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Search indexed NASA NTRS and DOE OSTI research on propulsion, heat transfer, battery materials and energy systems. Follow report and document links to the original sources.

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All sourcesNASA NTRSDOE OSTI
DOE OSTI2020

Lawrence Livermore National Laboratory Annual Environmental Report 2019

The purposes of the Lawrence Livermore National Laboratory (LLNL) Environmental Report 2019 are to record LLNL's compliance with environmental standards and requirements, describe LLNL’s environmental protection and remediation programs, and present the results of environmental monitoring at the two LLNL sites—the Livermore Site and Site 300. The report is prepared for the U.S. Department of Energy (DOE) by LLNL’s Environmental Functional Area. Submittal of the report satisfies requirements under DOE Order 231.1B, “Environment, Safety and Health Reporting,” and DOE Order 458.1, “Radiation Protection of the Public and Environment.” The report begins with an executive summary, which provides the purpose of the report and an overview of LLNL’s compliance and monitoring results. The first three chapters provide background information: Chapter 1 is an overview of the location, meteorology, and hydrogeology of the two LLNL sites; Chapter 2 is a summary of LLNL’s compliance with environmental regulations; and Chapter 3 is a description of LLNL’s environmental programs with an emphasis on the Environmental Management System including pollution prevention. The majority of the report covers LLNL’s environmental monitoring programs and monitoring data for 2019: effluent and ambient air monitoring and dose assessment (Chapter 4); waters, including wastewater, storm water runoff, surface water, rain, and groundwater (Chapter 5); and terrestrial, including soil, sediment, vegetation, foodstuff, ambient radiation, and special status wildlife and plants (Chapter 6). The remaining two chapters discuss LLNL’s groundwater remediation program (Chapter 7), and quality assurance for the environmental monitoring programs (Chapter 8). Complete monitoring data, which are summarized in the body of the report, are provided in Appendix A.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2022

Lawrence Livermore National Laboratory Environmental Report 2021

The purposes of the Lawrence Livermore National Laboratory Environmental Report 2021 are to record Lawrence Livermore National Laboratory’s (LLNL’s) compliance with environmental standards and requirements, describe LLNL’s environmental protection and remediation programs, and present the results of environmental monitoring at the two LLNL sites—the Livermore Site and Site 300. The report is prepared for the U.S. Department of Energy (DOE) by LLNL’s Environmental Functional Area. Submittal of the report satisfies requirements under DOE Order 231.1B, “Environment, Safety and Health Reporting,” and DOE Order 458.1, “Radiation Protection of the Public and Environment.” The report is distributed electronically and is available at https://saer.llnl.gov/, the website for the LLNL annual environmental report. Previous LLNL annual environmental reports beginning with 1994 are also on the website. Some references in the electronic report text are underlined, which indicates that they are clickable links. Clicking on one of these links will open the related document, data workbook, or website. Sampling location maps throughout this report were created using ArcGIS® software by Esri. The report begins with an executive summary, which provides the purpose of the report and an overview of LLNL’s compliance and monitoring results. The first three chapters provide background information: Chapter 1 is an overview of the location, meteorology, and hydrogeology of the two LLNL sites; Chapter 2 is a summary of LLNL’s compliance with environmental regulations; and Chapter 3 is a description of LLNL’s environmental programs with an emphasis on the Environmental Management System including pollution prevention. The majority of the report covers LLNL’s environmental monitoring programs and monitoring data for 2021: effluent and ambient air monitoring and dose assessment (Chapter 4); waters, including wastewater, storm water runoff, surface water, rain, and groundwater (Chapter 5); and terrestrial, including soil, sediment, vegetation, foodstuff, ambient radiation, and special status wildlife and plants (Chapter 6). The remaining two chapters discuss LLNL’s groundwater remediation program (Chapter 7), and quality assurance for the environmental monitoring programs (Chapter 8). Complete monitoring data, which are summarized in the body of the report, are provided in Appendix A. The report uses Système International units, consistent with the federal Metric Conversion Act of 1975 and Executive Order 12770, “Metric Usage in Federal Government Programs” (1991). For ease of comparison to environmental reports issued prior to 1991, dose values and many radiological measurements are given in both metric and U.S. customary units. A conversion table is provided in the glossary. The report is the responsibility of LLNL’s Environmental Functional Area. Monitoring data were obtained through the combined efforts of the Environmental Functional Area; Environmental Restoration Department; Physical and Life Sciences Environmental Monitoring Radiological Laboratory; and the Radiation Protection Functional Area.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Performance assessment for climate intervention (PACI): preliminary application to a stratospheric aerosol injection scenario

