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Institute
- Institut für Geowissenschaften (116) (remove)
Fluvial planation surfaces, such as straths, commonly serve as recorders of climatic and tectonic changes and are formed by the lateral erosion of rivers, a process that remains poorly understood. Here we present a study of kilometer-wide, fluvially eroded, low-relief surfaces on rapidly uplifting folds in the foreland of the southwestern Tian Shan. A combination of field work, digital elevation model analysis, and dating of fluvial deposits reveals that despite an arid climate and rapid average rock-uplift rates of 1-3mm/yr, rivers cut extensive (>1-2km wide) surfaces with typical height variations of <6m over periods of >2-6kyr. The extent of this beveling varies in space and time, such that different beveling episodes affect individual structures. Between times of planation, beveled surfaces are abandoned, incised, and deformed across the folds. In a challenge to models that link strath cutting and abandonment primarily to changes in river incision rates, we demonstrate that lateral erosion rates of antecedent streams crossing the folds have to vary by more than 1 order of magnitude to explain the creation of beveled platforms in the past and their incision at the present day. These variations do not appear to covary with climate variability and might be caused by relatively small (much less than an order of magnitude) changes in sediment or water fluxes. It remains uncertain in which settings variations in lateral bedrock erosion rates predominate over changes in vertical erosion rates. Therefore, when studying fluvial planation and strath terraces, variability of both lateral and vertical erosion rates should be considered.
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 this study, we validate and compare elevation accuracy and geomorphic metrics of satellite-derived digital elevation models (DEMs) on the southern Central Andean Plateau. The plateau has an average elevation of 3.7 km and is characterized by diverse topography and relief, lack of vegetation, and clear skies that create ideal conditions for remote sensing. At 30m resolution, SRTM-C, ASTER GDEM2, stacked ASTER L1A stereopair DEM, ALOS World 3D, and TanDEM-X have been analyzed. The higher-resolution datasets include 12m TanDEM-X, 10m single-CoSSC TerraSAR-X/TanDEM-X DEMs, and 5m ALOS World 3D. These DEMs are state of the art for optical (ASTER and ALOS) and radar (SRTM-C and TanDEM-X) spaceborne sensors. We assessed vertical accuracy by comparing standard deviations of the DEM elevation versus 307 509 differential GPS measurements across 4000m of elevation. For the 30m DEMs, the ASTER datasets had the highest vertical standard deviation at > 6.5 m, whereas the SRTM-C, ALOS World 3D, and TanDEM-X were all < 3.5 m. Higher-resolution DEMs generally had lower uncertainty, with both the 12m TanDEM-X and 5m ALOSWorld 3D having < 2m vertical standard deviation. Analysis of vertical uncertainty with respect to terrain elevation, slope, and aspect revealed the low uncertainty across these attributes for SRTM-C (30 m), TanDEM-X (12–30 m), and ALOS World 3D (5–30 m). Single-CoSSC TerraSAR-X/TanDEM-X 10m DEMs and the 30m ASTER GDEM2 displayed slight aspect biases, which were removed in their stacked counterparts (TanDEM-X and ASTER Stack). Based on low vertical standard deviations and visual inspection alongside optical satellite data, we selected the 30m SRTM-C, 12–30m TanDEM-X, 10m single-CoSSC TerraSAR-X/TanDEM-X, and 5m ALOS World 3D for geomorphic metric comparison in a 66 km2 catchment with a distinct river knickpoint. Consistent m=n values were found using chi plot channel profile analysis, regardless of DEM type and spatial resolution. Slope, curvature, and drainage area were calculated and plotting schemes were used to assess basin-wide differences in the hillslope-to-valley transition related to the knickpoint. While slope and hillslope length measurements vary little between datasets, curvature displays higher magnitude measurements with fining resolution. This is especially true for the optical 5m ALOS World 3D DEM, which demonstrated high-frequency noise in 2–8 pixel steps through a Fourier frequency analysis. The improvements in accurate space-radar DEMs (e.g., TanDEM-X) for geomorphometry are promising, but airborne or terrestrial data are still necessary for meter-scale analysis.
In this study, we validate and compare elevation accuracy and geomorphic metrics of satellite-derived digital elevation models (DEMs) on the southern Central Andean Plateau. The plateau has an average elevation of 3.7 km and is characterized by diverse topography and relief, lack of vegetation, and clear skies that create ideal conditions for remote sensing. At 30m resolution, SRTM-C, ASTER GDEM2, stacked ASTER L1A stereopair DEM, ALOS World 3D, and TanDEM-X have been analyzed. The higher-resolution datasets include 12m TanDEM-X, 10m single-CoSSC TerraSAR-X/TanDEM-X DEMs, and 5m ALOS World 3D. These DEMs are state of the art for optical (ASTER and ALOS) and radar (SRTM-C and TanDEM-X) spaceborne sensors. We assessed vertical accuracy by comparing standard deviations of the DEM elevation versus 307 509 differential GPS measurements across 4000m of elevation. For the 30m DEMs, the ASTER datasets had the highest vertical standard deviation at > 6.5 m, whereas the SRTM-C, ALOS World 3D, and TanDEM-X were all < 3.5 m. Higher-resolution DEMs generally had lower uncertainty, with both the 12m TanDEM-X and 5m ALOSWorld 3D having < 2m vertical standard deviation. Analysis of vertical uncertainty with respect to terrain elevation, slope, and aspect revealed the low uncertainty across these attributes for SRTM-C (30 m), TanDEM-X (12–30 m), and ALOS World 3D (5–30 m). Single-CoSSC TerraSAR-X/TanDEM-X 10m DEMs and the 30m ASTER GDEM2 displayed slight aspect biases, which were removed in their stacked counterparts (TanDEM-X and ASTER Stack). Based on low vertical standard deviations and visual inspection alongside optical satellite data, we selected the 30m SRTM-C, 12–30m TanDEM-X, 10m single-CoSSC TerraSAR-X/TanDEM-X, and 5m ALOS World 3D for geomorphic metric comparison in a 66 km2 catchment with a distinct river knickpoint. Consistent m=n values were found using chi plot channel profile analysis, regardless of DEM type and spatial resolution. Slope, curvature, and drainage area were calculated and plotting schemes were used to assess basin-wide differences in the hillslope-to-valley transition related to the knickpoint. While slope and hillslope length measurements vary little between datasets, curvature displays higher magnitude measurements with fining resolution. This is especially true for the optical 5m ALOS World 3D DEM, which demonstrated high-frequency noise in 2–8 pixel steps through a Fourier frequency analysis. The improvements in accurate space-radar DEMs (e.g., TanDEM-X) for geomorphometry are promising, but airborne or terrestrial data are still necessary for meter-scale analysis.
In this study, we validate and compare elevation accuracy and geomorphic metrics of satellite-derived digital elevation models (DEMs) on the southern Central Andean Plateau. The plateau has an average elevation of 3.7 km and is characterized by diverse topography and relief, lack of vegetation, and clear skies that create ideal conditions for remote sensing. At 30m resolution, SRTM-C, ASTER GDEM2, stacked ASTER L1A stereopair DEM, ALOS World 3D, and TanDEM-X have been analyzed. The higher-resolution datasets include 12m TanDEM-X, 10m single-CoSSC TerraSAR-X/TanDEM-X DEMs, and 5m ALOS World 3D. These DEMs are state of the art for optical (ASTER and ALOS) and radar (SRTM-C and TanDEM-X) spaceborne sensors. We assessed vertical accuracy by comparing standard deviations of the DEM elevation versus 307 509 differential GPS measurements across 4000m of elevation. For the 30m DEMs, the ASTER datasets had the highest vertical standard deviation at > 6.5 m, whereas the SRTM-C, ALOS World 3D, and TanDEM-X were all < 3.5 m. Higher-resolution DEMs generally had lower uncertainty, with both the 12m TanDEM-X and 5m ALOSWorld 3D having < 2m vertical standard deviation. Analysis of vertical uncertainty with respect to terrain elevation, slope, and aspect revealed the low uncertainty across these attributes for SRTM-C (30 m), TanDEM-X (12-30 m), and ALOS World 3D (5-30 m). Single-CoSSC TerraSAR-X/TanDEM-X 10m DEMs and the 30m ASTER GDEM2 displayed slight aspect biases, which were removed in their stacked counterparts (TanDEM-X and ASTER Stack). Based on low vertical standard deviations and visual inspection alongside optical satellite data, we selected the 30m SRTM-C, 12-30m TanDEM-X, 10m single-CoSSC TerraSAR-X/TanDEM-X, and 5m ALOS World 3D for geomorphic metric comparison in a 66 km2 catchment with a distinct river knickpoint. Consistent m = n values were found using chi plot channel profile analysis, regardless of DEM type and spatial resolution. Slope, curvature, and drainage area were calculated and plotting schemes were used to assess basin-wide differences in the hillslope-to-valley transition related to the knickpoint. While slope and hillslope length measurements vary little between datasets, curvature displays higher magnitude measurements with fining resolution. This is especially true for the optical 5m ALOS World 3D DEM, which demonstrated high-frequency noise in 2-8 pixel steps through a Fourier frequency analysis. The improvements in accurate space-radar DEMs (e. g., TanDEM-X) for geomorphometry are promising, but airborne or terrestrial data are still necessary for meter-scale analysis.
