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5 results for “Antecedent soil moisture”
Data from: Monitoring soil moisture at the catchment scale – A novel approach combining antecedent precipitation index and radar-derived rainfall data
<p>Knowledge about soil moisture is important for event-based rainfall-runoff models but monitoring conditions at the catchment scale is not a trivial task. Soil moisture is highly variable in space and time, particularly in dry climates with seasonal and spatially heterogeneous rainfall. Point measurements are difficult to upscale, and remotely sensed (RS) data often lack in spatial or temporal resolution for local or regional studies. Longer latency periods – the time required before data becomes available – of some RS data make them less applicable to time-sensitive analyses such as flash flood forecasting. This study evaluated a novel approach for estimating catchment-scale volumetric soil moisture using an antecedent precipitation index (API) -based model. The model was trained and tested using in-situ soil moisture measurements collected during a 3-month field sampling campaign in a 142 km<sup>2</sup><span><span><span><span><span><span><span><span><span> study area in central New Mexico. The calibrated model was applied at the catchment scale to produce soil moisture grids from radar-derived rainfall estimates. Model performance, resolution and latency were compared to satellite-based soil moisture estimates. Benefits of the proposed new method include high spatial resolution (1 × 1 km or less depending on the precipitation data source) and high prediction accuracy (root mean square errors 0.014–0.018 m</span></span></span></span></span></span></span></span></span><sup>3</sup><span><span><span><span><span><span><span><span><span>/m</span></span></span></span></span></span></span></span></span><sup>3</sup><span><span><span><span><span><span><span><span><span>). Given the short latency period for radar-derived rainfall data, the method has potential for use in operational flood risk assessment and forecasting.</span></span></span></span></span></span></span></span></span></p>
Data from: Monitoring soil moisture at the catchment scale – A novel approach combining antecedent precipitation index and radar-derived rainfall data
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Data from: Impact of antecedent soil moisture on runoff from a semiarid catchment
<p>Antecedent soil moisture is an important factor in the generation of runoff, but guidance for modeling moisture conditions in semiarid catchments is limited and conflicting. In this study, the impact of antecedent moisture was assessed at the plot scale (2.8 m<sup>2</sup>) using a portable rainfall simulator, and at the catchment scale based on observed precipitation and discharge for a 2.8 km<sup>2</sup> watershed in central New Mexico. Performance of three loss models commonly used for hydrologic analysis in the southwestern U.S. was tested at both scales. High initial moisture content led to substantially higher runoff ratios at both scales, confirming the importance of antecedent soil moisture for runoff predictions in semiarid drainages. Hydrologic parameters estimated based on plot experiments, however, were highly variable and cannot easily be upscaled to the catchment scale. Loss model performance was clearly scale dependent: more simplistic (one- and two parameter) loss methods out-performed a more complex (four parameter) model at the watershed scale, while the opposite held true for test plot simulations. At the catchment scale, all models performed poorly for small runoff events, but yielded acceptable results for storms causing large discharges if antecedent soil moisture was considered. Failing to account for antecedent moisture led to simulated runoff volume errors up to one order of magnitude.</p>
Data from: Impact of antecedent soil moisture on runoff from a semiarid catchment
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Supplemental Material for 'Global Soil Moisture Estimation based on GPM IMERG Data using a Site Specific Adjusted Antecedent Precipitation Index'
<p>This repository hosts all supplemental material for the publication:</p> <p><em>TBD</em></p>
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