As the prospect of exceeding global temperature targets set forth in the Paris Agreement becomes more likely, methods of climate intervention are increasingly being explored. With this increased interest there is a need for an assessment process to understand the range of impacts across different scenarios against a set of performance goals in order to support policy decisions. The methodology and tools developed for Performance Assessment (PA) for nuclear waste repositories shares many similarities with the needs and requirements for a framework for climate intervention. Using PA, we outline and test an evaluation framework for climate intervention, called Performance Assessment for Climate Intervention (PACI) with a focus on Stratospheric Aerosol Injection (SAI). We define a set of key technical components for the example PACI framework which include identifying performance goals, the extent of the system, and identifying which features, events, and processes are relevant and impactful to calculating model output for the system given the performance goals. Having identified a set of performance goals, the performance of the system, including uncertainty, can then be evaluated against these goals. Using the Geoengineering Large Ensemble (GLENS) scenario, we develop a set of performance goals for monthly temperature, precipitation, drought index, soil water, solar flux, and surface runoff. The assessment assumes that targets may be framed in the context of risk-risk via a risk ratio, or the ratio of the risk of exceeding the performance goal for the SAI scenario against the risk of exceeding the performance goal for the emissions scenario. From regional responses, across multiple climate variables, it is then possible to assess which pathway carries lower risk relative to the goals. The assessment is not comprehensive but rather a demonstration of the evaluation of an SAI scenario. Future work is needed to develop a more complete assessment that would provide additional simulations to cover parametric and aleatory uncertainty and enable a deeper understanding of impacts, informed scenario selection, and allow further refinements to the approach.

climate intervention↗
DOE OSTI2021

Disastrous Flash Floods Triggered by Moderate to Minor Rainfall Events. Recent Cases in Coastal Benguela (Angola)

The present work focuses on two recent flash floods in coastal Benguela (Angola), both triggered by moderate rainfall but which had disastrous consequences for local populations (namely 71 deaths in 2015 and 17 in 2019). The research involved a regional survey to establish the effects of these floods combined with a geomorphological and socio-economic analysis of the most affected areas to understand the main forcing factors. The two flash floods produced major damage in restricted sectors within very small coastal catchments (<16 km2). The prevalence of fine-grained sedimentary rocks, relatively steep hills, thin soil cover, and vegetation scarcity are natural factors that promote surface runoff. However, socio-economic conditions are most likely the main reasons of flood damage. Namely, rapid population growth with poor planning and making use of low-quality construction materials, the high waste yields that are not properly managed and the absence of flood risk awareness. In the small valleys around the fast-growing cities of coastal Benguela, hazardous flash floods occur recurrently, even after moderate precipitation. Most affected areas are determined by local conditions that compromise drainage at the time of the rainfall event, being very difficult to predict.

Dinis, Pedro A. (ORCID:0000000175587369)↗
DOE OSTI2022

BioRT-Flux-PIHM v1.0: a biogeochemical reactive transport model at the watershed scale

