Application of SMR to Modeling Watersheds in the Catskill Mountains

Mehta, Vishal K.; Walter, M. Todd; Brooks, Erin S.; Steenhuis, Tammo S.; Walter, Michael; Johnson, Mark S.; Boll, Jan; Thongs, Dominique

doi:10.1023/b:enmo.0000032096.13649.92

Cited by 58 publications

(62 citation statements)

References 23 publications

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“…Quantitatively, the depth of water stored in the soil, S(t), evolves over time using the water balance Different studies show that part of the interflow water from the steep hills appears at the hill bottoms during wet periods in the form of increased moisture content or overland flow (Frankenberger et al, 1999;Bayabil et al, 2010;Mehta et al, 2004;Tilahun et al, 2013). These findings reveal that the hill bottoms receive additional inputs to the soil reservoir from the steep upper parts of the hills besides the rainfall.…”

Section: Model Developmentmentioning

confidence: 99%

Analyzing runoff processes through conceptual hydrological modeling in the Upper Blue Nile Basin, Ethiopia

Dessie

Verhoest

Pauwels

et al. 2014

Hydrol. Earth Syst. Sci.

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Abstract. Understanding runoff processes in a basin is of paramount importance for the effective planning and management of water resources, in particular in data-scarce regions such as the Upper Blue Nile. Hydrological models representing the underlying hydrological processes can predict river discharges from ungauged catchments and allow for an understanding of the rainfall-runoff processes in those catchments. In this paper, such a conceptual process-based hydrological model is developed and applied to the upper Gumara and Gilgel Abay catchments (both located within the Upper Blue Nile Basin, the Lake Tana sub-basin) to study the runoff mechanisms and rainfall-runoff processes in the basin. Topography is considered as a proxy for the variability of most of the catchment characteristics. We divided the catchments into different runoff production areas using topographic criteria. Impermeable surfaces (rock outcrops and hard soil pans, common in the Upper Blue Nile Basin) were considered separately in the conceptual model. Based on model results, it can be inferred that about 65 % of the runoff appears in the form of interflow in the Gumara study catchment, and baseflow constitutes the larger proportion of runoff (44-48 %) in the Gilgel Abay catchment. Direct runoff represents a smaller fraction of the runoff in both catchments (18-19 % for the Gumara, and 20 % for the Gilgel Abay) and most of this direct runoff is generated through infiltration excess runoff mechanism from the impermeable rocks or hard soil pans. The study reveals that the hillslopes are recharge areas (sources of interflow and deep percolation) and direct runoff as saturated excess flow prevails from the flat slope areas. Overall, the model study suggests that identifying the catchments into different runoff production areas based on topography and including the impermeable rocky areas separately in the modeling process mimics the rainfall-runoff process in the Upper Blue Nile Basin well and yields a useful result for operational management of water resources in this data-scarce region.

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Section: Model Developmentmentioning

confidence: 99%

Analyzing runoff processes through conceptual hydrological modeling in the Upper Blue Nile Basin, Ethiopia

Dessie

Verhoest

Pauwels

et al. 2014

Hydrol. Earth Syst. Sci.

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“…[14] SMDR is a physically based, fully distributed, water balance model for shallow, sloping soils underlain by a restrictive layer [Steenhuis and van der Molen, 1986;Zollweg et al, 1996;Kuo et al, 1999;Frankenberger et al, 1999;Mehta et al, 2004;Gérard-Marchant et al, 2005]. The SMDR framework is adapted to run on the geographic information system (GIS) GRASS [U.S. Army Construction and Engineering Laboratory, 1997;Neteler and Mitasova, 2002].…”

Section: Soil Moisture Distribution and Routing Model Overviewmentioning

confidence: 99%

“…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.…”

