@article{TofeldeSchildgenSavietal.2017, author = {Tofelde, Stefanie and Schildgen, Taylor F. and Savi, Sara and Pingel, Heiko and Wickert, Andrew D. and Bookhagen, Bodo and Wittmann, Hella and Alonso, Ricardo N. and Cottle, John and Strecker, Manfred}, title = {100 kyr fluvial cut-and-fill terrace cycles since the Middle Pleistocene in the southern Central Andes, NW Argentina}, series = {Earth \& planetary science letters}, volume = {473}, journal = {Earth \& planetary science letters}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0012-821X}, doi = {10.1016/j.epsl.2017.06.001}, pages = {141 -- 153}, year = {2017}, abstract = {Fluvial fill terraces in intermontane basins are valuable geomorphic archives that can record tectonically and/or climatically driven changes of the Earth-surface process system. However, often the preservation of fill terrace sequences is incomplete and/or they may form far away from their source areas, complicating the identification of causal links between forcing mechanisms and landscape response, especially over multi-millennial timescales. The intermontane Toro Basin in the southern Central Andes exhibits at least five generations of fluvial terraces that have been sculpted into several-hundred-meter-thick Quaternary valley-fill conglomerates. New surface-exposure dating using nine cosmogenic Be-10 depth profiles reveals the successive abandonment of these terraces with a 100 kyr cyclicity between 75 +/- 7 and 487 +/- 34 ka. Depositional ages of the conglomerates, determined by four Al-26/Be-10 burial samples and U-Pb zircon ages of three intercalated volcanic ash beds, range from 18 +/- 141 to 936 +/- 170 ka, indicating that there were multiple cut-and-fill episodes. Although the initial onset of aggradation at similar to 1 Ma and the overall net incision since ca. 500 ka can be linked to tectonic processes at the narrow basin outlet, the superimposed 100 kyr cycles of aggradation and incision are best explained by eccentricity-driven climate change. Within these cycles, the onset of river incision can be correlated with global cold periods and enhanced humid phases recorded in paleoclimate archives on the adjacent Bolivian Altiplano, whereas deposition occurred mainly during more arid phases on the Altiplano and global interglacial periods. We suggest that enhanced runoff during global cold phases - due to increased regional precipitation rates, reduced evapotranspiration, or both - resulted in an increased sediment-transport capacity in the Toro Basin, which outweighed any possible increases in upstream sediment supply and thus triggered incision. Compared with two nearby basins that record precessional (21-kyr) and long-eccentricity (400-kyr) forcing within sedimentary and geomorphic archives, the recorded cyclicity scales with the square of the drainage basin length. (C) 2017 Elsevier B.V. All rights reserved.}, language = {en} } @article{RamezaniZiaraniBookhagenSchmidtetal.2021, author = {Ramezani Ziarani, Maryam and Bookhagen, Bodo and Schmidt, Torsten and Wickert, Jens and de la Torre, Alejandro and Deng, Zhiguo and Calori, Andrea}, title = {A model for the relationship between rainfall, GNSS-derived integrated water vapour, and CAPE in the eastern central Andes}, series = {Remote Sensing}, volume = {13}, journal = {Remote Sensing}, number = {18}, publisher = {MDPI}, address = {Basel}, issn = {2072-4292}, doi = {10.3390/rs13183788}, pages = {19}, year = {2021}, abstract = {Atmospheric water vapour content is a key variable that controls the development of deep convective storms and rainfall extremes over the central Andes. Direct measurements of water vapour are challenging; however, recent developments in microwave processing allow the use of phase delays from L-band radar to measure the water vapour content throughout the atmosphere: Global Navigation Satellite System (GNSS)-based integrated water vapour (IWV) monitoring shows promising results to measure vertically integrated water vapour at high temporal resolutions. Previous works also identified convective available potential energy (CAPE) as a key climatic variable for the formation of deep convective storms and rainfall in the central Andes. Our analysis relies on GNSS data from the Argentine Continuous Satellite Monitoring Network, Red Argentina de Monitoreo Satelital Continuo (RAMSAC) network from 1999 to 2013. CAPE is derived from version 2.0 of the ECMWF's (European Centre for Medium-Range Weather Forecasts) Re-Analysis (ERA-interim) and rainfall from the TRMM (Tropical Rainfall Measuring Mission) product. In this study, we first analyse the rainfall characteristics of two GNSS-IWV stations by comparing their complementary cumulative distribution function (CCDF). Second, we separately derive the relation between rainfall vs. CAPE and GNSS-IWV. Based on our distribution fitting analysis, we observe an exponential relation of rainfall to GNSS-IWV. In contrast, we report a power-law relationship between the daily mean value of rainfall and CAPE at the GNSS-IWV station locations in the eastern central Andes that is close to the theoretical relationship based on parcel theory. Third, we generate a joint regression model through a multivariable regression analysis using CAPE and GNSS-IWV to explain the contribution of both variables in the presence of each other to extreme rainfall during the austral summer season. We found that rainfall can be characterised with a higher statistical significance for higher rainfall quantiles, e.g., the 0.9 quantile based on goodness-of-fit criterion for quantile regression. We observed different contributions of CAPE and GNSS-IWV to rainfall for each station for the 0.9 quantile. Fourth, we identify the temporal relation between extreme rainfall (the 90th, 95th, and 99th percentiles) and both GNSS-IWV and CAPE at 6 h time steps. We observed an increase before the rainfall event and at the time of peak rainfall—both for GNSS-integrated water vapour and CAPE. We show higher values of CAPE and GNSS-IWV for higher rainfall percentiles (99th and 95th percentiles) compared to the 90th percentile at a 6-h temporal scale. Based on our correlation analyses and the dynamics of the time series, we show that both GNSS-IWV and CAPE had comparable magnitudes, and we argue to consider both climatic variables when investigating their effect on rainfall extremes.