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Institute
- Institut für Geowissenschaften (117) (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.
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.
Rivers draining the southern Himalaya provide most of the water supply for the densely populated Indo-Gangetic plains. Despite the importance of water resources in light of climate change, the relative contributions of rainfall, snow and glacier melt to discharge are not well understood, due to the scarcity of ground-based data in this complex terrain. Here, we quantify discharge sources in the Sutlej Valley, western Himalaya, from 2000 to 2012 with a distributed hydrological model that is based on daily, ground-calibrated remote-sensing observation. Based on the consistently good model performance, we analyzed the spatiotemporal distribution of hydrologic components and quantified their contribution to river discharge. Our results indicate that the Sutlej River's annual discharge at the mountain front is sourced to 55% by effective rainfall (rainfall reduced by evapotranspiration), 35% by snow melt and 10% by glacier melt. In the high-elevation orogenic interior glacial runoff contributes ∼30% to annual river discharge. These glacier melt contributions are especially important during years with substantially reduced rainfall and snowmelt runoff, as during 2004, to compensate for low river discharge and ensure sustained water supply and hydropower generation. In 2004, discharge of the Sutlej River totaled only half the maximum annual discharge; with 17.3% being sourced by glacier melt. Our findings underscore the importance of calibrating remote-sensing data with ground-based data to constrain hydrological models with reasonable accuracy. For instance, we found that TRMM (Tropical Rainfall Measuring Mission) product 3B42 V7 systematically overestimates rainfall in arid regions of our study area by a factor of up to 5. By quantifying the spatiotemporal distribution of water resources we provide an important assessment of the potential impact of global warming on river discharge in the western Himalaya. Given the near-global coverage of the utilized remote-sensing datasets this hydrological modeling approach can be readily transferred to other data-sparse regions.
Fluvial fill terraces preserve sedimentary archives of landscape responses to climate change, typically over millennial timescales. In the Humahuaca Basin of NW Argentina (Eastern Cordillera, southern Central Andes), our 29 new optically stimulated luminescence ages of late Pleistocene fill terrace sediments demonstrate that the timing of past river aggradation occurred over different intervals on the western and eastern sides of the valley, despite their similar bedrock lithology, mean slopes, and precipitation. In the west, aggradation coincided with periods of increasing precipitation, while in the east, aggradation coincided with decreasing precipitation or more variable conditions. Erosion rates and grain size dependencies in our cosmogenic Be-10 analyses of modern and fill terrace sediments reveal an increased importance of landsliding compared to today on the west side during aggradation, but of similar importance during aggradation on the east side. Differences in the timing of aggradation and the Be-10 data likely result from differences in valley geometry, which causes sediment to be temporarily stored in perched basins on the east side. It appears as if periods of increasing precipitation triggered landslides throughout the region, which induced aggradation in the west, but blockage of the narrow bedrock gorges downstream from the perched basins in the east. As such, basin geometry and fluvial connectivity appear to strongly influence the timing of sediment movement through the system. For larger basins that integrate subbasins with differing geometries or degrees of connectivity (like Humahuaca), sedimentary responses to climate forcing are likely attenuated.
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.
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.
Synergistic applications based on integrated hyperspectral and lidar data are receiving a growing interest from the remote-sensing community. A prerequisite for the optimum sensor fusion of hyperspectral and lidar data is an accurate geometric coalignment. The simple unadjusted integration of lidar elevation and hyperspectral reflectance causes a substantial loss of information and does not exploit the full potential of both sensors. This paper presents a novel approach for the geometric coalignment of hyperspectral and lidar airborne data, based on their respective adopted return intensity information. The complete approach incorporates ray tracing and subpixel procedures in order to overcome grid inherent discretization. It aims at the correction of extrinsic and intrinsic (camera resectioning) parameters of the hyperspectral sensor. In additional to a tie-point-based coregistration, we introduce a ray-tracing-based back projection of the lidar intensities for area-based cost aggregation. The approach consists of three processing steps. First is a coarse automatic tie-point-based boresight alignment. The second step coregisters the hyperspectral data to the lidar intensities. Third is a parametric coalignment refinement with an area-based cost aggregation. This hybrid approach of combining tie-point features and area-based cost aggregation methods for the parametric coregistration of hyperspectral intensity values to their corresponding lidar intensities results in a root-mean-square error of 1/3 pixel. It indicates that a highly integrated and stringent combination of different coalignment methods leads to an improvement of the multisensor coregistration.
