evolution of plate boundaries. We show that continental separation follows a characteristic evolution with four distinctive phases: (1) an initial slow rifting phase with low divergence velocities and maximum tensional stresses, (2) a synrift speed-up phase featuring an abrupt increase of extension rate with a simultaneous drop of tensional stress, (3) the breakup phase with inception of fast sea-floor spreading, and (4) a deceleration phase occurring in most but not all models where extensional velocities decrease. We find that the speed-up during rifting is compensated by subduction acceleration or subduction initiation even in distant localities. Our study illustrates new links between local rift dynamics, plate motions, and subduction kinematics during times of continental separation.
The Altiplano-Puna plateau, in Central Andes, is the second-largest continental plateau on Earth, extending between 22 degrees and 27 degrees S at an average altitude of 4400 m. The Puna plateau has been formed in consequence of the subduction of the oceanic Nazca Plate beneath the continental South American plate, which has an average crustal thickness of 50 km at this location. A large seismicity cluster, the Jujuy cluster, is observed at depth of 150-250 km beneath the central region of the Puna plateau. The cluster is seismically very active, with hundreds of earthquakes reported and a peak magnitude MW 6.6 on 25th August 2006. The cluster is situated in one of three band of intermediate-depth focus seismicity, which extend parallel to the trench roughly North to South. It has been hypothesized that the Jujuy cluster could be a seismic nest, a compact seismogenic region characterized by a high stationary activity relative to its surroundings. In this study, we collected more than 40 years of data from different catalogs and proof that the cluster meets the three conditions of a seismic nest. Compared to other known intermediate depth nests at Hindu Kush (Afganisthan) or Bucaramanga (Colombia), the Jujuy nest presents an outstanding seismicity rate, with more than 100 M4+ earthquakes per year. We additionally performed a detailed analysis of the rupture process of some of the largest earthquakes in the nest, by means of moment tensor inversion and directivity analysis. We focused on the time period 2017-2018, where the seismic monitoring was the most extended. Our results show that earthquakes in the nest take place within the eastward subducting oceanic plate, but rupture along sub-horizontal planes dipping westward. We suggest that seismicity at Jujuy nest is controlled by dehydration processes, which are also responsible for the generation of fluids ascending to the crust beneath the Puna volcanic region. We use the rupture plane and nest geometry to provide a constraint to maximal expected magnitude, which we estimate as MW -6.7.
Intraplate seismicity across the Cape Verde swell: A contribution from a temporary seismic network
(2014)
We present an analysis and characterization of the regional seismicity recorded by a temporary broadband seismic network deployed in the Cape Verde archipelago between November 2007 and September 2008.
The detection of earthquakes was based on spectrograms, allowing the discrimination from low-frequency volcanic signals, resulting in 358 events of which 265 were located, the magnitudes usually being smaller than 3. For the location, a new 1-D P-velocity model was derived for the region showing a crust consistent with an oceanic crustal structure. The seismicity is located mostly offshore the westernmost and geologically youngest areas of the archipelago, near the islands of Santo Antao and Sao Vicente in the NW and Brava and Fogo in the SW. The SW cluster has a lower occurrence rate and corresponds to seismicity concentrated mainly along an alignment between Brava and the Cadamosto seamount presenting normal faulting mechanisms. The existence of the NW cluster, located offshore SW of Santo Antao, was so far unknown and concentrates around a recently recognized submarine cone field; this cluster presents focal depths extending from the crust to the upper mantle and suggests volcanic unrest No evident temporal behaviour could be perceived, although the events tend to occur in bursts of activity lasting a few days. In this recording period, no significant activity was detected at Fogo volcano, the most active volcanic edifice in Cape Verde.
The seismicity characteristics point mainly to a volcanic origin. The correlation of the recorded seismicity with active volcanic structures agrees with the tendency for a westward migration of volcanic activity in the archipelago as indicated by the geologic record. (C) 2014 Elsevier B.V. All rights reserved.
Field investigations on the treatment of MTBE and benzene from contaminated groundwater in pilot or full-scale constructed wetlands are lacking hugely. The aim of this study was to develop a biological treatment technology that can be operated in an economic, reliable and robust mode over a long period of time. Two pilot-scale vertical-flow soil filter eco-technologies, a roughing filter (RF) and a polishing filter (PF) with plants (willows), were operated independently in a single-stage configuration and coupled together in a multi-stage (RF + PF) configuration to investigate the MTBE and benzene removal performances. Both filters were loaded with groundwater from a refinery site contaminated with MTBE and benzene as the main contaminants, with a mean concentration of 2970 +/- 816 and 13,966 +/- 1998 mu g L(-1), respectively. Four different hydraulic loading rates (HLRs) with a stepwise increment of 60, 120, 240 and 480 L m(-2) d(-1) were applied over a period of 388 days in the single-stage operation. At the highest HLR of 480 L m(-2)d(-1), the mean concentrations of MTBE and benzene were found to be 550 +/- 133 and 65 +/- 123 mu g L(-1) in the effluent of the RF. In the effluent of the PP system, respective mean MTBE and benzene concentrations of 49 +/- 77 and 0.5 +/- 0.2 mu g L(-1) were obtained, which were well below the relevant MTBE and benzene limit values of 200 and 1 mu g L-1 for drinking water quality. But a dynamic fluctuation in the effluent MTBE concentration showed a lack of stability in regards to the increase in the measured values by nearly 10%, which were higher than the limit value. Therefore, both (RF + PF) filters were combined in a multi-stage configuration and the combined system proved to be more stable and effective with a highly efficient reduction of the MTBE and benzene concentrations in the effluent. Nearly 70% of MTBE and 98% of benzene were eliminated from the influent groundwater by the first vertical filter (RF) and the remaining amount was almost completely diminished (similar to 100% reduction) after passing through the second filter (PF), with a mean MTBE and benzene concentration of 5 +/- 10 and 0.6 +/- 0.2 mu g L(-1) in the final effluent. The emission rate of volatile organic compounds mass into the air from the systems was less than 1% of the inflow mass loading rate. The results obtained in this study not only demonstrate the feasibility of vertical-flow soil filter systems for treating groundwater contaminated with MTBE and benzene, but can also be considered a major step forward towards their application under full-scale conditions for commercial purposes in the oil and gas industries.
Ostracodes (Ostracoda, Crustacea) are aquatic micro-crustaceans with a significant representation in the fossil record. If the environmental influence on the species composition of their communities is robustly quantified, past changes in ostracode communities reflected in fossil assemblages can be used for paleo-environmental reconstruction. We analyzed ostracode assemblages in recently deposited surface sediments from 56 lakes in western and central Mongolia, and simultaneously recorded local water chemistry and solute concentration in order to elucidate the distribution of individual ostracode species in relation to these broad environmental gradients. Multivariate analysis indicated that the species variation in ostracode assemblages could be mainly attributed to variations in percent calcium (%Ca) relative to total cation content, mean annual precipitation, calcium concentration, alkalinity, percent bicarbonate relative to total anion content, and mean July temperature. This matches well with the results of a similar analysis on presence/absence data of living ostracodes in nearshore samples, even though some differences exist between the faunal composition of both datasets. The documented response of ostracode species to environmental variation tracks the typical solute evolutionary pathway for surface waters in this region, characterized by calcite precipitation and consequent depletion in dissolved calcium. Hence, the best quantitative inference model (WA-PLS model with R-jack(2) = 0.70, RMSEP = 0.40) for paleolimnological application was obtained for %Ca. Comparison between this model and a specific conductance (SC) inference model based on the same dataset, and based on ostracode datasets from different regions, indicated that the %Ca inference model suffers less than the SC inference model from a step-change in reconstructed values. The statistical power of different inference models based on Mongolian ostracodes are variously affected by the common dominance of a single euryhaline species (Limnocythere inopinata), limited faunal turnover in the freshwater portion of the salinity gradient, and the bimodal frequency distribution of SC among regional lakes. The latter probably represents true scarcity of lakes with intermediate salinity rather than a biased representation in our dataset. In a broader context of ostracode ecology, and with respect to regional paleolimnological applications, we highlight the potential of fossil Mongolian ostracode assemblages to trace past hydrological shifts associated with changes in groundwater inflow.
Reconstructing rates and patterns of colluvial soil redistribution in agrarian (hummocky) landscapes
(2019)
Humans have triggered or accelerated erosion processes since prehistoric times through agricultural practices. Optically stimulated luminescence (OSL) is widely used to quantify phases and rates of the corresponding landscape change, by measuring the last moment of daylight exposure of sediments. However, natural and anthropogenic mixing processes, such as bioturbation and tillage, complicate the use of OSL as grains of different depositional ages become mixed, and grains become exposed to light even long after the depositional event of interest. Instead, OSL determines the stabilization age, indicating when sediments were buried below the active mixing zone. These stabilization ages can cause systematic underestimation when calculating deposition rates. Our focus is on colluvial deposition in a kettle hole in the Uckermark region, northeastern Germany. We took 32 samples from five locations in the colluvium filling the kettle hole to study both spatial and temporal patterns in colluviation. We combined OSL dating with advanced age modelling to determine the stabilization age of colluvial sediments. These ages were combined with an archaeological reconstruction of historical ploughing depths to derive the levels of the soil surface at the moment of stabilization; the deposition depths, which were then used to calculate unbiased deposition rates. We identified two phases of colluvial deposition. The oldest deposits (similar to 5 ka) were located at the fringe of the kettle hole and accumulated relatively slowly, whereas the youngest deposits (<0.3 ka) rapidly filled the central kettle hole with rates of two orders of magnitude higher. We suggest that the latter phase is related to artificial drainage, facilitating accessibility in the central depression for agricultural practices. Our results show the need for numerical dating techniques that take archaeological and soil-geomorphological information into account to identify spatiotemporal patterns of landscape change, and to correctly interpret landscape dynamics in anthropogenically influenced hilly landscapes. (c) 2019 The Authors. Earth Surface Processes and Landforms Published by John Wiley & Sons Ltd.
The ability of water to transport and transform soil materials is one of the main drivers of soil and landscape development. In turn, soil and landscape properties determine how water is distributed in soil landscapes. Understanding the complex dynamics of this co-evolution of soils, landscapes and the hydrological system is fundamental in adapting land management to changes in climate. Soil-Landscape Evolution Models (SLEMs) are used to simulate the development and evolution of soils and landscapes. However, many hydrologic processes, such as preferential flow and subsurface lateral flow, are currently absent in these models. This limits the applicability of SLEMs to improve our understanding of feedbacks in the hydro-pedo-geomorphological system. Implementation of these hydrologic processes in SLEMs faces several complications related to calculation demands, limited methods for linking pedogenic and hydrologic processes, and limited data on quantification of changes in the hydrological system over time. In this contribution, we first briefly review processes and feedbacks in soil-landscape-hydrological systems. Next, we elaborate on the development required to include these processes in SLEMs. We discuss the state-of-the-art knowledge, identify complications, give partial solutions and suggest important future development. The main requirements for incorporating hydrologic processes in SLEMs are: (1) designing a model framework that can deal with varying timescales for different sets of processes, (2) developing and implementing methods for simulating pedogenesis as a function of water flow, (3) improving and implementing knowledge on the evolution and dynamics of soil hydraulic properties over different timescales, and (4) improving the database on temporal changes and dynamics of flow paths.
Erosion processes, aggravated by human activity, have a large impact on the spatial variation of soil and topographic properties. Knowledge of the topography prior to human-induced erosion (paleotopography) in naturally stable landscapes is valuable for identifying vulnerable landscape positions and is required as starting point for erosion modelling exercises. However, developing accurate reconstructions of paleotopography provide a major challenge for geomorphologists. Here, we present a set of paleotopographies for a closed kettle hole catchment in north-east Germany (4 ha), obtained through different reconstruction approaches. Current soil and colluvium thickness, estimated from a dataset of 264 soil descriptions using Ordinary Kriging, were used as input for a mass balance, or were compared with a set of undisturbed soil thicknesses to estimate the amount of erosion. The performance of the different approaches was assessed with cross-validation and the count of mispredicted eroded, depositional or stable landscape positions. The paleotopographic reconstruction approach based on the average thickness of undisturbed soils in the study area showed the best performance. This thickness (1.00 m) is comparable to the average undisturbed soil thickness in the region and in line with global correlations of soil thickness as a function of rainfall and initial CaCO3 content. The performance of the different approaches depended more on mispredictions of landscape position due to the assumption of a spatially constant initial soil depth than on small variations in this depth. To conclude, we mention several methodological and practical points of attention for future topography reconstruction studies, concerning data quality and availability, spatial configuration of data and other processes affecting topography. (C) 2017 Elsevier B.V. All rights reserved.
Anthropogenic climate change alters the hydrological cycle. While certain areas experience more intense precipitation events, others will experience droughts and increased evaporation, affecting water storage in long-term reservoirs, groundwater, snow, and glaciers. High elevation environments are especially vulnerable to climate change, which will impact the water supply for people living downstream. The Himalaya has been identified as a particularly vulnerable system, with nearly one billion people depending on the runoff in this system as their main water resource. As such, a more refined understanding of spatial and temporal changes in the water cycle in high altitude systems is essential to assess variations in water budgets under different climate change scenarios.
However, not only anthropogenic influences have an impact on the hydrological cycle, but changes to the hydrological cycle can occur over geological timescales, which are connected to the interplay between orogenic uplift and climate change. However, their temporal evolution and causes are often difficult to constrain. Using proxies that reflect hydrological changes with an increase in elevation, we can unravel the history of orogenic uplift in mountain ranges and its effect on the climate.
In this thesis, stable isotope ratios (expressed as δ2H and δ18O values) of meteoric waters and organic material are combined as tracers of atmospheric and hydrologic processes with remote sensing products to better understand water sources in the Himalayas. In addition, the record of modern climatological conditions based on the compound specific stable isotopes of leaf waxes (δ2Hwax) and brGDGTs (branched Glycerol dialkyl glycerol tetraethers) in modern soils in four Himalayan river catchments was assessed as proxies of the paleoclimate and (paleo-) elevation. Ultimately, hydrological variations over geological timescales were examined using δ13C and δ18O values of soil carbonates and bulk organic matter originating from sedimentological sections from the pre-Siwalik and Siwalik groups to track the response of vegetation and monsoon intensity and seasonality on a timescale of 20 Myr.
I find that Rayleigh distillation, with an ISM moisture source, mainly controls the isotopic composition of surface waters in the studied Himalayan catchments. An increase in d-excess in the spring, verified by remote sensing data products, shows the significant impact of runoff from snow-covered and glaciated areas on the surface water isotopic values in the timeseries.
In addition, I show that biomarker records such as brGDGTs and δ2Hwax have the potential to record (paleo-) elevation by yielding a significant correlation with the temperature and surface water δ2H values, respectively, as well as with elevation. Comparing the elevation inferred from both brGDGT and δ2Hwax, large differences were found in arid sections of the elevation transects due to an additional effect of evapotranspiration on δ2Hwax. A combined study of these proxies can improve paleoelevation estimates and provide recommendations based on the results found in this study.
