Process-based watershed models are useful tools for understanding the impacts of natural and anthropogenic influences on water resources and for predicting water and solute fluxes exported from watersheds to receiving water bodies. The applicability of process-based hydrologic models has been previously limited to small catchments and short time frames. Computational demands, especially the solution to the three-dimensional subsurface flow domain, continue to pose significant constraints. This paper documents the mathematical development, numerical testing and the initial application of a new distributed hydrologic model PAWS (Process-based Adaptive Watershed Simulator). The model solves the governing equations for the major hydrologic processes efficiently so that large scale applications become relevant. PAWS evaluates the integrated hydrologic response of the surface–subsurface system using a novel non-iterative method that couples runoff and groundwater flow to vadose zone processes approximating the 3D Richards equation. The method is computationally efficient and produces physically consistent solutions. All flow components have been independently verified using analytical solutions and experimental data where applicable. The model is applied to a medium-sized watershed in Michigan (1169 km2) achieving high performance metrics in terms of streamflow prediction at two gages during the calibration and verification periods. PAWS uses public databases as input and possesses full capability to interact with GIS datasets. Future papers will describe applications to other watersheds and the development and application of fate and transport modules.

1 aShen, Chaopeng1 aPhanikumar, M. uhttps://icer.msu.edu/research/publications/process-based-distributed-hydrologic-model-based-large-scale-method-surface03043nas a2200133 4500008004100000245009200041210006900133260005000202300000800252490001000260520249600270100001902766856012402785 2009 eng d00aA process-based distributed hydrologic model and its application to a Michigan watersed0 aprocessbased distributed hydrologic model and its application to aEast LansingbMichigan State Universityc2009 a2880 vPh.D.3 aThe PAWS (Process-based Adaptive Watershed Simulator) model is a novel distributed hydrologic model that is based on solving partial differential equations (PDE) for physical conservation laws of the hydrologic cycle. The objective is to create an efficient physically-based modeling framework to describe the linkages between processes at different scales and to improve the applicability of physically-based models. The model simulates evapotranspiration, overland flow, channel flow, unsaturated soil moisture, groundwater flow, depression storage, vegetation growth and snowpack. PAWS focuses on the dynamic surface- subsurface interactions and integrated responses by efficiently coupling runoff and groundwater flow to the vadose zone processes governed by the Richards equation. This novel approach solves a long-standing bottleneck in PDE-based subsurface flow modeling by removing the computational limitations while maintaining physically consistent solutions. Surface flow is solved by ail efficient Runge-Kutta Finite Volume (RKFV) scheme. We follow the Freeze and Harlan (1969) blueprint in that we believe each component of the model should be verifiable by itself. All flow components have been independently verified using analytical solutions and experimental data where applicable. PAWS utilizes readily available data from national databases. The model is applied to a medium-sized watershed in Michigan achieving high performance metrics in terms of streamflow prediction at two gages during the calibration period and the verification period. The baseflow flow periods are described particularly well. Starting from a rough initial estimate of the groundwater heads, the model describes the observed groundwater heads well (R 2 =0.98). The annual hydrologic fluxes are close to those estimated by a calibrated SWAT model. The model is considerably less expensive than previous physically-based models of similar complexity. The model is able to elucidate the complex interactions of processes in space and time. Such detailed, quantitative and mechanistic descriptions cannot be produced by conceptual models. The watershed is found to be a subsurface-dominated system with saturation excess being the main runoff generation mechanism. Infiltration, recharge and ET are also found to be strongly related to topography and groundwater flow. The large seasonal variation of energy input drives the strong annual cycle and markedly different responses in streamflow.

1 aShen, Chaopeng uhttps://icer.msu.edu/research/publications/process-based-distributed-hydrologic-model-its-application-michigan-watersed03073nas a2200133 4500008004100000020001800041245009300059210006900152260005300221490002500274520249600299100001902795856012502814 2009 eng d a978110964010600aA process-based distributed hydrologic model and its application to a Michigan watershed0 aprocessbased distributed hydrologic model and its application to aEast LansingbMichigan State Universityc08/20100 vDoctor of Philosophy3 aThe PAWS (Process-based Adaptive Watershed Simulator) model is a novel distributed hydrologic model that is based on solving partial differential equations (PDE) for physical conservation laws of the hydrologic cycle. The objective is to create an efficient physically-based modeling framework to describe the linkages between processes at different scales and to improve the applicability of physically-based models. The model simulates evapotranspiration, overland flow, channel flow, unsaturated soil moisture, groundwater flow, depression storage, vegetation growth and snowpack. PAWS focuses on the dynamic surface- subsurface interactions and integrated responses by efficiently coupling runoff and groundwater flow to the vadose zone processes governed by the Richards equation. This novel approach solves a long-standing bottleneck in PDE-based subsurface flow modeling by removing the computational limitations while maintaining physically consistent solutions. Surface flow is solved by ail efficient Runge-Kutta Finite Volume (RKFV) scheme. We follow the Freeze and Harlan (1969) blueprint in that we believe each component of the model should be verifiable by itself. All flow components have been independently verified using analytical solutions and experimental data where applicable. PAWS utilizes readily available data from national databases. The model is applied to a medium-sized watershed in Michigan achieving high performance metrics in terms of streamflow prediction at two gages during the calibration period and the verification period. The baseflow flow periods are described particularly well. Starting from a rough initial estimate of the groundwater heads, the model describes the observed groundwater heads well (R 2 =0.98). The annual hydrologic fluxes are close to those estimated by a calibrated SWAT model. The model is considerably less expensive than previous physically-based models of similar complexity. The model is able to elucidate the complex interactions of processes in space and time. Such detailed, quantitative and mechanistic descriptions cannot be produced by conceptual models. The watershed is found to be a subsurface-dominated system with saturation excess being the main runoff generation mechanism. Infiltration, recharge and ET are also found to be strongly related to topography and groundwater flow. The large seasonal variation of energy input drives the strong annual cycle and markedly different responses in streamflow.

1 aShen, Chaopeng uhttps://icer.msu.edu/research/publications/process-based-distributed-hydrologic-model-its-application-michigan-watershed