Major earthquakes ( M > 8) have repeatedly ruptured the Nazca-South America plate interface of south-central Chile involving meter scale land-level changes. Earthquake recurrence intervals, however, extending beyond limited historical records are virtually unknown, but would provide crucial data on the tectonic behavior of forearcs. We analyzed the spatiotemporal pattern of Holocene earthquakes on Santa Maria Island (SMI; 37 degrees S), located 20 km off the Chilean coast and approximately 70 km east of the trench. SMI hosts a minimum of 21 uplifted beach berms, of which a subset were dated to calculate a mean uplift rate of 2.3 +/- 0.2 m/ky and a tilting rate of 0.022 +/- 0.002 degrees/ky. The inferred recurrence interval of strandline-forming earthquakes is similar to 180 years. Combining coseismic uplift and aseismic subsidence during an earthquake cycle, the net gain in strandline elevation in this environment is similar to 0.4 m per event
High Mountain Asia provides water for more than a billion downstream users. Many catchments receive the majority of their yearly water budget in the form of snow - the vast majority of which is not monitored by sparse weather networks. We leverage passive microwave data from the SSMI series of satellites (SSMI, SSMI/S, 1987-2016), reprocessed to 3.125 km resolution, to examine trends in the volume and spatial distribution of snow-water equivalent (SWE) in the Indus Basin. We find that the majority of the Indus has seen an increase in snow-water storage. There exists a strong elevation-trend relationship, where high-elevation zones have more positive SWE trends. Negative trends are confined to the Himalayan foreland and deeply-incised valleys which run into the Upper Indus. This implies a temperature-dependent cutoff below which precipitation increases are not translated into increased SWE. Earlier snowmelt or a higher percentage of liquid precipitation could both explain this cutoff.(1) Earlier work 2 found a negative snow-water storage trend for the entire Indus catchment over the time period 1987-2009 (-4 x 10(-3) mm/yr). In this study based on an additional seven years of data, the average trend reverses to 1.4 x 10(-3). This implies that the decade since the mid-2000s was likely wetter, and positively impacted long-term SWE trends. This conclusion is supported by an analysis of snowmelt onset and end dates which found that while long-term trends are negative, more recent (since 2005) trends are positive (moving later in the year).(3)
The interactions between atmosphere and steep topography in the eastern south–central Andes result in complex relations with inhomogenous rainfall distributions. The atmospheric conditions leading to deep convection and extreme rainfall and their spatial patterns—both at the valley and mountain-belt scales—are not well understood. In this study, we aim to identify the dominant atmospheric conditions and their spatial variability by analyzing the convective available potential energy (CAPE) and dew-point temperature (Td). We explain the crucial effect of temperature on extreme rainfall generation along the steep climatic and topographic gradients in the NW Argentine Andes stretching from the low-elevation eastern foreland to the high-elevation central Andean Plateau in the west. Our analysis relies on version 2.0 of the ECMWF’s (European Centre for Medium-RangeWeather Forecasts) Re-Analysis (ERA-interim) data and TRMM (Tropical Rainfall Measuring Mission) data. We make the following key observations: First, we observe distinctive gradients along and across strike of the Andes in dew-point temperature and CAPE that both control rainfall distributions. Second, we identify a nonlinear correlation between rainfall and a combination of dew-point temperature and CAPE through a multivariable regression analysis. The correlation changes in space along the climatic and topographic gradients and helps to explain controlling factors for extreme-rainfall generation. Third, we observe more contribution (or higher importance) of Td in the tropical low-elevation foreland and intermediate-elevation areas as compared to the high-elevation central Andean Plateau for 90th percentile rainfall. In contrast, we observe a higher contribution of CAPE in the intermediate-elevation area between low and high elevation, especially in the transition zone between the tropical and subtropical areas for the 90th percentile rainfall. Fourth, we find that the parameters of the multivariable regression using CAPE and Td can explain rainfall with higher statistical significance for the 90th percentile compared to lower rainfall percentiles. Based on our results, the spatial pattern of rainfall-extreme events during the past ∼16 years can be described by a combination of dew-point temperature and CAPE in the south–central Andes.
The interactions between atmosphere and steep topography in the eastern south–central Andes result in complex relations with inhomogenous rainfall distributions. The atmospheric conditions leading to deep convection and extreme rainfall and their spatial patterns—both at the valley and mountain-belt scales—are not well understood. In this study, we aim to identify the dominant atmospheric conditions and their spatial variability by analyzing the convective available potential energy (CAPE) and dew-point temperature (Td). We explain the crucial effect of temperature on extreme rainfall generation along the steep climatic and topographic gradients in the NW Argentine Andes stretching from the low-elevation eastern foreland to the high-elevation central Andean Plateau in the west. Our analysis relies on version 2.0 of the ECMWF’s (European Centre for Medium-RangeWeather Forecasts) Re-Analysis (ERA-interim) data and TRMM (Tropical Rainfall Measuring Mission) data. We make the following key observations: First, we observe distinctive gradients along and across strike of the Andes in dew-point temperature and CAPE that both control rainfall distributions. Second, we identify a nonlinear correlation between rainfall and a combination of dew-point temperature and CAPE through a multivariable regression analysis. The correlation changes in space along the climatic and topographic gradients and helps to explain controlling factors for extreme-rainfall generation. Third, we observe more contribution (or higher importance) of Td in the tropical low-elevation foreland and intermediate-elevation areas as compared to the high-elevation central Andean Plateau for 90th percentile rainfall. In contrast, we observe a higher contribution of CAPE in the intermediate-elevation area between low and high elevation, especially in the transition zone between the tropical and subtropical areas for the 90th percentile rainfall. Fourth, we find that the parameters of the multivariable regression using CAPE and Td can explain rainfall with higher statistical significance for the 90th percentile compared to lower rainfall percentiles. Based on our results, the spatial pattern of rainfall-extreme events during the past ∼16 years can be described by a combination of dew-point temperature and CAPE in the south–central Andes.
Understanding the rates and pattern of erosion is a key aspect of deciphering the impacts of climate and tectonics on landscape evolution. Denudation rates derived from terrestrial cosmogenic nuclides (TCNs) are commonly used to quantify erosion and bridge tectonic (Myr) and climatic (up to several kiloyears) time scales. However, how the processes of erosion in active orogens are ultimately reflected in Be-10 TCN samples remains a topic of discussion. We investigate this problem in the Arun Valley of eastern Nepal with 34 new Be-10-derived catchment-mean denudation rates. The Arun Valley is characterized by steep north-south gradients in topography and climate. Locally, denudation rates increase northward, from <0.2mmyr(-1) to similar to 1.5mmyr(-1) in tributary samples, while main stem samples appear to increase downstream from similar to 0.2mmyr(-1) at the border with Tibet to 0.91mmyr(-1) in the foreland. Denudation rates most strongly correlate with normalized channel steepness (R-2=0.67), which has been commonly interpreted to indicate tectonic activity. Significant downstream decrease of Be-10 concentration in the main stem Arun suggests that upstream sediment grains are fining to the point that they are operationally excluded from the processed sample. This results in Be-10 concentrations and denudation rates that do not uniformly represent the upstream catchment area. We observe strong impacts on Be-10 concentrations from local, nonfluvial geomorphic processes, such as glaciation and landsliding coinciding with areas of peak rainfall rates, pointing toward climatic modulation of predominantly tectonically driven denudation rates.
Mixed sand- and gravel-bed rivers record erosion, transport, and fining signals in their bedload size distributions. Thus, grain-size data are imperative for studying these processes. However, collecting hundreds to thousands of pebble measurements in steep and dynamic high-mountain river settings remains challenging. Using the recently published digital grain-sizing algorithm PebbleCounts, we were able to survey seven large (>= 1,000 m2) channel cross-sections and measure thousands to tens-of-thousands of grains per survey along a 100-km stretch of the trunk stream of the Toro Basin in Northwest Argentina. The study region traverses a steep topographic and environmental gradient on the eastern margin of the Central Andean Plateau. Careful counting and validation allows us to identify measurement errors and constrain percentile uncertainties using large sample sizes. In the coarse >= 2.5 cm fraction of bedload, only the uppermost size percentiles (>= 95th) vary significantly downstream, whereas the 50th and 84th percentiles show less variability. We note a relation between increases in these upper percentiles and along-channel junctions with large, steep tributaries. This signal is strongly influenced by lithology and geologic structures, and mixed with local hillslope input. In steep catchments like the Toro Basin, we suggest nonlinear relationships between geomorphic metrics and grain size, whereby the steepest parts of the landscape exert primary control on the upper grain-size percentiles. Thus, average or median metrics that do not apply weights or thresholds to steeper topography may be less predictive of grain-size distributions in such settings.