Ultimately, I infer that the expansion of C4 vegetation between 20 and 1 Myr was not solely dependent on atmospheric pCO2, but also on regional changes in aridity and seasonality from to the stable isotopic signature of the two sedimentary sections in the Himalaya (east and west).
This thesis shows that the stable isotope chemistry of surface waters can be applied as a tool to monitor the changing Himalayan water budget under projected increasing temperatures. Minimizing the uncertainties associated with the paleo-elevation reconstructions were assessed by the combination of organic proxies (δ2Hwax and brGDGTs) in Himalayan soil. Stable isotope ratios in bulk soil and soil carbonates showed the evolution of vegetation influenced by the monsoon during the late Miocene, proving that these proxies can be used to record monsoon intensity, seasonality, and the response of vegetation. In conclusion, the use of organic proxies and stable isotope chemistry in the Himalayas has proven to successfully record changes in climate with increasing elevation. The combination of δ2Hwax and brGDGTs as a new proxy provides a more refined understanding of (paleo-)elevation and the influence of climate.
The SiDroForest (Siberian drone-mapped forest inventory) data collection is an attempt to remedy the scarcity of forest structure data in the circumboreal region by providing adjusted and labeled tree-level and vegetation plot-level data for machine learning and upscaling purposes. We present datasets of vegetation composition and tree and plot level forest structure for two important vegetation transition zones in Siberia, Russia; the summergreen-evergreen transition zone in Central Yakutia and the tundra-taiga transition zone in Chukotka (NE Siberia). The SiDroForest data collection consists of four datasets that contain different complementary data types that together support in-depth analyses from different perspectives of Siberian Forest plot data for multi-purpose applications. i. Dataset 1 provides unmanned aerial vehicle (UAV)-borne data products covering the vegetation plots surveyed during fieldwork (Kruse et al., 2021, ). The dataset includes structure-from-motion (SfM) point clouds and red-green-blue (RGB) and red-green-near-infrared (RGN) orthomosaics. From the orthomosaics, point-cloud products were created such as the digital elevation model (DEM), canopy height model (CHM), digital surface model (DSM) and the digital terrain model (DTM). The point-cloud products provide information on the three-dimensional (3D) structure of the forest at each plot. Dataset 2 contains spatial data in the form of point and polygon shapefiles of 872 individually labeled trees and shrubs that were recorded during fieldwork at the same vegetation plots (van Geffen et al., 2021c, ). The dataset contains information on tree height, crown diameter, and species type. These tree and shrub individually labeled point and polygon shapefiles were generated on top of the RGB UVA orthoimages. The individual tree information collected during the expedition such as tree height, crown diameter, and vitality are provided in table format. This dataset can be used to link individual information on trees to the location of the specific tree in the SfM point clouds, providing for example, opportunity to validate the extracted tree height from the first dataset. The dataset provides unique insights into the current state of individual trees and shrubs and allows for monitoring the effects of climate change on these individuals in the future. Dataset 3 contains a synthesis of 10 000 generated images and masks that have the tree crowns of two species of larch ( and ) automatically extracted from the RGB UAV images in the common objects in context (COCO) format (van Geffen et al., 2021a, ). As machine-learning algorithms need a large dataset to train on, the synthetic dataset was specifically created to be used for machine-learning algorithms to detect Siberian larch species. Larix gmeliniiLarix cajanderiDataset 4 contains Sentinel-2 (S-2) Level-2 bottom-of-atmosphere processed labeled image patches with seasonal information and annotated vegetation categories covering the vegetation plots (van Geffen et al., 2021b, ). The dataset is created with the aim of providing a small ready-to-use validation and training dataset to be used in various vegetation-related machine-learning tasks. It enhances the data collection as it allows classification of a larger area with the provided vegetation classes. The SiDroForest data collection serves a variety of user communities. <br /> The detailed vegetation cover and structure information in the first two datasets are of use for ecological applications, on one hand for summergreen and evergreen needle-leaf forests and also for tundra-taiga ecotones. Datasets 1 and 2 further support the generation and validation of land cover remote-sensing products in radar and optical remote sensing. In addition to providing information on forest structure and vegetation composition of the vegetation plots, the third and fourth datasets are prepared as training and validation data for machine-learning purposes. For example, the synthetic tree-crown dataset is generated from the raw UAV images and optimized to be used in neural networks. Furthermore, the fourth SiDroForest dataset contains S-2 labeled image patches processed to a high standard that provide training data on vegetation class categories for machine-learning classification with JavaScript Object Notation (JSON) labels provided. The SiDroForest data collection adds unique insights into remote hard-to-reach circumboreal forest regions.
Due to its high spatial and temporal variability, preferential flow is difficult to measure and quantify. Earthworms create macropores that provide common pathways for preferential flow. Therefore in this article, we link earthworm abundance to macropore numbers and hydrological effectiveness, with the future aim to use species distribution models of earthworms for the spatial parameterization of preferential flow.
Earthworms are generally categorized into three ecological types with varying burrowing behaviour, resulting in a different impact on soil hydrological processes. Therefore, we studied the relationships between the abundance of the earthworm ecological types and macropores of different size classes and in different soil depths. The abundance and biomass of earthworms were well correlated to different sizes of macropores in different soil depths. This is mainly the case for the larger, vertically oriented macropores (>6mm diameter), which are generally connected to the soil surface and hydrologically most effective. The correlation of total earthworm biomass and macropores ranges from 072 to 089 for different soil depths.
Although there is quite some variation in infiltration patterns, infiltration from macropores into the matrix is profile-specific, as it varies strongly between profiles, but not within one profile. Macropore coating seems to have a larger effect on this macropore matrix interaction than the soil physical properties of the matrix. Although the amount of macropores and their effectiveness are clearly related to the earthworm distribution, the variation in infiltration from macropores to soil matrix should be further studied.
Earthworms play a key role in regulating soil ecosystem functions and services. The small scale variability in earthworm abundance is often found to be very high, which is a problem for representative sampling of earthworm abundance at larger scales. In agricultural fields, soil tillage may influence both the average earthworm abundance as well as the spatial distribution of earthworms. Therefore we studied the abundance and spatial pattern of the different ecological earthworm types, i.e. endogeic, epigeic and anecic earthworms, in four agricultural fields differing in soil tillage (two fields with regular tillage and two fields with conservation tillage) and surrounding land use (other cropped fields or apple orchard and forest). To this aim we sampled earthworms on a total number of 430 plots (50 x 50 cm(2)) using a combination of extraction with mustard solution and hand sorting. The results exhibit large differences in average earthworm abundance between the four fields. Only one of the two fields with conservation tillage had a comparatively very high overall abundance of earthworms. Furthermore, we found a high spatial variability of earthworms within the field scale often exhibiting a patchy distribution. We detected a trend of decreasing earthworm abundances from the field border into the field for different earthworm groups on each of the fields. In three fields with low total earthworm abundance (and only very few epigeic earthworms) there was a short scale autocorrelation with ranges varying strongly for the endogeic earthworms (37.9 m, 62.6 m, and 85.2 m) compared to anecic earthworms (19.8 m, 22.8 m, and 27.4 m). In the field with high abundance, after trend removal, the variogram models for anecic and endogeic earthworms were rejected based on their negative explained variances. On this field, we found only a short scale autocorrelation for the epigeic earthworms with a range of 143 m. Based on these results it seems that ploughing alone cannot explain the differences in abundance and range of autocorrelation found on the four fields. The trend of strongly decreasing earthworm abundance from the field border into the field in the one field with high abundance does indicate that the field border or surrounding land use may also influence the recolonization of fields, but more research is required to provide further evidence for this hypothesis. Due to the very different patterns of earthworm distributions in the fields it remains difficult to recommend an optimal number and distance of samples to obtain a representative earthworm abundance for the field scale. (C) 2016 Elsevier B.V. All rights reserved.
Subsurface stormflow is thought to occur mainly in humid environments with steep terrains. However, in semi-arid areas, preferential flow through macropores can also result in a significant contribution of subsurface stormflow to catchment runoff for varying catchment conditions. Most hydrological models neglect this important subsurface preferential flow. Here, we use the process-oriented hydrological model Hillflow-3D, which includes a macropore flow approach, to simulate rainfall-runoff in the semi-arid Parapunos catchment in Spain, where macropore flow was observed in previous research. The model was extended for this study to account for sorptivity under very dry soil conditions. The results of the model simulations with and without macropore flow are compared. Both model versions give reasonable results for average rainfall situations, although the approach with the macropore concept provides slightly better results. The model results for scenarios of extreme rainfall events (>13.3mm30min(-1)) however show large differences between the versions with and without macropores. These model results compared with measured rainfall-runoff data show that the model with the macropore concept is better. Our conclusion is that preferential flow is important in controlling surface runoff in case of specific, high intensity rainfall events. Therefore, preferential flow processes must be included in hydrological models where we know that preferential flow occurs. Hydrological process models with a less detailed process description may fit observed average events reasonably well but can result in erroneous predictions for more extreme events. Copyright (c) 2013 John Wiley & Sons, Ltd.
The importance of cultural ecosystem services in agricultural landscapes is increasingly recognized as agricultural scale enlargement and abandonment affect aesthetic and recreational values of agricultural landscapes. Landscape preference studies addressing these type of values often yield context-specific outcomes, limiting the applicability of their outcomes in landscape policy. Our approach measures the relative importance of landscape features across agricultural landscapes. This approach was applied in the agricultural landscapes of Winterswijk, The Netherlands (n=191) and the Markische Schweiz, Germany (n=113) among visitors in the agricultural landscape. We set up a parallel designed choice experiment, using regionally specific, photorealistic visualizations of four comparable landscape attributes. In the Dutch landscape visitors highly value hedgerows and tree lines, whereas groups of trees and crop diversity are highly valued in the German landscape. Furthermore, we find that differences in relative preference for landscape attributes are, to some extent, explained by socio-cultural background variables such as education level and affinity with agriculture of the visitors. This approach contributes to a better understanding of the cross-regional variation of aesthetic and recreational values and how these values relate to characteristics of the agricultural landscape, which could support the integration of cultural services in landscape policy. (C) 2015 Elsevier B.V. All rights reserved.
Analysis of contemporary and past gully erosion and infilling processes allowed to reconstruct the long-term evolution of a permanent gully system under cropland. An active and a buried gully under cropland were investigated. The recent sediment deposits within the active gully, adjacent to the buried gully, showed that the recent gully was filling in at a mean rate of 6.4 cm a(-1). In the buried gully, several erosion and deposition phases could be identified and the type of deposited sediments revealed a complex infilling history. Charcoal, pottery and brick fragments of different sizes were found at all depths of the gully infilling. Their age indicates that the first gully incised after the midst of the 17th century, most probably in the second half of the 18th century or the early 19th century. Gully morphology and analogy with the processes in the recent gully indicate that the buried gully filled in rapidly. Overall, five cycles of cut and fill occurred in 350 years or less and four cycles even within little less than a few decades, indicating that gully development and infilling under cropland can be very rapid processes. (c) 2005 Elsevier B.V All rights reserved
Coastal uplift and tsunami effects associated to the 2010 M(w)8.8 Maule earthquake in Central Chile
(2011)
On February 27, 2010 at 03:34:08 AM an M(w)8.8 earthquake, with epicenter located off Cobquecura (73.24 degrees W; 36.29 degrees S), severely hit Central Chile. The tsunami waves that followed this event affected the coastal regions between the cities of Valparaiso and Valdivia, with minor effects as far as Coquimbo. The earthquake occurred along the subduction of the Nazca oceanic plate beneath the South American plate. Coseismic coastal uplift was estimated through observations of bleached lithothamnioids crustose coralline algae, which were exposed after the mainshock between 34.13 degrees S and 38.34 degrees S, suggesting the latitudinal distribution of the earthquake rupture. The measured coastal uplift values varied between 240 +/- 20 cm at sites closer to the trench along the western coast of the Arauco peninsula and 15 +/- 10 cm at sites located farther east. A maximum value of 260 +/- 50 cm was observed at the western coast of Santa Maria Island, which is similar to the reported uplift associated with the 1835 earthquake at Concepcion. Land subsidence values on the order of 0.5 m to 1 m evidenced a change in polarity and position of the coseismic hinge at 110-120 km from the trench. In four sites along the coast we observed a close match between coastal uplift values deduced from bleached lithothamnioids algae and GPS measurements. According to field observations tsunami heights reached ea. 14 m in the coastal area of the Maule Region immediately north of the epicenter, and diminished progressively northwards to 4-2 m near Valparaiso. Along the coast of Cobquecura, tsunami height values were inferior to 2-4 m. More variable tsunami heights of 6-8 m were measured at Dichato-Talcahuano and Tirua-Puerto Saavedra, in the Biobio and Arauco regions, respectively, to the south of the epicenter. According to eyewitnesses, the tsunami reached the coast between 12 to 20 and 30 to 45 minutes in areas located closer and faraway from the earthquake rupture zone, respectively. Destructive tsunami waves arrived also between 2.5 and 4.5 hours after the mainshock, especially along the coast of the Biobio and Arauco regions. The tsunami effects were highly variable along the coast, as a result of geomorphological and bathymetric local conditions, besides potential complexities induced by the main shock.
Cretaceous magmatism in the Eastern Cordillera of Colombia is related to lithospheric stretching during the late Early-early Late Cretaceous. The small amount of preserved igneous material is represented by small mafic intrusions. This study focuses on three localities, from east to west: Pajarito, Pacho, and Caceres. The investigated igneous bodies are classified as gabbros, pyroxene-hornblende-gabbros, and pyroxene-hornblendites mainly composed of plagioclase, clinopyroxene, and/or amphibole. Although their timing of emplacement and geodynamic position seem similar, significant differences in their geochemical and petrological characteristics rule out simple models of melt genesis. Clinopyroxene and bulk chemistry indicate increasing alkalinity from west to east. Trace element concentrations point to melt sources that range from a slightly enriched mantle in the west to a highly enriched one in the east. In addition, the data reflect a decreasing degree of partial melting from west to east and the decreasing importance of residual garnet in the mantle source. Probable mantle metasomatism in the source region by slab-derived fluids, as displayed by high Ba/Nb and moderate Sr-n/P-n, is clear in the west and very slight to the east. Mantle metasomatism and melt generation probably are processes of different epochs. The lack of large volumes of igneous rocks and the absence of tectonically controlled unconformities in the investigated areas indicate that a mantle plume did not affect the regional tectonics and magmatism. We favor a model of rift-related magmatism in which melt composition is modified from east to west from a highly enriched to a less enriched mantle region, the latter metasomatized by fluids derived from an older subduction phase. (c) 2005 Elsevier Ltd. All rights reserved
The Eastern Cordillera of the Colombian Andes represents an inverted Cretaceous basin where Cretaceous magmatism is characterized by rare mafic dykes and sills. We use Ar-40/Ar-39, Sr-Nd-Pb isotopes, as well as major and trace elements analyses of Cretaceous intrusions from both flanks of the Eastern Cordillera in combination with structural data to document the complex evolution of the basin. Magmatism, which is diachronous and geochemically diverse, seems to be related to mantle melting beneath the most subsiding segments of each sub-basin during enhanced extensional tectonics. The mafic intrusions display two different compositional series: an alkaline one with OIB-like pattern and a tholeiitic one with MORB-like features. This indicates at least two diverse mantle sources. Trace-element patterns suggest that the intrusions were emplaced in an extensional setting. Ar-40/Ar-39 dating on primary plagioclase and hornblende provides plateau ages between similar to 136 and similar to 74 Ma. The geochemical and temporal diversities show that the emplacement of the magmas was tectonically controlled, each sub-basin reflecting an individual subsidence event.
