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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.
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 Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) with its land and vegetation height data product (ATL08), and Global Ecosystem Dynamics Investigation (GEDI) with its terrain elevation and height metrics data product (GEDI Level 2A) missions have great potential to globally map ground and canopy heights. Canopy height is a key factor in estimating above-ground biomass and its seasonal changes; these satellite missions can also improve estimated above-ground carbon stocks. This study presents a novel Sparse Vegetation Detection Algorithm (SVDA) which uses ICESat-2 (ATL03, geolocated photons) data to map tree and vegetation heights in a sparsely vegetated savanna ecosystem. The SVDA consists of three main steps: First, noise photons are filtered using the signal confidence flag from ATL03 data and local point statistics. Second, we classify ground photons based on photon height percentiles. Third, tree and grass photons are classified based on the number of neighbors. We validated tree heights with field measurements (n = 55), finding a root-mean-square error (RMSE) of 1.82 m using SVDA, GEDI Level 2A (Geolocated Elevation and Height Metrics product): 1.33 m, and ATL08: 5.59 m. Our results indicate that the SVDA is effective in identifying canopy photons in savanna ecosystems, where ATL08 performs poorly. We further identify seasonal vegetation height changes with an emphasis on vegetation below 3 m; widespread height changes in this class from two wet-dry cycles show maximum seasonal changes of 1 m, possibly related to seasonal grass-height differences. Our study shows the difficulties of vegetation measurements in savanna ecosystems but provides the first estimates of seasonal biomass changes.
The Ice, Cloud, and Land Elevation Satellite-2 (ICESat-2) with its land and vegetation height data product (ATL08), and Global Ecosystem Dynamics Investigation (GEDI) with its terrain elevation and height metrics data product (GEDI Level 2A) missions have great potential to globally map ground and canopy heights. Canopy height is a key factor in estimating above-ground biomass and its seasonal changes; these satellite missions can also improve estimated above-ground carbon stocks. This study presents a novel Sparse Vegetation Detection Algorithm (SVDA) which uses ICESat-2 (ATL03, geolocated photons) data to map tree and vegetation heights in a sparsely vegetated savanna ecosystem. The SVDA consists of three main steps: First, noise photons are filtered using the signal confidence flag from ATL03 data and local point statistics. Second, we classify ground photons based on photon height percentiles. Third, tree and grass photons are classified based on the number of neighbors. We validated tree heights with field measurements (n = 55), finding a root-mean-square error (RMSE) of 1.82 m using SVDA, GEDI Level 2A (Geolocated Elevation and Height Metrics product): 1.33 m, and ATL08: 5.59 m. Our results indicate that the SVDA is effective in identifying canopy photons in savanna ecosystems, where ATL08 performs poorly. We further identify seasonal vegetation height changes with an emphasis on vegetation below 3 m; widespread height changes in this class from two wet-dry cycles show maximum seasonal changes of 1 m, possibly related to seasonal grass-height differences. Our study shows the difficulties of vegetation measurements in savanna ecosystems but provides the first estimates of seasonal biomass changes.
We modeled the two most extreme highstands of Lake Naivasha during the last 175 k.y. to estimate potential precipitation/ evaporation changes in this basin. In a first step, the bathymetry of the paleolakes at f135 and 9 k.y. BP was reconstructed from sediment cores and surface outcrops. Second, we modeled the paleohydrologic budget during the highstands using a simplified coupled energy mass-balance model. Our results show that the hydrologic and hence the climate conditions at f135 and 9 k.y. BP were similar, but significantly different from today. The main difference is a f15% higher value in precipitation compared to the present. An adaptation and migration of vegetation in the cause of climate changes would result in a f30% increase in precipitation. The most likely cause for such a wetter climate at f135 and 9 k.y. BP is a more intense intertropical convergence and increased precipitation in East Africa.
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.
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.
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.