}, language = {en} } @misc{RamezaniZiaraniBookhagenSchmidtetal.2021, author = {Ramezani Ziarani, Maryam and Bookhagen, Bodo and Schmidt, Torsten and Wickert, Jens and de la Torre, Alejandro and Deng, Zhiguo and Calori, Andrea}, title = {A model for the relationship between rainfall, GNSS-derived integrated water vapour, and CAPE in the eastern central Andes}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1172}, issn = {1866-8372}, doi = {10.25932/publishup-52325}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-523256}, pages = {21}, year = {2021}, abstract = {Atmospheric water vapour content is a key variable that controls the development of deep convective storms and rainfall extremes over the central Andes. Direct measurements of water vapour are challenging; however, recent developments in microwave processing allow the use of phase delays from L-band radar to measure the water vapour content throughout the atmosphere: Global Navigation Satellite System (GNSS)-based integrated water vapour (IWV) monitoring shows promising results to measure vertically integrated water vapour at high temporal resolutions. Previous works also identified convective available potential energy (CAPE) as a key climatic variable for the formation of deep convective storms and rainfall in the central Andes. Our analysis relies on GNSS data from the Argentine Continuous Satellite Monitoring Network, Red Argentina de Monitoreo Satelital Continuo (RAMSAC) network from 1999 to 2013. CAPE is derived from version 2.0 of the ECMWF's (European Centre for Medium-Range Weather Forecasts) Re-Analysis (ERA-interim) and rainfall from the TRMM (Tropical Rainfall Measuring Mission) product. In this study, we first analyse the rainfall characteristics of two GNSS-IWV stations by comparing their complementary cumulative distribution function (CCDF). Second, we separately derive the relation between rainfall vs. CAPE and GNSS-IWV. Based on our distribution fitting analysis, we observe an exponential relation of rainfall to GNSS-IWV. In contrast, we report a power-law relationship between the daily mean value of rainfall and CAPE at the GNSS-IWV station locations in the eastern central Andes that is close to the theoretical relationship based on parcel theory. Third, we generate a joint regression model through a multivariable regression analysis using CAPE and GNSS-IWV to explain the contribution of both variables in the presence of each other to extreme rainfall during the austral summer season. We found that rainfall can be characterised with a higher statistical significance for higher rainfall quantiles, e.g., the 0.9 quantile based on goodness-of-fit criterion for quantile regression. We observed different contributions of CAPE and GNSS-IWV to rainfall for each station for the 0.9 quantile. Fourth, we identify the temporal relation between extreme rainfall (the 90th, 95th, and 99th percentiles) and both GNSS-IWV and CAPE at 6 h time steps. We observed an increase before the rainfall event and at the time of peak rainfall—both for GNSS-integrated water vapour and CAPE. We show higher values of CAPE and GNSS-IWV for higher rainfall percentiles (99th and 95th percentiles) compared to the 90th percentile at a 6-h temporal scale. Based on our correlation analyses and the dynamics of the time series, we show that both GNSS-IWV and CAPE had comparable magnitudes, and we argue to consider both climatic variables when investigating their effect on rainfall extremes.}, language = {en} } @article{RheinwahltGoswamiBookhagen2019, author = {Rheinwahlt, Aljoscha and Goswami, Bedartha and Bookhagen, Bodo}, title = {A network-based flow accumulation algorithm for point clouds}, series = {Journal of geophysical research : Earth surface}, volume = {124}, journal = {Journal of geophysical research : Earth surface}, number = {7}, publisher = {American Geophysical Union}, address = {Washington}, issn = {2169-9003}, doi = {10.1029/2018JF004827}, pages = {2013 -- 2033}, year = {2019}, abstract = {Flow accumulation algorithms estimate the steady state of flow on real or modeled topographic surfaces and are crucial for hydrological and geomorphological assessments, including delineation of river networks, drainage basins, and sediment transport processes. Existing flow accumulation algorithms are typically designed to compute flows on regular grids and are not directly applicable to arbitrarily sampled topographic data such as lidar point clouds. In this study we present a random sampling scheme that generates homogeneous point densities, in combination with a novel flow path tracing approach-the Facet-Flow Network (FFN)-that estimates flow accumulation in terms of specific catchment area (SCA) on triangulated surfaces. The random sampling minimizes biases due to spatial sampling and the FFN allows for direct flow estimation from point clouds. We validate our approach on a Gaussian hill surface and study the convergence of its SCA compared to the analytical solution. Here, our algorithm outperforms the multiple flow direction algorithm, which is optimized for divergent surfaces. We also compute the SCA of a 6-km(2)-steep, vegetated catchment on Santa Cruz Island, California, based on airborne lidar point-cloud data. Point-cloud-based SCA values estimated by our method compare well with those estimated by the D-infinity or multiple flow direction algorithm on gridded data. The advantage of computing SCA from point clouds becomes relevant especially for divergent topography and for small drainage areas: These are depicted with much more detail due to the higher sampling density of point clouds.