Watersheds are the fundamental Earth surface functioning units that connect the land to aquatic systems. Many watershed-scale models represent hydrological processes but not biogeochemical reactive transport processes. This has limited our capability to understand and predict solute export, water chemistry and quality, and Earth system response to changing climate and anthropogenic conditions. Here we present a recently developed BioRT-Flux-PIHM (BioRT hereafter) v1.0, a watershed-scale biogeochemical reactive transport model. The model augments the previously developed RT-Flux-PIHM that integrates land-surface interactions, surface hydrology, and abiotic geochemical reactions. It enables the simulation of (1) shallow and deep-water partitioning to represent surface runoff, shallow soil water, and deeper groundwater and of (2) biotic processes including plant uptake, soil respiration, and nutrient transformation. The reactive transport part of the code has been verified against the widely used reactive transport code CrunchTope. BioRT-Flux-PIHM v1.0 has recently been applied in multiple watersheds under diverse climate, vegetation, and geological conditions. This paper briefly introduces the governing equations and model structure with a focus on new aspects of the model. It also showcases one hydrology example that simulates shallow and deep-water interactions and two biogeochemical examples relevant to nitrate and dissolved organic carbon (DOC). These examples are illustrated in two simulation modes of complexity. One is the spatially lumped mode (i.e., two land cells connected by one river segment) that focuses on processes and average behavior of a watershed. Another is the spatially distributed mode (i.e., hundreds of cells) that includes details of topography, land cover, and soil properties. Whereas the spatially lumped mode represents averaged properties and processes and temporal variations, the spatially distributed mode can be used to understand the impacts of spatial structure and identify hot spots of biogeochemical reactions. The model can be used to mechanistically understand coupled hydrological and biogeochemical processes under gradients of climate, vegetation, geology, and land use conditions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Greenland Surface Melt Dominated by Solar and Sensible Heating

The Greenland Ice Sheet is the primary source of global Barystatic sea-level rise, and at least half of its recent mass-loss acceleration is caused by surface meltwater runoff. Previous studies on surface melt have examined various thermodynamic and dynamic drivers, yet their contributions are not compared using unified observations. We use decade-long in-situ measurements from automatic weather stations throughout the ablation zone to assess energy components and identify the leading physical processes in this area. Large melt events exceeding 3σ contribute only ~2% to total surface melt since 2007. The day-to-day variability of all melt is dominated by sensible heat exchange (31 ± 7%) and shortwave radiation (28 ± 5%). Sensible and solar heating correlate with the occurrence of dry and fast gravity-driven winds. These katabatic winds increase sensible heating of the surface mainly by enhancing vertical mixing that reduces the temperature inversion. The concomitant low humidity and clear skies yield increased solar heating.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

Significant Rural Contributions to Severe Coastal Urban Flooding Through Flow Connectivity

Coastal cities are increasingly threatened by hurricane-induced compound flooding. However, the relative contributions of rainfall-surge interactions and other flood drivers, such as runoff from surrounding rural and local impervious areas, in shaping urban flooding remain unclear. Here, we use a multi-scale Earth system modeling framework to disentangle the contributions of diverse flooding drivers. The results show that urban flooding is primarily affected by topographic factors (low elevation, flat slopes, and localized flow constrictions), rather than increased runoff from their impervious surfaces. Importantly, runoff from rural areas contributes more to severely flooded urban areas with inundation depth exceeding 1.7 m than local runoff. Although rainfall–surge interactions and sea-level rise exacerbate inundation along the coastline, over 90% of the compounding effects are absorbed by wetlands. By resolving flooding processes across scales and components, this study emphasizes the role of runoff from surrounding rural areas in shaping zones of severe urban flooding.

58 GEOSCIENCES↗
DOE OSTI2023

An ensemble of 48 physically perturbed model estimates of the 1/8° terrestrial water budget over the conterminous United States, 1980–2015

Terrestrial water budget (TWB) data over large domains are of high interest for various hydrological applications. Spatiotemporally continuous and physically consistent estimations of TWB rely on land surface models (LSMs). As an augmentation of the operational North American Land Data Assimilation System Phase 2 (NLDAS-2) four-LSM ensemble, this paper describes a dataset simulated from an ensemble of 48 physics configurations of the Noah LSM with multi-physics options (Noah-MP). The 48 Noah-MP physics configurations are selected to give a representative cross-section of commonly used LSMs for parameterizing runoff, atmospheric surface layer turbulence, soil moisture limitation on photosynthesis, and stomatal conductance. The dataset spans from 1980 to 2015 over the conterminous United States (CONUS) at a monthly temporal resolution and a 1/8° spatial resolution. The dataset variables include total evapotranspiration and its constituents (canopy evaporation, soil evaporation, and transpiration), runoff (the surface and subsurface components), as well as terrestrial water storage (snow water equivalent, four-layer soil water content from the surface down to 2 m, and the groundwater storage anomaly). The dataset is available at https://doi.org/10.5281/zenodo.7109816. Evaluations carried out in this study and previous investigations show that the ensemble per forms well in reproducing the observed terrestrial water storage, snow water equivalent, soil moisture, and runoff. Noah-MP complements the NLDAS models well, and adding Noah-MP consistently improves the NLDAS es timations of the above variables in most areas of CONUS. Besides, the perturbed-physics ensemble facilitates the identification of model deficiencies. The parameterizations of shallow snow, spatially varying groundwater dynamics, and near-surface atmospheric turbulence should be improved in future model versions.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