Centroid moment tensor (CMT) parameters can be estimated from seismic waveforms. Since these data indirectly observe the deformation process, CMTs are inferred as solutions to inverse problems which are generally underdetermined and require significant assumptions, including assumptions about data noise. Broadly speaking, we consider noise to include both theory and measurement errors, where theory errors are due to assumptions in the inverse problem and measurement errors are caused by the measurement process. While data errors are routinely included in parameter estimation for full CMTs, less attention has been paid to theory errors related to velocity-model uncertainties and how these affect the resulting moment-tensor (MT) uncertainties. Therefore, rigorous uncertainty quantification for CMTs may require theory-error estimation which becomes a problem of specifying noise models. Various noise models have been proposed, and these rely on several assumptions. All approaches quantify theory errors by estimating the covariance matrix of data residuals. However, this estimation can be based on explicit modelling, empirical estimation and/or ignore or include covariances. We quantitatively compare several approaches by presenting parameter and uncertainty estimates in nonlinear full CMT estimation for several simulated data sets and regional field data of the M-1 4.4, 2015 June 13 Fox Creek, Canada, event. While our main focus is at regional distances, the tested approaches are general and implemented for arbitrary source model choice. These include known or unknown centroid locations, full MTs, deviatoric MTs and double-couple MTs. We demonstrate that velocity-model uncertainties can profoundly affect parameter estimation and that their inclusion leads to more realistic parameter uncertainty quantification. However, not all approaches perform equally well. Including theory errors by estimating non-stationary (non-Toeplitz) error covariance matrices via iterative schemes during Monte Carlo sampling performs best and is computationally most efficient. In general, including velocity-model uncertainties is most important in cases where velocity structure is poorly known.
Several thousands of moraine-dammed and supraglacial lakes spread over the Hindu Kush Himalayan (HKH) region, and some have grown rapidly in past decades due to glacier retreat. The sudden emptying of these lakes releases large volumes of water and sediment in destructive glacial lake outburst floods (GLOFs), one of the most publicised natural hazards to the rapidly growing Himalayan population. Despite the growing number and size of glacial lakes, the frequency of documented GLOFs is remarkably constant. We explore this possible reporting bias and offer a new processing chain for establishing a more complete Himalayan GLOF inventory. We make use of the full seasonal archive of Landsat images between 1988 and 2016, and track automatically where GLOFs left shrinking water bodies, and tails of sediment at high elevations. We trained a Random Forest classifier to generate fuzzy land cover maps for 2491 images, achieving overall accuracies of 91%. We developed a likelihood-based change point technique to estimate the timing of GLOFs at the pixel scale. Our method objectively detected ten out of eleven documented GLOFs, and another ten lakes that gave rise to previously unreported GLOFs. We thus nearly doubled the existing GLOF record for a study area covering similar to 10% of the HKH region. Remaining challenges for automatically detecting GLOFs include image insufficiently accurate co-registration, misclassifications in the land cover maps and image noise from clouds, shadows or ice. Yet our processing chain is robust and has the potential for being applied on the greater HKH and mountain ranges elsewhere, opening the door for objectively expanding the knowledge base on GLOF activity over the past three decades.
Shrinking glaciers in the Hindu Kush-Karakoram-Himalaya-Nyainqentanglha (HKKHN) region have formed several thousand moraine-dammed glacial lakes(1-3), some of these having grown rapidly in past decades(3,4). This growth may promote more frequent and potentially destructive glacial lake outburst floods (GLOFs)(5-7). Testing this hypothesis, however, is confounded by incomplete databases of the few reliable, though selective, case studies. Here we present a consistent Himalayan GLOF inventory derived automatically from all available Landsat imagery since the late 1980s. We more than double the known GLOF count and identify the southern Himalayas as a hotspot region, compared to the more rarely affected Hindu Kush-Karakoram ranges. Nevertheless, the average annual frequency of 1.3 GLOFs has no credible posterior trend despite reported increases in glacial lake areas in most of the HKKHN3,8, so that GLOF activity per unit lake area has decreased since the late 1980s. We conclude that learning more about the frequency and magnitude of outburst triggers, rather than focusing solely on rapidly growing glacial lakes, might improve the appraisal of GLOF hazards.
Thousands of glacier lakes have been forming behind natural dams in high mountains following glacier retreat since the early 20th century. Some of these lakes abruptly released pulses of water and sediment with disastrous downstream consequences. Yet it remains unclear whether the reported rise of these glacier lake outburst floods (GLOFs) has been fueled by a warming atmosphere and enhanced meltwater production, or simply a growing research effort. Here we estimate trends and biases in GLOF reporting based on the largest global catalog of 1,997 dated glacier-related floods in six major mountain ranges from 1901 to 2017. We find that the positive trend in the number of reported GLOFs has decayed distinctly after a break in the 1970s, coinciding with independently detected trend changes in annual air temperatures and in the annual number of field-based glacier surveys (a proxy of scientific reporting). We observe that GLOF reports and glacier surveys decelerated, while temperature rise accelerated in the past five decades. Enhanced warming alone can thus hardly explain the annual number of reported GLOFs, suggesting that temperature-driven glacier lake formation, growth, and failure are weakly coupled, or that outbursts have been overlooked. Indeed, our analysis emphasizes a distinct geographic and temporal bias in GLOF reporting, and we project that between two to four out of five GLOFs on average might have gone unnoticed in the early to mid-20th century. We recommend that such biases should be considered, or better corrected for, when attributing the frequency of reported GLOFs to atmospheric warming.
Thousands of glacier lakes have been forming behind natural dams in high mountains following glacier retreat since the early 20th century. Some of these lakes abruptly released pulses of water and sediment with disastrous downstream consequences. Yet it remains unclear whether the reported rise of these glacier lake outburst floods (GLOFs) has been fueled by a warming atmosphere and enhanced meltwater production, or simply a growing research effort. Here we estimate trends and biases in GLOF reporting based on the largest global catalog of 1,997 dated glacier-related floods in six major mountain ranges from 1901 to 2017. We find that the positive trend in the number of reported GLOFs has decayed distinctly after a break in the 1970s, coinciding with independently detected trend changes in annual air temperatures and in the annual number of field-based glacier surveys (a proxy of scientific reporting). We observe that GLOF reports and glacier surveys decelerated, while temperature rise accelerated in the past five decades. Enhanced warming alone can thus hardly explain the annual number of reported GLOFs, suggesting that temperature-driven glacier lake formation, growth, and failure are weakly coupled, or that outbursts have been overlooked. Indeed, our analysis emphasizes a distinct geographic and temporal bias in GLOF reporting, and we project that between two to four out of five GLOFs on average might have gone unnoticed in the early to mid-20th century. We recommend that such biases should be considered, or better corrected for, when attributing the frequency of reported GLOFs to atmospheric warming.
Thousands of glacier lakes have been forming behind natural dams in high mountains following glacier retreat since the early 20th century. Some of these lakes abruptly released pulses of water and sediment with disastrous downstream consequences. Yet it remains unclear whether the reported rise of these glacier lake outburst floods (GLOFs) has been fueled by a warming atmosphere and enhanced meltwater production, or simply a growing research effort. Here we estimate trends and biases in GLOF reporting based on the largest global catalog of 1,997 dated glacier-related floods in six major mountain ranges from 1901 to 2017. We find that the positive trend in the number of reported GLOFs has decayed distinctly after a break in the 1970s, coinciding with independently detected trend changes in annual air temperatures and in the annual number of field-based glacier surveys (a proxy of scientific reporting). We observe that GLOF reports and glacier surveys decelerated, while temperature rise accelerated in the past five decades. Enhanced warming alone can thus hardly explain the annual number of reported GLOFs, suggesting that temperature-driven glacier lake formation, growth, and failure are weakly coupled, or that outbursts have been overlooked. Indeed, our analysis emphasizes a distinct geographic and temporal bias in GLOF reporting, and we project that between two to four out of five GLOFs on average might have gone unnoticed in the early to mid-20th century. We recommend that such biases should be considered, or better corrected for, when attributing the frequency of reported GLOFs to atmospheric warming.
External climate forcings-such as long-term changes in solar insolation-generate different climate responses in tropical and high latitude regions(1). Documenting the spatial and temporal variability of past climates is therefore critical for understanding how such forcings are translated into regional climate variability. In contrast to the data- richmiddle and high latitudes, high-quality climate-proxy records from equatorial regions are relatively few(2-4), especially from regions experiencing the bimodal seasonal rainfall distribution associated with twice-annual passage of the Intertropical Convergence Zone. Here we present a continuous and well-resolved climate-proxy record of hydrological variability during the past 25,000 years from equatorial East Africa. Our results, based on complementary evidence from seismic-reflection stratigraphy and organic biomarker molecules in the sediment record of Lake Challa near Mount Kilimanjaro, reveal that monsoon rainfall in this region varied at half-precessional (similar to 11,500-year) intervals in phase with orbitally controlled insolation forcing. The southeasterly and northeasterly monsoons that advect moisture from the western Indian Ocean were strengthened in alternation when the inter-hemispheric insolation gradient was at a maximum; dry conditions prevailed when neither monsoon was intensified and modest local March or September insolation weakened the rain season that followed. On sub-millennial timescales, the temporal pattern of hydrological change on the East African Equator bears clear high-northern-latitude signatures, but on the orbital timescale it mainly responded to low-latitude insolation forcing. Predominance of low-latitude climate processes in this monsoon region can be attributed to the low-latitude position of its continental regions of surface air flow convergence, and its relative isolation from the Atlantic Ocean, where prominent meridional overturning circulation more tightly couples low-latitude climate regimes to high-latitude boundary conditions.
Architectural analysis of the Late Cretaceous alveolinaceans of the Caribbean palaeobioprovince has made it possible to separate four genera: Praechubbina, Chubbinella gen. nov., Chubbina and Caribalveolina. The first three genera belong to the family Rhapydioninidae, while the fourth is placed in the family Alveolinidae. Two species, Praechubbina breviclaustra and P. oxchucensis sp. nov., represent the primitive genus Praechubbina, while the species cardenasensis and obesa, previously ascribed to this genus, must be reassigned respectively to Chubbinella gen. nov. and Caribalveolina. The species Chubbina jamaicensis, C. macgillavryi and C. fourcadei sp. nov. complete the inventory of Chubbina. The alveolinid genus Caribalveolina comprises two species, C. obesa and C. michaudi. Caribbean alveolinaceans include two successive assemblages. The lower assemblage is characterized by Praechubbina oxchucensis, P. brevisclaustra, Chubbinella cardenasensis and Caribalveolina obesa. The upper assemblage is represented by the genus Chubbina, with C. fourcadei, C. jamaicensis and C. macgillavryi, and Caribalveolina michaudi. The age of the lower assemblage is uncertain (probably Late CampanianEarly Maastrichtian), while the upper assemblage has been dated by strontium isotope stratigraphy as Late Maastrichtian.
Shell architectures of the larger foraminiferal genera cyclopseudedomia, and Rhapydionina were studied by comparing topotypes of previously described species with new specimens retrieved from Late Cretaceous shallow-water carbonates of Pylos (Peloponnese, Greece), where the three genera are found in association. The megalospheric generation of each genus exhibits a distinctive shell shape in adult specimens (i.e., fan-shaped in Cyclopseudedomia, conical in Rhapydionina, and cylindrical in Cuvillierinella). Although their microspheric adults are similarly thin, flat, and discoidal, they can be identified at the genus level by means of a detailed structural analysis. Cavillierinella shows the septula to be interrupted by a large preseptal space, while Cyclopseudedomia and Rhapydionina exhibit continuous, non-interrupted septula. In addition, Cyclopseudedomia presents only one row of medullar chamberlets, whereas Rhapydionina shows numerous medullar chamberlets distributed in a thick basal layer.
Two new species, Cuvillierinella pylosensis and Rhapydionina fleuryi, are described. The former is a more complex taxon than the type species, C salentina, while the latter corresponds to a more primitive species, R. liburnica. Strontium-isotope stratigraphy indicates an uppermost Campanian-lowermost Maastrichtian age for these new species.
We used inverse modelling techniques and soil moisture measured by the cosmic-ray neutron sensing (CRS) to estimate root-zone soil hydraulic properties at the field scale. A HYDRUS-1D model was developed for inverse modelling and calibrated with parameter estimation software (PEST) using a global optimizer. Integral CRS measurements recorded from a sunflower farm in Germany comprised the model input. Data were transformed to soil water storage to enable direct model calibration with a HYDRUS soil-water balance. Effective properties at the CRS scale were compared against local measurements and other inversely estimated soil properties from independent soil moisture profiles. Moreover, CRS-scale soil properties were tested on the basis of how field soil moisture (vertical distribution) and soil water storage were reproduced. This framework provided good estimates of effective soil properties at the CRS scale. Simulated soil moisture at different depths at the CRS scale agreed with field observations. Moreover, simulated soil water storage at the CRS scale compared well with calculations from point-scale profiles, despite their different support volumes. The CRS-scale soil properties estimated with the inverse model were within the range of variation of properties identified from all inverse simulations at the local scale. This study demonstrates the potential of CRS for inverse estimation of soil hydraulic properties.
On 7 January 2020, an M-w 6.4 earthquake occurred in the northeastern Caribbean, a few kilometers offshore of the island of Puerto Rico. It was the mainshock of a complex seismic sequence, characterized by a large number of energetic earthquakes illuminating an east-west elongated area along the southwestern coast of Puerto Rico. Deformation fields constrained by Interferometric Synthetic Aperture Radar and Global Navigation Satellite System data indicate that the coseismic movements affected only the western part of the island. To assess the mainshock's source fault parameters, we combined the geodetically derived coseismic deformation with teleseismic waveforms using Bayesian inference. The results indicate a roughly east-west oriented fault, dipping northward and accommodating similar to 1.4 m of transtensional motion. Besides, the determined location and orientation parameters suggest an offshore continuation of the recently mapped North Boqueron Bay-Punta Montalva fault in southwest Puerto Rico. This highlights the existence of unmapped faults with moderate-to-large earthquake potential within the Puerto Rico region.