}, language = {en} } @article{BookhagenThiedeStrecker2005, author = {Bookhagen, Bodo and Thiede, Rasmus Christoph and Strecker, Manfred}, title = {Abnormal monsoon years and their control on erosion and sediment flux in the high, and northwest Himalaya}, year = {2005}, abstract = {The interplay between topography and Indian summer monsoon circulation profoundly controls precipitation distribution, sediment transport, and river discharge along the Southern Himalayan Mountain Front (SHF). The Higher Himalayas form a major orographic barrier that separates humid sectors to the south and and regions to the north. During the Indian summer monsoon, vortices transport moisture from the Bay of Bengal, swirl along the SHF to the northwest, and cause heavy rainfall when colliding with the mountain front. In the eastern and central parts of the Himalaya, precipitation measurements derived from passive microwave analysis (SSM/I) show a strong gradient, with high values at medium elevations and extensive penetration of moisture along major river valleys into the orogen. The end of the monsoonal conveyer belt is near the Sutlej Valley in the NW Himalaya, where precipitation is lower and rainfall maxima move to lower elevations. This region thus comprises a climatic transition zone that is very sensitive to changes in Indian summer monsoon strength. To constrain magnitude, temporal, and spatial distribution of precipitation, we analyzed high-resolution passive microwave data from the last decade and identified an abnormal monsoon year (AMY) in 2002. During the 2002 AMY, violent rainstorms conquered orographic barriers and penetrated far into otherwise and regions in the northwest Himalaya at elevations in excess of 3 km asl. While precipitation in these regions was significantly increased and triggered extensive erosional processes (i.e., debris flows) on sparsely vegetated, steep hillslopes, mean rainfall along the low to medium elevations was not significantly greater in magnitude. This shift may thus play an important role in the overall sediment flux toward the Himalayan foreland. Using extended precipitation and sediment flux records for the last century, we show that these events have a decadal recurrence interval during the present-day monsoon circulation. Hence, episodically occurring AMYs control geomorphic processes primarily in the high-elevation and sectors of the orogen, while annual recurring monsoonal rainfall distribution dominates erosion in the low- to medium- elevation parts along the SHF. (C) 2004 Elsevier B.V. All rights reserved}, language = {en} } @article{BriegerHerzschuhPestryakovaetal.2019, author = {Brieger, Frederic and Herzschuh, Ulrike and Pestryakova, Luidmila Agafyevna and Bookhagen, Bodo and Zakharov, Evgenii S. and Kruse, Stefan}, title = {Advances in the Derivation of Northeast Siberian Forest Metrics Using High-Resolution UAV-Based Photogrammetric Point Clouds}, series = {Remote sensing}, volume = {11}, journal = {Remote sensing}, number = {12}, publisher = {MDPI}, address = {Basel}, issn = {2072-4292}, doi = {10.3390/rs11121447}, pages = {24}, year = {2019}, abstract = {Forest structure is a crucial component in the assessment of whether a forest is likely to act as a carbon sink under changing climate. Detailed 3D structural information about the tundra-taiga ecotone of Siberia is mostly missing and still underrepresented in current research due to the remoteness and restricted accessibility. Field based, high-resolution remote sensing can provide important knowledge for the understanding of vegetation properties and dynamics. In this study, we test the applicability of consumer-grade Unmanned Aerial Vehicles (UAVs) for rapid calculation of stand metrics in treeline forests. We reconstructed high-resolution photogrammetric point clouds and derived canopy height models for 10 study sites from NE Chukotka and SW Yakutia. Subsequently, we detected individual tree tops using a variable-window size local maximum filter and applied a marker-controlled watershed segmentation for the delineation of tree crowns. With this, we successfully detected 67.1\% of the validation individuals. Simple linear regressions of observed and detected metrics show a better correlation (R2) and lower relative root mean square percentage error (RMSE\%) for tree heights (mean R2 = 0.77, mean RMSE\% = 18.46\%) than for crown diameters (mean R2 = 0.46, mean RMSE\% = 24.9\%). The comparison between detected and observed tree height distributions revealed that our tree detection method was unable to representatively identify trees <2 m. Our results show that plot sizes for vegetation surveys in the tundra-taiga ecotone should be adapted to the forest structure and have a radius of >15-20 m to capture homogeneous and representative forest stands. Additionally, we identify sources of omission and commission errors and give recommendations for their mitigation. In summary, the efficiency of the used method depends on the complexity of the forest's stand structure.