Revisiting scaling laws in river basins: New considerations across hillslope and fluvial regimes

Increasing availability of high‐resolution (1 m) topography data and enhanced computational processing power present new opportunities to study landscape organization at a detail not possible before. Here we propose the use of “directed distance from the divide” as the scale parameter (instead of Horton’s stream order or upstream contributing area) for performing detailed probabilistic analysis of landscapes over a broad range of scales. This scale parameter offers several advantages for applications in hydrology, geomorphology, and ecology in that it can be directly related to length‐scale dependent processes, it can be applied seamlessly across the hillslope and fluvial regimes, and it is a continuous parameter allowing accurate statistical characterization (higher‐order statistical moments) across scales. Application of this scaling formalism to three basins in California demonstrates the emergence of three distinct geomorphic regimes of divergent, highly convergent, and moderately convergent fluvial pathways, with notable differences in their scaling relationships and in the variability, or spatial heterogeneity, of topographic attributes in each regime. We show that topographic attributes, such as slopes and curvatures, conditional on directed distance from the divide exhibit less variability than those same attributes conditional on upstream contributing area, thus affording a sharper identification of regime transitions and increased accuracy in the scaling analysis

HYDROLOGICAL MODELING USING REMOTE SENSING AND GIS; A CASE STUDY OF BATA RIVER BASIN

A Hydrological model was developed for the Bata River basin, which is one ofthe tributaries of the Yamuna River, Infiltration and losses, unit hydrograph andriver routing are the main model components. ILWIS and Auto CAD softwarewere used to hydrological modeling. Satellite Remote Sensing and GIS techniqueswere used to estimate the relevant spatial parameters, which are used as input tothe hydrological model. SOl topomap, data collected from the field work, IRSLISS-lll temporal satellite data for rabi and khari f seasons and IRS PAN data areused as input for the model. SCS curve number method is used for the infiltrationlosses and synthesis of unit hydrographs. Complete watershed is divided to 10subareas. Ten hydrographs were developed as one for each subareas.Characteristics of the watershed were evaluated by modeling the watershed as awhole as well as subarea basis by routing the unit hydrographs along the riverreach. Muskingum hydrologica routing method is used for river routing. Theconstructed model is capable of forecasting the runoff for the particular event ofrainfall and derives hydrographs for required time duration.

Temperature as a potent driver of regional forest drought stress and tree mortality

As the climate changes, drought may reduce tree productivity and survival across many forest ecosystems; however, the relative influence of specific climate parameters on forest decline is poorly understood. We derive a forest drought-stress index (FDSI) for the southwestern United States using a comprehensive tree-ring data set representing AD 1000–2007. The FDSI is approximately equally influenced by the warm-season vapour-pressure deficit (largely controlled by temperature) and cold-season precipitation, together explaining 82% of the FDSI variability. Correspondence between the FDSI and measures of forest productivity, mortality, bark-beetle outbreak and wildfire validate the FDSI as a holistic forest-vigour indicator. If the vapour-pressure deficit continues increasing as projected by climate models, the mean forest drought-stress by the 2050s will exceed that of the most severe droughts in the past 1,000 years. Collectively, the results foreshadow twenty-first-century changes in forest structures and compositions, with transition of forests in the southwestern United States, and perhaps water-limited forests globally, towards distributions unfamiliar to modern civilization

Global satellite monitoring of climate-induced vegetation disturbances

Terrestrial disturbances are accelerating globally, but their full impact is not quantified because we lack an adequate monitoring system. Remote sensing offers a means to quantify the frequency and extent of disturbances globally. Here, we review the current application of remote sensing to this problem and offer a framework for more systematic analysis in the future. We recommend that any proposed monitoring system should not only detect disturbances, but also be able to: identify the proximate cause(s); integrate a range of spatial scales; and, ideally, incorporate process models to explain the observed patterns and predicted trends in the future. Significant remaining challenges are tied to the ecology of disturbances. To meet these challenges, more effort is required to incorporate ecological principles and understanding into the assessments of disturbance worldwide

DSP baseline data: model baseline datasets for a river basin: Limpopo example

Print out of powerpoint presentation made at the Observing river basins from space: why is it important for IWMI - A Remote Sensing and GIS (RS/GIS) Workshop held at the International Water Management Institute, Colombo, Sri Lanka, 28 June 2004. RS/GIS training material

Scale invariance and scaling breaks - new metrics for inferring process signature from high resolution LiDAR topography.