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.
Snowfall comprises a significant percentage of the annual water budget in High Mountain Asia (HMA), but snow water equivalent (SWE) is poorly constrained due to lack of in-situ measurements and complex terrain that limits the efficacy of modeling and observations. Over the past few decades, SWE has been estimated with passive microwave (PM) sensors with generally good results in wide, flat, terrain, and lower reliability in densely forested, complex, or high-elevation areas. In this study, we use raw swath data from five satellite - sensors the Special Sensor Microwave/Imager (SSMI) and Special Sensor Microwave Imager/Sounder (SSMIS) (1987-2015, F08, F11, F13, F17), Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E, 2002-2011), AMSR2 (2012-2015), and the Global Precipitation Measurement (GPM, 2014-2015) - in order to understand the spatial and temporal structure of native sensor, topographic, and land cover biases in SWE estimates in HMA. We develop a thorough understanding of the uncertainties in our SWE estimates by examining the impacts of topographic parameters (aspect, relief, hillslope angle, and elevation), land cover, native sensor biases, and climate parameters (precipitation, temperature, and wind speed). HMA, with its high seasonality, large topographic gradients and low relief at high elevations provides an excellent context to examine a wide range of climatic, land-cover, and topographic settings to better constrain SWE uncertainties and potential sensor bias. Using a multi-parameter regression, we compare long-term SWE variability to forest fraction, maximal multiyear snow depth, topographic parameters, and long-term average wind speed across both individual sensor time series and a merged multi-sensor dataset. In regions where forest cover is extensive, it is the strongest control on SWE variability. In those regions where forest density is low (<5%), maximal snow depth dominates the uncertainty signal. In our regression across HMA, we find that forest fraction is the strongest control on SWE variability (75.8%), followed by maximal multi-year snow depth (7.82%), 90th percentile 10-m wind speed of a 10-year December-January-February (DJF) time series (5.64%), 25th percentile DJF 10-m wind speed (5.44%), and hillslope angle (5.24%). Elevation, relief, and terrain aspect show very low influence on SWE variability (<1%). We find that the GPM sensor provides the most robust regression results, and can be reliably used to estimate SWE in our study region. While forest cover and elevation have been integrated into many SWE algorithms, wind speed and long-term maximal snow depth have not. Our results show that wind redistribution of snow can have impacts on SWE, especially over large, flat, areas. Using our regression results, we have developed an understanding of sensor specific SWE uncertainties and their spatial patterns. The uncertainty maps developed in this study provide a first-order approximation of SWE-estimate reliability for much of HMA, and imply that high-fidelity SWE estimates can be produced for many high-elevation areas. (C) 2016 Elsevier Inc. All rights reserved.
Deciphering the response of sediment routing systems to climatic forcing is fundamental for understanding the impacts of climate change on landscape evolution. In the Kangra Basin (northwest Sub-Himalaya, India), upper Pleistocene to Holocene alluvial fills and fluvial terraces record periodic fluctuations of sediment supply and transport capacity on timescales of 10(3) to 10(5) yr. To evaluate the potential influence of climate change on these fluctuations, we compare the timing of aggradation and incision phases recorded within remnant alluvial fans and terraces with climate archives. New surface-exposure dating of six terrace levels with in-situ cosmogenic Be-10 indicates the onset of incision phases. Two terrace surfaces from the highest level (T1) sculpted into the oldest preserved alluvial fan (AF1) date back to 53.4 +/- 3.2 ka and 43.0 +/- 2.7 ka (1 sigma). T2 surfaces sculpted into the remnants of AF1 have exposure ages of 18.6 +/- 1.2 ka and 15.3 +/- 0.9 ka, while terraces sculpted into the upper Pleistocene-Holocene fan (AF2) provide ages of 9.3 +/- 0.4 ka (T3), 7.1 +/- 0.4 ka (T4), 5.2 +/- 0.4 ka (T5) and 3.6 +/- 0.2 ka (T6). Together with previously published OSL ages yielding the timing of aggradation, we find a correlation between variations in sediment transport with oxygen-isotope records from regions affected by the Indian Summer Monsoon. During periods of increased monsoon intensity and post-Last Glacial Maximum glacial retreat, aggradation occurred in the Kangra Basin, likely due to high sediment flux, whereas periods of weakened monsoon intensity or lower sediment supply coincide with incision. (C) 2016 Elsevier B.V. All rights reserved.