This paper employs a complex network approach to determine the topology and evolution of the network of extreme precipitation that governs the organization of extreme rainfall before, during, and after the Indian Summer Monsoon (ISM) season. We construct networks of extreme rainfall events during the ISM (June-September), post-monsoon (October-December), and pre-monsoon (March-May) periods from satellite-derived (Tropical Rainfall Measurement Mission, TRMM) and rain-gauge interpolated (Asian Precipitation Highly Resolved Observational Data Integration Towards the Evaluation of Water Resources, APHRODITE) data sets. The structure of the networks is determined by the level of synchronization of extreme rainfall events between different grid cells throughout the Indian subcontinent. Through the analysis of various complex-network metrics, we describe typical repetitive patterns in North Pakistan (NP), the Eastern Ghats (EG), and the Tibetan Plateau (TP). These patterns appear during the pre-monsoon season, evolve during the ISM, and disappear during the post-monsoon season. These are important meteorological features that need further attention and that may be useful in ISM timing and strength prediction.
The Upper Indus Basin (UIB), which covers a wide range of climatic and topographic settings, provides an ideal venue to explore the relationship between climate and topography. While the distribution of snow and glaciers is spatially and temporally heterogeneous, there exist regions with similar elevation-snow relationships. In this work, we construct elevation-binned snow-cover statistics to analyze 3415 watersheds and 7357 glaciers in the UIB region. We group both glaciers and watersheds using a hierarchical clustering approach and find that (1) watershed clusters mirror large-scale moisture transport patterns and (2) are highly dependent on median watershed elevation. (3) Glacier clusters are spatially heterogeneous and are less strongly controlled by elevation, but rather by local topographic parameters that modify solar insolation. Our clustering approach allows us to clearly define self-similar snow-topographic regions. Eastern watersheds in the UIB show a steep snow cover-elevation relationship whereas watersheds in the central and western UIB have moderately sloped relationships, but cluster in distinct groups. We highlight this snow-cover-topographic transition zone and argue that these watersheds have different hydrologic responses than other regions. Our hierarchical clustering approach provides a potential new framework to use in defining climatic zones in the cyrosphere based on empirical data.
Forecasting the onset and withdrawal of the Indian summer monsoon is crucial for the life and prosperity of more than one billion inhabitants of the Indian subcontinent. However, accurate prediction of monsoon timing remains a challenge, despite numerous efforts. Here we present a method for prediction of monsoon timing based on a critical transition precursor. We identify geographic regions-tipping elements of the monsoon-and use them as observation locations for predicting onset and withdrawal dates. Unlike most predictability methods, our approach does not rely on precipitation analysis but on air temperature and relative humidity, which are well represented both in models and observations. The proposed method allows to predict onset 2 weeks earlier and withdrawal dates 1.5 months earlier than existing methods. In addition, it enables to correctly forecast monsoon duration for some anomalous years, often associated with El Nino-Southern Oscillation.
The Weather Research and Forecasting (WRF) model is used to simulate the spatiotemporal distribution of precipitation over central Asia over the year April 2005 through March 2006. Experiments are performed at 6.7 km horizontal grid spacing, with an emphasis on winter and summer precipitation over the Himalaya. The model and the Tropical Rainfall Measuring Mission show a similar inter-seasonal cycle of precipitation, from extratropical cyclones to monsoon precipitation, with agreement also in the diurnal cycle of monsoon precipitation. In winter months, WRF compares better in timeseries of daily precipitation to stations below than above 3-km elevation, likely due to inferior measurement of snow than rain by the stations, highlighting the need for reliable snowfall measurements at high elevations in winter. In summer months, the nocturnal precipitation cycle in the foothills and valleys of the Himalaya is captured by this 6.7-km WRF simulation, while coarser simulations with convective parameterization show near zero nocturnal precipitation. In winter months, higher resolution is less important, serving only to slightly increase precipitation magnitudes due to steeper slopes. However, even in the 6.7-km simulation, afternoon precipitation is overestimated at high elevations, which can be reduced by even higher-resolution (2.2-km) simulations. These results indicate that WRF provides skillful simulations of precipitation relevant for studies of water resources over the complex terrain in the Himalaya.
The spatial pattern of extreme precipitation from 40 years of gauge data in the central Himalaya
(2022)
The topography of the Himalaya exerts a substantial control on the spatial distribution of monsoonal rainfall, which is a vital water source for the regional economy and population. But the occurrence of short-lived and high-intensity precipitation results in socio-economic losses. This study relies on 40 years of daily data from 204 ground stations in Nepal to derive extreme precipitation thresholds, amounts, and days at the 95th percentile. We additionally determine the precipitation magnitude-frequency relation. We observe that extreme precipitation amounts follow an almost uniform band parallel to topographic contour lines in the southern Himalaya mountains in central and eastern Nepal but not in western Nepal. The relationship of extreme precipitation indices with topographic relief shows that extreme precipitation thresholds decrease with increasing elevation, but extreme precipitation days increase in higher elevation areas. Furthermore, stations above 1 km elevation exhibit a power-law relation in the rainfall magnitude-frequency framework. Stations at higher elevations generally have lower values of power-law exponents than low elevation areas. This suggests a fundamentally different behaviour of the rainfall distribution and an increased occurrence of extreme rainfall storms in the high elevation areas of Nepal.
Birds migrating across the Himalayan region fly over the highest peaks in the world, facing immense physiological and climatic challenges. The authors show the different strategies used by birds to cope with these challenges. Many wetland avian species are seen in the high-altitude lakes of the Himalayas and the adjoining Tibetan Plateau, such as Bar-Headed Geese. Ringing programmes have generated information about origins and destinations, and this book is the first to present information on the bird's exact migratory paths. Capitalising on knowledge generated through satellite telemetry, the authors describe the migratory routes of a multitude of birds flying over or skirting the Himalayas. The myriad of threats to migratory birds and the wetland system in the Central Asian Flyway are discussed, with ways to mitigate them. This volume will inform and persuade policy-makers and conservation practitioners to take appropriate measures for the long-term survival of this unique migration
Restoring degraded lands in rural environments that are heavily managed to meet subsistence needs is a challenge due to high rates of disturbance and resource extraction. This study investigates the efficacy of erosion control structures (ECSs) as restoration tools in the context of a watershed rehabilitation and wet meadow (bofedal) restoration program in the Bolivian Andes. In an effort to enhance water security and increase grazing stability, Aymara indigenous communities built over 15,000 check dams, 9,100 terraces, 5,300 infiltration ditches, and 35 pasture improvement trials. Communities built ECSs at different rates, and we compared vegetation change in the highest restoration management intensity, lowest restoration management intensity, and nonproject control communities. We used line transects to measure changes in vegetation cover and standing water in gullies with check dams and without check dams, and related these ground measurements to a time series (1986-2009) of normalized difference vegetation index derived from Landsat TM5 images. Evidence suggests that check dams increase bofedal vegetation and standing water at a local scale, and lead to increased greenness at a basin scale when combined with other ECSs. Watershed rehabilitation enhances ecosystem services significant to local communities (grazing stability, water security), which creates important synergies when conducting land restoration in rural development settings.
The effect of Indian Summer Monsoon rainfall on surface water delta D values in the central Himalaya
(2018)
Stable isotope proxy records, such as speleothems, plant-wax biomarker records, and ice cores, are suitable archives for the reconstruction of regional palaeohydrologic conditions. But the interpretation of these records in the tropics, especially in the Indian Summer Monsoon (ISM) domain, is difficult due to differing moisture and water sources: precipitation from the ISM and Winter Westerlies, as well as snow- and glacial meltwater. In this study, we use interannual differences in ISM strength (2011-2012) to understand the stable isotopic composition of surface water in the Arun River catchment in eastern Nepal. We sampled main stem and tributary water (n = 204) for stable hydrogen and oxygen isotope analysis in the postmonsoon phase of two subsequent years with significantly distinct ISM intensities. In addition to the 2011/2012 sampling campaigns, we collected a 12-month time series of main stem waters (2012/2013, n = 105) in order to better quantify seasonal effects on the variability of surface water delta O-18/delta D. Furthermore, remotely sensed satellite data of rainfall, snow cover, glacial coverage, and evapotranspiration was evaluated. The comparison of datasets from both years revealed that surface waters of the main stem Arun and its tributaries were D-enriched by similar to 15 parts per thousand when ISM rainfall decreased by 20%. This strong response emphasizes the importance of the ISM for surface water run-off in the central Himalaya. However, further spatio-temporal analysis of remote sensing data in combination with stream water d-excess revealed that most high-altitude tributaries and the Tibetan part of the Arun receive high portions of glacial melt water and likely Winter Westerly Disturbances precipitation. We make the following two implications: First, palaeohydrologic archives found in high-altitude tributaries and on the southern Tibetan Plateau record a mixture of past precipitation delta D values and variable amounts of additional water sources. Second, surface water isotope ratios of lower elevated tributaries strongly reflect the isotopic composition of ISM rainfall implying a suitable region for the analysis of potential delta D value proxy records.