University of Minnesota Ph.D. dissertation. October 2009. Major: Civil Engineering. Advisor: Efi Foufoula. 1 computer file (PDF); xvi, 132 pages. Ill. (some col.)Landscapes posses many scales of variability, from hillslopes to the river network structure, and have been the subject of intense research over the past three decades. Despite this tremendous variability, it has been well documented by now that scale-invariances do exist in several landscape attributes reflecting the natural organization of processes responsible for the formation of those landscapes. The availability of very high resolution (sub-meter scale) digital topography data from laser altimetry (LiDAR) offers an unprecedented opportunity to probe into the structure of landscapes at scales never imagined before and extract properties useful for modeling water, sediment, and nutrient fluxes in a watershed. In this work, we take advantage of these high resolution topography data to introduce new metrics for quantifying landscape organization and explore scaling laws across the continuum of hillslope-fluvial regimes. The innovations we introduce rely on: (1) adapting a new scale parameter which we call ``directed distance from the divide'' which allows examining divergent and convergent parts of the landscape under a single framework; (2) using this new scale parameter to identify the signature of landslides on a landscape allowing thus an objective mapping of those landslides; (3) introduction of the ``incremental drainage area'' function along the mainstream to quantify the hierarchy and clustering of tributaries; and (4) introduction of an non-traditional horizontal function that measures ``valley width''as one fills up the channels beyond their banks and maps the left and right extend of the landscape. A common theme in all of the above developments is the quest for mapping the complex three dimensional structure of landscapes onto simpler, preferably one dimensional, functions that reflect different aspects of the landscape organization. Once this is accomplished, our common method of analysis relies on the theory of multi-scaling using wavelets, i.e., in quantifying how the statistical structure of the extracted attributes changes when one sees them at different scales

Global River Width and Inundation Database from Sentinel-1 SAR Satellites

High resolution surface water maps and water body temporal dynamics are absent in many regions of the world. Still, the surface water inventories are crucial for water resources planning, water-bound transportation planning, and helping flood-prone communities prepare for and even prevent catastrophic flood events. Recent advancements of cloud based computing and machine learning algorithms enable near-real-time access and processing of satellite data and delivering surface water products to the research and applications communities. Most existing river width, inundations, and satellite-based streamflow databases are affected by cloudy or extreme meteorological conditions or coarser resolutions. Recent developments in SAR (Synthetic Aperture Radar) based satellites facilitate the generation of surface water products at unprecedented spatial/temporal resolutions. We are using the Sentinel-1 SAR satellite data archive from 2015 to the present to create a global river width and surface water database at the reach scale. A modified version of the Sentinel-1 surface water mapping algorithm developed within the HydroSAR project lead by the University of Alaska Fairbanks and the NASA Alaska Satellite Facility (ASF) is used to map the surface water extent approximately every 36 days or better at 10m spatial resolution globally. This 10m water mask is fed to a workflow to quantify the river widths and surface water inundations in stream networks. We will soon be producing three data products based on our analysis: Effective river widths for the SWORD (SWOT A priori River Database) river reaches from 2015 to near real-time for the Sentinel-1 images. Pixel-level river widths for river center lines derived from Sentinel-1 images over time for river reaches. An inundation map for river reaches covering the entire globe assimilates satellite data with other low temporal frequency elevation datasets. Additionally, we are linking our river width and inundation products using a cloud database in Amazon Web Services so that users can retrieve the river width/inundation time-series information over the web. Furthermore, our river width products will be available to use with other river geometry and historical streamflow discharge information to provide estimated river flow rates to enhance NASA SWOT mission time series. This presentation was given at the 2022 NASA ESDSWG Meeting (April 19-21, 2022).</p

Surface albedo decreases from anthropogenic impacts over High Mountain Asia with implications of positive radiative forcing feedbacks

Human and climate induced land surface changes resulting from irrigation, snow cover decreases, and greening impact the radiative forcing by changing the surface albedo. Here we use a partial information decomposition approach and remote sensing data to quantify the effects of the changes in leaf area index, soil moisture, and snow cover on the surface albedo in High Mountain Asia (HMA), home to over a billion people, from 2003 to 2020. The study establishes strong evidence of anthropogenic agricultural water use over irrigated lands (e.g., Ganges-Brahmaputra) which causes the highest surface albedo decreases (£1%/year). Greening and decreased snow cover from warming also drive changes in visible and near-infrared surface albedo in different areas of HMA. The significant role of human management and human-induced greening in influencing albedo suggests the potential of a positive feedback cycle where albedo decreases lead to increased evaporative demand and increased stress on water resources.This research was supported by the grant from the National Aeronautics and Space Administration High Mountain Asia program (19-HMA19-0012). Computing was supported by the resources at the NASA Center for Climate Simulation.https://www.researchsquare.com/article/rs-1413058/v