SMR (Soil Moisture Routing Model)

SMR is a distributed, grid-based water balance model well-adapted to regions with steep-sloping land and shallow soils.

distributedgrid-basedwater balancesteep-slopingshallow soils
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contributed at 2019-12-15

Authorship

Affiliation:  
Department of Agricultural and Biological Engineering, Purdue University
Affiliation:  
Department of Agricultural and Biological Engineering, Cornell University
Affiliation:  
Department of Agricultural and Biological Engineering, Cornell University
Affiliation:  
Department of Agricultural and Biological Engineering, Cornell University
Affiliation:  
Department of Agricultural and Biological Engineering, Cornell University
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Application-focused categoriesNatural-perspectiveLand regions

Model Description

English {{currentDetailLanguage}} English

Quoted fromYourek, Matt, Erin S. Brooks, Dave J. Brown, Matteo Poggio, and Caley Gasch. "Development and application of the soil moisture routing (SMR) model to identify subfield-scale hydrologic classes in dryland cropping systems using the Budyko framework." Journal of Hydrology 573 (2019): 153-167.  https://doi.org/10.1016/j.jhydrol.2019.03.030 

SMR is a distributed, grid-based water balance model well-adapted to regions with steep-sloping land and shallow soils. It was developed as a spatially explicit management tool to inform management decisions addressing nonpoint source pollution from dairy farms in the Catskill Mountains of New York (Frankenberger et al., 1999Walter et al., 2000). As a management tool, it was developed to be a relatively simple model with few parameters and requiring minimal calibration (Brooks et al., 2007Frankenberger et al., 1999). This 3D model simulates both vertical water fluxes within a grid cell (e.g. rainfall, snow accumulation and melt, evapotranspiration, deep percolation below the root zone) as well as net lateral subsurface flow between cells. Surface runoff occurs in the landscape whenever the accumulated volume of soil water in a grid cell exceeds available pore space (i.e. saturation excess runoff). Surface runoff is not explicitly routed overland to the outlet of the catchment but rather is assumed to reach the watershed outlet within the model timestep. Infiltration excess runoff is not directly simulated by the model, which makes the model best suited to regions where the soil infiltration capacity is greater than the typical rainfall intensity (Boll et al., 1998Frankenberger et al., 1999Mehta et al., 2004). Subsurface lateral flow out of a grid cell is simulated using Darcy’s equation with hydraulic gradient equal to the land slope and routed to up to eight neighboring cells following the approach described in Brooks et al. (2007). Variability in soil characteristics with depth (e.g. bulk density and lateral saturated hydraulic conductivity) are represented by explicit functions. The soil water balance in SMR for each grid cell (Eq. (5)) consists of positive fluxes: precipitation (P) and incoming lateral flow (Qin), and negative fluxes: actual evapotranspiration (ETA), deep percolation (DP), outgoing lateral flow (Qout), and surface runoff (RO). Positive and negative fluxes balance to equal change in soil water storage (ΔS/Δt).

ΔS/Δt=P+Qin-ETA-DP-Qout-RO

Additional details about model development and functioning can be found in the literature (Frankenberger et al., 1999Brooks and Boll, 2005Brooks et al., 2007).

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How to Cite

Jane R. Frankenberger, Erin S. Brooks, M. Todd Walter, Michael F. Walter, Tammo S. Steenhuis (2019). SMR (Soil Moisture Routing Model), Model Item, OpenGMS, https://geomodeling.njnu.edu.cn/modelItem/cfac8985-f05a-41cf-9b16-ecfecffce20e
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Last modifier : 
zhangshuo
Last modify time : 
2021-01-07
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Contributor(s)

Initial contribute: 2019-12-15

Authorship

Affiliation:  
Department of Agricultural and Biological Engineering, Purdue University
Affiliation:  
Department of Agricultural and Biological Engineering, Cornell University
Affiliation:  
Department of Agricultural and Biological Engineering, Cornell University
Affiliation:  
Department of Agricultural and Biological Engineering, Cornell University
Affiliation:  
Department of Agricultural and Biological Engineering, Cornell University
Is authorship not correct? Feedback

History

Last modifier : 
zhangshuo
Last modify time : 
2021-01-07
Modify times : 
View History

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