This paper reports on a project to compare predictions from a range of catchment models applied to a mesoscale river basin in central Germany and to assess various ensemble predictions of catchment streamflow. The models encompass a large range in inherent complexity and input requirements. In approximate order of decreasing complexity, they are DHSVM, MIKE-SHE, TOPLATS, WASIM-ETH, SWAT, PRMS, SLURP, HBV, LASCAM and IHACRES. The models are calibrated twice using different sets of input data. The two predictions from each model are then combined by simple averaging to produce a single-model ensemble. The 10 resulting single-model ensembles are combined in various ways to produce multi-model ensemble predictions. Both the single-model ensembles and the multi-model ensembles are shown to give predictions that are generally superior to those of their respective constituent models, both during a 7-year calibration period and a 9- year validation period. This occurs despite a considerable disparity in performance of the individual models. Even the weakest of models is shown to contribute useful information to the ensembles they are part of. The best model combination methods are a trimmed mean (constructed using the central four or six predictions each day) and a weighted mean ensemble (with weights calculated from calibration performance) that places relatively large weights on the better performing models. Conditional ensembles. in which separate model weights are used in different system states (e.g. summer and winter, high and low flows) generally yield little improvement over the weighted mean ensemble. However a conditional ensemble that discriminates between rising and receding flows shows moderate improvement. An analysis of ensemble predictions shows that the best ensembles are not necessarily those containing the best individual models. Conversely, it appears that some models that predict well individually do not necessarily combine well with other models in multi-model ensembles. The reasons behind these observations may relate to the effects of the weighting schemes, non- stationarity of the climate series and possible cross-correlations between models.
P receiver functions from 23 stations of the SASE experiment in southern Africa are inverted simultaneously with SKS waveforms for azimuthal anisotropy in the upper mantle. Our analysis resolves the long-standing issue of depth dependence and origins of anisotropy beneath southern Africa. In the uppermost mantle we observe anisotropy with a nearly E-W fast direction, parallel to the trend of the Limpopo belt. This anisotropy may be frozen since the Archean. At a depth of 160 km the fast direction of anisotropy changes to 40 degrees and becomes close to the recent plate motion direction. This transition is nearly coincident in depth with activation of dominant glide systems in olivine and with a pronounced change in other properties of the upper mantle. Another large change in the fast direction of anisotropy corresponds to the previously found low-S-velocity layer atop the 410-km discontinuity. Citation: Vinnik, L., S. Kiselev, M. Weber, S. Oreshin, and L. Makeyeva (2012), Frozen and active seismic anisotropy beneath southern Africa, Geophys. Res. Lett., 39, L08301, doi: 10.1029/2012GL051326.
We investigate the crust, upper mantle and mantle transition zone of the Cape Verde hotspot by using seismic P and S receiver functions from several tens of local seismograph stations. We find a strong discontinuity at a depth of similar to 10 km underlain by a similar to 15-km thick layer with a high (similar to 1.9) Vp/Vs velocity ratio. We interpret this discontinuity and the underlying layer as the fossil Moho, inherited from the pre-hotspot era, and the plume-related magmatic underplate. Our uppermost-mantle models are very different from those previously obtained for this region: our S velocity is much lower and there are no indications of low densities. Contrary to previously published arguments for the standard transition zone thickness our data indicate that this thickness under the Cape Verde islands is up to similar to 30 km less than in the ambient mantle. This reduction is a combined effect of a depression of the 410-km discontinuity and an uplift of the 660-km discontinuity. The uplift is in contrast to laboratory data and some seismic data on a negligible dependence of depth of the 660-km discontinuity on temperature in hotspots. A large negative pressure-temperature slope which is suggested by our data implies that the 660-km discontinuity may resist passage of the plume.
Our data reveal beneath the islands a reduction of S velocity of a few percent between 470-km and 510-km depths. The low velocity layer in the upper transition zone under the Cape Verde archipelago is very similar to that previously found under the Azores and a few other hotspots. In the literature there are reports on a regional 520-km discontinuity, the impedance of which is too large to be explained by the known phase transitions. Our observations suggest that the 520-km discontinuity may present the base of the low-velocity layer in the transition zone.
Even though quite different in occurrence and consequences, from a modeling perspective many natural hazards share similar properties and challenges. Their complex nature as well as lacking knowledge about their driving forces and potential effects make their analysis demanding: uncertainty about the modeling framework, inaccurate or incomplete event observations and the intrinsic randomness of the natural phenomenon add up to different interacting layers of uncertainty, which require a careful handling. Nevertheless deterministic approaches are still widely used in natural hazard assessments, holding the risk of underestimating the hazard with disastrous effects. The all-round probabilistic framework of Bayesian networks constitutes an attractive alternative. In contrast to deterministic proceedings, it treats response variables as well as explanatory variables as random variables making no difference between input and output variables. Using a graphical representation Bayesian networks encode the dependency relations between the variables in a directed acyclic graph: variables are represented as nodes and (in-)dependencies between variables as (missing) edges between the nodes. The joint distribution of all variables can thus be described by decomposing it, according to the depicted independences, into a product of local conditional probability distributions, which are defined by the parameters of the Bayesian network. In the framework of this thesis the Bayesian network approach is applied to different natural hazard domains (i.e. seismic hazard, flood damage and landslide assessments). Learning the network structure and parameters from data, Bayesian networks reveal relevant dependency relations between the included variables and help to gain knowledge about the underlying processes. The problem of Bayesian network learning is cast in a Bayesian framework, considering the network structure and parameters as random variables itself and searching for the most likely combination of both, which corresponds to the maximum a posteriori (MAP score) of their joint distribution given the observed data. Although well studied in theory the learning of Bayesian networks based on real-world data is usually not straight forward and requires an adoption of existing algorithms. Typically arising problems are the handling of continuous variables, incomplete observations and the interaction of both. Working with continuous distributions requires assumptions about the allowed families of distributions. To "let the data speak" and avoid wrong assumptions, continuous variables are instead discretized here, thus allowing for a completely data-driven and distribution-free learning. An extension of the MAP score, considering the discretization as random variable as well, is developed for an automatic multivariate discretization, that takes interactions between the variables into account. The discretization process is nested into the network learning and requires several iterations. Having to face incomplete observations on top, this may pose a computational burden. Iterative proceedings for missing value estimation become quickly infeasible. A more efficient albeit approximate method is used instead, estimating the missing values based only on the observations of variables directly interacting with the missing variable. Moreover natural hazard assessments often have a primary interest in a certain target variable. The discretization learned for this variable does not always have the required resolution for a good prediction performance. Finer resolutions for (conditional) continuous distributions are achieved with continuous approximations subsequent to the Bayesian network learning, using kernel density estimations or mixtures of truncated exponential functions. All our proceedings are completely data-driven. We thus avoid assumptions that require expert knowledge and instead provide domain independent solutions, that are applicable not only in other natural hazard assessments, but in a variety of domains struggling with uncertainties.
Modern natural hazards research requires dealing with several uncertainties that arise from limited process knowledge, measurement errors, censored and incomplete observations, and the intrinsic randomness of the governing processes. Nevertheless, deterministic analyses are still widely used in quantitative hazard assessments despite the pitfall of misestimating the hazard and any ensuing risks.
In this paper we show that Bayesian networks offer a flexible framework for capturing and expressing a broad range of uncertainties encountered in natural hazard assessments. Although Bayesian networks are well studied in theory, their application to real-world data is far from straightforward, and requires specific tailoring and adaptation of existing algorithms. We offer suggestions as how to tackle frequently arising problems in this context and mainly concentrate on the handling of continuous variables, incomplete data sets, and the interaction of both. By way of three case studies from earthquake, flood, and landslide research, we demonstrate the method of data-driven Bayesian network learning, and showcase the flexibility, applicability, and benefits of this approach.
Our results offer fresh and partly counterintuitive insights into well-studied multivariate problems of earthquake-induced ground motion prediction, accurate flood damage quantification, and spatially explicit landslide prediction at the regional scale. In particular, we highlight how Bayesian networks help to express information flow and independence assumptions between candidate predictors. Such knowledge is pivotal in providing scientists and decision makers with well-informed strategies for selecting adequate predictor variables for quantitative natural hazard assessments.
Flood damage estimation is a core task in flood risk assessments and requires reliable flood loss models. Identifying the driving factors of flood loss at residential buildings and gaining insight into their relations is important to improve our understanding of flood damage processes. For that purpose, we learn probabilistic graphical models, which capture and illustrate (in-)dependencies between the considered variables. The models are learned based on postevent surveys with flood-affected residents after six flood events, which occurred in Germany between 2002 and 2013. Besides the sustained building damage, the survey data contain information about flooding parameters, early warning and emergency measures, property-level mitigation measures and preparedness, socioeconomic characteristics of the household, and building characteristics. The analysis considers the entire data set with a total of 4,468 cases as well as subsets of the data set partitioned into single flood events and flood types: river floods, levee breaches, surface water flooding, and groundwater floods, to reveal differences in the damaging processes. The learned networks suggest that the flood loss ratio of residential buildings is directly influenced by hydrological and hydraulic aspects as well as by building characteristics and property-level mitigation measures. The study demonstrates also that for different flood events and process types the building damage is influenced by varying factors. This suggests that flood damage models need to be capable of reproducing these differences for spatial and temporal model transfers.
Pompeii, buried by the explosive A. D. 79 eruption of Somma-Vesuvius, is one of the most studied ancient cities in the Roman world. However, until very recently, the rural settlement in its hinterland had been largely ignored by systematic archaeological research. The ancient landscape around Pompeii consisted of a dense network of Roman farms (villae rusticae). They are believed to have played a vital role in ancient rural life and economy and thus represented the interactive rural-urban relationship in the Sarno River plain. The systematic investigation of published work combined with new fieldwork has yielded a data set of 140 villae rusticae in the Sarno River plain. Geographic information system based spatial statistics as well as predictive modeling were applied to gain a more detailed understanding of the ancient rural settlement structure in relation to the underlying paleoenvironmental and socioeconomic conditions. A high-resolution pre-A. D. 79 paleolandscape model of the Sarno River plain was utilized. The aim of this paper is to address theoretical considerations, the methodological implementation, and the archaeological discussion of the analysis of the ancient rural settlements and agriculture around Pompeii. (C) 2016 Wiley Periodicals, Inc.
The Himalaya has a major influence on global and regional climate, in particular on the Asian monsoon system. The foreland basin of the Himalaya contains a record of tectonics and paleoclimate since the Miocene. Previous work on the evolution of vegetation and climate has focused on the central and western Himalaya, where a shift from C3 to C4 vegetation has been observed at similar to 7 Ma and linked to increased seasonality, but the climatic evolution of the eastern part of the orogen is less well understood. In order to track vegetation as a marker of monsoon intensity and seasonality, we analyzed delta C-13 and 8180 values of soil carbonate and associated delta C-13 values of bulk organic carbon from previously dated sedimentary sections exposing the syn-orogenic detrital Dharamsala and Siwalik Groups in the west, and, for the first time, the Siwalik Group in the east of the Himalayan foreland basin. Sedimentary records span from 20 to 1 Myr in the west (Joginder Nagar, Jawalamukhi, and Haripur Kolar sections) and from 13 to 1 Myr in the east (Kameng section), respectively. The presence of soil carbonate in the west and its absence in the east is a first indication of long-term lateral climatic variation, as soil carbonate requires seasonally arid conditions to develop. delta C-13 values in soil carbonate show a shift from around -10 parts per thousand to -2 parts per thousand at similar to 7 Ma in the west, which is confirmed by delta C-13 analyses on bulk organic carbon that show a shift from around -23 parts per thousand to -19 parts per thousand at the same time. Such a shift in isotopic values is likely to be associated with a change from C3 to C4 vegetation. In contrast, delta C-13 values of bulk organic carbon remain at 23 parts per thousand o in the east. Thus, our data show that the current east -west variation in climate was established at similar to 7 Ma. We propose that the regional change towards a more seasonal climate in the west is linked to a decrease of the influence of the Westerlies, delivering less winter precipitation to the western Himalaya, while the east remained annually humid due to its proximity to the monsoonal moisture source. (C) 2017 Elsevier B.V. All rights reserved.
Changes in snowpack associated with climatic warming has drastic impacts on surface energy balance in the cryosphere. Yet, traditional monitoring techniques, such as punctual measurements in the field, do not cover the full snowpack spatial and temporal variability, which hampers efforts to upscale measurements to the global scale. This variability is one of the primary constraints in model development. In terms of spatial resolution, active microwaves (synthetic aperture radar - SAR) can address the issue and outperform methods based on passive microwaves. Thus, high-spatial-resolution monitoring of snow depth (SD) would allow for better parameterization of local processes that drive the spatial variability of snow. The overall objective of this study is to evaluate the potential of the TerraSAR-X (TSX) SAR sensor and the wave co-polar phase difference (CPD) method for characterizing snow cover at high spatial resolution. Consequently, we first (1) investigate SD and depth hoar fraction (DHF) variability between different vegetation classes in the Ice Creek catchment (Qikiqtaruk/Herschel Island, Yukon, Canada) using in situ measurements collected over the course of a field campaign in 2019; (2) evaluate linkages between snow characteristics and CPD distribution over the 2019 dataset; and (3) determine CPD seasonality considering meteorological data over the 2015-2019 period. SD could be extracted using the CPD when certain conditions are met. A high incidence angle (>30 circle) with a high topographic wetness index (TWI) (>7.0) showed correlation between SD and CPD (R2 up to 0.72). Further, future work should address a threshold of sensitivity to TWI and incidence angle to map snow depth in such environments and assess the potential of using interpolation tools to fill in gaps in SD information on drier vegetation types.
Neodymium isotopic composition (epsilon Nd) has enjoyed widespread use as a palaeotracer, principally because it behaves quasi-conservatively in the modern ocean. However, recent bottom water epsilon Nd reconstructions from the eastern North Atlantic are difficult to interpret under assumptions of conservative behaviour. The observation that this apparent departure from conservative behaviour increases with enhanced ice-rafted debris (IRD) fluxes has resulted in the suggestion that IRD leads to the overprinting of bottom water epsilon Nd through reversible scavenging. In this study, a simple water column model successfully reproduces epsilon Nd reconstructions from the eastern North Atlantic at the Last Glacial Maximum and Heinrich Stadial 1, and demonstrates that the changes in scavenging intensity required for good model-data fit is in good agreement with changes in the observed IRD flux. Although uncertainties in model parameters preclude a more definitive conclusion, the results indicate that the suggestion of IRD as a source of non-conservative behaviour in the epsilon Nd tracer is reasonable and that further research into the fundamental chemistry underlying the marine neodymium cycle is necessary to increase confidence in assumptions of conservative epsilon Nd behaviour in the past.