Understanding the evolution of continental deformation zones relies on quantifying spatial and temporal changes in deformation rates of tectonic structures. Along the eastern boundary of the Pamir-Tian Shan collision zone, we constrain secular variations of rock uplift rates for a series of five Quaternary detachment- and fault-related folds from their initiation to the modern day. When combined with GPS data, decomposition of interferometric synthetic aperture radar time series constrains the spatial pattern of surface and rock uplift on the folds deforming at decadal rates of 1-5mm/yr. These data confirm the previously proposed basinward propagation of structures during the Quaternary. By fitting our geodetic rates and previously published geologic uplift rates with piecewise linear functions, we find that gradual rate changes over >100kyr can explain the interferometric synthetic aperture radar observations where changes in average uplift rates are greater than similar to 1 mm/yr among different time intervals (similar to 10(1), 10(4-5), and 10(5-6) years).
We document Quaternary fluvial incision driven by fault-controlled surface deformation in the inverted intermontane Gökirmak Basin in the Central Pontide mountains along the northern margin of the Central Anatolian Plateau. In-situ-produced Be-10, Ne-21, and Cl-36 concentrations from gravel-covered fluvial terraces and pediment surfaces along the trunk stream of the basin (the Gökirmak River) yield model exposure ages ranging from 71ka to 34645ka and average fluvial incision rates over the past similar to 350ka of 0.280.01mm a(-1). Similarities between river incision rates and coastal uplift rates at the Black Sea coast suggest that regional uplift is responsible for the river incision. Model exposure ages of deformed pediment surfaces along tributaries of the trunk stream range from 605ka to 110 +/- 10ka, demonstrating that the thrust faults responsible for pediment deformation were active after those times and were likely active earlier as well as explaining the topographic relief of the region. Together, our data demonstrate cumulative incision that is linked to active internal shortening and uplift of similar to 0.3mm a(-1) in the Central Pontide orogenic wedge, which may ultimately contribute to the lateral growth of the northern Anatolian Plateau.
Erosion in the Himalaya is responsible for one of the greatest mass redistributions on Earth and has fueled models of feedback loops between climate and tectonics. Although the general trends of erosion across the Himalaya are reasonably well known, the relative importance of factors controlling erosion is less well constrained. Here we present 25 Be-10-derived catchment-averaged erosion rates from the Yamuna catchment in the Garhwal Himalaya, northern India. Tributary erosion rates range between similar to 0.1 and 0.5mmyr(-1) in the Lesser Himalaya and similar to 1 and 2mmyr(-1) in the High Himalaya, despite uniform hillslope angles. The erosion-rate data correlate with catchment-averaged values of 5 km radius relief, channel steepness indices, and specific stream power but to varying degrees of nonlinearity. Similar nonlinear relationships and coefficients of determination suggest that topographic steepness is the major control on the spatial variability of erosion and that twofold to threefold differences in annual runoff are of minor importance in this area. Instead, the spatial distribution of erosion in the study area is consistent with a tectonic model in which the rock uplift pattern is largely controlled by the shortening rate and the geometry of the Main Himalayan Thrust fault (MHT). Our data support a shallow dip of the MHT underneath the Lesser Himalaya, followed by a midcrustal ramp underneath the High Himalaya, as indicated by geophysical data. Finally, analysis of sample results from larger main stem rivers indicates significant variability of Be-10-derived erosion rates, possibly related to nonproportional sediment supply from different tributaries and incomplete mixing in main stem channels.
The tectonic and climatic boundary conditions of the broken foreland and the orogen interior of the southern Central Andes of northwestern Argentina cause strong contrasts in elevation, rainfall, and surface-process regimes. The climatic gradient in this region ranges from the wet, windward eastern flanks (similar to 2 m/yr rainfall) to progressively drier western basins and ranges (similar to 0.1 m/yr) bordering the arid Altiplano-Puna Plateau. In this study, we analyze the impact of spatiotemporal climatic gradients on surface erosion: First, we present 41 new catchment-mean erosion rates derived from cosmogenic nuclide inventories to document spatial erosion patterns. Second, we re-evaluate paleoclimatic records from the Calchaquies basin (66 W, 26 S), a large intermontane basin bordered by high (> 4.5 km) mountain ranges, to demonstrate temporal variations in erosion rates associated with changing climatic boundary conditions during the late Pleistocene and Holocene. Three key observations in this region emphasize the importance of climatic parameters on the efficiency of surface processes in space and time: (1) First-order spatial patterns of erosion rates can be explained by a simple specific stream power (SSP) approach. We explicitly account for discharge by routing high-resolution, satellite derived rainfall. This is important as the steep climatic gradient results in a highly non-linear relation between drainage area and discharge. This relation indicates that erosion rates (ER) scale with ER similar to SSP1.4 on cosmogenic-nuclide time scales. (2) We identify an intrinsic channel-slope behavior in different climatic compartments. Channel slopes in dry areas (< 0.25 m/yr rainfall) are slightly steeper than in wet areas (> 0.75 m/yr) with equal drainage areas, thus compensating lower amounts of discharge with steeper slopes. (3) Erosion rates can vary by an order of magnitude between presently dry (similar to 0.05 mm/yr) and well-defined late Pleistocene humid (similar to 0.5 mm/yr) conditions within an intemontane basin. Overall, we document a strong climatic impact on erosion rates and channel slopes. We suggest that rainfall reaching areas with steeper channel slopes in the orogen interior during wetter climate periods results in intensified sediment mass transport, which is primarily responsible for maintaining the balance between surface uplift, erosion, sediment routing and transient storage in the orogen.
High Mountain Asia (HMA) - encompassing the Tibetan Plateau and surrounding mountain ranges - is the primary water source for much of Asia, serving more than a billion downstream users. Many catchments receive the majority of their yearly water budget in the form of snow, which is poorly monitored by sparse in situ weather networks. Both the timing and volume of snowmelt play critical roles in downstream water provision, as many applications - such as agriculture, drinking-water generation, and hydropower - rely on consistent and predictable snowmelt runoff. Here, we examine passive microwave data across HMA with five sensors (SSMI, SSMIS, AMSR-E, AMSR2, and GPM) from 1987 to 2016 to track the timing of the snowmelt season - defined here as the time between maximum passive microwave signal separation and snow clearance. We validated our method against climate model surface temperatures, optical remote-sensing snow-cover data, and a manual control dataset (n = 2100, 3 variables at 25 locations over 28 years); our algorithm is generally accurate within 3-5 days. Using the algorithm-generated snowmelt dates, we examine the spatiotemporal patterns of the snowmelt season across HMA. The climatically short (29-year) time series, along with complex interannual snowfall variations, makes determining trends in snowmelt dates at a single point difficult. We instead identify trends in snowmelt timing by using hierarchical clustering of the passive microwave data to determine trends in self-similar regions. We make the following four key observations. (1) The end of the snowmelt season is trending almost universally earlier in HMA (negative trends). Changes in the end of the snowmelt season are generally between 2 and 8 days decade 1 over the 29-year study period (5-25 days total). The length of the snowmelt season is thus shrinking in many, though not all, regions of HMA. Some areas exhibit later peak signal separation (positive trends), but with generally smaller magnitudes than trends in snowmelt end. (2) Areas with long snowmelt periods, such as the Tibetan Plateau, show the strongest compression of the snowmelt season (negative trends). These trends are apparent regardless of the time period over which the regression is performed. (3) While trends averaged over 3 decades indicate generally earlier snowmelt seasons, data from the last 14 years (2002-2016) exhibit positive trends in many regions, such as parts of the Pamir and Kunlun Shan. Due to the short nature of the time series, it is not clear whether this change is a reversal of a long-term trend or simply interannual variability. (4) Some regions with stable or growing glaciers - such as the Karakoram and Kunlun Shan - see slightly later snowmelt seasons and longer snowmelt periods. It is likely that changes in the snowmelt regime of HMA account for some of the observed heterogeneity in glacier response to climate change. While the decadal increases in regional temperature have in general led to earlier and shortened melt seasons, changes in HMA's cryosphere have been spatially and temporally heterogeneous.