An Extreme-Preserving Long-Term Gridded Daily Precipitation Data Set for the Conterminous United States

Extreme daily precipitation contributes to flooding that can cause significant economic damages, and so is important to properly capture in gridded meteorological data sets. This work examines precipitation extremes, the mean precipitation on wet days, and fraction of wet days in two widely used gridded data sets over the conterminous U.S. (CONUS). When compared to the underlying station observations, the gridded data show a 27% reduction in annual 1-day maximum precipitation, 25% increase in wet day fraction, 1.5 to 2.5 day increase in mean wet spell length, 30% low bias in 20-year return values of daily precipitation, and 25% decrease in mean precipitation on wet days. It is shown these changes arise primarily from the time-adjustment applied to put the precipitation gauge observations into a uniform time frame, with the gridding process playing a lesser role. A new daily precipitation data set is developed that omits the time-adjustment (as well as extending the gridded data by 7 years) and is shown to perform significantly better in reproducing extreme precipitation metrics. When the new data set is used to force a land surface model, annually averaged 1-day maximum runoff increases 38% compared to the original data, annual mean runoff increases 17%, evapotranspiration drops 2.3%, and fewer wet days leads to a 3.3% increase in estimated solar insolation. Consequently, these changes are large enough to affect portrayals of flood risk and water balance components important for ecological and climate-change applications across the CONUS.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2021

Long-term shifts in feedbacks among glacier surface change, melt generation and runoff, McMurdo Dry Valleys, Antarctica

Glaciers of the McMurdo dry valleys (MDVs) Antarctica are the main source of streamflow in this polar desert. Because summer air temperatures hover near 0°C small changes in the energy balance strongly affect meltwater generation. In this work, we demonstrate that increased surface roughness, which alters the turbulent transfer of energy between the ice surface and atmosphere, yields a detectable increase in meltwater runoff. At low elevations on the glaciers, basin-like topography became significantly rougher over 13 years between repeat lidar surveys, yielding greater melt. In contrast, the smoother ice at higher elevation exhibited no detectable change in roughness. We pose a conceptual model of the cycle of glacier surface change as a result of climate forcing whereby glacier surfaces transition from being dominated by sublimation to becoming increasingly melt-dominated, which is reversible under prolonged cool periods. This research advances our understanding of warm season effects on polar glaciers.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2025

Uniting Surface Properties With Hydrodynamic Roughness in Shallow Overland Flow Models

Describing flow resistance from the properties of an underlying surface is a challenge in surface hydrology. Runoff models must specify a resistance formulation or “roughness scheme”—describing the functional relationship between flow resistance and flow depth/velocity—and its parameters. Uncertainty in runoff predictions derives from both the selected roughness scheme (e.g., Darcy Weisbach, Manning's, or laminar flow equations), and its parameterization with a roughness coefficient (e.g., Manning's n). Both choices are informed by model calibration to data, usually discharge, and, if available, velocity. In this study, a Saint Venant Equation-based runoff model is calibrated to discharge and velocity data from 112 rainfall simulator experiments. The results are used to identify the optimal roughness scheme among four widely-used options for each experiment, and to explore whether surface properties can be used to select the optimal roughness scheme and its coefficient. Among the tested roughness schemes, a transitional flow equation provided the best fit to the plurality of experiments. The most suitable roughness scheme for a given experiment was not related to measured surface properties. Regression models predicted the calibrated roughness coefficients with adjusted values between 0.48 and 0.54, depending on the roughness scheme used. Litter cover was the best predictor of the roughness coefficient, followed by soil cover and average canopy gap size. The results suggest that selection of an optimal roughness scheme based on surface properties alone remains difficult, but that once a scheme is selected, roughness coefficients can be estimated from surface properties.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2026