The Greater and Lesser Caucasus mountains and their associated foreland basins contain similar rock types, experience a similar two-fold, along-strike variation in mean annual precipitation, and were affected by extreme base-level drops of the neighboring Caspian Sea. However, the two Caucasus ranges are characterized by decidedly different tectonic regimes and rates of deformation that are subject to moderate (less than an order of magnitude) gradients in climate, and thus allow for a unique opportunity to isolate the effects of climate and tectonics in the evolution of topography within active orogens. There is an apparent disconnect between modern climate, shortening rates, and topography of both the Greater Caucasus and Lesser Caucasus which exhibit remarkably similar topography along-strike despite the gradients in forcing. By combining multiple datasets, we examine plausible causes for this disconnect by presenting a detailed analysis of the topography of both ranges utilizing established relationships between catchment-mean erosion rates and topography (local relief, hillslope gradients, and channel steepness) and combining it with a synthesis of previously published low-temperature thermochronologic data. Modern climate of the Caucasus region is assessed through an analysis of remotely-sensed data (TRMM and MODIS) and historical streamflow data. Because along-strike variation in either erosional efficiency or thickness of accreted material fail to explain our observations, we suggest that the topography of both the western Lesser and Greater Caucasus are partially supported by different geodynamic forces. In the western Lesser Caucasus, high relief portions of the landscape likely reflect uplift related to ongoing mantle lithosphere delamination beneath the neighboring East Anatolian Plateau. In the Greater Caucasus, maintenance of high topography in the western portion of the range despite extremely low (<2-4 mm/y) modern convergence rates may be related to dynamic topography from detachment of the north-directed Greater Caucasus slab or to a recent slowing of convergence rates. Large-scale spatial gradients in climate are not reflected in the topography of the Caucasus and do not seem to exert any significant control on the tectonics or structure of either range. (C) 2016 Elsevier B.V. All rights reserved.
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 southernmost thrust of the Himalayan orogenic wedge that separates the foreland from the orogen, the Main Frontal Thrust, is thought to accommodate most of the ongoing crustal shortening in the Sub-Himalaya. Steepened longitudinal river profile segments, terrace offsets, and back-tilted fluvial terraces within the Kangra reentrant of the NW Sub-Himalaya suggest Holocene activity of the Jwalamukhi Thrust (JMT) and other thrust faults that may be associated with strain partitioning along the toe of the Himalayan wedge. To assess the shortening accommodated by the JMT, we combine morphometric terrain analyses with in situ Be-10-based surface-exposure dating of the deformed terraces. Incision into upper Pleistocene sediments within the Kangra Basin created two late Pleistocene terrace levels (T1 and T2). Subsequent early Holocene aggradation shortly before similar to 10ka was followed by episodic reincision, which created four cut-and-fill terrace levels, the oldest of which (T3) was formed at 10.10.9ka. A vertical offset of 445m of terrace T3 across the JMT indicates a shortening rate of 5.60.8 to 7.51.1mma(-1) over the last similar to 10ka. This result suggests that thrusting along the JMT accommodates 40-60% of the total Sub-Himalayan shortening in the Kangra reentrant over the Holocene. We speculate that this out-of-sequence shortening may have been triggered or at least enhanced by late Pleistocene and Holocene erosion of sediments from the Kangra Basin.
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.