High Mountain Asia (HMA) - encompassing the Tibetan Plateau and surrounding mountain ranges - is the primary water source for much of Asia, serving more than a billion downstream users. Many catchments receive the majority of their yearly water budget in the form of snow, which is poorly monitored by sparse in situ weather networks. Both the timing and volume of snowmelt play critical roles in downstream water provision, as many applications - such as agriculture, drinking-water generation, and hydropower - rely on consistent and predictable snowmelt runoff. Here, we examine passive microwave data across HMA with five sensors (SSMI, SSMIS, AMSR-E, AMSR2, and GPM) from 1987 to 2016 to track the timing of the snowmelt season - defined here as the time between maximum passive microwave signal separation and snow clearance. We validated our method against climate model surface temperatures, optical remote-sensing snow-cover data, and a manual control dataset (n = 2100, 3 variables at 25 locations over 28 years); our algorithm is generally accurate within 3-5 days. Using the algorithm-generated snowmelt dates, we examine the spatiotemporal patterns of the snowmelt season across HMA. The climatically short (29-year) time series, along with complex interannual snowfall variations, makes determining trends in snowmelt dates at a single point difficult. We instead identify trends in snowmelt timing by using hierarchical clustering of the passive microwave data to determine trends in self-similar regions. We make the following four key observations. (1) The end of the snowmelt season is trending almost universally earlier in HMA (negative trends). Changes in the end of the snowmelt season are generally between 2 and 8 days decade 1 over the 29-year study period (5-25 days total). The length of the snowmelt season is thus shrinking in many, though not all, regions of HMA. Some areas exhibit later peak signal separation (positive trends), but with generally smaller magnitudes than trends in snowmelt end. (2) Areas with long snowmelt periods, such as the Tibetan Plateau, show the strongest compression of the snowmelt season (negative trends). These trends are apparent regardless of the time period over which the regression is performed. (3) While trends averaged over 3 decades indicate generally earlier snowmelt seasons, data from the last 14 years (2002-2016) exhibit positive trends in many regions, such as parts of the Pamir and Kunlun Shan. Due to the short nature of the time series, it is not clear whether this change is a reversal of a long-term trend or simply interannual variability. (4) Some regions with stable or growing glaciers - such as the Karakoram and Kunlun Shan - see slightly later snowmelt seasons and longer snowmelt periods. It is likely that changes in the snowmelt regime of HMA account for some of the observed heterogeneity in glacier response to climate change. While the decadal increases in regional temperature have in general led to earlier and shortened melt seasons, changes in HMA's cryosphere have been spatially and temporally heterogeneous.
In this study, we provide a comprehensive analysis of trends in the extremes during the Indian summer monsoon (ISM) months (June to September) at different temporal and spatial scales. Our goal is to identify and quantify spatiotemporal patterns and trends that have emerged during the recent decades and may be associated with changing climatic conditions. Our analysis primarily relies on quantile regression that avoids making any subjective choices on spatial, temporal, or intensity pattern of extreme rainfall events. Our analysis divides the Indian monsoon region into climatic compartments that show different and partly opposing trends. These include strong trends toward intensified droughts in Northwest India, parts of Peninsular India, and Myanmar; in contrast, parts of Pakistan, Northwest Himalaya, and Central India show increased extreme daily rain intensity leading to higher flood vulnerability. Our analysis helps explain previously contradicting results of trends in average ISM rainfall.
The South American Andes are frequently exposed to intense rainfall events with varying moisture sources and precipitation-forming processes. In this study, we assess the spatiotemporal characteristics and geographical origins of rainfall over the South American continent. Using high-spatiotemporal resolution satellite data (TRMM 3B42 V7), we define four different types of rainfall events based on their (1) high magnitude, (2) long temporal extent, (3) large spatial extent, and (4) high magnitude, long temporal and large spatial extent combined. In a first step, we analyze the spatiotemporal characteristics of these events over the entire South American continent and integrate their impact for the main Andean hydrologic catchments. Our results indicate that events of type 1 make the overall highest contributions to total seasonal rainfall (up to 50%). However, each consecutive episode of the infrequent events of type 4 still accounts for up to 20% of total seasonal rainfall in the subtropical Argentinean plains. In a second step, we employ complex network theory to unravel possibly non-linear and long-ranged climatic linkages for these four event types on the high-elevation Altiplano-Puna Plateau as well as in the main river catchments along the foothills of the Andes. Our results suggest that one to two particularly large squall lines per season, originating from northern Brazil, indirectly trigger large, long-lasting thunderstorms on the Altiplano Plateau. In general, we observe that extreme rainfall in the catchments north of approximately 20 degrees S typically originates from the Amazon Basin, while extreme rainfall at the eastern Andean foothills south of 20 degrees S and the Puna Plateau originates from southeastern South America.
Controversy about the current state and future evolution of Himalayan glaciers has been stirred up by erroneous statements in the fourth report by the Intergovernmental Panel on Climate Change(1,2). Variable retreat rates(3-6) and a paucity of glacial mass-balance data(7,8) make it difficult to develop a coherent picture of regional climate-change impacts in the region. Here, we report remotely-sensed frontal changes and surface velocities from glaciers in the greater Himalaya between 2000 and 2008 that provide evidence for strong spatial variations in glacier behaviour which are linked to topography and climate. More than 65% of the monsoon-influenced glaciers that we observed are retreating, but heavily debris-covered glaciers with stagnant low-gradient terminus regions typically have stable fronts. Debris-covered glaciers are common in the rugged central Himalaya, but they are almost absent in subdued landscapes on the Tibetan Plateau, where retreat rates are higher. In contrast, more than 50% of observed glaciers in the westerlies-influenced Karakoram region in the northwestern Himalaya are advancing or stable. Our study shows that there is no uniform response of Himalayan glaciers to climate change and highlights the importance of debris cover for understanding glacier retreat, an effect that has so far been neglected in predictions of future water availability(9,10) or global sea level(11).
This work explores the control of fore-arc structure on segmentation of megathrust earthquake ruptures using coastal geomorphic markers. The Arauco-Nahuelbuta region at the south-central Chile margin constitutes an anomalous fore- arc sector in terms of topography, geology, and exhumation, located within the overlap between the Concepcion and Valdivia megathrust segments. This boundary, however, is only based on similar to 500 years of historical records. We integrate deformed marine terraces dated by cosmogenic nuclides, syntectonic sediments, published fission track data, seismic reflection profiles, and microseismicity to analyze this earthquake boundary over 10(2) -10(6) years. Rapid exhumation of Nahuelbuta's dome-like core started at 4 +/- 1.2 Ma, coeval with inversion of the adjacent Arauco basin resulting in emergence of the Arauco peninsula. Here, similarities between topography, spatiotemporal trends in fission track ages, Pliocene-Pleistocene growth strata, and folded marine terraces suggest that margin-parallel shortening has dominated since Pliocene time. This shortening likely results from translation of a fore-arc sliver or microplate, decoupled from South America by an intra-arc strike-slip fault. Microplate collision against a buttress leads to localized uplift at Arauco accrued by deep-seated reverse faults, as well as incipient oroclinal bending. The extent of the Valdivia segment, which ruptured last in 1960 with an M-w 9.5 event, equals the inferred microplate. We propose that mechanical homogeneity of the fore-arc microplate delimits the Valdivia segment and that a marked discontinuity in the continental basement at Arauco acts as an inhomogeneous barrier controlling nucleation and propagation of 1960-type ruptures. As microplate-related deformation occurs since the Pliocene, we propose that this earthquake boundary and the extent of the Valdivia segment are spatially stable seismotectonic features at million year scale.
Seasonal precipitation gradients and their impact on fluvial sediment flux in the Northwest Himalaya
(2010)
Precipitation in the form of rain and snowfall throughout the Himalaya controls river discharge and erosional processes and, thus, has a first-order control on the fluvial sediment flux. Here, we analyze daily precipitation data (1998-2007) of 80 weather stations from the northwestern Himalaya in order to decipher temporal and spatial moisture gradients. In addition, suspended sediment data allow assessment of the impact of precipitation on the fluvial sediment flux for a 10(3)-km(2) catchment (Baspa). We find that weather stations located at the mountain front receive similar to 80% of annual precipitation during summer (May-Oct), whereas stations in the orogenic interior, i.e., leeward of the orographic barrier, receive similar to 60% of annual precipitation during winter (Nov-Apr). In both regions 4-6 rainstorm days account for similar to 40% of the summer budgets, while rainstorm magnitude-frequency relations, derived from 40-year precipitation time-series, indicate a higher storm variability in the interior than in the frontal region. This high variability in maximum annual rainstorm days in the orogenic interior is reflected by a high variability in extreme suspended sediment events in the Baspa Valley, which strongly affect annual erosion yields. The two most prominent 5-day-long erosional events account for 50% of the total 5-year suspended sediment flux and coincide with synoptic-scale monsoonal rainstorms. This emphasizes the erosional impact of the Indian Summer Monsoon as the main driving force for erosion processes in the orogenic interior, despite more precipitation falling during the winter season.
