Distributed and integrated response of a geographic information system‐based hydrologic model in the eastern Palouse region, Idaho

Abstract

Abstract:Verification of distributed hydrologic models is rare owing to the lack of spatially detailed field measurements and a common mismatch between the scale at which soil hydraulic properties are measured and the scale of a single modelling unit. In this study, two of the most commonly calibrated parameters, i.e. soil depth and the vertical distribution of lateral saturated hydraulic conductivity K s , were eliminated by a spatially detailed soil characterization and results of a hillslope-scale field experiment. The soil moisture routing (SMR) model, a geographic information system-based hydrologic model, was modified to represent the dominant hydrologic processes for the Palouse region of northern Idaho. Modifications included K s as a double exponential function of depth in a single soil layer, a snow accumulation and melt algorithm, and a simple relationship between storage and perched water depth (PWD) using the drainable porosity. The model was applied to a 2 ha catchment without calibration to measured data. Distributed responses were compared with observed PWD over a 3-year period on a 10 m ð 15 m grid. Integrated responses were compared with observed surface runoff at the catchment outlet. The modified SMR model simulated the PWD fluctuations remarkably well, especially considering the shallow soils in this catchment: a 0Ð20 m error in PWD is equivalent to only a 1Ð6% error in predicted soil moisture content. Simulations also captured PWD fluctuations during a year with high spatial variability of snow accumulation and snowmelt rates at upslope, mid-slope, and toe slope positions with errors as low as 0Ð09 m, 0Ð12 m, and 0Ð12 m respectively. Errors in distributed and integrated model simulations were attributed mostly to misrepresentation of rain events and snowmelt timing problems. In one location in the catchment, simulated PWD was consistently greater than observed PWD, indicating a localized recharge zone, which was not identified by the soil morphological survey.

Groundwater recharge in Pleistocene sediments overlying basalt aquifers in the Palouse Basin, USA: modeling of distributed recharge potential and identification of water pathways

“…The soil moisture routing (SMR) model, a geographic information system (GIS)-based distributed hydrology model adapted and validated for the Palouse region (Brooks et al 2007;Brooks and Boll 2002) was used to identify the relative potential for groundwater recharge throughout the PC watershed. Simulations were run for the PC watershed over a 7-year period (2002)(2003)(2004)(2005)(2006)(2007)(2008).…”

“…A daily, two-soil layer version of the SMR model was used to simulate the hydrology of the PC watershed. Further details on the SMR model are available in Brooks et al (2007).…”

“…The vertical percolation rate through the Sediments of Bovill was set at 0.24 mm d -1 , which is equivalent to the rate reported for argillic horizons within Southwick and Taney soils. Sensitivity and SMR model error was previously assessed by Brooks et al (2007) using detailed integrated and distributed hydrometric data. Brooks et al (2007) compared simulated and observed perched water-table depths recorded every 12 h over a 3-year period at over 100 shallow well locations in a 2-ha catchment.…”

“…Sensitivity and SMR model error was previously assessed by Brooks et al (2007) using detailed integrated and distributed hydrometric data. Brooks et al (2007) compared simulated and observed perched water-table depths recorded every 12 h over a 3-year period at over 100 shallow well locations in a 2-ha catchment. Model agreement with perched water-table depths was very good with average root mean square error (RMSE) values less than 18 cm which equated to less than 1-cm error in total depth of water stored in the soil profile (Brooks et al 2007).…”

Hydrologic assessment of an urban variable source watershed in the northeast United States

“…Grayson et al [1992] state that distributed models with numerous calibration parameters should be used for hypothesis testing or research purposes, not for management applications. For management applications, distributed models should avoid calibration; utilize simple input data, and clearly state hydrologic assumptions [Brooks et al, 2007]. One of the few models that requires little or no calibration, uses easily available input data, and generates a spatially distributed output is the soil moisture distribution and routing model (SMDR) [Zollweg et al, 1996;Frankenberger et al, 1999;Kuo et al, 1999, Mehta et al, 2004.…”