Introducing PebbleCounts
(2019)
Grain-size distributions are a key geomorphic metric of gravel-bed rivers. Traditional measurement methods include manual counting or photo sieving, but these are achievable only at the 1–10 ㎡ scale. With the advent of drones and increasingly high-resolution cameras, we can now generate orthoimagery over hectares at millimeter to centimeter resolution. These scales, along with the complexity of high-mountain rivers, necessitate different approaches for photo sieving. As opposed to other image segmentation methods that use a watershed approach, our open-source algorithm, PebbleCounts, relies on k-means clustering in the spatial and spectral domain and rapid manual selection of well-delineated grains. This improves grain-size estimates for complex riverbed imagery, without post-processing. We also develop a fully automated method, PebbleCountsAuto, that relies on edge detection and filtering suspect grains, without the k-means clustering or manual selection steps. The algorithms are tested in controlled indoor conditions on three arrays of pebbles and then applied to 12 × 1 ㎡ orthomosaic clips of high-energy mountain rivers collected with a camera-on-mast setup (akin to a low-flying drone). A 20-pixel b-axis length lower truncation is necessary for attaining accurate grain-size distributions. For the k-means PebbleCounts approach, average percentile bias and precision are 0.03 and 0.09 ψ, respectively, for ∼1.16 mm pixel⁻¹ images, and 0.07 and 0.05 ψ for one 0.32 mm pixel⁻¹ image. The automatic approach has higher bias and precision of 0.13 and 0.15 ψ, respectively, for ∼1.16 mm pixel⁻¹ images, but similar values of −0.06 and 0.05 ψ for one 0.32 mm pixel⁻¹ image. For the automatic approach, only at best 70 % of the grains are correct identifications, and typically around 50 %. PebbleCounts operates most effectively at the 1 ㎡ patch scale, where it can be applied in ∼5–10 min on many patches to acquire accurate grain-size data over 10–100 ㎡ areas. These data can be used to validate PebbleCountsAuto, which may be applied at the scale of entire survey sites (102–104 ㎡ ). We synthesize results and recommend best practices for image collection, orthomosaic generation, and grain-size measurement using both algorithms.
Introducing PebbleCounts
(2019)
Grain-size distributions are a key geomorphic metric of gravel-bed rivers. Traditional measurement methods include manual counting or photo sieving, but these are achievable only at the 1–10 ㎡ scale. With the advent of drones and increasingly high-resolution cameras, we can now generate orthoimagery over hectares at millimeter to centimeter resolution. These scales, along with the complexity of high-mountain rivers, necessitate different approaches for photo sieving. As opposed to other image segmentation methods that use a watershed approach, our open-source algorithm, PebbleCounts, relies on k-means clustering in the spatial and spectral domain and rapid manual selection of well-delineated grains. This improves grain-size estimates for complex riverbed imagery, without post-processing. We also develop a fully automated method, PebbleCountsAuto, that relies on edge detection and filtering suspect grains, without the k-means clustering or manual selection steps. The algorithms are tested in controlled indoor conditions on three arrays of pebbles and then applied to 12 × 1 ㎡ orthomosaic clips of high-energy mountain rivers collected with a camera-on-mast setup (akin to a low-flying drone). A 20-pixel b-axis length lower truncation is necessary for attaining accurate grain-size distributions. For the k-means PebbleCounts approach, average percentile bias and precision are 0.03 and 0.09 ψ, respectively, for ∼1.16 mm pixel⁻¹ images, and 0.07 and 0.05 ψ for one 0.32 mm pixel⁻¹ image. The automatic approach has higher bias and precision of 0.13 and 0.15 ψ, respectively, for ∼1.16 mm pixel⁻¹ images, but similar values of −0.06 and 0.05 ψ for one 0.32 mm pixel⁻¹ image. For the automatic approach, only at best 70 % of the grains are correct identifications, and typically around 50 %. PebbleCounts operates most effectively at the 1 ㎡ patch scale, where it can be applied in ∼5–10 min on many patches to acquire accurate grain-size data over 10–100 ㎡ areas. These data can be used to validate PebbleCountsAuto, which may be applied at the scale of entire survey sites (102–104 ㎡ ). We synthesize results and recommend best practices for image collection, orthomosaic generation, and grain-size measurement using both algorithms.
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.
Determining the optimal grid resolution for topographic analysis on an airborne lidar dataset
(2019)
Digital elevation models (DEMs) are a gridded representation of the surface of the Earth and typically contain uncertainties due to data collection and processing. Slope and aspect estimates on a DEM contain errors and uncertainties inherited from the representation of a continuous surface as a grid (referred to as truncation error; TE) and from any DEM uncertainty. We analyze in detail the impacts of TE and propagated elevation uncertainty (PEU) on slope and aspect.