Multiple P-T-d-t paths reveal the evolution of the final Nuna assembly in northeast Australia
(2020)
The final assembly of the Mesoproterozoic supercontinent Nuna was marked by the collision of Laurentia and Australia at 1.60 Ga, which is recorded in the Georgetown Inlier of NE Australia. Here, we decipher the metamorphic evolution of this final Nuna collisional event using petrostructural analysis, major and trace element compositions of key minerals, thermodynamic modelling, and multi-method geochronology. The Georgetown Inlier is characterised by deformed and metamorphosed 1.70-1.62 Ga sedimentary and mafic rocks, which were intruded byc. 1.56 Ga old S-type granites. Garnet Lu-Hf and monazite U-Pb isotopic analyses distinguish two major metamorphic events (M1 atc. 1.60 Ga and M2 atc. 1.55 Ga), which allows at least two composite fabrics to be identified at the regional scale-c. 1.60 Ga S1 (consisting in fabrics S1a and S1b) andc. 1.55 Ga S2 (including fabrics S2a and S2b). Also, three tectono-metamorphic domains are distinguished: (a) the western domain, with S1 defined by low-P(LP) greenschist facies assemblages; (b) the central domain, where S1 fabric is preserved as medium-P(MP) amphibolite facies relicts, and locally as inclusion trails in garnet wrapped by the regionally dominant low-Pamphibolite facies S2 fabric; and (c) the eastern domain dominated by upper amphibolite to granulite facies S2 foliation. In the central domain, 1.60 GaMP-medium-T(MT) metamorphism (M1) developed within the staurolite-garnet stability field, with conditions ranging from 530-550 degrees C at 6-7 kbar (garnet cores) to 620-650 degrees C at 8-9 kbar (garnet rims), and it is associated with S1 fabric. The onset of 1.55 GaLP-high-T(HT) metamorphism (M2) is marked by replacement of staurolite by andalusite (M2a/D2a), which was subsequently pseudomorphed by sillimanite (M2b/D2b) where granite and migmatite are abundant.P-Tconditions ranged from 600 to 680 degrees C and 4-6 kbar for the M2b sillimanite stage. 1.60 Ga garnet relicts within the S2 foliation highlight the progressive obliteration of the S1 fabric by regional S2 in the central zone during peak M2 metamorphism. In the eastern migmatitic complex, partial melting of paragneiss and amphibolite occurred syn- to post-S2, at 730-770 degrees C and 6-8 kbar, and at 750-790 degrees C and 6 kbar, respectively. The pressure-temperature-deformation-time paths reconstructed for the Georgetown Inlier suggest ac. 1.60 Ga M1/D1 event recorded under greenschist facies conditions in the western domain and under medium-Pand medium-Tconditions in the central domain. This event was followed by the regional 1.56-1.54 Ga low-Pand high-Tphase (M2/D2), extensively recorded in the central and eastern domains. Decompression between these two metamorphic events is ascribed to an episode of exhumation. The two-stage evolution supports the previous hypothesis that the Georgetown Inlier preserves continental collisional and subsequent thermal perturbation associated with granite emplacement.
The steady increase of ground-motion data not only allows new possibilities but also comes with new challenges in the development of ground-motion models (GMMs). Data classification techniques (e.g., cluster analysis) do not only produce deterministic classifications but also probabilistic classifications (e.g., probabilities for each datum to belong to a given class or cluster). One challenge is the integration of such continuous classification in regressions for GMM development such as the widely used mixed-effects model. We address this issue by introducing an extension of the mixed-effects model to incorporate data weighting. The parameter estimation of the mixed-effects model, that is, fixed-effects coefficients of the GMMs and the random-effects variances, are based on the weighted likelihood function, which also provides analytic uncertainty estimates. The data weighting permits for earthquake classification beyond the classical, expert-driven, binary classification based, for example, on event depth, distance to trench, style of faulting, and fault dip angle. We apply Angular Classification with Expectation-maximization, an algorithm to identify clusters of nodal planes from focal mechanisms to differentiate between, for example, interface- and intraslab-type events. Classification is continuous, that is, no event belongs completely to one class, which is taken into account in the ground-motion modeling. The theoretical framework described in this article allows for a fully automatic calibration of ground-motion models using large databases with automated classification and processing of earthquake and ground-motion data. As an example, we developed a GMM on the basis of the GMM by Montalva et al. (2017) with data from the strong-motion flat file of Bastias and Montalva (2016) with similar to 2400 records from 319 events in the Chilean subduction zone. Our GMM with the data-driven classification is comparable to the expert-classification-based model. Furthermore, the model shows temporal variations of the between-event residuals before and after large earthquakes in the region.
The selection of earthquake focal mechanisms (FMs) for stress tensor inversion (STI) is commonly done on a spatial basis, that is, hypocentres. However, this selection approach may include data that are undesired, for example, by mixing events that are caused by different stress tensors when for the STI a single stress tensor is assumed. Due to the significant increase of FM data in the past decades, objective data-driven data selection is feasible, allowing more refined FM catalogues that avoid these issues and provide data weights for the STI routines. We present the application of angular classification with expectation-maximization (ACE) as a tool for data selection. ACE identifies clusters of FM without a priori information. The identified clusters can be used for the classification of the style-of-faulting and as weights of the FM data. We demonstrate that ACE effectively selects data that can be associated with a single stress tensor. Two application examples are given for weighted STI from South America. We use the resulting clusters and weights as a priori information for an STI for these regions and show that uncertainties of the stress tensor estimates are reduced significantly.
The propagation of a seismic rupture on a fault introduces spatial variations in the seismic wave field surrounding the fault. This directivity effect results in larger shaking amplitudes in the rupture propagation direction. Its seismic radiation pattern also causes amplitude variations between the strike-normal and strike-parallel components of horizontal ground motion. We investigated the landslide response to these effects during the 2016 Kumamoto earthquake (M-w 7.1) in central Kyushu (Japan). Although the distribution of some 1500 earthquake-triggered landslides as a function of rupture distance is consistent with the observed Arias intensity, the landslides were more concentrated to the northeast of the southwest-northeast striking rupture. We examined several landslide susceptibility factors: hillslope inclination, the median amplification factor (MAF) of ground shaking, lithology, land cover, and topographic wetness. None of these factors sufficiently explains the landslide distribution or orientation (aspect), although the landslide head scarps have an elevated hillslope inclination and MAF. We propose a new physics-based ground-motion model (GMM) that accounts for the seismic rupture effects, and we demonstrate that the low-frequency seismic radiation pattern is consistent with the overall landslide distribution. Its spatial pattern is influenced by the rupture directivity effect, whereas landslide aspect is influenced by amplitude variations between the fault-normal and fault-parallel motion at frequencies < 2 Hz. This azimuth dependence implies that comparable landslide concentrations can occur at different distances from the rupture. This quantitative link between the prevalent landslide aspect and the low-frequency seismic radiation pattern can improve coseismic landslide hazard assessment.
This paper investigates the transferability of calibrated HBV model parameters under stable and contrasting conditions in terms of flood seasonality and flood generating processes (FGP) in five Norwegian catchments with mixed snowmelt/rainfall regimes. We apply a series of generalized (differential) split-sample tests using a 6-year moving window over (i) the entire runoff observation periods, and (ii) two subsets of runoff observations distinguished by the seasonal occurrence of annual maximum floods during either spring or autumn. The results indicate a general model performance loss due to the transfer of calibrated parameters to independent validation periods of -5 to -17%, on average. However, there is no indication that contrasting flood seasonality exacerbates performance losses, which contradicts the assumption that optimized parameter sets for snowmelt-dominated floods (during spring) perform particularly poorly on validation periods with rainfall-dominated floods (during autumn) and vice versa.
Climate change is likely to impact the seasonality and generation processes of floods in the Nordic countries, which has direct implications for flood risk assessment, design flood estimation, and hydropower production management. Using a multi-model/multi-parameter approach to simulate daily discharge for a reference (1961–1990) and a future (2071–2099) period, we analysed the projected changes in flood seasonality and generation processes in six catchments with mixed snowmelt/rainfall regimes under the current climate in Norway. The multi-model/multi-parameter ensemble consists of (i) eight combinations of global and regional climate models, (ii) two methods for adjusting the climate model output to the catchment scale, and (iii) one conceptual hydrological model with 25 calibrated parameter sets. Results indicate that autumn/winter events become more frequent in all catchments considered, which leads to an intensification of the current autumn/winter flood regime for the coastal catchments, a reduction of the dominance of spring/summer flood regimes in a high-mountain catchment, and a possible systematic shift in the current flood regimes from spring/summer to autumn/winter in the two catchments located in northern and south-eastern Norway. The changes in flood regimes result from increasing event magnitudes or frequencies, or a combination of both during autumn and winter. Changes towards more dominant autumn/winter events correspond to an increasing relevance of rainfall as a flood generating process (FGP) which is most pronounced in those catchments with the largest shifts in flood seasonality. Here, rainfall replaces snowmelt as the dominant FGP primarily due to increasing temperature.We further analysed the ensemble components in contributing to overall uncertainty in the projected changes and found that the climate
projections and the methods for downscaling or bias correction tend to be the largest contributors. The relative role of hydrological parameter uncertainty, however, is highest for those catchments showing the largest changes in flood seasonality, which confirms the lack of robustness in hydrological model parameterization for simulations under transient hydrometeorological conditions.
Climate change is likely to impact the seasonality and generation processes of floods in the Nordic countries, which has direct implications for flood risk assessment, design flood estimation, and hydropower production management. Using a multi-model/multi-parameter approach to simulate daily discharge for a reference (1961–1990) and a future (2071–2099) period, we analysed the projected changes in flood seasonality and generation processes in six catchments with mixed snowmelt/rainfall regimes under the current climate in Norway. The multi-model/multi-parameter ensemble consists of (i) eight combinations of global and regional climate models, (ii) two methods for adjusting the climate model output to the catchment scale, and (iii) one conceptual hydrological model with 25 calibrated parameter sets. Results indicate that autumn/winter events become more frequent in all catchments considered, which leads to an intensification of the current autumn/winter flood regime for the coastal catchments, a reduction of the dominance of spring/summer flood regimes in a high-mountain catchment, and a possible systematic shift in the current flood regimes from spring/summer to autumn/winter in the two catchments located in northern and south-eastern Norway. The changes in flood regimes result from increasing event magnitudes or frequencies, or a combination of both during autumn and winter. Changes towards more dominant autumn/winter events correspond to an increasing relevance of rainfall as a flood generating process (FGP) which is most pronounced in those catchments with the largest shifts in flood seasonality. Here, rainfall replaces snowmelt as the dominant FGP primarily due to increasing temperature.We further analysed the ensemble components in contributing to overall uncertainty in the projected changes and found that the climate projections and the methods for downscaling or bias correction tend to be the largest contributors. The relative role of hydrological parameter uncertainty, however, is highest for those catchments showing the largest changes in flood seasonality, which confirms the lack of robustness in hydrological model parameterization for simulations under transient hydrometeorological conditions.
There is increasing evidence for recent changes in the intensity and frequency of heavy precipitation and in the number of days with snow cover in many parts of Norway. The question arises as to whether these changes are also discernable with respect to their impacts on the magnitude and frequency of flooding and on the processes producing high flows. In this study, we tested up to 211 catchments for trends in peak flow discharge series by applying the Mann-Kendall test and Poisson regression for three different time periods (1962-2012, 1972-2012, 1982-2012). Field-significance was tested using a bootstrap approach. Over threshold discharge events were classified into rainfall vs. snowmelt dominated floods, based on a simple water balance approach utilizing a nationwide 1 x 1 km(2) gridded data set with daily observed rainfall and simulated snowmelt data. Results suggest that trends in flood frequency are more pronounced than trends in flood magnitude and are more spatially consistent with observed changes in the hydrometeorological drivers. Increasing flood frequencies in southern and western Norway are mainly due to positive trends in the frequency of rainfall dominated events, while decreasing flood frequencies in northern Norway are mainly the result of negative trends in the frequency of snowmelt dominated floods. Negative trends in flood magnitude are found more often than positive trends, and the regional patterns of significant trends reflect differences in the flood generating processes (FGPs). The results illustrate the benefit of distinguishing FGPs rather than simply applying seasonal analyses. The results further suggest that rainfall has generally gained an increasing importance for the generation of floods in Norway, while the role of snowmelt has been decreasing and the timing of snowmelt dominated floods has become earlier. (C) 2016 Elsevier B.V. All rights reserved.
Scenario-neutral response surfaces illustrate the sensitivity of a simulated natural system, represented by a specific impact variable, to systematic perturbations of climatic parameters. This type of approach has recently been developed as an alternative to top-down approaches for the assessment of climate change impacts. A major limitation of this approach is the underrepresentation of changes in the temporal structure of the climate input data (i.e., the seasonal and day-to-day variability) since this is not altered by the perturbation. This paper presents a framework that aims to examine this limitation by perturbing both observed and projected climate data time series for a future period, which both serve as input into a hydrological model (the HBV model). The resulting multiple response surfaces are compared at a common domain, the standardized runoff response surface (SRRS). We apply this approach in a case study catchment in Norway to (i) analyze possible changes in mean and extreme runoff and (ii) quantify the influence of changes in the temporal structure represented by 17 different climate input sets using linear mixed-effect models. Results suggest that climate change induced increases in mean and peak flow runoff and only small changes in low flow. They further suggest that the effect of the different temporal structures of the climate input data considerably affects low flows and floods (at least 21% influence), while it is negligible for mean runoff.
This paper presents a simple approach for the temporal disaggregation from daily to 3-hourly observed gridded temperature and precipitation (1 x 1km(2)) on the national scale. The intended use of the disaggregated 3-hourly data is to recalibrate the hydrological model currently used by the Norwegian Water Resources and Energy Directorate (NVE) for daily flood forecasting. By adapting the hydrological model to a 3-hourly temporal scale, the flood forecasting can benefit from available meteorological forecasts with finer temporal resolution and can better represent critical events of short duration and at small spatial scales. By consulting the temporal patterns of a High-Resolution Limited-Area Model (HIRLAM) hindcast series for northern Europe with an hourly temporal and a 0.1 degrees spatial resolution, existing daily 1 x 1km(2) grids for temperature and precipitation covering all of Norway (the seNorge data) were disaggregated into 3-hourly values for the time period September 1957 to December 2010. For the period 2000-05, the disaggregated 3-hourly temperature and precipitation data are validated against observed values from five meteorological stations and against 3-hourly data from the HIRLAM hindcast and daily seNorge data simply split into eight fractions. The results show that the disaggregated data perform best with anomaly correlation coefficients between 0.89 and 0.92 for temperature. With regard to precipitation, the disaggregated data also provide the highest correlations and the lowest errors. In addition, the disaggregated data prove to be best in estimating intervals without precipitation and tend to be most appropriate in estimating extreme precipitation with low occurrence probability (<20%).