Megathrust earthquakes impose changes of differential stress and pore pressure in the lithosphere-asthenosphere system that are transiently relaxed during the postseismic period primarily due to afterslip, viscoelastic and poroelastic processes.
Especially during the early postseismic phase, however, the relative contribution of these processes to the observed surface deformation is unclear.
To investigate this, we use geodetic data collected in the first 48 days following the 2010 Maule earthquake and a poro-viscoelastic forward model combined with an afterslip inversion.
This model approach fits the geodetic data 14% better than a pure elastic model. Particularly near the region of maximum coseismic slip, the predicted surface poroelastic uplift pattern explains well the observations.
If poroelasticity is neglected, the spatial afterslip distribution is locally altered by up to +/- 40%.
Moreover, we find that shallow crustal aftershocks mostly occur in regions of increased postseismic pore-pressure changes, indicating that both processes might be mechanically coupled.
Vegetation has long been hypothesized to influence the nature and rates of surface processes. We test the possible impact of vegetation and climate on denudation rates at orogen scale by taking advantage of a pronounced along-strike gradient in rainfall and vegetation density in the Himalaya. We combine 12 new Be-10 denudation rates from the Sutlej Valley and 123 published denudation rates from fluvially-dominated catchments in the Himalaya with remotely-sensed measures of vegetation density and rainfall metrics, and with tectonic and lithologic constraints. In addition, we perform topographic analyses to assess the contribution of vegetation and climate in modulating denudation rates along strike. We observe variations in denudation rates and the relationship between denudation and topography along strike that are most strongly controlled by local rainfall amount and vegetation density, and cannot be explained by along-strike differences in tectonics or lithology. A W-E along-strike decrease in denudation rate variability positively correlates with the seasonality of vegetation density (R = 0.95, p < 0.05), and negatively correlates with mean vegetation density (R = -0.84, p < 0.05). Vegetation density modulates the topographic response to changing denudation rates, such that the functional relationship between denudation rate and topographic steepness becomes increasingly linear as vegetation density increases. We suggest that while tectonic processes locally control the pattern of denudation rates across strike of the Himalaya (i.e., S-N), along strike of the orogen (i.e., E-W) climate exerts a measurable influence on how denudation rates scatter around long-term, tectonically-controlled erosion, and on the functional relationship between topography and denudation. (C) 2016 Elsevier B.V. All rights reserved.
Recent studies have shown that the 1976-77 global climate shift strongly affected the South American climate. In our study, we observed a link between this climate shift and river-discharge variability in the subtropical Southern Central Andes. We analyzed the daily river-discharge time series between 1940 and 1999 from small to medium mountain drainage basins (10(2)-10(4) km(2) ) across a steep climatic and topographic gradient. We document that the discharge frequency distribution changed significantly, with higher percentiles exhibiting more pronounced trends. A change point between 1971 and 1977 marked an intensification of the hydrological cycle, which resulted in increased river discharge. In the upper Rio Bermejo basin of the northernmost Argentine Andes, the mean annual discharge increased by 40% over 7 years. Our findings are important for flood risk management in areas impacted by the 1976-77 climate shift; discharge frequency distribution analysis provides important insights into the variability of the hydrological cycle in the Andean realm.
The eastern flanks of the Central Andes are characterized by deep convection, exposing them to hydrometeorological extreme events, often resulting in floods and a variety of mass movements. We assessed the spatiotemporal pattern of rainfall trends and the changes in the magnitude and frequency of extreme events (ae<yen>95th percentile) along an E-W traverse across the southern Central Andes using rain-gauge and high-resolution gridded datasets (CPC-uni and TRMM 3B42 V7). We generated different climate indices and made three key observations: (1) an increase of the annual rainfall has occurred at the transition between low (< 0.5 km) and intermediate (0.5-3 km) elevations between 1950 and 2014. Also, rainfall increases during the wet season and, to a lesser degree, decreases during the dry season. Increasing trends in annual total amounts characterize the period 1979-2014 in the arid, high-elevation southern Andean Plateau, whereas trend reversals with decreasing annual total amounts were found at low elevations. (2) For all analyzed periods, we observed small or no changes in the median values of the rainfall-frequency distribution, but significant trends with intensification or attenuation in the 95th percentile. (3) In the southern Andean Plateau, extreme rainfall events exhibit trends towards increasing magnitude and, to a lesser degree, frequency during the wet season, at least since 1979. Our analysis revealed that low (< 0.5 km), intermediate (0.5-3 km), and high-elevation (> 3 km) areas respond differently to changing climate conditions, and the transition zone between low and intermediate elevations is characterized by the most significant changes.
Based on high-spatiotemporal-resolution data, the authors perform a climatological study of strong rainfall events propagating from southeastern South America to the eastern slopes of the central Andes during the monsoon season. These events account for up to 70% of total seasonal rainfall in these areas. They are of societal relevance because of associated natural hazards in the form of floods and landslides, and they form an intriguing climatic phenomenon, because they propagate against the direction of the low-level moisture flow from the tropics. The responsible synoptic mechanism is analyzed using suitable composites of the relevant atmospheric variables with high temporal resolution. The results suggest that the low-level inflow from the tropics, while important for maintaining sufficient moisture in the area of rainfall, does not initiate the formation of rainfall clusters. Instead, alternating low and high pressure anomalies in midlatitudes, which are associated with an eastward-moving Rossby wave train, in combination with the northwestern Argentinean low, create favorable pressure and wind conditions for frontogenesis and subsequent precipitation events propagating from southeastern South America toward the Bolivian Andes.
This study analyzes the discharge variability of small to medium drainage basins (10(2)-10(4) km(2)) in the southern Central Andes of NW Argentina. The Hilbert-Huang Transform (HHT) was applied to evaluate non-stationary oscillatory modes of variability and trends, based on four time series of monthly normalized discharge anomaly between 1940 and 2015. Statistically significant trends reveal increasing discharge during the past decades and document an intensification of the hydrological cycle during this period. An Ensemble Empirical Mode Decomposition (EEMD) analysis revealed that discharge variability in this region can be best described by five quasi-periodic statistically significant oscillatory modes, with mean periods varying from 1 to 20 y. Moreover, we show that discharge variability is most likely linked to the phases of the Pacific Decadal Oscillation (PDO) at multi-decadal timescales (similar to 20 y) and, to a lesser degree, to the Tropical South Atlantic SST anomaly (TSA) variability at shorter timescales (similar to 2-5 y). Previous studies highlighted a rapid increase in discharge in the southern Central Andes during the 1970s, inferred to have been associated with the global 1976-77 climate shift. Our results suggest that the rapid discharge increase in the NW Argentine Andes coincides with the periodic enhancement of discharge, which is mainly linked to a negative to positive transition of the PDO phase and TSA variability associated with a long-term increasing trend. We therefore suggest that variations in discharge in this region are largely driven by both natural variability and the effects of global climate change. We furthermore posit that the links between atmospheric and hydrologic processes result from a combination of forcings that operate on different spatiotemporal scales. (C) 2017 Elsevier B.V. All rights reserved.
With the advent of the two Sentinel-1 (S1) satellites, Synthetic Aperture Radar (SAR) data with high temporal and spatial resolution are freely available. This provides a promising framework to facilitate detailed investigations of surface instabilities and movements on large scales with high temporal resolution, but also poses substantial processing challenges because of storage and computation requirements. Methods are needed to efficiently detect short term changes in dynamic environments. Approaches considering pair-wise processing of a series of consecutive scenes to retain maximum temporal resolution in conjunction with time series analyses are required. Here we present OSARIS, the “Open Source SAR Investigation System,” as a framework to process large stacks of S1 data on high-performance computing clusters. Based on Generic Mapping Tools SAR, shell scripts, and the workload manager Slurm, OSARIS provides an open and modular framework combining parallelization of high-performance C programs, flexible processing schemes, convenient configuration, and generation of geocoded stacks of analysis-ready base data, including amplitude, phase, coherence, and unwrapped interferograms. Time series analyses can be conducted by applying automated modules to the data stacks. The capabilities of OSARIS are demonstrated in a case study from the northwestern Tien Shan, Central Asia. After merging of slices, a total of 80 scene pairs were processed from 174 total input scenes. The coherence time series exhibits pronounced seasonal variability, with relatively high coherence values prevailing during the summer months in the nival zone. As an example of a time series analysis module, we present OSARIS' “Unstable Coherence Metric” which identifies pixels affected by significant drops from high to low coherence values. Measurements of motion provided by LOSD measurements require careful evaluation because interferometric phase unwrapping is prone to errors. Here, OSARIS provides a series of modules to detect and mask unwrapping errors, correct for atmospheric disturbances, and remove large-scale trends. Wall clock processing time for the case study (area ~9,000 km2) was ~12 h 4 min on a machine with 400 cores and 2 TB RAM. In total, ~12 d 10 h 44 min (~96%) were saved through parallelization. A comparison of selected OSARIS datasets to results from two state-of-the-art SAR processing suites, ISCE and SNAP, shows that OSARIS provides products of competitive quality despite its high level of automatization. OSARIS thus facilitates efficient S1-based region-wide investigations of surface movement events over multiple years.