Section: Introductionmentioning

confidence: 99%

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

Easton

Gerard-Marchant

Walter

et al. 2007

Water Resources Research

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[1] Effective control of nonpoint source contaminants in runoff from urbanized watersheds requires knowledge about the locations of runoff source areas under a variety of conditions. Physical monitoring of spatially variant processes, such as runoff production form variable source areas, is time-consuming and expensive. Thus modeling the processes may provide a valuable cost-effective alternative. In this paper we adapt and validate a variable source model for an urban watershed to predict areas of the landscape prone to elevated soil moisture levels and saturation excess runoff. We modified the soil moisture distribution and routing (SMDR) model to simulate hydrologic processes in an urban upstate New York watershed by considering the impact of impervious surfaces, hydraulic control structures (detention basins), and land use on the water balance. In our model, infiltration excess runoff from impervious surfaces infiltrates in the surrounding soils. Simulated and observed streamflow agreed well, and more importantly, the distribution of soil moisture levels and overland flow throughout the watershed were well predicted. Removing urban features from the model resulted in substantially lower peak stormflows than observed, and the base and interflows increased accordingly. Both modeled and measured distributed results indicated that the more urbanized areas of the study site had both higher soil moistures and runoff losses due to shallower soils, greater upslope contributing areas, and a larger area of impervious surfaces generating runoff. The model results helped identify processes that describe how urbanization impacts integrated and distributed hydrology, which provides useful information for targeted water quality management.

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“…Details of the water balance components are presented in a companion to this paper (Gérard-Marchant et al, 2006). The model has been successfully applied to several New York and Pennsylvania watersheds (Frankenberger et al, 1999;Kuo et al, 1999;Johnson et al, 2003;Mehta et al, 2004;Srinivasan et al, 2005). The model is designed to simulate sloping areas, and does not work in flatter areas such as alluvial floodplains, nor does it account for infiltration excess runoff that can be produced on dry soils by brief, intense summer rainstorms.…”

Section: Introductionmentioning

confidence: 99%

Distributed hydrological modeling of total dissolved phosphorus transport in an agricultural landscape, part II: dissolved phosphorus transport

Hively

Gerard-Marchant

Steenhuis

2006

Hydrol. Earth Syst. Sci.

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Abstract. Reducing non-point source phosphorus (P) loss to drinking water reservoirs is a main concern for New York City watershed planners, and modeling of P transport can assist in the evaluation of agricultural effects on nutrient dynamics. A spatially distributed model of total dissolved phosphorus (TDP) loading was developed using raster maps covering a 164-ha dairy farm watershed. Transport of TDP was calculated separately for baseflow and for surface runoff from manure-covered and non-manure-covered areas. Soil test P, simulated rainfall application, and land use were used to predict concentrations of TDP in overland flow from non-manure covered areas. Concentrations in runoff for manure-covered areas were computed from predicted cumulative flow and elapsed time since manure application, using field-specific manure spreading data. Baseflow TDP was calibrated from observed concentrations using a temperaturedependent coefficient. An additional component estimated loading associated with manure deposition on impervious areas, such as barnyards and roadways. Daily baseflow and runoff volumes were predicted for each 10-m cell using the Soil Moisture Distribution and Routing Model (SMDR). For each cell, daily TDP loads were calculated as the product of predicted runoff and estimated TDP concentrations. Predicted loads agreed well with loads observed at the watershed outlet when hydrology was modeled accurately (R 2 79% winter, 87% summer). Lack of fit in early spring was attributed to difficulty in predicting snowmelt. Overall, runoff from non-manured areas appeared to be the dominant TDP loading source factor.

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Application of SMR to Modeling Watersheds in the Catskill Mountains

Cited by 58 publications

References 23 publications

Analyzing runoff processes through conceptual hydrological modeling in the Upper Blue Nile Basin, Ethiopia

Analyzing runoff processes through conceptual hydrological modeling in the Upper Blue Nile Basin, Ethiopia

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

Distributed hydrological modeling of total dissolved phosphorus transport in an agricultural landscape, part II: dissolved phosphorus transport

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