Case Study of Distributed Hydrologic Model for Soil and Nutrient Loss Estimation in Small Watershed

Author(s):  
Rui Xu ◽  
Xiaoxue Huang ◽  
Lin Luo ◽  
Hongbing Luo
2015 ◽  
Vol 527 ◽  
pp. 943-957 ◽  
Author(s):  
Aline S. Falck ◽  
Viviana Maggioni ◽  
Javier Tomasella ◽  
Daniel A. Vila ◽  
Fábio L.R. Diniz

Water ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 1279
Author(s):  
Tyler Madsen ◽  
Kristie Franz ◽  
Terri Hogue

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.


2014 ◽  
Vol 46 (3) ◽  
pp. 400-410 ◽  
Author(s):  
Hitesh Patel ◽  
Ataur Rahman

In rainfall–runoff modeling, Design Event Approach is widely adopted in practice, which assumes that the rainfall depth of a given annual exceedance probability (AEP), can be converted to a flood peak of the same AEP by assuming a representative fixed value for the other model inputs/parameters such as temporal pattern, losses and storage-delay parameter of the runoff routing model. This paper presents a case study which applies Monte Carlo simulation technique (MCST) to assess the probabilistic nature of the storage delay parameter (kc) of the RORB model for the Cooper's Creek catchment in New South Wales, Australia. It has been found that the values of kc exhibit a high degree of variability, and different sets of plausible values of kc result in quite different flood peak estimates. It has been shown that a stochastic kc in the MCST provides more accurate design flood estimates than a fixed representative value of kc. The method presented in this study can be adapted to other catchments/countries to derive more accurate design flood estimates, in particular for important flood study projects, which require a sensitivity analysis to investigate the impacts of parameter uncertainty on design flood estimates.


2004 ◽  
Vol 298 (1-4) ◽  
pp. 61-79 ◽  
Author(s):  
Theresa M. Carpenter ◽  
Konstantine P. Georgakakos

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