Climatic observables are often correlated across long spatial distances, and extreme events, such as heatwaves or floods, are typically assumed to be related to such teleconnections(1,2). Revealing atmospheric teleconnection patterns and understanding their underlying mechanisms is of great importance for weather forecasting in general and extreme-event prediction in particular(3,4), especially considering that the characteristics of extreme events have been suggested to change under ongoing anthropogenic climate change(5-8). Here we reveal the global coupling pattern of extreme-rainfall events by applying complex-network methodology to high-resolution satellite data and introducing a technique that corrects for multiple-comparison bias in functional networks. We find that the distance distribution of significant connections (P < 0.005) around the globe decays according to a power law up to distances of about 2,500 kilometres. For longer distances, the probability of significant connections is much higher than expected from the scaling of the power law. We attribute the shorter, power-law-distributed connections to regional weather systems. The longer, super-power-law-distributed connections form a global rainfall teleconnection pattern that is probably controlled by upper-level Rossby waves. We show that extreme-rainfall events in the monsoon systems of south-central Asia, east Asia and Africa are significantly synchronized. Moreover, we uncover concise links between south-central Asia and the European and North American extratropics, as well as the Southern Hemisphere extratropics. Analysis of the atmospheric conditions that lead to these teleconnections confirms Rossby waves as the physical mechanism underlying these global teleconnection patterns and emphasizes their crucial role in dynamical tropical-extratropical couplings. Our results provide insights into the function of Rossby waves in creating stable, global-scale dependencies of extreme-rainfall events, and into the potential predictability of associated natural hazards.
Birds migrating across the Himalayan region fly over the highest peaks in the world, facing immense physiological and climatic challenges. The authors show the different strategies used by birds to cope with these challenges. Many wetland avian species are seen in the high-altitude lakes of the Himalayas and the adjoining Tibetan Plateau, such as Bar-Headed Geese. Ringing programmes have generated information about origins and destinations, and this book is the first to present information on the bird's exact migratory paths. Capitalising on knowledge generated through satellite telemetry, the authors describe the migratory routes of a multitude of birds flying over or skirting the Himalayas. The myriad of threats to migratory birds and the wetland system in the Central Asian Flyway are discussed, with ways to mitigate them. This volume will inform and persuade policy-makers and conservation practitioners to take appropriate measures for the long-term survival of this unique migration
The India-Eurasia continental collision zone provides a spectacular example of active mountain building and climatic forcing. In order to quantify the critically important process of mass removal, I analyzed spatial and temporal precipitation patterns of the oscillating monsoon system and their geomorphic imprints. I processed passive microwave satellite data to derive high-resolution rainfall estimates for the last decade and identified an abnormal monsoon year in 2002. During this year, precipitation migrated far into the Sutlej Valley in the northwestern part of the Himalaya and reached regions behind orographic barriers that are normally arid. There, sediment flux, mean basin denudation rates, and channel-forming processes such as erosion by debris-flows increased significantly. Similarly, during the late Pleistocene and early Holocene, solar forcing increased the strength of the Indian summer monsoon for several millennia and presumably lead to analogous precipitation distribution as were observed during 2002. However, the persistent humid conditions in the steep, high-elevation parts of the Sutlej River resulted in deep-seated landsliding. Landslides were exceptionally large, mainly due to two processes that I infer for this time: At the onset of the intensified monsoon at 9.7 ka BP heavy rainfall and high river discharge removed material stored along the river, and lowered the baselevel. Second, enhanced discharge, sediment flux, and increased pore-water pressures along the hillslopes eventually lead to exceptionally large landslides that have not been observed in other periods. The excess sediments that were removed from the upstream parts of the Sutlej Valley were rapidly deposited in the low-gradient sectors of the lower Sutlej River. Timing of downcutting correlates with centennial-long weaker monsoon periods that were characterized by lower rainfall. I explain this relationship by taking sediment flux and rainfall dynamics into account: High sediment flux derived from the upstream parts of the Sutlej River during strong monsoon phases prevents fluvial incision due to oversaturation the fluvial sediment-transport capacity. In contrast, weaker monsoons result in a lower sediment flux that allows incision in the low-elevation parts of the Sutlej River.
