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

Shuttle Radar Topography Mission (SRTM) data for Sri Lanka: potential contributions in river basin research

In De Silva, R. P. (Ed.). Geo-informatics research and applications: proceedings of the First Symposium on Geo-informatics, Peradeniya, Sri Lanka, 30 July 2004. Peradeniya, Sri Lanka: Geo-Informatics Society of Sri Lanka (GISSL)

Assimilation of NASA's Airborne Snow Observatory Snow Measurements for Improved Hydrological Modeling: A Case Study Enabled by the Coupled LIS/WRF-Hydro System

The NASA LIS/WRF-Hydro system is a coupled modeling framework that combines the modeling and data assimilation (DA) capabilities of the NASA Land Information System (LIS) with the multi-scale surface hydrological modeling capabilities of the WRF-Hydro model, both of which are widely used in both operations and research. This coupled modeling framework builds on the linkage between land surface models (LSMs), which simulate surface boundary conditions in atmospheric models, and distributed hydrologic models, which simulate horizontal surface and sub-surface flow, adding new land DA capabilities. In the present study, we employ this modeling framework in the Tuolumne River basin in central California. We demonstrate the added value of the assimilation of NASA Airborne Snow Observatory (ASO) snow water equivalent (SWE) estimates in the Tuolumne basin. This analysis is performed in both LIS as an LSM column model and LIS/WRF-Hydro, with hydrologic routing. Results demonstrate that ASO DA in the basin reduced snow bias by as much as 30% from an open-loop (OL) simulation compared to three independent datasets. It also reduces downstream streamflow runoff biases by as much as 40%, and improves streamflow skill scores in both wet and dry years. Analysis of soil moisture and evapotranspiration (ET) also reveals the impacts of hydrologic routing from WRF-Hydro in the simulations, which would otherwise not be resolved in an LSM column model. By demonstrating the beneficial impact of SWE DA on the improving streamflow forecasts, the article outlines the importance of such observational inputs for reservoir operations and related water management applications.https://doi.org/10.1029/2021WR02986

RS/GIS training materials for awareness: version 1.0

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