Using synthetic data as a control, we define functions to quantify both TE and PEU for arbitrary grids. We then develop a quality metric which captures the combined impact of both TE and PEU on the calculation of topographic metrics. Our quality metric allows us to examine the spatial patterns of error and uncertainty in topographic metrics and to compare calculations on DEMs of different sizes and accuracies.
Using lidar data with point density of ∼10 pts m−2 covering Santa Cruz Island in southern California, we are able to generate DEMs and uncertainty estimates at several grid resolutions. Slope (aspect) errors on the 1 m dataset are on average 0.3∘ (0.9∘) from TE and 5.5∘ (14.5∘) from PEU. We calculate an optimal DEM resolution for our SCI lidar dataset of 4 m that minimizes the error bounds on topographic metric calculations due to the combined influence of TE and PEU for both slope and aspect calculations over the entire SCI. Average slope (aspect) errors from the 4 m DEM are 0.25∘ (0.75∘) from TE and 5∘ (12.5∘) from PEU. While the smallest grid resolution possible from the high-density SCI lidar is not necessarily optimal for calculating topographic metrics, high point-density data are essential for measuring DEM uncertainty across a range of resolutions.
Determining the optimal grid resolution for topographic analysis on an airborne lidar dataset
(2019)
Digital elevation models (DEMs) are a gridded representation of the surface of the Earth and typically contain uncertainties due to data collection and processing. Slope and aspect estimates on a DEM contain errors and uncertainties inherited from the representation of a continuous surface as a grid (referred to as truncation error; TE) and from any DEM uncertainty. We analyze in detail the impacts of TE and propagated elevation uncertainty (PEU) on slope and aspect.
Using synthetic data as a control, we define functions to quantify both TE and PEU for arbitrary grids. We then develop a quality metric which captures the combined impact of both TE and PEU on the calculation of topographic metrics. Our quality metric allows us to examine the spatial patterns of error and uncertainty in topographic metrics and to compare calculations on DEMs of different sizes and accuracies.
Using lidar data with point density of ∼10 pts m−2 covering Santa Cruz Island in southern California, we are able to generate DEMs and uncertainty estimates at several grid resolutions. Slope (aspect) errors on the 1 m dataset are on average 0.3∘ (0.9∘) from TE and 5.5∘ (14.5∘) from PEU. We calculate an optimal DEM resolution for our SCI lidar dataset of 4 m that minimizes the error bounds on topographic metric calculations due to the combined influence of TE and PEU for both slope and aspect calculations over the entire SCI. Average slope (aspect) errors from the 4 m DEM are 0.25∘ (0.75∘) from TE and 5∘ (12.5∘) from PEU. While the smallest grid resolution possible from the high-density SCI lidar is not necessarily optimal for calculating topographic metrics, high point-density data are essential for measuring DEM uncertainty across a range of resolutions.
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 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.
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 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.
Improving semi-automated glacier mapping with a multi-method approach: applications in central Asia
(2015)
Studies of glaciers generally require precise glacier outlines. Where these are not available, extensive manual digitization in a geographic information system (GIS) must be performed, as current algorithms struggle to delineate glacier areas with debris cover or other irregular spectral profiles. Although several approaches have improved upon spectral band ratio delineation of glacier areas, none have entered wide use due to complexity or computational intensity.
In this study, we present and apply a glacier mapping algorithm in Central Asia which delineates both clean glacier ice and debris-covered glacier tongues. The algorithm is built around the unique velocity and topographic characteristics of glaciers and further leverages spectral and spatial relationship data. We found that the algorithm misclassifies between 2 and 10% of glacier areas, as compared to a similar to 750 glacier control data set, and can reliably classify a given Landsat scene in 3-5 min.
The algorithm does not completely solve the difficulties inherent in classifying glacier areas from remotely sensed imagery but does represent a significant improvement over purely spectral-based classification schemes, such as the band ratio of Landsat 7 bands three and five or the normalized difference snow index. The main caveats of the algorithm are (1) classification errors at an individual glacier level, (2) reliance on manual intervention to separate connected glacier areas, and (3) dependence on fidelity of the input Landsat data.