VIC-Global Parameter Dataset Sensitivity with the Variable Infiltration Capacity Model: Evaluating the importance of dynamic land surface parameters when using the VIC-Global parameter dataset

Accurate prediction of runoff is essential to water resources management, flood risk assessment, and ecosystem protection. However, many hydrological models still have relatively substantial limitations when representing the influence of land use and land cover (LULC) on runoff generation and routing. Changes in LULC, such as deforestation, urban expansion, agricultural intensification, and wetland loss, have been shown to alter the water balance at the land surface through fundamental hydrologic processes (e.g., interception, infiltration, evapotranspiration, and soil storage). However, it remains an open question what the exact magnitude and timing of these impacts are for the spatial and temporal scales commonly used in engineering applications. In this analysis we focus on one aspect of recent LULC change for assessing human impacts, which is urbanization. Specifically we seek to determine the impacts of urbanization on the magnitude and timing of surface runoff and baseflow in HUC-12 basins in Clark County, Nevada which has experienced rapid urbanization. We use the Variable Infiltration Capacity (VIC) hydrology model with a widely used off-the-shelf dataset of land surface parameters, VIC-Global, both of which have been commonly used in the past for water and energy balance modeling for large scale hydrologic studies. We examine two scenarios where the first scenario removes all urbanized land cover and parameterizes those areas of the basins as barren or open shrubland. The second scenario tests the opposite case where all areas of the basins are classified as urban regardless of their present classification. The results from the VIC model show there is a low sensitivity for daily surface runoff between scenarios. The daily baseflow values indicate similar low sensitivity to the classification change during specific periods, but then have substantial differences during other period when large precipitation events are occurring. This is likely due to the assumed parameter values for the urban land cover classification made by the VIC-Global dataset. Using a static land cover parameterization is reasonable for large domain hydrology models that are being used for near-term planning horizons (<30 years). However, longer planning horizons where feedbacks between the atmosphere and land surface are important, especially in transient climate situations, considerations for how to update land surface parameters should be incorporated.

42 ENGINEERING↗
DOE OSTI2020

Planning green infrastructure placement based on projected precipitation data

Continued urbanization has led to tremendous changes on the landscape. These changes have exacerbated the effects of extreme climatic events such as flooding because of constrained water infiltration and increased surface flow. Typical runoff control measures involve sophisticated gray infrastructure that guide excess surface flow into storage and disposal sites. In a dynamic climate system, these measures are not sustainable since they cannot be easily modified to accommodate large volumes of runoff. Green Infrastructure (GI) is an adaptable technique that can be used to minimize runoff, in addition to offering an array of additional benefits (urban heat regulation, aesthetics, improved air quality etc.). Strategic placement of GI is key to achieving maximum utility. While physical site characteristics play a major role in determining suitable GI placement sites, knowledge of future precipitation patterns is crucial to ensure successful flood mitigation. Here, suitable GI sites within the city of Knoxville, Tennessee, were determined based on potential impact of an extreme flood event as indicated by site characteristics. Then, the relative potential likelihood of a flood event was determined based on projected precipitation data and knowledge of existing flood zones. By combining potential impact with likelihood information, low, medium, and high priority GI implementation sites were established. Results indicate that high priority sites are in the central parts of the city with priority decreasing outward. The GI prioritization scheme presented here, offers valuable guidance to city planners and policy makers who wish to exploit the GI approach for flood mitigation.

54 ENVIRONMENTAL SCIENCES↗
DOE OSTI2023

Achieving Realistic Runoff in the Western United States with a Land Surface Model Forced by Dynamically Downscaled Meteorology

