Abstract
Demand for reliable estimates of streamflow has increased as society becomes more susceptible to climatic extremes such as droughts and flooding, especially at small scales where local population centers and infrastructure can be affected by rapidly occurring events. In the current study, the Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) (NOAA/NWS, Silver Spring, MD, USA) was used to explore the accuracy of a distributed hydrologic model to simulate discharge at watershed scales ranging from 20 to 2500 km2. The model was calibrated and validated using observed discharge data at the basin outlets, and discharge at uncalibrated subbasin locations was evaluated. Two precipitation products with nominal spatial resolutions of 12.5 km and 4 km were tested to characterize the role of input resolution on the discharge simulations. In general, model performance decreased as basin size decreased. When sub-basin area was less than 250 km2 or 20–40% of the total watershed area, model performance dropped below the defined acceptable levels. Simulations forced with the lower resolution precipitation product had better model evaluation statistics; for example, the Nash–Sutcliffe efficiency (NSE) scores ranged from 0.50 to 0.67 for the verification period for basin outlets, compared to scores that ranged from 0.33 to 0.52 for the higher spatial resolution forcing.
Highlights
Hydrologic models are essential for improving our understanding of the various components of the hydrologic cycle and are valuable tools for water resources modeling, drought and flood forecasting, and climate change impact assessment studies
Distributed models are supported by readily available geographic information system (GIS) data and rapidly increasing computing power, and it has been anticipated that spatially distributed models would provide more accurate and timely hydrologic information due to their innate ability to account for basin heterogeneities and spatially distributed inputs [7,8,9,10,11]
Model performance measures indicated that the Hydrology Laboratory-Research Distributed Hydrologic Model (HL-RDHM) reproduced the observed hourly flows at each outlet with reasonably low Percent Bias (Pbias) and good correlation (Table 5)
Summary
Hydrologic models are essential for improving our understanding of the various components of the hydrologic cycle and are valuable tools for water resources modeling, drought and flood forecasting, and climate change impact assessment studies. Efforts have been made to advance hydrologic modeling and forecasting through the use of spatially distributed models [1,2,3,4,5,6]. Distributed models are supported by readily available geographic information system (GIS) data and rapidly increasing computing power, and it has been anticipated that spatially distributed models would provide more accurate and timely hydrologic information due to their innate ability to account for basin heterogeneities and spatially distributed inputs [7,8,9,10,11]. Distributed models are able to simulate hydrologic responses at interior locations within the basin drainage network, a benefit not afforded by lumped models.
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