Major earthquakes ( M > 8) have repeatedly ruptured the Nazca-South America plate interface of south-central Chile involving meter scale land-level changes. Earthquake recurrence intervals, however, extending beyond limited historical records are virtually unknown, but would provide crucial data on the tectonic behavior of forearcs. We analyzed the spatiotemporal pattern of Holocene earthquakes on Santa Maria Island (SMI; 37 degrees S), located 20 km off the Chilean coast and approximately 70 km east of the trench. SMI hosts a minimum of 21 uplifted beach berms, of which a subset were dated to calculate a mean uplift rate of 2.3 +/- 0.2 m/ky and a tilting rate of 0.022 +/- 0.002 degrees/ky. The inferred recurrence interval of strandline-forming earthquakes is similar to 180 years. Combining coseismic uplift and aseismic subsidence during an earthquake cycle, the net gain in strandline elevation in this environment is similar to 0.4 m per event
Aluminum-26 and beryllium-10 surface exposure dating on cut-and-fill river-terrace surfaces from the lower Sutlej Valley (northwest Himalaya) documents the close link between Indian Summer Monsoon (ISM) oscillations and intervals of enhanced fluvial incision. During the early Holocene ISM optimum, precipitation was enhanced and reached far into the internal parts of the orogen. The amplified sediment flux from these usually dry but glaciated areas caused alluviation of downstream valleys up to 120 m above present grade at ca. 9.9 k.y. B.P. Terrace formation (i.e., incision) in the coarse deposits occurred during century-long weak ISM phases that resulted in reduced moisture availability and most likely in lower sediment flux. Here, we suggest that the lower sediment flux during weak ISM phases allowed rivers to incise episodically into the alluvial fill
Hydrological modelling of a Pleistocene landslide-dammed lake in the Santa Maria Basin, NW Argentina
(2001)
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.
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
Late Quaternary intensified monsoon phases control landscape evolution in the northwest Himalaya
(2005)
The intensity of the Asian summer-monsoon circulation varies over decadal to millennial time scales and is reflected in changes in surface processes, terrestrial environments, and marine sediment records. However, the mechanisms of long-lived (2-5 k.y.) intensified monsoon phases, the related changes in precipitation distribution, and their effect on landscape evolution and sedimentation rates are not yet well understood. The and high-elevation sectors of the orogen correspond to a climatically sensitive zone that currently receives rain only during abnormal (i.e., strengthened) monsoon seasons. Analogous to present-day rainfall anomalies, enhanced precipitation during an intensified monsoon phase is expected to have penetrated far into these geomorphic threshold regions where hillslopes are close to the angle of failure. We associate landslide triggering during intensified monsoon phases with enhanced precipitation, discharge, and sediment flux leading to an increase in pore-water pressure, lateral scouring of rivers, and over- steepening of hillslopes, eventually resulting in failure of slopes and exceptionally large mass movements. Here we use lacustrine deposits related to spatially and temporally clustered large landslides (>0.5 km(3)) in the Sutlej Valley region of the northwest Himalaya to calculate sedimentation rates and to infer rainfall patterns during late Pleistocene (29-24 ka) and Holocene (10-4 ka) intensified monsoon phases. Compared to present-day sediment-flux measurements, a fivefold increase in sediment-transport rates recorded by sediments in landslide-dammed lakes characterized these episodes of high climatic variability. These changes thus emphasize the pronounced imprint of millennial-scale climate change on surface processes and landscape evolution
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.
Remote Sensing technologies allow to map biophysical, biochemical, and earth surface parameters of the land surface. Of especial interest for various applications in environmental and urban sciences is the combination of spectral and 3D elevation information. However, those two data streams are provided separately by different instruments, namely airborne laser scanner (ALS) for elevation and a hyperspectral imager (HSI) for high spectral resolution data. The fusion of ALS and HSI data can thus lead to a single data entity consistently featuring rich structural and spectral information. In this study, we present the application of fusing the first pulse return information from ALS data at a sub-decimeter spatial resolution with the lower-spatial resolution hyperspectral information available from the HSI into a hyperspectral point cloud (HSPC). During the processing, a plausible hyperspectral spectrum is assigned to every first-return ALS point. We show that the complementary implementation of spectral and 3D information at the point-cloud scale improves object-based classification and information extraction schemes. This improvements have great potential for numerous land cover mapping and environmental applications.