Point clouds provide high-resolution topographic data which is often classified into bare-earth, vegetation, and building points and then filtered and aggregated to gridded Digital Elevation Models (DEMs) or Digital Terrain Models (DTMs). Based on these equally-spaced grids flow-accumulation algorithms are applied to describe the hydrologic and geomorphologic mass transport on the surface. In this contribution, we propose a stochastic point-cloud filtering that, together with a spatial bootstrap sampling, allows for a flow accumulation directly on point clouds using Facet-Flow Networks (FFN). Additionally, this provides a framework for the quantification of uncertainties in point-cloud derived metrics such as Specific Catchment Area (SCA) even though the flow accumulation itself is deterministic.
The northwest Argentine Andes constitute a premier natural laboratory to assess the complex interactions between isolated uplifts, orographic precipitation gradients, and related erosion and sedimentation patterns. Here we present new stratigraphic observations and age information from intermontane basin sediments to elucidate the Neogene to Quaternary shortening history and associated sediment dynamics of the broken Salta foreland. This part of the Andean orogen, which comprises an array of basement-cored range uplifts, is located at similar to 25 degrees S and lies to the east of the arid intraorogenic Altiplano/Puna plateau. In the Salta foreland, spatially and temporally disparate range uplift along steeply dipping inherited faults has resulted in foreland compartmentalization with steep basin-tobasin precipitation gradients. Sediment architecture and facies associations record a three-phase (similar to 10, similar to 5, and <2 Ma), east directed, yet unsystematic evolution of shortening, foreland fragmentation, and ensuing changes in precipitation and sediment transport. The provenance signatures of these deposits reflect the trapping of sediments in the intermontane basins of the Andean hinterland, as well as the evolution of a severed fluvial network. Present-day moisture supply to the hinterland is determined by range relief and basin elevation. The conspiring effects of range uplift and low rainfall help the entrapment and long-term storage of sediments, ultimately raising basin elevation in the hinterland, which may amplify aridification in the orogen interior.
Multiple landslide clusters record quaternary climate changes in the northwestern Argentine andes
(2003)
The chronology of multiple landslide deposits and related lake sediments in the semi-arid eastern Argentine Cordillera suggests that major mass movements cluster in two time periods during the Quaternary, i.e. between 40 and 25 and after 5 14C kyr BP. These clusters may correspond to the Minchin (maximum at around 28-27 14C kyr BP) and Titicaca wet periods (after 3.9 14C kyr BP). The more humid conditions apparently caused enhanced landsliding in this environment. In contrast, no landslide-related damming and associated lake sediments occurred during the Coipasa (11.5- 10 14C yr BP) and Tauca wet periods (14.5-11 14C yr BP). The two clusters at 40-25 and after 5 14C kyr BP may correspond to periods where the El Niño-Southern Oscillation (ENSO) and Tropical Atlantic Sea Surface Temperature Variability (TAV) were active. This, however, was not the case during the Coipasa and Tauca wet periods. Lake-balance modelling of a landslide-dammed lake suggests a 10-15% increase in precipitation and a 3-4 ° C decrease in temperature at ~30 14C kyr BP as compared to the present. In addition, time-series analysis reveals a strong ENSO and TAV during that time. The landslide clusters in northwestern Argentina are therefore best explained by periods of more humid and more variable climates.
Uplifted Neogene marine sediments and Quaternary fluvial terraces in the Mut Basin, southern Turkey, reveal a detailed history of surface uplift along the southern margin of the Central Anatolian plateau from the Late Miocene to the present. New surface exposure ages (Be-10, Al-26, and Ne-21) of gravels capping fluvial strath terraces located between 28 and 135 m above the Goksu River in the Mut Basin yield ages ranging from ca. 25 to 130 ka, corresponding to an average incision rate of 0.52 to 0.67 mm/yr. Published biostratigraphic data combined with new interpretations of the fossil assemblages from uplifted marine sediments reveal average uplift rates of 0.25 to 0.37 mm/yr since Late Miocene time (starting between 8 and 5.45 Ma), and 0.72 to 0.74 mm/yr after 1.66 to 1.62 Ma. Together with the terrace abandonment ages, the data imply 0.6 to 0.7 mm/yr uplift rates from 1.6 Ma to the present. The different post-Late Miocene and post-1.6 Ma uplift rates can imply increasing uplift rates through time, or multi-phased uplift with slow uplift or subsidence in between. Longitudinal profiles of rivers in the upper catchment of the Mut and Ermenek basins show no apparent lithologic or fault control on some knickpoints that occur at 1.2 to 1.5 km elevation, implying a transient response to a change in uplift rates. Projections of graded upper relict channel segments to the modern outlet, together with constraints from uplifted marine sediments, show that a slower incision/uplift rate of 0.1 to 0.2 mm/yr preceded the 0.7 mm/yr uplift rate. The river morphology and profile projections therefore reflect multi-phased uplift of the plateau margin, rather than steadily increasing uplift rates. Multi-phased uplift can be explained by lithospheric slab break-off and possibly also the arrival of the Eratosthenes Seamount at the collision zone south of Cyprus.
The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) with its land and vegetation height data product (ATL08), and Global Ecosystem Dynamics Investigation (GEDI) with its terrain elevation and height metrics data product (GEDI Level 2A) missions have great potential to globally map ground and canopy heights. Canopy height is a key factor in estimating above-ground biomass and its seasonal changes; these satellite missions can also improve estimated above-ground carbon stocks. This study presents a novel Sparse Vegetation Detection Algorithm (SVDA) which uses ICESat-2 (ATL03, geolocated photons) data to map tree and vegetation heights in a sparsely vegetated savanna ecosystem. The SVDA consists of three main steps: First, noise photons are filtered using the signal confidence flag from ATL03 data and local point statistics. Second, we classify ground photons based on photon height percentiles. Third, tree and grass photons are classified based on the number of neighbors. We validated tree heights with field measurements (n = 55), finding a root-mean-square error (RMSE) of 1.82 m using SVDA, GEDI Level 2A (Geolocated Elevation and Height Metrics product): 1.33 m, and ATL08: 5.59 m. Our results indicate that the SVDA is effective in identifying canopy photons in savanna ecosystems, where ATL08 performs poorly. We further identify seasonal vegetation height changes with an emphasis on vegetation below 3 m; widespread height changes in this class from two wet-dry cycles show maximum seasonal changes of 1 m, possibly related to seasonal grass-height differences. Our study shows the difficulties of vegetation measurements in savanna ecosystems but provides the first estimates of seasonal biomass changes.
The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) with its land and vegetation height data product (ATL08), and Global Ecosystem Dynamics Investigation (GEDI) with its terrain elevation and height metrics data product (GEDI Level 2A) missions have great potential to globally map ground and canopy heights. Canopy height is a key factor in estimating above-ground biomass and its seasonal changes; these satellite missions can also improve estimated above-ground carbon stocks. This study presents a novel Sparse Vegetation Detection Algorithm (SVDA) which uses ICESat-2 (ATL03, geolocated photons) data to map tree and vegetation heights in a sparsely vegetated savanna ecosystem. The SVDA consists of three main steps: First, noise photons are filtered using the signal confidence flag from ATL03 data and local point statistics. Second, we classify ground photons based on photon height percentiles. Third, tree and grass photons are classified based on the number of neighbors. We validated tree heights with field measurements (n = 55), finding a root-mean-square error (RMSE) of 1.82 m using SVDA, GEDI Level 2A (Geolocated Elevation and Height Metrics product): 1.33 m, and ATL08: 5.59 m. Our results indicate that the SVDA is effective in identifying canopy photons in savanna ecosystems, where ATL08 performs poorly. We further identify seasonal vegetation height changes with an emphasis on vegetation below 3 m; widespread height changes in this class from two wet-dry cycles show maximum seasonal changes of 1 m, possibly related to seasonal grass-height differences. Our study shows the difficulties of vegetation measurements in savanna ecosystems but provides the first estimates of seasonal biomass changes.