Abstract In this study, we calibrate a regional climate model’s (RCM) underlying land surface model (LSM). In addition to providing a realistic representation of runoff across the hydroclimatically diverse western United States, this is done to take advantage of the RCM’s ability to physically resolve meteorological forcing data in ungauged regions, and to prepare the calibrated hydrologic model for tight coupling, or the ability to represent land surface–atmosphere interactions, with the RCM. Specifically, we use a 9-km resolution meteorological forcing dataset across the western United States, from the fifth generation ECMWF Reanalysis (ERA5) downscaled by the Weather Research Forecasting (WRF) regional climate model, as an offline forcing for Noah-Multiparameterization (Noah-MP). We detail the steps involved in producing an LSM capable of accurately representing runoff, including physical parameterization selection, parameter calibration, and regionalization to ungauged basins. Based on our model evaluation from 1954 to 2021 for 586 basins with daily natural streamflow, the streamflow bias is reduced from 24.2% to 4.4%, and the median daily Nash–Sutcliffe efficiency (NSE) is improved from 0.12 to 0.36. When validating against basins with monthly natural streamflow data, we obtain a similar reduction in bias and a median monthly NSE improvement from 0.18 to 0.56. In this study, we also discover the optimal setup when using a donor-basin method to regionalize parameters to ungauged basins, which can vary by 0.06 NSE for unique designs of this regionalization method. Significance Statement This study provides useful guidance for improving a land surface model to accurately represent runoff across a spatially extensive and hydroclimatically diverse region (the western United States). The land surface model is updated to represent runoff more accurately at gauged basins, and then additionally updated for basins without observational data using a mathematical approach called the donor-basin method. We make use of a regional climate model’s reanalysis-derived meteorological data and its underlying land surface model to achieve realistic runoff. The calibrated land surface model can thus be tightly coupled in subsequent studies in a manner that should more accurately reflect runoff conditions. Findings from this study will serve as a useful reference for the atmospheric (and hydrologic) modeling communities and their ability to represent large-scale hydrology accurately.

Meteorology & Atmospheric Sciences↗
DOE OSTI2024

Measuring and modeling soil moisture and runoff at solar farms using a disconnected impervious surface approach

Abstract Ground‐mounted photovoltaic sites are often treated as impervious surfaces in stormwater permits. This ignores the pervious soils beneath and between solar arrays and leads to an overestimation of runoff. Our objective was to improve solar farm stormwater hydrology models by explicitly considering the disconnected impervious nature of solar design and site characteristics. Experimental sites established on utility scale solar farms in Colorado, Georgia, Minnesota, New York, and Oregon had perennial vegetative plantings with mean precipitation ranging from 40.6 to 124.5 cm, and soil texture ranging from loamy sand to clay. Soil moisture measurements were collected beneath arrays, under drip edges, and in the vegetated area between arrays at each site. Hydrus‐3D models for soil moisture and stormwater hydrology were developed that accounted for precipitation falling on solar panels, drip edge redistribution of rainfall, infiltration, and runoff in the pervious areas between solar arrays and beneath panels. Drip edge runoff averaged 3‐ to 10‐times incident precipitation at the New York and Minnesota sites, respectively. Root mean square error values between measured sub‐hourly soil moisture and predicted moisture for large measured single storm events averaged 0.029 across all five sites. Predicted runoff depths were strongly affected by precipitation depth, soil texture, soil profile depth, and soil bulk density. Runoff depths across the five experimental sites averaged 13%, 25%, and 45% of the 2‐, 10‐, and 100‐year design storm depths, clearly showing that these solar farms do not behave like impervious surfaces, but rather as disconnected impervious surfaces with substantial infiltration of runoff in the vegetated areas between and beneath solar arrays.

Agriculture↗
DOE OSTI2023

Hydrologic Connectivity and Patch‐To‐Hillslope Scale Relations in Dryland Ecosystems

Abstract In drylands, runoff during storms redistributes water and nutrients from bare soil areas to vegetated patches, subsidizing vegetation with additional resources. The extent of this redistribution depends on the interplay between surface roughness and permeability; greater permeability in vegetated patches promotes run‐on to vegetation, but greater surface roughness diverts runoff, producing tortuous flow paths that bypass vegetation. Here, this interplay is examined in virtual experiments using the 2D Saint Venant Equations to measure runoff connectivity. Flowpaths are delineated using tracers advected by the flow. Distances between tracer sources and sinks along flowpaths measure hydrologic connectivity at two lengthscales: connectivity to the hillslope outlet and within‐slope source‐sink connectivity. Differences between these connectivity lengthscales indicate how flow may “by‐pass” vegetated patches within hillslopes. At the hillslope scale, a derived power‐law relation between the runoff coefficient and outlet connectivity describes hillslope water losses, providing a foundation for identifying landscapes likely to shed water.

54 ENVIRONMENTAL SCIENCES↗