Extreme Rainfall of the South American Monsoon System: A Dataset Comparison Using Complex Networks
(2015)
In this study, the authors compare six different rainfall datasets for South America with a focus on their representation of extreme rainfall during the monsoon season (December February): the gauge-calibrated TRMM 3B42 V7 satellite product; the near-real-time TRMM 3B42 V7 RT, the GPCP 1 degrees daily (1DD) V1.2 satellite gauge combination product, the Interim ECMWF Re-Analysis (ERA-Interim) product; output of a high-spatial-resolution run of the ECHAM6 global circulation model; and output of the regional climate model Eta. For the latter three, this study can be understood as a model evaluation. In addition to statistical values of local rainfall distributions, the authors focus on the spatial characteristics of extreme rainfall covariability. Since traditional approaches based on principal component analysis are not applicable in the context of extreme events, they apply and further develop methods based on complex network theory. This way, the authors uncover substantial differences in extreme rainfall patterns between the different datasets: (i) The three model-derived datasets yield very different results than the satellite gauge combinations regarding the main climatological propagation pathways of extreme events as well as the main convergence zones of the monsoon system. (ii) Large discrepancies are found for the development of mesoscale convective systems in southeastern South America. (iii) Both TRMM datasets and ECHAM6 indicate a linkage of extreme rainfall events between the central Amazon basin and the eastern slopes of the central Andes, but this pattern is not reproduced by the remaining datasets. The authors' study suggests that none of the three model-derived datasets adequately captures extreme rainfall patterns in South America.
Piggyback basins on the margins of growing orogens commonly serve as sensitive recorders of the onset of thrust deformation and changes in source areas. The Bieertuokuoyi piggyback basin, located in the hanging wall of the Pamir Frontal Thrust, provides an unambiguous record of the outward growth of the northeast Pamir margin in northwest China from the Miocene through the Quaternary. To reconstruct the deformation along the margin, we synthesized structural mapping, stratigraphy, magnetostratigraphy, and cosmogenic burial dating of basin fill and growth strata. The Bieertuokuoyi basin records the initiation of the Pamir Frontal Thrust and the Takegai Thrust similar to 5-6Ma, as well as clast provenance and paleocurrent changes resulting from the Pliocene-to-Recent uplift and exhumation of the Pamir to the south. Our results show that coeval deformation was accommodated on the major structures on the northeast Pamir margin throughout the Miocene to Recent. Furthermore, our data support a change in the regional kinematics around the Miocene-Pliocene boundary (similar to 5-6Ma). Rapid exhumation of NE Pamir extensional domes, coupled with cessation of the Kashgar-Yecheng Transfer System on the eastern margin of the Pamir, accelerated the outward propagation of the northeastern Pamir margin and the southward propagation of the Kashi-Atushi fold-and-thrust belt in the southern Tian Shan. This coeval deformation signifies the coupling of the Pamir and Tarim blocks and the transfer of shortening north to the Pamir frontal faults and across the quasi-rigid Tarim Basin to the southern Tian Shan Kashi-Atushi fold-and-thrust system.
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.
The mechanisms by which climate and vegetation affect erosion rates over various time scales lie at the heart of understanding landscape response to climate change. Plot-scale field experiments show that increased vegetation cover slows erosion, implying that faster erosion should occur under low to moderate vegetation cover. However, demonstrating this concept over long time scales and across landscapes has proven to be difficult, especially in settings complicated by tectonic forcing and variable slopes. We investigate this problem by measuring cosmogenic Be-10-derived catchment-mean denudation rates across a range of climate zones and hillslope gradients in the Kenya Rift, and by comparing our results with those published from the Rwenzori Mountains of Uganda. We find that denudation rates from sparsely vegetated parts of the Kenya Rift are up to 0.13 mm/yr, while those from humid and more densely vegetated parts of the Kenya Rift flanks and the Rwenzori Mountains reach a maximum of 0.08 mm/yr, despite higher median hillslope gradients. While differences in lithology and recent land-use changes likely affect the denudation rates and vegetation cover values in some of our studied catchments, hillslope gradient and vegetation cover appear to explain most of the variation in denudation rates across the study area. Our results support the idea that changing vegetation cover can contribute to complex erosional responses to climate or land-use change and that vegetation cover can play an important role in determining the steady-state slopes of mountain belts through its stabilizing effects on the land surface.
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.
