Development of a soil moisture‐based distributed hydrologic model for determining hydrologically based critical source areas

Abstract

A simple grid cell‐based distributed hydrologic model was developed to provide spatial information on hydrologic components for determining hydrologically based critical source areas. The model represents the critical process (soil moisture variation) to run‐off generation accounting for both local and global water balance. In this way, it simulates both infiltration excess run‐off and saturation excess run‐off. The model was tested by multisite and multivariable evaluation on the 50‐km2 Little River Experimental Watershed I in Georgia, U.S. and 2 smaller nested subwatersheds. Water balance, hydrograph, and soil moisture were simulated and compared to observed data. For streamflow calibration, the daily Nash‐Sutcliffe coefficient was 0.78 at the watershed outlet and 0.56 and 0.75 at the 2 nested subwatersheds. For the validation period, the Nash‐Sutcliffe coefficients were 0.79 at the watershed outlet and 0.85 and 0.83 at the 2 subwatersheds. The per cent bias was less than 15% for all sites. For soil moisture, the model also predicted the rising and declining trends at 4 of the 5 measurement sites. The spatial distribution of surface run‐off simulated by the model was mainly controlled by local characteristics (precipitation, soil properties, and land cover) on dry days and by global watershed characteristics (relative position within the watershed and hydrologic connectivity) on wet days when saturation excess run‐off was simulated. The spatial details of run‐off generation and travel time along flow paths provided by the model are helpful for watershed managers to further identify critical source areas of non‐point source pollution and develop best management practices.

Systematic visual analysis of groundwater hydrographs: potential benefits and challenges

“…In (groundwater) hydrology, visual inspection and comparison of time series is quite frequently mentioned as part of a workflow or diagnostic tool. However, most of the related publications do not explicitly describe how the visual analysis was carried out and what role it played in the work flow (e.g., Guzha and Hardy 2009;Harrigan et al 2014;Li et al 2017). Of the few articles that not only mention the use of visual tools, but also address their role as a part of the methodology, the most relevant in the context of this article is Ehret and Zehe (2011).…”

Preferred Hierarchical Control Strategy of Non-Point Source Pollution at Regional Scale

“…For large-scale watersheds, most CSAs are identified through sub-catchment units, which is an efficient approach for the identification of CSAs; however, it neglects the heterogeneity of NPS pollution load distribution in sub-catchments (Liu et al 2016b, Niraula et al 2013, Pradhanang &Briggs 2014, Ruan et al 2020, Wang et al 2018. Considering that administrative units (such as a county) or farms, which are distinct and disconnected with hydrological units, are used for management in most situations (Ghebremichael et al 2013, Li et al 2017, it is difficult to achieve accurate prevention and control of NPS pollution and to effectively allocate BMPs. For small watersheds, CSAs are mostly identified by grids (Zhuang et al 2016).…”