}, language = {en} } @misc{BriegerHerzschuhPestryakovaetal.2019, author = {Brieger, Frederic and Herzschuh, Ulrike and Pestryakova, Luidmila Agafyevna and Bookhagen, Bodo and Zakharov, Evgenii S. and Kruse, Stefan}, title = {Advances in the derivation of Northeast Siberian forest metrics using high-resolution UAV-based photogrammetric point clouds}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1337}, issn = {1866-8372}, doi = {10.25932/publishup-47331}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-473318}, pages = {24}, year = {2019}, abstract = {Forest structure is a crucial component in the assessment of whether a forest is likely to act as a carbon sink under changing climate. Detailed 3D structural information about the tundra-taiga ecotone of Siberia is mostly missing and still underrepresented in current research due to the remoteness and restricted accessibility. Field based, high-resolution remote sensing can provide important knowledge for the understanding of vegetation properties and dynamics. In this study, we test the applicability of consumer-grade Unmanned Aerial Vehicles (UAVs) for rapid calculation of stand metrics in treeline forests. We reconstructed high-resolution photogrammetric point clouds and derived canopy height models for 10 study sites from NE Chukotka and SW Yakutia. Subsequently, we detected individual tree tops using a variable-window size local maximum filter and applied a marker-controlled watershed segmentation for the delineation of tree crowns. With this, we successfully detected 67.1\% of the validation individuals. Simple linear regressions of observed and detected metrics show a better correlation (R2) and lower relative root mean square percentage error (RMSE\%) for tree heights (mean R2 = 0.77, mean RMSE\% = 18.46\%) than for crown diameters (mean R2 = 0.46, mean RMSE\% = 24.9\%). The comparison between detected and observed tree height distributions revealed that our tree detection method was unable to representatively identify trees <2 m. Our results show that plot sizes for vegetation surveys in the tundra-taiga ecotone should be adapted to the forest structure and have a radius of >15-20 m to capture homogeneous and representative forest stands. Additionally, we identify sources of omission and commission errors and give recommendations for their mitigation. In summary, the efficiency of the used method depends on the complexity of the forest's stand structure.}, language = {en} } @article{HarveyBurbankBookhagen2015, author = {Harvey, Jonathan E. and Burbank, Douglas W. and Bookhagen, Bodo}, title = {Along-strike changes in Himalayan thrust geometry: Topographic and tectonic discontinuities in western Nepal}, series = {Lithosphere}, volume = {7}, journal = {Lithosphere}, number = {5}, publisher = {American Institute of Physics}, address = {Boulder}, issn = {1941-8264}, doi = {10.1130/L444.1}, pages = {511 -- 518}, year = {2015}, abstract = {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.}, language = {en} } @article{NeelyBookhagenBurbank2017, author = {Neely, Alexander B. and Bookhagen, Bodo and Burbank, Douglas W.}, title = {An automated knickzone selection algorithm (KZ-Picker) to analyze transient landscapes: Calibration and validation}, series = {Journal of geophysical research : Earth surface}, volume = {122}, journal = {Journal of geophysical research : Earth surface}, publisher = {American Geophysical Union}, address = {Washington}, issn = {2169-9003}, doi = {10.1002/2017JF004250}, pages = {1236 -- 1261}, year = {2017}, abstract = {Streams commonly respond to base-level fall by localizing erosion within steepened, convex knickzone reaches. Localized incision causes knickzone reaches to migrate upstream. Such migrating knickzones dictate the pace of landscape response to changes in tectonics or erosional efficiency and can help quantify the timing and source of base-level fall. Identification of knickzones typically requires individual selection of steepened reaches: a process that is tedious and subjective and has no efficient means to measure knickzone size. We construct an algorithm to automate this procedure by selecting the bounds of knickzone reaches in a -space (drainage-area normalized) framework. An automated feature calibrates algorithm parameters to a subset of knickzones handpicked by the user. The algorithm uses these parameters as consistent criteria to identify knickzones objectively, and then the algorithm measures the height, length, and slope of each knickzone reach. We test the algorithm on 1, 10, and 30m resolution digital elevation models (DEMs) of six catchments (trunk-stream lengths: 2.1-5.4km) on Santa Cruz Island, southern California. On the 1m DEM, algorithm-selected knickzones confirm 93\% of handpicked knickzone positions (n=178) to a spatial accuracy of 100m, 88\% to an accuracy within 50m, and 46\% to an accuracy within 10m. Using 10 and 30m DEMs, accuracy is similar: 88-86\% to 100m and 82\% to 50m (n=38 and 36, respectively). The algorithm enables efficient regional comparison of the size and location of knickzones with geologic structures, mapped landforms, and hillslope morphology, thereby facilitating approaches to characterize the dynamics of transient landscapes. Plain Language Summary The shape of rivers reflects the environments that they flow through and the environments that they link together: mountains and oceans. Anywhere along the length of a river, changes in environmental conditions are propagated upstream and downstream as the river changes its morphology to match the new environmental conditions. Commonly, rivers steepen as land uplifts faster in regions of high tectonic convergence. The steepening of river gradients is propagated upstream and can be mapped to trace zones of high tectonic activity across landscapes and estimate the source and timing of environmental change. Such insights may indicate regions where earthquakes have become more frequent in the recent past and how rivers respond to these changes. In this submission, we detail an algorithm that can use digital topographic data (similar to google earth), to automatically map and measure anomalously steep river reaches across continental scales. This technology can highlight areas that have experienced recent sustained changes in environmental conditions, evident by changes in the morphology of rivers. Such environmental conditions could be changes in tectonic uplift and earthquake activity, changes in sea level, changes in land-use, or changes in climate, all factors that can produce measurable differences in river morphology over time.