In undisturbed tropical montane rainforests massive organic layers accommodate the majority of roots and only a small fraction of roots penetrate the mineral soil. We investigated the contribution of vegetation to slope stability in such environments by modifying a standard model for slope stability to include an organic layer with distinct mechanical properties. The importance of individual model parameters was evaluated using detailed measurements of soil and vegetation properties to reproduce the observed depth of 11 shallow landslides in the Andes of southern Ecuador. By distinguishing mineral soil, organic layer and above-ground biomass, it is shown that in this environment vegetation provides a destabilizing effect mainly due to its contribution to the mass of the organic layer (up to 973 t ha-1 under wet conditions). Sensitivity analysis shows that the destabilizing effect of the mass of soil and vegetation can only be effective on slopes steeper than 37.9 degrees. This situation applies to 36% of the study area. Thus, on the steep slopes of this megadiverse ecosystem, the mass of the growing forest promotes landsliding, which in turn promotes a new cycle of succession. This feedback mechanism is worth consideration in further investigations of the impact of landslides on plant diversity in similar environments.
Landslides are a hazard for humans and artificial structures. From an ecological point of view, they represent an important ecosystem disturbance, especially in tropical montane forests. Here, shallow translational landslides are a frequent natural phenomenon and one local determinant of high levels of biodiversity. In this paper, we apply weighted ensembles of advanced phenomenological models from statistics and machine learning to analyze the driving factors of natural landslides in a tropical montane forest in South Ecuador. We exclusively interpret terrain attributes, derived from a digital elevation model, as proxies to several driving factors of landslides and use them as predictors in our models which are trained on a set of five historical landslide inventories. We check the model generality by transferring them in time and use three common performance criteria (i.e. AUC, explained deviance and slope of model calibration curve) to, on the one hand, compare several state-of-the-art model approaches and on the other hand, to create weighted model ensembles. Our results suggest that it is important to consider more than one single performance criterion.
Approaching our main question, we compare responses of weighted model ensembles that were trained on distinct functional units of landslides (i.e. initiation, transport and deposition zones). This way, we are able to show that it is quite possible to deduce driving factors of landslides, if the consistency between the training data and the processes is maintained. Opening the 'black box' of statistical models by interpreting univariate model response curves and relative importance of single predictors regarding their plausibility, we provide a means to verify this consistency.
With the exception of classification tree analysis, all techniques performed comparably well in our case study while being outperformed by weighted model ensembles. Univariate response curves of models trained on distinct functional units of landslides exposed different shapes following our expectations. Our results indicate the occurrence of landslides to be mainly controlled by factors related to the general position along a slope (i.e. ridge, open slope or valley) while landslide initiation seems to be favored by small scale convexities on otherwise plain open slopes.
Variation of deuterium excess in surface waters across a 5000-m elevation gradient in eastern Nepal
(2020)
The strong elevation gradient of the Himalaya allows for investigation of altitude and orographic impacts on surface water delta O-18 and delta D stable isotope values. This study differentiates the time- and altitude-variable contributions of source waters to the Arun River in eastern Nepal. It provides isotope data along a 5000-m gradient collected from tributaries as well as groundwater, snow, and glacial-sourced surface waters and time-series data from April to October 2016. We find nonlinear trends in delta O-18 and delta D lapse rates with high-elevation lapse rates (4000-6000 masl) 5-7 times more negative than low-elevation lapse rates (1000-3000 masl). A distinct seasonal signal in delta O-18 and delta D lapse rates indicates time-variable source-water contributions from glacial and snow meltwater as well as precipitation transitions between the Indian Summer Monsoon and Winter Westerly Disturbances. Deuterium excess correlates with the extent of snowpack and tracks melt events during the Indian Summer Monsoon season. Our analysis identifies the influence of snow and glacial melt waters on river composition during low-flow conditions before the monsoon (April/May 2016) followed by a 5-week transition to the Indian Summer Monsoon-sourced rainfall around mid-June 2016. In the post-monsoon season, we find continued influence from glacial melt waters as well as ISM-sourced groundwater.
In the last decades, an increasing number of studies analyzed spatial patterns in throughfall by means of variograms. The estimation of the variogram from sample data requires an appropriate sampling scheme: most importantly, a large sample and a layout of sampling locations that often has to serve both variogram estimation and geostatistical prediction. While some recommendations on these aspects exist, they focus on Gaussian data and high ratios of the variogram range to the extent of the study area. However, many hydrological data, and throughfall data in particular, do not follow a Gaussian distribution. In this study, we examined the effect of extent, sample size, sampling design, and calculation method on variogram estimation of throughfall data. For our investigation, we first generated non Gaussian random fields based on throughfall data with large outliers. Subsequently, we sampled the fields with three extents (plots with edge lengths of 25 m, 50 m, and 100 m), four common sampling designs (two grid-based layouts, transect and random sampling) and five sample sizes (50, 100, 150, 200, 400). We then estimated the variogram parameters by method-of-moments (non-robust and robust estimators) and residual maximum likelihood. Our key findings are threefold. First, the choice of the extent has a substantial influence on the estimation of the variogram. A comparatively small ratio of the extent to the correlation length is beneficial for variogram estimation. Second, a combination of a minimum sample size of 150, a design that ensures the sampling of small distances and variogram estimation by residual maximum likelihood offers a good compromise between accuracy and efficiency. Third, studies relying on method-of-moments based variogram estimation may have to employ at least 200 sampling points for reliable variogram estimates. These suggested sample sizes exceed the number recommended by studies dealing with Gaussian data by up to 100 %. Given that most previous through fall studies relied on method-of-moments variogram estimation and sample sizes <<200, currently available data are prone to large uncertainties. (C) 2016 Elsevier B.V. All rights reserved.
Lake Towuti is a tectonic basin, surrounded by ultramafic rocks. Lateritic soils form through weathering and deliver abundant iron (oxy)hydroxides but very little sulfate to the lake and its sediment. To characterize the sediment biogeochemistry, we collected cores at three sites with increasing water depth and decreasing bottom water oxygen concentrations. Microbial cell densities were highest at the shallow site a feature we attribute to the availability of labile organic matter (OM) and the higher abundance of electron acceptors due to oxic bottom water conditions. At the two other sites, OM degradation and reduction processes below the oxycline led to partial electron acceptor depletion. Genetic information preserved in the sediment as extracellular DNA (eDNA) provided information on aerobic and anaerobic heterotrophs related to Nitrospirae. Chloroflexi, and Therrnoplasmatales. These taxa apparently played a significant role in the degradation of sinking OM. However, eDNA concentrations rapidly decreased with core depth. Despite very low sulfate concentrations, sulfate-reducing bacteria were present and viable in sediments at all three sites, as confirmed by measurement of potential sulfate reduction rates. Microbial community fingerprinting supported the presence of taxa related to Deltaproteobacteria and Firmicutes with demonstrated capacity for iron and sulfate reduction. Concomitantly, sequences of Ruminococcaceae, Clostridiales, and Methanornicrobiales indicated potential for fermentative hydrogen and methane production. Such first insights into ferruginous sediments showed that microbial populations perform successive metabolisms related to sulfur, iron, and methane. In theory, iron reduction could reoxidize reduced sulfur compounds and desorb OM from iron minerals to allow remineralization to methane. Overall, we found that biogeochemical processes in the sediments can be linked to redox differences in the bottom waters of the three sites, like oxidant concentrations and the supply of labile OM. At the scale of the lacustrine record, our geomicrobiological study should provide a means to link the extant subsurface biosphere to past environments.
Neogene magmatism and its possible causal relationship with hydrocarbon generation in SW Colombia
(2009)
The Cretaceous oil-bearing source and reservoir sedimentary succession in the Putumayo Basin, SW Colombia, was intruded by gabbroic dykes and sills. The petrological and geochemical character of the magmatic rocks shows calc- alkaline tendency, pointing to a subduction-related magmatic event. K/Ar dating of amphibole indicates a Late Miocene to Pliocene age (6.1 +/- A 0.7 Ma) for the igneous episode in the basin. Therefore, we assume the intrusions to be part of the Andean magmatism of the Northern Volcanic Zone (NVZ). The age of the intrusions has significant tectonic and economic implications because it coincides with two regional events: (1) the late Miocene/Pliocene Andean orogenic uplift of most of the sub-Andean regions in Peru, Ecuador and Colombia and (2) a pulse of hydrocarbon generation and expulsion that has reached the gas window. High La/Yb, K/Nb and La/Nb ratios, and the obtained Sr-Nd-Pb isotopic compositions suggest the involvement of subducted sediments and/or the assimilation of oceanic crust of the subducting slab. We discuss the possibility that magma chamber(s) west of the basin, below the Cordillera, did increase the heat flow in the basin causing generation and expulsion of hydrocarbons and CO2.
Mafic magmatism in the Eastern Cordillera and Putumayo Basin, Colombia : causes and consequences
(2007)
The Eastern Cordillera of Colombia is mainly composed of sedimentary rocks deposited since early Mesozoic times. Magmatic rocks are scarce. They are represented only by a few locally restricted occurrences of dykes and sills of mafic composition presumably emplaced in the Cretaceous and of volcanic rocks of Neogene age. This work is focused on the study of the Cretaceous magmatism with the intention to understand the processes causing the genesis of these rocks and their significance in the regional tectonic setting of the Northern Andes. The magmatic rocks cut the Cretaceous sedimentary succession of black shales and marlstones that crop out in both flanks of the Eastern Cordillera. The studied rocks were classified as gabbros (Cáceres, Pacho, Rodrigoque), tonalites (Cáceres, La Corona), diorites and syenodiorites (La Corona), pyroxene-hornblende gabbros (Pacho), and pyroxene-hornblendites (Pajarito). The gabbroic samples are mainly composed of plagioclase, clinopyroxene, and/or green to brown hornblende, whereas the tonalitic rocks are mainly composed of plagioclase and quartz. The samples are highly variable in crystal sizes from fine- to coarse-grained. Accessory minerals such as biotite, titanite and zircon are present. Some samples are characterized by moderate to strong alteration, and show the presence of epidote, actinolite and chlorite. Major and trace element compositions of the rocks as well as the rock-forming minerals show significant differences in the geochemical and petrological characteristics for the different localities, suggesting that this magmatism does not result from a single melting process. The wide compositional spectrum of trace elements in the intrusions is characteristic for different degrees of mantle melting and enrichment of incompatible elements. MORB- and OIB-like compositions suggest at least two different sources of magma with tholeiitic and alkaline affinity, respectively. Evidence of slab-derived fluids can be recognized in the western part of the basin reflected in higher Ba/Nb and Sr/P ratios and also in the Sr radiogenic isotope ratios, which is possible a consequence of metasomatism in the mantle due to processes related to the presence of a previously subducted slab. The trace element patterns evidence an extensional setting in the Cretaceous basin producing a continental rift, with continental crust being stretched until oceanic crust was generated in the last stages of this extension. Electron microprobe analyses (EMPA) of the major elements and synchrotron radiation micro-X-ray fluorescence (μ-SRXRF) analyses of the trace element composition of the early crystallized minerals of the intrusions (clinopyroxenes and amphiboles) reflect the same dual character that has been found in the bulk-rock analyses. Despite the observed alteration of the rocks, the mineral composition shows evidences for an enriched and a relative depleted magma source. Even the normalization of the trace element concentrations of clinopyroxenes and amphiboles to the whole rock nearly follows the pattern predicted by published partition coefficients, suggesting that the alteration did not change the original trace element compositions of the investigated minerals. Sr-Nd-Pb isotope data reveal a large isotopic variation but still suggest an initial origin of the magmas in the mantle. Samples have moderate to highly radiogenic compositions of 143Nd/144Nd and high 87Sr/86Sr ratios and follow a trend towards enriched mantle compositions, like the local South American Paleozoic crust. The melts experienced variable degrees of contamination by sediments, crust, and seawater. The age corrected Pb isotope ratios show two separated groups of samples. This suggests that the chemical composition of the mantle below the Northern Andes has been modified by the interaction with other components resulting in a heterogeneous combination of materials of diverse origins. Although previous K/Ar age dating have shown that the magmatism took place in the Cretaceous, the high error of the analyses and the altered nature of the investigated minerals did preclude reliable interpretations. In the present work 40Ar/39Ar dating was carried out. The results show a prolonged history of magmatism during the Cretaceous over more than 60 Ma, from ~136 to ~74 Ma (Hauterivian to Campanian). Pre-Cretaceous rifting phases occurred in the Triassic-Jurassic for the western part of the basin and in the Paleozoic for the eastern part. Those previous rifting phases are decisive mechanisms controlling the localization and composition of the Cretaceous magmatism. Therefore, it is the structural position and not the age of the intrusions which preconditions the kind of magmatism and the degree of melting. The divergences on ages are the consequence of the segmentation of the basin in several sub-basins which stretching, thermal evolution and subsidence rate evolved independently. The first hypothesis formulated at the beginning of this investigation was that the Cretaceous gabbroic intrusions identified in northern Ecuador could be correlated with the intrusions described in the Eastern Cordillera. The mafic occurrences should mark the location of the most subsiding places of the large Cretaceous basin in northern South America. For this reason, the gabbroic intrusions cutting the Cretaceous succession in the Putumayo Basin, southern Colombia, were investigated. The results of the studies were quite unexpected. The petrologic and geochemical character of the magmatic rocks indicates subduction-related magmatism. K/Ar dating of amphibole yields a Late Miocene to Pliocene age (6.1 ± 0.7 Ma) for the igneous event in the basin. Although there is no correlation between this magmatic event and the Cretaceous magmatic event, the data obtained has significant tectonic and economic implications. The emplacement of the Neogene gabbroic rocks coincides with the late Miocene/Pliocene Andean orogenic uplift as well as with a significant pulse of hydrocarbon generation and expulsion.
Cenozoic magnetostratigraphy and magnetic properties of the southern Issyk-Kul basin, Kyrgyzstan
(2014)
We present paleomagnetic data from the northern flank of the Tianshan range, southeast of Lake Issyk-Kul (Kyrgyzstan). 613 cores were collected in two parallel sections with a total thickness of 960 m (Chon Kyzylsuu, CK) and 990 m Jeti Oguz, JO), as well as 48 cores at six sites in a nearby anticline. Rock magnetic analyses identify both magnetite and hematite in the fluvial-lacustrine sediments. The concentration of both minerals, the magnetite:hematite ratio, and the average magnetite grain size increase upward in both sections. Anisotropy of anhysteretic remanent magnetization defines a tectonic fabric with sub-horizontal maximum axes that parallel the strike direction together with intermediate and minimum axes that streak out about a great circle orthogonal to the maximum axes suggestive of a tectonic fabric emplaced during folding. Stepwise thermal demagnetization isolates interpretable magnetization components in 284 samples that define 26 polarity chrons in CK and 19 in JO. A positive fold test, dual polarities and systematic changes in rock-magnetic parameters with depth suggest that the high temperature magnetization component was acquired coevally with deposition. An age model based on a visual magnetostratigraphic correlation of both sections with the geomagnetic polarity time scale defines absolute ages from 26.0 to 13.3 Ma, with a fairly constant sedimentation rate of 9-10 cm/ka. A correlation based on a numerical algorithm arrives at a slightly different conclusion, with deposition ages from 25.2 to 11.0 Ma and sedimentation rates from 5 to 8 cm/ka. In comparison with sedimentation rates found at other magnetostratigraphic sections in the Tianshan realm, we infer that the sedimentary record in this part of the Issyk-Kul Basin precedes the more rapid phase of uplift of the Kyrgyz Tianshan. The onset of deposition and concomitant erosion of the adjacent Terskey Range is in good agreement with independent assessments of the exhumation history of this mountain range, with erosion increasing at 25-20 Ma and accelerating after 11-13 Ma. (C) 2014 Elsevier B.V. All rights reserved.
