منابع مشابه
The Regional Hydrologic Extremes Assessment System: A software framework for hydrologic modeling and data assimilation
The Regional Hydrologic Extremes Assessment System (RHEAS) is a prototype software framework for hydrologic modeling and data assimilation that automates the deployment of water resources nowcasting and forecasting applications. A spatially-enabled database is a key component of the software that can ingest a suite of satellite and model datasets while facilitating the interfacing with Geograph...
متن کاملUsing GRACE Satellite Gravimetry for Assessing Large-Scale Hydrologic Extremes
Global assessment of the spatiotemporal variability in terrestrial total water storage anomalies (TWSA) in response to hydrologic extremes is critical for water resources management. Using TWSA derived from the gravity recovery and climate experiment (GRACE) satellites, this study systematically assessed the skill of the TWSA-climatology (TC) approach and breakpoint (BP) detection method for id...
متن کاملRegional Frequency Analysis Methods for Evaluating Changes in Hydrologic Extremes
A common assumption in frequency analysis is that hydrologic extremes ( oods or heavy precipitation) are generated by a random process. This implies that natural climatic variability does not change the distribution of extreme events. A regional frequency analysis approach is proposed to test the hypothesis of randomness over secular time scales. Observed regional occurrences of extreme events ...
متن کاملResponse of snow-dependent hydrologic extremes to continued global warming.
Snow accumulation is critical for water availability in the northern hemisphere 1,2, raising concern that global warming could have important impacts on natural and human systems in snow-dependent regions 1,3. Although regional hydrologic changes have been observed (e.g., 1,3-5), the time of emergence of extreme changes in snow accumulation and melt remains a key unknown for assessing climate c...
متن کاملTerrestrial Sediment Yield Projection under the Bias-Corrected Nonstationary Scenarios with Hydrologic Extremes
For reliable prediction of sediment yield in a watershed, fine-scale projections for hydro-climate components were first obtained using the statistical bias correction and downscaling scheme based on the combination of an Artificial Neural Network (ANN), Nonstationary Quantile Mapping (NSQM) and Stochastic Typhoon Synthesis (STS) sub-modules. Successively, the hydrologic runoff and sediment yie...
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ژورنال
عنوان ژورنال: Journal of Water and Climate Change
سال: 2020
ISSN: 2040-2244,2408-9354
DOI: 10.2166/wcc.2020.400