}, language = {en} } @misc{MilewskiChabrillatBookhagen2020, author = {Milewski, Robert and Chabrillat, Sabine and Bookhagen, Bodo}, title = {Analyses of Namibian Seasonal Salt Pan Crust Dynamics and Climatic Drivers Using Landsat 8 Time-Series and Ground Data}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {988}, issn = {1866-8372}, doi = {10.25932/publishup-47568}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-475685}, pages = {26}, year = {2020}, abstract = {Salt pans are highly dynamic environments that are difficult to study by in situ methods because of their harsh climatic conditions and large spatial areas. Remote sensing can help to elucidate their environmental dynamics and provide important constraints regarding their sedimentological, mineralogical, and hydrological evolution. This study utilizes spaceborne multitemporal multispectral optical data combined with spectral endmembers to document spatial distribution of surface crust types over time on the Omongwa pan located in the Namibian Kalahari. For this purpose, 49 surface samples were collected for spectral and mineralogical characterization during three field campaigns (2014-2016) reflecting different seasons and surface conditions of the salt pan. An approach was developed to allow the spatiotemporal analysis of the salt pan crust dynamics in a dense time-series consisting of 77 Landsat 8 cloud-free scenes between 2014 and 2017, covering at least three major wet-dry cycles. The established spectral analysis technique Sequential Maximum Angle Convex Cone (SMACC) extraction method was used to derive image endmembers from the Landsat time-series stack. Evaluation of the extracted endmember set revealed that the multispectral data allowed the differentiation of four endmembers associated with mineralogical mixtures of the crust's composition in dry conditions and three endmembers associated with flooded or muddy pan conditions. The dry crust endmember spectra have been identified in relation to visible, near infrared, and short-wave infrared (VNIR-SWIR) spectroscopy and X-ray diffraction (XRD) analyses of the collected surface samples. According these results, the spectral endmembers are interpreted as efflorescent halite crust, mixed halite-gypsum crust, mixed calcite quartz sepiolite crust, and gypsum crust. For each Landsat scene the spatial distribution of these crust types was mapped with the Spectral Angle Mapper (SAM) method and significant spatiotemporal dynamics of the major surface crust types were observed. Further, the surface crust dynamics were analyzed in comparison with the pan's moisture regime and other climatic parameters. The results show that the crust dynamics are mainly driven by flooding events in the wet season, but are also influenced by temperature and aeolian activity in the dry season. The approach utilized in this study combines the advantages of multitemporal satellite data for temporal event characterization with advantages from hyperspectral methods for the image and ground data analyses that allow improved mineralogical differentiation and characterization.}, language = {en} } @article{MilewskiChabrillatBookhagen2020, author = {Milewski, Robert and Chabrillat, Sabine and Bookhagen, Bodo}, title = {Analyses of Namibian Seasonal Salt Pan Crust Dynamics and Climatic Drivers Using Landsat 8 Time-Series and Ground Data}, series = {Remote Sensing}, journal = {Remote Sensing}, number = {3}, publisher = {MDPI}, address = {Basel}, issn = {2072-4292}, doi = {10.3390/rs12030474}, pages = {24}, year = {2020}, abstract = {Salt pans are highly dynamic environments that are difficult to study by in situ methods because of their harsh climatic conditions and large spatial areas. Remote sensing can help to elucidate their environmental dynamics and provide important constraints regarding their sedimentological, mineralogical, and hydrological evolution. This study utilizes spaceborne multitemporal multispectral optical data combined with spectral endmembers to document spatial distribution of surface crust types over time on the Omongwa pan located in the Namibian Kalahari. For this purpose, 49 surface samples were collected for spectral and mineralogical characterization during three field campaigns (2014-2016) reflecting different seasons and surface conditions of the salt pan. An approach was developed to allow the spatiotemporal analysis of the salt pan crust dynamics in a dense time-series consisting of 77 Landsat 8 cloud-free scenes between 2014 and 2017, covering at least three major wet-dry cycles. The established spectral analysis technique Sequential Maximum Angle Convex Cone (SMACC) extraction method was used to derive image endmembers from the Landsat time-series stack. Evaluation of the extracted endmember set revealed that the multispectral data allowed the differentiation of four endmembers associated with mineralogical mixtures of the crust's composition in dry conditions and three endmembers associated with flooded or muddy pan conditions. The dry crust endmember spectra have been identified in relation to visible, near infrared, and short-wave infrared (VNIR-SWIR) spectroscopy and X-ray diffraction (XRD) analyses of the collected surface samples. According these results, the spectral endmembers are interpreted as efflorescent halite crust, mixed halite-gypsum crust, mixed calcite quartz sepiolite crust, and gypsum crust. For each Landsat scene the spatial distribution of these crust types was mapped with the Spectral Angle Mapper (SAM) method and significant spatiotemporal dynamics of the major surface crust types were observed. Further, the surface crust dynamics were analyzed in comparison with the pan's moisture regime and other climatic parameters. The results show that the crust dynamics are mainly driven by flooding events in the wet season, but are also influenced by temperature and aeolian activity in the dry season. The approach utilized in this study combines the advantages of multitemporal satellite data for temporal event characterization with advantages from hyperspectral methods for the image and ground data analyses that allow improved mineralogical differentiation and characterization.