In the arctic and high mountains it is common to measure vertical changes of ice sheets and glaciers via digital elevation model (DEM) differencing. This requires the signal of change to outweigh the noise associated with the datasets. Excluding large landslides, on the ice-free earth the land-level change is smaller in vertical magnitude and thus requires more accurate DEMs for differencing and identification of change. Previously, this has required meter to submeter data at small spatial scales. Following careful corrections, we are able to measure land-level changes in gravel-bed channels and steep hillslopes in the south-central Andes using the SRTM-C (collected in 2000) and the TanDEM-X (collected from 2010 to 2015) near-global 12–30m DEMs. Long-standing errors in the SRTM-C are corrected using the TanDEM-X as a control surface and applying cosine-fit co-registration to remove ∼ 1∕10 pixel (∼ 3m) shifts, fast Fourier transform (FFT) and filtering to remove SRTM-C short- and long-wavelength stripes, and blocked shifting to remove remaining complex biases. The datasets are then differenced and outlier pixels are identified as a potential signal for the case of gravel-bed channels and hillslopes. We are able to identify signals of incision and aggradation (with magnitudes down to ∼ 3m in the best case) in two > 100km river reaches, with increased geomorphic activity downstream of knickpoints. Anthropogenic gravel excavation and piling is prominently measured, with magnitudes exceeding ±5m (up to > 10m for large piles). These values correspond to conservative average rates of 0.2 to > 0.5myr−1 for vertical changes in gravel-bed rivers. For hillslopes, since we require stricter cutoffs for noise, we are only able to identify one major landslide in the study area with a deposit volume of 16±0.15×106m3. Additional signals of change can be garnered from TanDEM-X auxiliary layers; however, these are more difficult to quantify. The methods presented can be extended to any region of the world with SRTM-C and TanDEM-X coverage where vertical land-level changes are of interest, with the caveat that remaining vertical uncertainties in primarily the SRTM-C limit detection in steep and complex topography.
In the arctic and high mountains it is common to measure vertical changes of ice sheets and glaciers via digital elevation model (DEM) differencing. This requires the signal of change to outweigh the noise associated with the datasets. Excluding large landslides, on the ice-free earth the land-level change is smaller in vertical magnitude and thus requires more accurate DEMs for differencing and identification of change. Previously, this has required meter to submeter data at small spatial scales. Following careful corrections, we are able to measure land-level changes in gravel-bed channels and steep hillslopes in the south-central Andes using the SRTM-C (collected in 2000) and the TanDEM-X (collected from 2010 to 2015) near-global 12–30m DEMs. Long-standing errors in the SRTM-C are corrected using the TanDEM-X as a control surface and applying cosine-fit co-registration to remove ∼ 1∕10 pixel (∼ 3m) shifts, fast Fourier transform (FFT) and filtering to remove SRTM-C short- and long-wavelength stripes, and blocked shifting to remove remaining complex biases. The datasets are then differenced and outlier pixels are identified as a potential signal for the case of gravel-bed channels and hillslopes. We are able to identify signals of incision and aggradation (with magnitudes down to ∼ 3m in the best case) in two > 100km river reaches, with increased geomorphic activity downstream of knickpoints. Anthropogenic gravel excavation and piling is prominently measured, with magnitudes exceeding ±5m (up to > 10m for large piles). These values correspond to conservative average rates of 0.2 to > 0.5myr−1 for vertical changes in gravel-bed rivers. For hillslopes, since we require stricter cutoffs for noise, we are only able to identify one major landslide in the study area with a deposit volume of 16±0.15×106m3. Additional signals of change can be garnered from TanDEM-X auxiliary layers; however, these are more difficult to quantify. The methods presented can be extended to any region of the world with SRTM-C and TanDEM-X coverage where vertical land-level changes are of interest, with the caveat that remaining vertical uncertainties in primarily the SRTM-C limit detection in steep and complex topography.
Mapping urban forest leaf area index with airborne lidar using penetration metrics and allometry
(2015)
In urban areas, leaf area index (LAI) is a key ecosystem structural attribute with implications for energy and water balance, gas exchange, and anthropogenic energy use. In this study, we estimated LAI spatially using airborne lidar in downtown Santa Barbara, California, USA. We implemented two different modeling approaches. First, we directly estimated effective LAI (LAIe) using scan angle- and clump-corrected lidar laser penetration metrics (LPM). Second, we adapted existing allometric equations to estimate crown structural metrics including tree height and crown base height using lidar. The latter approach allowed for LAI estimates at the individual tree-crown scale. The LPM method, at both high and decimated point densities, resulted in good linear agreement with estimates from ground-based hemispherical photography (r(2) = 0.82, y = 0.99x) using a model that assumed a spherical leaf angle distribution. Within individual tree crown segments, the lidar estimates of crown structure closely paralleled field measurements (e.g., r(2) = 0.87 for crown length). LAI estimates based on the lidar crown measurements corresponded well with estimates from field measurements (r(2) = 0.84, y = 0.97x + 0.10). Consistency of the LPM and allometric lidar methods was also strong at 71 validation plots (r(2) = 0.88) and at 450 additional sample locations across the entire study area (r(2) = 0.72). This level of correspondence exceeded that of the canopy hemispherical photography and allometric, ground-based estimates (r(2) = 0.53). The first-order alignment of these two disparate methods may indicate that the error bounds for mapping LAI in cities are small enough to pursue large scale, spatially explicit estimation. (C) 2015 Elsevier Inc All rights reserved.
Mapping Damage-Affected Areas after Natural Hazard Events Using Sentinel-1 Coherence Time Series
(2018)
The emergence of the Sentinel-1A and 1B satellites now offers freely available and widely accessible Synthetic Aperture Radar (SAR) data. Near-global coverage and rapid repeat time (6–12 days) gives Sentinel-1 data the potential to be widely used for monitoring the Earth’s surface. Subtle land-cover and land surface changes can affect the phase and amplitude of the C-band SAR signal, and thus the coherence between two images collected before and after such changes. Analysis of SAR coherence therefore serves as a rapidly deployable and powerful tool to track both seasonal changes and rapid surface disturbances following natural disasters. An advantage of using Sentinel-1 C-band radar data is the ability to easily construct time series of coherence for a region of interest at low cost. In this paper, we propose a new method for Potentially Affected Area (PAA) detection following a natural hazard event. Based on the coherence time series, the proposed method (1) determines the natural variability of coherence within each pixel in the region of interest, accounting for factors such as seasonality and the inherent noise of variable surfaces; and (2) compares pixel-by-pixel syn-event coherence to temporal coherence distributions to determine where statistically significant coherence loss has occurred. The user can determine to what degree the syn-event coherence value (e.g., 1st, 5th percentile of pre-event distribution) constitutes a PAA, and integrate pertinent regional data, such as population density, to rank and prioritise PAAs. We apply the method to two case studies, Sarpol-e, Iran following the 2017 Iran-Iraq earthquake, and a landslide-prone region of NW Argentina, to demonstrate how rapid identification and interpretation of potentially affected areas can be performed shortly following a natural hazard event.
Mapping Damage-Affected Areas after Natural Hazard Events Using Sentinel-1 Coherence Time Series
(2018)
The emergence of the Sentinel-1A and 1B satellites now offers freely available and widely accessible Synthetic Aperture Radar (SAR) data. Near-global coverage and rapid repeat time (6–12 days) gives Sentinel-1 data the potential to be widely used for monitoring the Earth’s surface. Subtle land-cover and land surface changes can affect the phase and amplitude of the C-band SAR signal, and thus the coherence between two images collected before and after such changes. Analysis of SAR coherence therefore serves as a rapidly deployable and powerful tool to track both seasonal changes and rapid surface disturbances following natural disasters. An advantage of using Sentinel-1 C-band radar data is the ability to easily construct time series of coherence for a region of interest at low cost. In this paper, we propose a new method for Potentially Affected Area (PAA) detection following a natural hazard event. Based on the coherence time series, the proposed method (1) determines the natural variability of coherence within each pixel in the region of interest, accounting for factors such as seasonality and the inherent noise of variable surfaces; and (2) compares pixel-by-pixel syn-event coherence to temporal coherence distributions to determine where statistically significant coherence loss has occurred. The user can determine to what degree the syn-event coherence value (e.g., 1st, 5th percentile of pre-event distribution) constitutes a PAA, and integrate pertinent regional data, such as population density, to rank and prioritise PAAs. We apply the method to two case studies, Sarpol-e, Iran following the 2017 Iran-Iraq earthquake, and a landslide-prone region of NW Argentina, to demonstrate how rapid identification and interpretation of potentially affected areas can be performed shortly following a natural hazard event.
We modeled the two most extreme highstands of Lake Naivasha during the last 175 k.y. to estimate potential precipitation/ evaporation changes in this basin. In a first step, the bathymetry of the paleolakes at f135 and 9 k.y. BP was reconstructed from sediment cores and surface outcrops. Second, we modeled the paleohydrologic budget during the highstands using a simplified coupled energy mass-balance model. Our results show that the hydrologic and hence the climate conditions at f135 and 9 k.y. BP were similar, but significantly different from today. The main difference is a f15% higher value in precipitation compared to the present. An adaptation and migration of vegetation in the cause of climate changes would result in a f30% increase in precipitation. The most likely cause for such a wetter climate at f135 and 9 k.y. BP is a more intense intertropical convergence and increased precipitation in East Africa.