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.
Geodetic and seismologic studies support a tectonic model for the central Himalaya wherein similar to 2 cm/yr of Indo-Asian convergence is accommodated along the primary decollement under the range, the Main Himalayan thrust. A steeper midcrustal ramp in the Main Himalayan thrust is commonly invoked as driving rapid rock uplift along a range-parallel band in the Greater Himalaya. This tectonic model, developed primarily from studies in central Nepal, is commonly assumed to project along strike with little lateral variation in Main Himalayan thrust geometry or associated rock uplift patterns. Here, we synthesize multiple lines of evidence for a major discontinuity in the Main Himalayan thrust in western Nepal. Analysis of topography and seismicity indicates that west of similar to 82.5 degrees E, the single band of steep topography and seismicity along the Main Himalayan thrust ramp in central Nepal bifurcates around a high-elevation, low-relief landscape, resulting in a two-step topographic front along an similar to 150 km segment of the central Himalaya. Although multiple models could explain this bifurcation, the full suite of data appears to be most consistent with a northward bend to the Main Himalayan thrust ramp and activation of a young duplex horse to the south. This poorly documented segmentation of the Main Himalayan thrust has important implications for the seismogenic potential of the western Nepal seismic gap and for models of the ongoing evolution of the orogen.
The response of surface processes to climatic forcing is fundamental for understanding the impacts of climate change on landscape evolution. In the Himalaya, most large rivers feature prominent fill terraces that record an imbalance between sediment supply and transport capacity, presumably due to past fluctuations in monsoon precipitation and/or effects of glaciation at high elevation. Here, we present volume estimates, chronological constraints, and Be-10-derived paleo-erosion rates from a prominent valley fill in the Yamuna catchment, Garhwal Himalaya, to elucidate the coupled response of rivers and hillslopes to Pleistocene climate change. Although precise age control is complicated due to methodological problems, the new data support formation of the valley fill during the late Pleistocene and its incision during the Holocene. We interpret this timing to indicate that changes in discharge and river-transport capacity were major controls. Compared to the present day, late Pleistocene hillslope erosion rates were higher by a factor of similar to 2-4, but appear to have decreased during valley aggradation. The higher late Pleistocene erosion rates are largely unrelated to glacial erosion and could be explained by enhanced sediment production on steep hillslopes due to increased periglacial activity that declined as temperatures increased. Alternatively, erosion rates that decrease during valley aggradation are also consistent with reduced landsliding from threshold hillslopes as a result of rising base levels. In that case, the similarity of paleo-erosion rates near the end of the aggradation period with modern erosion rates might imply that channels and hillslopes are not yet fully coupled everywhere and that present-day hillslope erosion rates may underrepresent long-term incision rates. (C) 2015 Elsevier B.V. All rights reserved.
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.
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.
A valley-filling ignimbrite re-exposed through subsequent river incision at the southern margin of the Andean (Puna) plateau preserves pristine geological evidence of pre-late Miocene palaeotopography in the north western Argentine Andes. Our new Ar-40/(39) Ar dating of the Las Papas Ignimbrites yields a plateau age of 9.24 +/- 0.03 Ma, indicating valley-relief and orographic-barrier conditions comparable to the present-day. A later infill of Plio-Pleistocene coarse conglomerates has been linked to wetter conditions, but resulted in no additional net incision of the Las Papas valley, considering that the base of the ignimbrite remains unexposed in the valley bottom. Our observations indicate that at least 550 m of local plateau margin relief (and likely > 2 km) existed by 9 Ma at the southern Puna margin, which likely aided the efficiency of the orographic barrier to rainfall along the eastern and south eastern flanks of the Puna and causes aridity in the plateau interior.
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).
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.