}, language = {en} } @article{OlenBookhagen2020, author = {Olen, Stephanie M. and Bookhagen, Bodo}, title = {Applications of SAR interferometric coherence time series}, series = {Journal of geophysical research : Earth surface}, volume = {125}, journal = {Journal of geophysical research : Earth surface}, number = {3}, publisher = {American Geophysical Union}, address = {Washington}, issn = {2169-9003}, doi = {10.1029/2019JF005141}, pages = {22}, year = {2020}, abstract = {Sediment transport domains in mountain landscapes are characterized by fundamentally different processes and rates depending on several factors, including geology, climate, and biota. Accurately identifying where transitions between transport domains occur is an important step to quantify the past, present, and future contribution of varying erosion and sedimentation processes and enhance our predictive capabilities. We propose a new methodology based on time series of synthetic aperture radar (SAR) interferometric coherence images to map sediment transport regimes across arid and semiarid landscapes. Using 4 years of Sentinel-1 data, we analyze sediment transport regimes for the south-central Andes in northwestern Argentina characterized by steep topographic and climatic gradients. We observe seasonally low coherence during the regional wet season, particularly on hillslopes and in alluvial channels. The spatial distribution of coherence is compared to drainage areas extracted from digital topography to identify two distinct transitions within watersheds: (a) a hillslope-to-fluvial and (b) a fluvial-to-alluvial transition. While transitions within a given basin can be well-constrained, the relative role of each sediment transport domain varies widely over the climatic and topographic gradients. In semiarid regions, we observe larger relative contributions from hillslopes compared to arid regions. Across regional gradients, the range of coherence within basins positively correlates to previously published millennial catchment-wide erosion rates and to topographic metrics used to indicate long-term uplift. Our study suggests that a dense time series of interferometric coherence can be used as a proxy for surface sediment movement and landscape stability in vegetation-free settings at event to decadal timescales.}, language = {en} } @misc{SmithBookhagen2020, author = {Smith, Taylor and Bookhagen, Bodo}, title = {Assessing Multi-Temporal Snow-Volume Trends in High Mountain Asia From 1987 to 2016 Using High-Resolution Passive Microwave Data}, series = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Postprints der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, number = {1020}, issn = {1866-8372}, doi = {10.25932/publishup-48417}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-484176}, pages = {15}, year = {2020}, abstract = {High Mountain Asia (HMA) is dependent upon both the amount and timing of snow and glacier meltwater. Previous model studies and coarse resolution (0.25° × 0.25°, ∼25 km × 25 km) passive microwave assessments of trends in the volume and timing of snowfall, snowmelt, and glacier melt in HMA have identified key spatial and seasonal heterogeneities in the response of snow to changes in regional climate. Here we use recently developed, continuous, internally consistent, and high-resolution passive microwave data (3.125 km × 3.125 km, 1987-2016) from the special sensor microwave imager instrument family to refine and extend previous estimates of changes in the snow regime of HMA. We find an overall decline in snow volume across HMA; however, there exist spatially contiguous regions of increasing snow volume—particularly during the winter season in the Pamir, Karakoram, Hindu Kush, and Kunlun Shan. Detailed analysis of changes in snow-volume trends through time reveal a large step change from negative trends during the period 1987-1997, to much more positive trends across large regions of HMA during the periods 1997-2007 and 2007-2016. We also find that changes in high percentile monthly snow-water volume exhibit steeper trends than changes in low percentile snow-water volume, which suggests a reduction in the frequency of high snow-water volumes in much of HMA. Regions with positive snow-water storage trends generally correspond to regions of positive glacier mass balances.}, language = {en} } @article{SmithBookhagen2020, author = {Smith, Taylor and Bookhagen, Bodo}, title = {Assessing Multi-Temporal Snow-Volume Trends in High Mountain Asia From 1987 to 2016 Using High-Resolution Passive Microwave Data}, series = {Frontiers in Earth Science}, volume = {8}, journal = {Frontiers in Earth Science}, publisher = {Frontiers Media}, address = {Lausanne}, issn = {2296-6463}, doi = {10.3389/feart.2020.559175}, pages = {13}, year = {2020}, abstract = {High Mountain Asia (HMA) is dependent upon both the amount and timing of snow and glacier meltwater. Previous model studies and coarse resolution (0.25° × 0.25°, ∼25 km × 25 km) passive microwave assessments of trends in the volume and timing of snowfall, snowmelt, and glacier melt in HMA have identified key spatial and seasonal heterogeneities in the response of snow to changes in regional climate. Here we use recently developed, continuous, internally consistent, and high-resolution passive microwave data (3.125 km × 