The nature restoration project ‘Lenzener Elbtalaue’, realised from 2002 to 2011 at the river Elbe, included the first large scale dike relocation in Germany (420 ha). Its aim was to initiate the development of endangered natural wetland habitats and processes, accompanied by greater biodiversity in the former grassland dominated area. The monitoring of spatial and temporal variations of soil moisture in this dike relocation area is therefore particularly important for estimating the restoration success. The topsoil moisture monitoring from 1990 to 2017 is based on the Soil Moisture Index (SMI)1 derived with the triangle method2 by use of optical remotely sensed data: land surface temperature and Normalized Differnce Vegetation Index are calculated from Landsat 4/5/7/8 data and atmospheric corrected by use of MODIS data. Spatial and temporal soil moisture variations in the restored area of the dike relocation are compared to the agricultural and pasture area behind the new dike. Ground truth data in the dike relocation area was obtained from field measurements in October 2017 with a FDR device. Additionally, data from a TERENO soil moisture sensor network (SoilNet) and mobile cosmic ray neutron sensing (CRNS) rover measurements are compared to the results of the triangle method for a region in the Harz Mountains (Germany). The SMI time series illustrates, that the dike relocation area has become significantly wetter between 1990 and 2017, due to restructuring measurements. Whereas the SMI of the dike hinterland reflects constant and drier conditions. An influence of climate is unlikely. However, validation of the dimensionless index with ground truth measurements is very difficult, mostly due to large differences in scale.
Agriculture is one of the most important human activities providing food and more agricultural goods for seven billion people around the world and is of special importance in sub-Saharan Africa. The majority of people depends on the agricultural sector for their livelihoods and will suffer from negative climate change impacts on agriculture until the middle and end of the 21st century, even more if weak governments, economic crises or violent conflicts endanger the countries’ food security. The impact of temperature increases and changing precipitation patterns on agricultural vegetation motivated this thesis in the first place. Analyzing the potentials of reducing negative climate change impacts by adapting crop management to changing climate is a second objective of the thesis. As a precondition for simulating climate change impacts on agricultural crops with a global crop model first the timing of sowing in the tropics was improved and validated as this is an important factor determining the length and timing of the crops´ development phases, the occurrence of water stress and final crop yield. Crop yields are projected to decline in most regions which is evident from the results of this thesis, but the uncertainties that exist in climate projections and in the efficiency of adaptation options because of political, economical or institutional obstacles have to be considered. The effect of temperature increases and changing precipitation patterns on crop yields can be analyzed separately and varies in space across the continent. Southern Africa is clearly the region most susceptible to climate change, especially to precipitation changes. The Sahel north of 13° N and parts of Eastern Africa with short growing seasons below 120 days and limited wet season precipitation of less than 500 mm are also vulnerable to precipitation changes while in most other part of East and Central Africa, in contrast, the effect of temperature increase on crops overbalances the precipitation effect and is most pronounced in a band stretching from Angola to Ethiopia in the 2060s. The results of this thesis confirm the findings from previous studies on the magnitude of climate change impact on crops in sub-Saharan Africa but beyond that helps to understand the drivers of these changes and the potential of certain management strategies for adaptation in more detail. Crop yield changes depend on the initial growing conditions, on the magnitude of climate change, and on the crop, cropping system and adaptive capacity of African farmers which is only now evident from this comprehensive study for sub-Saharan Africa. Furthermore this study improves the representation of tropical cropping systems in a global crop model and considers the major food crops cultivated in sub-Saharan Africa and climate change impacts throughout the continent.
Surveys for more than 9,500 households were conducted in the growing seasons 2002/2003 or 2003/2004 in eleven African countries: Burkina Faso, Cameroon, Ghana, Niger and Senegal in western Africa; Egypt in northern Africa; Ethiopia and Kenya in eastern Africa; South Africa, Zambia and Zimbabwe in southern Africa. Households were chosen randomly in districts that are representative for key agro-climatic zones and farming systems. The data set specifies farming systems characteristics that can help inform about the importance of each system for a country’s agricultural production and its ability to cope with short- and long-term climate changes or extreme weather events. Further it informs about the location of smallholders and vulnerable systems and permits benchmarking agricultural systems characteristics.
The determination of the total carbon storage of peatlands is of high relevance in the context of climate-change mitigation efforts. This determination relies on data about stratigraphy and peat properties, which are conventionally collected by coring. Ground-penetrating radar (GPR) and electrical resistivity imaging (ERI) can support these point data by providing subsoil information in two-dimensional cross-sections. In this study, GPR and ERI were conducted at two groundwater-fed fen sites located in the temperate zone in north-east Germany. The fens of this region are embedded in low conductive glacial sand and are characterised by thick layers of gyttja, which can be either mineral or organic. The two study sites are representative of this region with respect to stratigraphy (total thickness, peat and gyttja types) and ecological conditions (pH-value, trophic condition). The aim of this study is to assess the suitability of GPR and ERI to detect stratigraphy and peat properties under these characteristic site conditions. Results show that GPR clearly detects the interfaces between (i) Carex and brown-moss peat, (ii) brown-moss peat and organic gyttja, (iii) organic- and mineral gyttja, and (iv) mineral gyttja and the parent material (glacial sand). These layers differ in bulk density and the related organic matter content. ERI, however, does not delineate these layers; rather it delineates regions of varying properties. At our base-rich site, pore fluid conductivity and cation.exchange capacity are the main factors that determine peat electrical conductivity (reverse of resistivity), whereas organic matter and water content are most influential at the more acidic site. Thus the correlation between peat properties and electrical conductivity are driven by site-specific conditions, which are mainly determined by the solute load in the groundwater at fens. When the total organic deposits exceed a thickness of 5 m, the depth of investigation by GPR is limited due to increasing attenuation. This is not a limiting factor for ERI, where the transition from organic deposits to glacial sand is visible at both sites. Due to these specific sensitivities, a combined application of GPR and ERI meets the demand for up-to-date information on carbon storage of peatlands, which is, moreover, very site-specific because of the inherent variety of ecological conditions and stratigraphy between peatlands in general and between fens and bogs in particular. (C) 2016 Elsevier B.V. All rights reserved.
The application of electrical resistivity tomography to peatlands supports conventional coring by providing data on the current condition of peatlands, including data on stratigraphy, peat properties and thickness of organic deposits. Data on the current condition of drained peatlands are particularly required to improve estimates of carbon storage as well as losses and emissions from agriculturally used peatlands. However, most of the studies focusing on electrical resistivity tomography surveys have been conducted on natural peatlands with higher groundwater levels. Peatlands drained for agriculture have not often been studied using geophysical techniques. Drained sites are characterized by low groundwater levels and high groundwater fluctuations during the year, which lead to varying levels of water saturation. To validate better electrical resistivity tomography surveys of drained peatlands, the aim of this laboratory study is to investigate the influence of varying water saturation levels on electrical conductivity (reciprocal of resistivity) for a variety of peat and gyttja types, as well as for different degrees of peat decomposition. Results show that different levels of water saturation strongly influence bulk electrical conductivity. Distinct differences in this relationship exist between peat and gyttja substrates and between different degrees of peat decomposition. Peat shows an exponential relationship for all degrees of decomposition, whereas gyttja, in particular organic-rich gyttja, is characterized by a rather unimodal relationship. The slopes for the relationship between electrical conductivity and water content are steeper at high degrees of decomposition than for peat of low degrees of decomposition. These results have direct implications for field electrical resistivity tomography surveys. In drained peatlands that are strongly susceptible to drying, electrical resistivity tomography surveys have a high potential to monitor the actual field water content. In addition, at comparable water saturations, high or low degrees of decomposition can be inferred from electrical conductivity.
Multi-scale analysis of electrical conductivity of peatlands for the assessment of peat properties
(2015)
Peatlands store large amounts of carbon. This storage function has been reduced through intensive drainage, which leads to the decomposition of peat, resulting in a loss of carbon. Measurements of the real (sigma) and imaginary part (sigma) of electrical conductivity can deliver information on peat properties, such as the pore fluid conductivity (sigma(w)), cation exchange capacity (CEC), bulk density ((b)), water content (WC) and soil organic matter (SOM) content. These properties change with the peat's degree of decomposition (DD). To explore the relationships between the peat properties, sigma, sigma and DD, we focused on three different types of survey and scales. First, point measurements were made with a conductivity probe at various locations over a large area of northeast Germany to determine the degree of correlation between sigma and DD. Second, nine of these locations were selected for sampling to determine which of the properties sigma(w), CEC, (b), WC and SOM predominantly influence sigma and sigma. This multisite dataset includes the entire range of DD and was analysed in the laboratory. Third, one site was selected for a survey of sigma including sampling, to identify which properties mainly control sigma in a single-site approach. Statistical analysis revealed that for the multisite laboratory dataset, sigma(w) has the strongest effect on sigma, followed by CEC, whereas sigma is mainly determined by CEC. In a single-site approach, WC followed by CEC had a dominant effect on sigma. No clear correlation could be observed between (i) DD and peat properties and (ii) DD and sigma or sigma. This is because of the complex changes in properties with increasing DD.
The Pleistocene archeological record in East Africa has revealed unusual accumulations of Acheulean handaxes at prehistoric sites. In particular, there has been intensive debate concerning whether the artifact accumulation at the Middle Pleistocene Olorgesailie (Southern Kenya Rift) and Kariandusi (Central Kenya Rift) sites were a result of fluvial reworking or of in situ deposition by hominids. We used a two-step approach to test the hypothesis of fluvial reworking. Firstly, the behavior of handaxes in water currents was investigated in a current flume and the flow threshold required to reorientate the handaxes was determined. The results of these experiments suggested that, in relatively high energy and non-steady flow conditions, handaxes will reorientate themselves perpendicular to the current direction. Secondly, an automated image analysis routine was developed and applied to archeological plans from three Acheulean sites, two at Olorgesailie and one at Kariandusi, in order to determine the orientations of the handaxes. A Rayleigh test was then applied to the orientation data to test for a preferred orientation. The results revealed that the handaxes at the Upper Kariandusi Site and the Olorgesailie Main Site Mid Trench had a preferential orientation, suggesting reworking by a paleocurrent. The handaxes from the Olorgesailie Main Site H/6A, however, appeared to be randomly oriented and in situ deposition by the producers therefore remains a possibility.
Interannual variations in ecosystem primary productivity are dominated by water availability. Until recently, characterizing the photosynthetic response of different ecosystems to soil moisture anomalies was hampered by observational limitations. Here, we use a number of satellite-based proxies for productivity, including spectral indices, sun-induced chlorophyll fluorescence, and data-driven estimates of gross primary production, to reevaluate the relationship between terrestrial photosynthesis and water. In contrast to nonwoody vegetation, we find a resilience of forested ecosystems to reduced soil moisture. Sun-induced chlorophyll fluorescence and data-driven gross primary production indicate an increase in photosynthesis as a result of the accompanying higher amounts of light and temperature despite lowered light-use-efficiency. Conversely, remote sensing indicators of greenness reach their detection limit and largely remain stable. Our study thus highlights the differential responses of ecosystems along a tree cover gradient and illustrates the importance of differentiating photosynthesis indicators from those of greenness for the monitoring and understanding of ecosystems. Plain Language Summary The capacity of vegetation to thrive and to sequester carbon depends on how much water they can have access to. In this work, we evaluate how different types of satellite observations can describe the response of vegetation to changes in soil moisture over the entire planet. The first source of observation measures only the greenness of the land surface, the second measures light that is emitted by pigments in plants which are photosynthetically active (chlorophyll fluorescence), and the third are simulations of gross carbon uptake derived from machine learning techniques. For periods of water shortage all three indicate a reduction of growth in ecosystems with few trees. However, in cold boreal forests, when soil moisture is particularly low, we still detect an increase in photosynthesis due to higher light and temperature conditions, but this is not reflected in the greenness indicator. This work illustrates how lack of water is not necessarily harmful for catching carbon through photosynthesis, but to monitor this effect, we need remote sensing indicators that measure more than just how green the plants are, and fluorescence is likely a good candidate.
High-latitude treeless ecosystems represent spatially highly heterogeneous landscapes with small net carbon fluxes and a short growing season. Reliable observations and process understanding are critical for projections of the carbon balance of the climate-sensitive tundra. Space-borne remote sensing is the only tool to obtain spatially continuous and temporally resolved information on vegetation greenness and activity in remote circumpolar areas. However, confounding effects from persistent clouds, low sun elevation angles, numerous lakes, widespread surface inundation, and the sparseness of the vegetation render it highly challenging. Here, we conduct an extensive analysis of the timing of peak vegetation productivity as shown by satellite observations of complementary indicators of plant greenness and photosynthesis. We choose to focus on productivity during the peak of the growing season, as it importantly affects the total annual carbon uptake. The suite of indicators are as follows: (1) MODIS-based vegetation indices (VIs) as proxies for the fraction of incident photosynthetically active radiation (PAR) that is absorbed (fPAR), (2) VIs combined with estimates of PAR as a proxy of the total absorbed radiation (APAR), (3) sun-induced chlorophyll fluorescence (SIF) serving as a proxy for photosynthesis, (4) vegetation optical depth (VOD), indicative of total water content and (5) empirically upscaled modelled gross primary productivity (GPP). Averaged over the pan-Arctic we find a clear order of the annual peak as APAR <= GPP < SIF < VIs/VOD. SIF as an indicator of photosynthesis is maximised around the time of highest annual temperatures. The modelled GPP peaks at a similar time to APAR. The time lag of the annual peak between APAR and instantaneous SIF fluxes indicates that the SIF data do contain information on light-use efficiency of tundra vegetation, but further detailed studies are necessary to verify this. Delayed peak greenness compared to peak photosynthesis is consistently found across years and land-cover classes. A particularly late peak of the normalised difference vegetation index (NDVI) in regions with very small seasonality in greenness and a high amount of lakes probably originates from artefacts. Given the very short growing season in circumpolar areas, the average time difference in maximum annual photosynthetic activity and greenness or growth of 3 to 25 days (depending on the data sets chosen) is important and needs to be considered when using satellite observations as drivers in vegetation models.
