Modeling Streamflow in a Snow-Dominated Forest Watershed Using the Water Erosion Prediction Project (WEPP) Model

Abstract

Abstract. The Water Erosion Prediction Project (WEPP) model was originally developed for hillslope and small watershed applications. Recent improvements to WEPP have led to enhanced computations for deep percolation, subsurface lateral flow, and frozen soil. In addition, the incorporation of channel routing has made the WEPP model well suited for large watersheds with perennial flows. However, WEPP is still limited in modeling forested watersheds where groundwater baseflow is substantial. The objectives of this study were to (1) incorporate nonlinear algorithms into WEPP (v2012.8) for estimating groundwater baseflow, (2) auto-calibrate the current and modified WEPP model using a model-independent parameter estimation tool, and (3) evaluate and compare the performance of the current version of WEPP without baseflow (WEPP-Cur) and the modified WEPP model with baseflow (WEPP-Mod) in simulating the hydrology of a snow-dominated watershed in the U.S. Pacific Northwest. A subwatershed of the Upper Cedar River Watershed in western Washington State was chosen for WEPP application and assessment. Simulations were conducted for two periods: 1997-2003 to calibrate the model and 2004-2011 to assess the model performance. The WEPP-Cur simulations resulted in Nash-Sutcliffe efficiency (NSE) and deviation of runoff volume (Dv) values of 0.55 and 24%, respectively, for the calibration period, and 0.60 and 21%, respectively, for the assessment period. The WEPP-Mod simulated streamflow showed improved agreement with observed streamflow, with NSE and Dv values of 0.76 and 6%, respectively, for the calibration period, and 0.74 and 2%, respectively, for the assessment period. The WEPP-Mod model reproduced hydrograph recessions during the low-flow periods and the general trend of the hydrographs, demonstrating its applicability to a watershed where groundwater baseflow was significant. The incorporation of a baseflow component into WEPP will help forest managers to assess the alterations in hydrological processes and water yield for their forest management practices. Keywords: Baseflow, Forest watershed, Hydrological modeling, Streamflow, U.S. Pacific Northwest, WEPP.

Evaluation of random forests for short-term daily streamflow forecasting in rainfall- and snowmelt-driven watersheds

“…The MDA value can be negative when a predictor has no predictive power and adds noise to the model. Strobl et al (2007), however, expressed caution that permutation-based measures such as MDA could show a bias towards correlated predictor variables by overestimating their importance, particularly in high-dimensional datasets.…”

Designing tools to predict and mitigate impacts on water quality following the Australian 2019/2020 wildfires: Insights from Sydney's largest water supply catchment

“…To overcome this limitation, new procedures were put in place by automating catchment delineation and using GIS products to specify ash loads. Overcoming this limitation was particularly important given the ongoing increase in the probability of large fires not only in SE Australia (Lindenmayer and Taylor 2020) (Wang et al 2010;Srivastava et al 2013;Brooks et al 2016;Srivastava et al 2017), sediment transport and routing (Srivastava et al 2018), which increase in importance with catchment size (Kampf et al 2020). As the catchment size increases, stream processes become more dominant, and runofferosion models become more reliant on sediment and ash transport models.…”

Evaluation of Random Forest for short-term daily streamflow forecast in rainfall and snowmelt driven watersheds

“…9) where the RF performs worse in watersheds with higher hydraulic conductivities (i.e., higher sand content). This could be a result of rapid subsurface flow from soil profile enabled by soil macropores in mountainous forested area (Srivastava et al, 2017), where subsurface flow is the predominant mechanism. Without a quantification of the partition of discharge into surface flow and subsurface flow at individual watersheds, it is difficult to determine the relative importance of subsurface runoff mechanisms in regulating streafmlow and how that may have affected the RF performance.…”