3.125 km, 1987-2016) from the special sensor microwave imager instrument family to refine and extend previous estimates of changes in the snow regime of HMA. We find an overall decline in snow volume across HMA; however, there exist spatially contiguous regions of increasing snow volume—particularly during the winter season in the Pamir, Karakoram, Hindu Kush, and Kunlun Shan. Detailed analysis of changes in snow-volume trends through time reveal a large step change from negative trends during the period 1987-1997, to much more positive trends across large regions of HMA during the periods 1997-2007 and 2007-2016. We also find that changes in high percentile monthly snow-water volume exhibit steeper trends than changes in low percentile snow-water volume, which suggests a reduction in the frequency of high snow-water volumes in much of HMA. Regions with positive snow-water storage trends generally correspond to regions of positive glacier mass balances.}, language = {en} } @article{SmithBookhagen2016, author = {Smith, Taylor and Bookhagen, Bodo}, title = {Assessing uncertainty and sensor biases in passive microwave data across High Mountain Asia}, series = {Remote sensing of environment : an interdisciplinary journal}, volume = {181}, journal = {Remote sensing of environment : an interdisciplinary journal}, publisher = {Elsevier}, address = {New York}, issn = {0034-4257}, doi = {10.1016/j.rse.2016.03.037}, pages = {174 -- 185}, year = {2016}, abstract = {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.}, language = {en} } @article{CastinoBookhagenDelaTorre2020, author = {Castino, Fabiana and Bookhagen, Bodo and De la Torre, Alejandro}, title = {Atmospheric dynamics of extreme discharge events from 1979 to 2016 in the southern Central Andes}, series = {Climate dynamics : observational, theoretical and computational research on the climate system}, volume = {55}, journal = {Climate dynamics : observational, theoretical and computational research on the climate system}, number = {11-12}, publisher = {Springer}, address = {Berlin ; Heidelberg [u.a.]}, issn = {0930-7575}, doi = {10.1007/s00382-020-05458-1}, pages = {3485 -- 3505}, year = {2020}, abstract = {During the South-American Monsoon season, deep convective systems occur at the eastern flank of the Central Andes leading to heavy rainfall and flooding. We investigate the large- and meso-scale atmospheric dynamics associated with extreme discharge events (> 99.9th percentile) observed in two major river catchments meridionally stretching from humid to semi-arid conditions in the southern Central Andes. Based on daily gauge time series and ERA-Interim reanalysis, we made the following three key observations: (1) for the period 1940-2016 daily discharge exhibits more pronounced variability in the southern, semi-arid than in the northern, humid catchments. This is due to a smaller ratio of discharge magnitudes between intermediate (0.2 year return period) and rare events (20 year return period) in the semi-arid compared to the humid areas; (2) The climatological composites of the 40 largest discharge events showed characteristic atmospheric features of cold surges based on 5-day time-lagged sequences of geopotential height at different levels in the troposphere; (3) A subjective classification revealed that 80\% of the 40 largest discharge events are mainly associated with the north-northeastward migration of frontal systems and 2/3 of these are cold fronts, i.e. cold surges. This work highlights the importance of cold surges and their related atmospheric processes for the generation of heavy rainfall events and floods in the southern Central Andes.}, language = {en} } @article{PurintonBookhagen2021, author = {Purinton, Benjamin and Bookhagen, Bodo}, title = {Beyond Vertical Point Accuracy}, series = {Frontiers in Earth Science}, journal = {Frontiers in Earth Science}, publisher = {Frontiers Media}, address = {Lausanne, Schweiz}, issn = {2296-6463}, doi = {10.3389/feart.2021.758606}, pages = {1 -- 24}, year = {2021}, abstract = {Quantitative geomorphic research depends on accurate topographic data often collected via remote sensing. Lidar, and photogrammetric methods like structure-from-motion, provide the highest quality data for generating digital elevation models (DEMs). Unfortunately, these data are restricted to relatively small areas, and may be expensive or time-consuming to collect. Global and near-global DEMs with 1 arcsec (∼30 m) ground sampling from spaceborne radar and optical sensors offer an alternative gridded, continuous surface at the cost of resolution and accuracy. Accuracy is typically defined with respect to external datasets, often, but not always, in the form of point or profile measurements from sources like differential Global Navigation Satellite System (GNSS), spaceborne lidar (e.g., ICESat), and other geodetic measurements. Vertical point or profile accuracy metrics can miss the pixel-to-pixel variability (sometimes called DEM noise) that is unrelated to true topographic signal, but rather sensor-, orbital-, and/or processing-related artifacts. This is most concerning in selecting a DEM for geomorphic analysis, as this variability can affect derivatives of elevation (e.g., slope and curvature) and impact flow routing. We use (near) global DEMs at 1 arcsec resolution (SRTM, ASTER, ALOS, TanDEM-X, and the recently released Copernicus) and develop new internal accuracy metrics to assess inter-pixel variability without reference data. Our study area is in the arid, steep Central Andes, and is nearly vegetation-free, creating ideal conditions for remote sensing of the bare-earth surface. We use a novel hillshade-filtering approach to detrend long-wavelength topographic signals and accentuate short-wavelength variability. Fourier transformations of the spatial signal to the frequency domain allows us to quantify: 1) artifacts in the un-projected 1 arcsec DEMs at wavelengths greater than the Nyquist (twice the nominal resolution, so > 2 arcsec); and 2) the relative variance of adjacent pixels in DEMs resampled to 30-m resolution (UTM projected). We translate results into their impact on hillslope and channel slope calculations, and we highlight the quality of the five DEMs. We find that the Copernicus DEM, which is based on a carefully edited commercial version of the TanDEM-X, provides the highest quality landscape representation, and should become the preferred DEM for topographic analysis in areas without sufficient coverage of higher-quality local DEMs.