High Asian glacial landscapes have large variations in topographic relief and the size and steepness of snow accumulation areas. Associated differences in glacial cover and dynamics allow a first-order determination of the dominant processes shaping these landscapes. Here we provide a regional synthesis of the topography and flow characteristics of 287 glaciers across High Asia using digital elevation analysis and remotely sensed glacier surface velocities. Glaciers situated in low-relief areas on the Tibetan Plateau are mainly nourished by direct snowfall, have little or no debris cover, and have a relatively symmetrical distribution of velocities along their length. In contrast, avalanche-fed glaciers with steep accumulation areas, which occur at the deeply incised edges of the Tibetan Plateau, are heavily covered with supraglacial debris, and flow velocities are highest along short segments near their headwalls but greatly reduced along their debris-mantled lower parts. The downstream distribution of flow velocities suggests that the glacial erosion potential is progressively shifted upstream as accumulation areas get steeper and hillslope debris fluxes increase. Our data suggest that the coupling of hillslopes and glacial dynamics increases with topographic steepness and debris cover. The melt-lowering effect of thick debris cover allows the existence of glaciers even when they are located entirely below the snow line. However, slow velocities limit the erosion potential of such glaciers, and their main landscape-shaping contribution may simply be the evacuation of debris from the base of glacial headwalls, which inhibits the formation of scree slopes and thereby allows ongoing headwall retreat by periglacial hillslope processes. We propose a conceptual model in which glacially influenced plateau margins evolve from low-relief to high-relief landscapes with distinctive contributions of hillslope processes and glaciers to relief production and decay.
The sediment flux through Himalayan rivers directly impacts water quality and is important for sustaining agriculture as well as maintaining drinking-water and hydropower generation. Despite the recent increase in demand for these resources, little is known about the triggers and sources of extreme sediment flux events, which lower water quality and account for extensive hydropower reservoir filling and turbine abrasion. Here, we present a comprehensive analysis of the spatiotemporal trends in suspended sediment flux based on daily data during the past decade (2001-2009) from four sites along the Sutlej River and from four of its main tributaries. In conjunction with satellite data depicting rainfall and snow cover, air temperature and earthquake records, and field observations, we infer climatic and geologic controls of peak suspended sediment concentration (SSC) events. Our study identifies three key findings: First, peak SSC events (a parts per thousand yen 99th SSC percentile) coincide frequently (57-80%) with heavy rainstorms and account for about 30% of the suspended sediment flux in the semi-arid to arid interior of the orogen. Second, we observe an increase of suspended sediment flux from the Tibetan Plateau to the Himalayan Front at mean annual timescales. This sediment-flux gradient suggests that averaged, modern erosion in the western Himalaya is most pronounced at frontal regions, which are characterized by high monsoonal rainfall and thick soil cover. Third, in seven of eight catchments, we find an anticlockwise hysteresis loop of annual sediment flux variations with respect to river discharge, which appears to be related to enhanced glacial sediment evacuation during late summer. Our analysis emphasizes the importance of unconsolidated sediments in the high-elevation sector that can easily be mobilized by hydrometeorological events and higher glacial-meltwater contributions. In future climate change scenarios, including continuous glacial retreat and more frequent monsoonal rainstorms across the Himalaya, we expect an increase in peak SSC events, which will decrease the water quality and impact hydropower generation.
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 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.
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.
Erosional exhumation and topography in mountain belts are temporally and spatially variable over million year timescales because of changes in both the location of deformation and climate. We investigate spatiotemporal variations in exhumation across a 150 x 250 km compartment of the NW Himalaya, India. Twenty-four new and 241 previously published apatite and zircon fission track and white mica Ar-40/Ar-39 ages are integrated with a 1-D numerical model to quantify rates and timing of exhumation alongstrike of several major structures in the Lesser, High, and Tethyan Himalaya. Analysis of thermochronometer data suggests major temporal variations in exhumation occurred in the early middle Miocene and at the Plio-Pleistocene transition. (1) Most notably, exhumation rates for the northern High Himalayan compartments were high (2-3 mm a(-1)) between similar to 23-19 and similar to 3-0 Ma and low (0.5-0.7 mm a(-1)) in between similar to 19-3 Ma. (2) Along the southern High Himalayan slopes, however, high exhumation rates of 1-2 mm a(-1) existed since 11 Ma. (3) Our thermochronology data sets are poorly correlated with present-day rainfall, local relief, and specific stream power which may likely result from (1) a lack of sensitivity of changes in crustal cooling to spatial variations in erosion at high exhumation rates (>similar to 1 mm a(-1)), (2) spatiotemporal variation in erosion not mimicking the present-day topographic or climatic conditions, or (3) the thermochronometer samples in this region having cooled under topography that only weakly resembled the modern-day topography.