High-latitude treeless ecosystems represent spatially highly heterogeneous landscapes with small net carbon fluxes and a short growing season. Reliable observations and process understanding are critical for projections of the carbon balance of the climate-sensitive tundra. Space-borne remote sensing is the only tool to obtain spatially continuous and temporally resolved information on vegetation greenness and activity in remote circumpolar areas. However, confounding effects from persistent clouds, low sun elevation angles, numerous lakes, widespread surface inundation, and the sparseness of the vegetation render it highly challenging. Here, we conduct an extensive analysis of the timing of peak vegetation productivity as shown by satellite observations of complementary indicators of plant greenness and photosynthesis. We choose to focus on productivity during the peak of the growing season, as it importantly affects the total annual carbon uptake. The suite of indicators are as follows: (1) MODIS-based vegetation indices (VIs) as proxies for the fraction of incident photosynthetically active radiation (PAR) that is absorbed (fPAR), (2) VIs combined with estimates of PAR as a proxy of the total absorbed radiation (APAR), (3) sun-induced chlorophyll fluorescence (SIF) serving as a proxy for photosynthesis, (4) vegetation optical depth (VOD), indicative of total water content and (5) empirically upscaled modelled gross primary productivity (GPP). Averaged over the pan-Arctic we find a clear order of the annual peak as APAR ≦ GPP<SIF<VIs/VOD. SIF as an indicator of photosynthesis is maximised around the time of highest annual temperatures. The modelled GPP peaks at a similar time to APAR. The time lag of the annual peak between APAR and instantaneous SIF fluxes indicates that the SIF data do contain information on light-use efficiency of tundra vegetation, but further detailed studies are necessary to verify this. Delayed peak greenness compared to peak photosynthesis is consistently found across years and land-cover classes. A particularly late peak of the normalised difference vegetation index (NDVI) in regions with very small seasonality in greenness and a high amount of lakes probably originates from artefacts. Given the very short growing season in circumpolar areas, the average time difference in maximum annual photosynthetic activity and greenness or growth of 3 to 25 days (depending on the data sets chosen) is important and needs to be considered when using satellite observations as drivers in vegetation models.
Scenario analysis is a widely used approach to incorporate uncertainties in global change research. In the context of regional ecosystem service and landscape management where global IPCC climate simulations and their downscaled derivates are applied, it can be useful to work with regional sodo-economic scenarios that are coherent with the global IPCC scenarios. The consistency with the original source scenarios, transparency and reproducibility of the methods used as well as the internal consistency of the derived scenarios are important methodological prerequisites for coherently downscaling pre-existing source scenarios. In contrast to well-established systematic-qualitative scenario techniques, we employ here a formal technique of scenario construction which combines expert judgement with a quantitative, indicator-based selection algorithm in order to deduce a formally consistent set of focus scenario. In our case study, these focus scenarios reflect the potential development pathways of major national-level drivers for ecosystem service management in Swiss mountain regions. The integration of an extra impact factor ("Global Trends") directly referring to the four principle SRES scenario families, helped us to formally internalise base assumptions of IPCC SRES scenarios to regional scenarios that address a different thematic focus (ecosystem service management), spatial level (national) and time horizon (2050). Compared to the well-established systematic-qualitative approach, we find strong similarities between the two methods, including the susceptibility to personal judgement which is only partly reduced by the formal method. However, the formalised scenario approach conveys four clear advantages, (1) the better documentation of the process, (2) its reproducibility, (3) the openness in terms of the number and directions of the finally selected set of scenarios, and (4) its analytical power. (C) 2013 Elsevier Inc. All rights reserved.
Sociocultural valuation (SCV) of ecosystem services (ES) discloses the principles, importance or preferences expressed by people towards nature. Although ES research has increasingly addressed sociocultural values in past years, little effort has been made to systematically review the components of sociocultural valuation applications for different decision contexts (i.e. awareness raising, accounting, priority setting, litigation and instrument design). In this analysis, we investigate the characteristics of 48 different sociocultural valuation applications—characterised by unique combinations of decision context, methods, data collection formats and participants—across ten European case studies. Our findings show that raising awareness for the sociocultural value of ES by capturing people’s perspective and establishing the status quo, was found the most frequent decision context in case studies, followed by priority setting and instrument development. Accounting and litigation issues were not addressed in any of the applications. We reveal that applications for particular decision contexts are methodologically similar, and that decision contexts determine the choice of methods, data collection formats and participants involved. Therefore, we conclude that understanding the decision context is a critical first step to designing and carrying out fit-for-purpose sociocultural valuation of ES in operational ecosystem management.
Many hydrological models have been calibrated and validated using hydrographs alone. Because streamflow integrates water fluxes in space, many distributed hydrological models tend to have multiple feasible descriptions of hydrological processes. This equifinality usually leads to substantial prediction uncertainty. In this study, additional constraintsnamely, the spatial patterns of long-term average evapotranspiration (ET), shallow groundwater level, and land cover changewere used to investigate the reduction of equifinality and prediction uncertainty in the Soil and Water Assessment Tool (SWAT) in the Wami River basin in Tanzania. The additional constraints were used in the set-up, parameter emulation and calibration of the SWAT model termed an improved hydrological model (IHM). The IHM was then compared with a classical hydrological model (CHM) that was also developed using the SWAT model but without additional constraints. In the calibration, the CHM used only the hydrograph, but the IHM used the hydrograph and the spatial pattern of long-term average ET as an additional constraint. The IHM produced a single, unique behavioural simulation, whereas the CHM produced many behavioural simulations that resulted in prediction uncertainty. The performance of the IHM with respect to the hydrograph was more consistent than that of the CHM, and the former clearly captured the mean behaviour of ET in the river basin. Therefore, we conclude that additional constraints substantially reduce equifinality and prediction uncertainty in a distributed hydrological model.
Information about the hydrological behaviour of a river basin prior to setting up, calibrating and validating a distributed hydrological model requires extensive datasets that are hardly available for many parts of the world due to insufficient monitoring networks. In this study, the focus was on prevailing spatio-temporal patterns of remotely sensed evapotranspiration (ET) that enabled conclusions to be drawn about the hydrological behaviour and spatial peculiarities of a river basin at rather high spatial resolution. The prevailing spatio-temporal patterns of ET were identified using a principal component analysis of a time series of 644 images of MODIS ET covering the Wami River basin (Tanzania) between the years 2000 and 2013. The time series of the loadings on the principal components were analysed for seasonality and significant long-term trends. The spatial patterns of principal component scores were tested for significant correlation with elevations and slopes, and for differences between different soil texture and land use classes. The results inferred that the temporal and spatial patterns of ET were related to those of preceding rainfalls. At the end of the dry season, high ET was maintained only in areas of shallow groundwater and in cloud forest nature reserves. A region of clear reduction of ET in the long-term was related to massive land use change. The results also confirmed that most soil texture and land use classes differed significantly. Moreover, ET was exceptionally high in natural forests and loam soil, and very low in bushland and sandy-loam soil. Clearly, this approach has shown great potential of publicly available remote sensing data in providing a sound basis for water resources management as well as for distributed hydrological models in data-scarce river basins at lower latitudes.
In this study, we developed an autodetection technique for the equatorial plasma depletions (EPDs) and their occurrence and depletion amplitudes based on in situ electron density measurements gathered by Swarm A satellite. For the first time, comparisons are made among the detected EPDs and their amplitudes with the loss of Global Positioning System (GPS) signal of receivers onboard Swarm A, and the Swarm Level-2 product, Ionospheric Bubble Index (IBI). It has been found that the highest rate of EPD occurrence takes place generally between 2200 and 0000 magnetic local time (MLT), in agreement with the IBI. However, the largest amplitudes of EPD are detected earlier at about 1900-2100 MLT. This coincides with the moment of higher background electron density and the largest occurrence of GPS signal loss. From a longitudinal perspective, the higher depletion amplitude is always witnessed in spatial bins with higher background electron density. At most longitudes, the occurrence rate of postmidnight EPDs is reduced compared to premidnight ones; while more postmidnight EPDs are observed at African longitudes. CHAMP observations confirm this point regardless of high or low solar activity condition. Further by comparing with previous studies and the plasma vertical drift velocity from ROCSAT-1, we suggest that while the F region vertical plasma drift plays a key role in dominating the occurrence of EPDs during premidnight hours, the postmidnight EPDs are the combined results from the continuing of former EPDs and newborn EPDs, especially during June solstice. And these newborn EPDs during postmidnight hours seem to be less related to the plasma vertical drift.
BACKROUND: Few studies have been carried out to connect nutrients recovery from wastewater and heavy metals immobilization in contaminated soil. To achieve the goal, ammonia nitrogen (AN) and phosphorus (P) were recovered from rare-earth wastewater by using the formation of struvite, which was used as the amendment with plant ash for copper, lead and chromium immobilization. RESULTS: AN removal efficiency and residual P reached 95.32 +/- 0.73% and 6.14 +/- 1.72mgL(-1) under optimal conditions: pH= 9.0, n(Mg): n(N): n(P)= 1.2: 1: 1.1, which were obtained using response surface methodology (RSM). The minimum available concentrations of Cu, Pb and Cr (CPC) separately reduced to 320.82 mg kg(-1), 190.77 mg kg(-1) and 121.46 mg kg(-1) with increasing immobilization time at the mass ratio of phosphate precipitate (PP)/plant ash (PA) of 1: 3. Humic acid (HA) and fulvic acid (FA) were beneficial to immobilize Cu, both of which showed no effect or even a negative effect on Pb and Cr immobilization.
The change of the mechanical properties of granular materials with pressure is an important topic associated with many industrial applications. In this paper we investigate the influence of hydrostatic pressure (P-e) on the effective bulk compressibility (C-eff) of a granular material by applying two modified theoretical approaches that are based on contact mechanics and micromechanics, respectively. For a granular material composed of rough grains, an extended contact model is developed to elucidate the effect of roughness of grain surfaces on bulk compressibility. At relatively low pressures, the model predicts that the decrease of bulk compressibility with pressure may be described by a power law with an exponent of -1/2 (i.e., C-eff proportional to P-e(1/2) ), but deviates at intermediate pressures. At elevated pressures beyond full contact, bulk compressibility remains almost unchanged, which may be roughly evaluated by continuum contact mechanics. As an alternative explanation of pressure-dependent bulk compressibility, we suggest a micromechanical model that accounts for effects of different types of pore space present in granular materials. Narrow and compliant inter-granular cracks are approximated by three-dimensional oblate spheroidal cracks with rough surfaces, whereas the equant and stiff pores surrounded by three and four neighboring grains are modeled as tubular pores with cross sections of three and four cusp-like corners, respectively. In this model, bulk compressibility is strongly reduced with increasing pressure by progressive closure of rough-walled cracks. At pressures exceeding crack closure pressure, deformation of the remaining equant pores is largely insensitive to pressure, with almost no further change in bulk compressibility. To validate these models, we performed hydrostatic compression tests on Bentheim sandstone (a granular rock consisting of quartz with high porosity) under a wide range of pressure. The relation between observed microstructures and measured pressure-dependent bulk compressibility is well explained by both suggested models.
Understanding the relation between injection-induced seismic moment release and operational parameters is crucial for early identification of possible seismic hazards associated with fluid-injection projects. We conducted laboratory fluid-injection experiments on permeable sandstone samples containing a critically stressed fault at different fluid pressurization rates. The observed fluid-induced fault deformation is dominantly aseismic. Fluid-induced stick-slip and fault creep reveal that total seismic moment release of acoustic emission (AE) events is related to total injected volume, independent of respective fault slip behavior. Seismic moment release rate of AE scales with measured fault slip velocity. For injection-induced fault slip in a homogeneous pressurized region, released moment shows a linear scaling with injected volume for stable slip (steady slip and fault creep), while we find a cubic relation for dynamic slip. Our results highlight that monitoring evolution of seismic moment release with injected volume in some cases may assist in discriminating between stable slip and unstable runaway ruptures.
Knowledge of pressure-dependent static and dynamic moduli of porous reservoir rocks is of key importance for evaluating geological setting of a reservoir in geo-energy applications. We examined experimentally the evolution of static and dynamic bulk moduli for porous Bentheim sandstone with increasing confining pressure up to about 190 MPa under dry and water-saturated conditions. The static bulk moduli (K-s) were estimated from stress-volumetric strain curves while dynamic bulk moduli (K-d) were derived from the changes in ultrasonic P- and S- wave velocities (similar to 1 MHz) along different traces, which were monitored simultaneously during the entire deformation. In conjunction with published data of other porous sandstones (Berea, Navajo and Weber sandstones), our results reveal that the ratio between dynamic and static bulk moduli (K-d/K-s) reduces rapidly from about 1.5 - 2.0 at ambient pressure to about 1.1 at high pressure under dry conditions and from about 2.0 - 4.0 to about 1.5 under water-saturated conditions, respectively. We interpret such a pressure-dependent reduction by closure of narrow (compliant) cracks, highlighting thatK(d)/K(s)is positively correlated with the amount of narrow cracks. Above the crack closure pressure, where equant (stiff) pores dominate the void space,K-d/K(s)is almost constant. The enhanced difference between dynamic and static bulk moduli under water saturation compared to dry conditions is possibly caused by high pore pressure that is locally maintained if measured using high-frequency ultrasonic wave velocities. In our experiments, the pressure dependence of dynamic bulk modulus of water-saturated Bentheim sandstone at effective pressures above 5 MPa can be roughly predicted by both the effective medium theory (Mori-Tanaka scheme) and the squirt-flow model. Static bulk moduli are found to be more sensitive to narrow cracks than dynamic bulk moduli for porous sandstones under dry and water-saturated conditions.
Due to large uncertainties and non-uniqueness in fault slip inversion, the investigation of stress coupling based on the direct comparison of independent slip inversions, for example, between the coseismic slip distribution and the interseismic slip deficit, may lead to ambiguous conclusions. In this study, we therefore adopt the stress-constrained joint inversion in the Bayesian approach of Wang et al., and implement the physical hypothesis of stress coupling as a prior. We test the hypothesis that interseismic locking is coupled with the coseismic rupture, and the early post-seismic deformation is a stress relaxation process in response to the coseismic stress perturbation. We characterize the role of stress coupling in the seismic cycle by evaluating the efficiency of the model to explain the available data. Taking the 2004 M6 Parkfield earthquake as a study case, we find that the stress coupling hypothesis is in agreement with the data. The coseismic rupture zone is found to be strongly locked during the interseismic phase and the post-seismic slip zone is indicated to be weakly creeping. The post-seismic deformation plays an important role to rebuild stress in the coseismic rupture zone. Based on our results for the stress accumulation during both inter- and post-seismic phase in the coseismic rupture zone, together with the coseismic stress drop, we estimate a recurrence time of M6 earthquake in Parkfield around 23-41 yr, suggesting that the duration of 38 yr between the two recent M6 events in Parkfield is not a surprise.
The Himalayan mountains are dissected by some of the deepest and most impressive gorges on Earth. Constraining the interplay between river incision and rock uplift is important for understanding tectonic deformation in this region. We report here the discovery of a deeply incised canyon of the Yarlung Tsangpo River, at the eastern end of the Himalaya, which is now buried under more than 500 meters of sediments. By reconstructing the former valley bottom and dating sediments at the base of the valley fill, we show that steepening of the Tsangpo Gorge started at about 2 million to 2.5 million years ago as a consequence of an increase in rock uplift rates. The high erosion rates within the gorge are therefore a direct consequence of rapid rock uplift.