}, language = {en} } @misc{PurintonBookhagen2021, author = {Purinton, Benjamin and Bookhagen, Bodo}, title = {Beyond Vertical Point Accuracy}, series = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, journal = {Zweitver{\"o}ffentlichungen der Universit{\"a}t Potsdam : Mathematisch-Naturwissenschaftliche Reihe}, publisher = {Universit{\"a}tsverlag Potsdam}, address = {Potsdam}, issn = {1866-8372}, doi = {10.25932/publishup-54980}, url = {http://nbn-resolving.de/urn:nbn:de:kobv:517-opus4-549805}, pages = {1 -- 24}, year = {2021}, abstract = {Quantitative geomorphic research depends on accurate topographic data often collected via remote sensing. Lidar, and photogrammetric methods like structure-from-motion, provide the highest quality data for generating digital elevation models (DEMs). Unfortunately, these data are restricted to relatively small areas, and may be expensive or time-consuming to collect. Global and near-global DEMs with 1 arcsec (∼30 m) ground sampling from spaceborne radar and optical sensors offer an alternative gridded, continuous surface at the cost of resolution and accuracy. Accuracy is typically defined with respect to external datasets, often, but not always, in the form of point or profile measurements from sources like differential Global Navigation Satellite System (GNSS), spaceborne lidar (e.g., ICESat), and other geodetic measurements. Vertical point or profile accuracy metrics can miss the pixel-to-pixel variability (sometimes called DEM noise) that is unrelated to true topographic signal, but rather sensor-, orbital-, and/or processing-related artifacts. This is most concerning in selecting a DEM for geomorphic analysis, as this variability can affect derivatives of elevation (e.g., slope and curvature) and impact flow routing. We use (near) global DEMs at 1 arcsec resolution (SRTM, ASTER, ALOS, TanDEM-X, and the recently released Copernicus) and develop new internal accuracy metrics to assess inter-pixel variability without reference data. Our study area is in the arid, steep Central Andes, and is nearly vegetation-free, creating ideal conditions for remote sensing of the bare-earth surface. We use a novel hillshade-filtering approach to detrend long-wavelength topographic signals and accentuate short-wavelength variability. Fourier transformations of the spatial signal to the frequency domain allows us to quantify: 1) artifacts in the un-projected 1 arcsec DEMs at wavelengths greater than the Nyquist (twice the nominal resolution, so > 2 arcsec); and 2) the relative variance of adjacent pixels in DEMs resampled to 30-m resolution (UTM projected). We translate results into their impact on hillslope and channel slope calculations, and we highlight the quality of the five DEMs. We find that the Copernicus DEM, which is based on a carefully edited commercial version of the TanDEM-X, provides the highest quality landscape representation, and should become the preferred DEM for topographic analysis in areas without sufficient coverage of higher-quality local DEMs.}, language = {en} } @article{RohrmannStreckerBookhagenetal.2014, author = {Rohrmann, Alexander and Strecker, Manfred and Bookhagen, Bodo and Mulch, Andreas and Sachse, Dirk and Pingel, Heiko and Alonso, Ricardo N. and Schildgen, Taylor F. and Montero, Carolina}, title = {Can stable isotopes ride out the storms? The role of convection for water isotopes in models, records, and paleoaltimetry studies in the central Andes}, series = {Earth \& planetary science letters}, volume = {407}, journal = {Earth \& planetary science letters}, publisher = {Elsevier}, address = {Amsterdam}, issn = {0012-821X}, doi = {10.1016/j.epsl.2014.09.021}, pages = {187 -- 195}, year = {2014}, language = {en} } @article{SmithBookhagen2018, author = {Smith, Taylor and Bookhagen, Bodo}, title = {Changes in seasonal snow water equivalent distribution in High Mountain Asia (1987 to 2009)}, series = {Science Advances}, volume = {4}, journal = {Science Advances}, number = {1}, publisher = {American Assoc. for the Advancement of Science}, address = {Washington}, issn = {2375-2548}, doi = {10.1126/sciadv.1701550}, pages = {8}, year = {2018}, abstract = {Snow meltwaters account for most of the yearly water budgets of many catchments in High Mountain Asia (HMA). We examine trends in snow water equivalent (SWE) using passive microwave data (1987 to 2009). We find an overall decrease in SWE in HMA, despite regions of increased SWE in the Pamir, Kunlun Shan, Eastern Himalaya, and Eastern Tien Shan. Although the average decline in annual SWE across HMA (contributing area, 2641 x 10(3) km(2)) is low (average, -0.3\%), annual SWE losses conceal distinct seasonal and spatial heterogeneities across the study region. For example, the Tien Shan has seen both strong increases in winter SWE and sharp declines in spring and summer SWE. In the majority of catchments, the most negative SWE trends are found in mid-elevation zones, which often correspond to the regions of highest snow-water storage and are somewhat distinct from glaciated areas. Negative changes in SWE storage in these mid-elevation zones have strong implications for downstream water availability.}, language = {en} }