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Watershed Analysis Risk Management Framework (WARMF) is a comprehensive watershed model and decision support system designed for stakeholders to formulate alternatives for point and nonpoint source pollution controls, evaluate their technical ability to meet water quality criteria, and make changes to negotiate the preferred plan. WARMF uses physically based model input parameters to describe the watershed. Many of these are known from data or watershed-specific studies, but others are determined through the calibration process. The model calibration is performed by systematically adjusting model input parameters within their normal ranges to match the simulated results to the observed data. The GUI enables users to make changes to model input parameters and/or data and graphically compare the simulated results and observed data. WARMF calculates correlation coefficient, relative error, absolute error, cumulative volume balance, and other measures to evaluate the calibration quantitatively. Relative error and absolute error are the preferred measures of accuracy and precision used in WARMF calibration. Long-term observed data may be split into two periods, one for model calibration and the other for validation. New data may also be collected for model validation. A case study is presented to demonstrate the calibration of flow and electrical conductivity (EC) for the San Joaquin River watershed in California. Soil properties were adjusted so the simulated flow would match the measured flow data during both the winter rainy season and summer irrigation season. Soil chemistry inputs were calibrated to ensure long-term stability of pore water concentrations and so the simulated water quality of the San Joaquin River followed the magnitude and pattern of in-stream monitoring data. The simulation of flow produced a 1% relative error and 13% absolute error over the eight-year calibration period. The EC calibration had relative error of 5% and absolute error of 15%. [ABSTRACT FROM AUTHOR]

Herr, Joel W., Krish Vijayaraghavan, and Eladio Knipping, 2010. Comparison of Measured and MM5 Modeled Meteorology Data for Simulating Flow in a Mountain Watershed. Journal of the American Water Resources Association (JAWRA) 46(6):1255-1263. DOI: 10.1111/j.1752-1688.2010.00489.x Accurate simulation of time-varying flow in a river system depends on the quality of meteorology inputs. The density of meteorology measurement stations can be insufficient to capture spatial heterogeneity of precipitation, especially in mountainous areas. The Watershed Analysis Risk Management Framework (WARMF) model was applied to the Catawba River watershed of North and South Carolina to simulate flow and water quality in rivers and a series of 11 reservoirs. WARMF was linked with the AMSTERDAM air model to analyze the water quality benefit from reduced atmospheric emissions. The linkage requires accurate simulation of meteorology for all seasons and for all types of precipitation events. WARMF was driven by the mesoscale meteorology model MM5 processed by the Meteorology Chemistry Interface Processor, which provides greater spatial density but less accuracy than meteorology stations. WARMF was also run with measured data from the National Climatic Data Center (NCDC) to compare the performance of the watershed model using measured data vs. modeled meteorology as input. A one year simulation using MM5 modeled meteorology performed better overall than the simulation using NCDC data for the volumetric water balance measure used for calibration, but MM5 represented precipitation from a dissipated hurricane poorly, which propagated into errors of simulated flow. [ABSTRACT FROM AUTHOR]

The watershed analysis risk management framework (WARMF) model was applied to Wetland S6 of the Marcell Experimental Forest, using the data from a field experiment, conducted to investigate the effect of sulfate additions on mercury methylation in the wetland. The wetland was modeled as interconnected land catchments. Actual meteorology data and mercury and sulfate concentrations of precipitation were input to the model. To simulate the sulfate sprinkling, the experimental section of the bog was irrigated with sulfate water on the actual dates of sulfate additions. The model simulated wetland outflows that matched the measured outflows with an R-square of 0.856. WARMF also simulated other phenomena observed in the experiment: higher sulfate and MeHg levels at the wetland outlet after every sulfate addition, and higher sulfate and MeHg levels in the pore water of the bog after only the May addition, not the July and September additions. According to WARMF, the low groundwater table in May allowed the sprinkled sulfate to percolate to the soil stratum 10–30 cm below the ground level of the bog, where the pore water was sampled. In July and September, the sulfate could not reach that zone because the percolation was blocked by high groundwater tables. The sampled soil stratum was not the site of methylation that contributed MeHg to the wetland outlet. The saturated zone of the top 10 cm of bog was the site that produced MeHg, which was flushed to the outlet after all sulfate additions. WARMF predicted that quadrupling the sulfate deposition would increase the MeHg output by 216%, which might become lower with more data and better model calibration. [ABSTRACT FROM AUTHOR]

The Watershed Analysis Risk Management Framework watershed model was enhanced to simulate the transport and fate of mercury and to calculate the fish mercury concentrations (FMC) attained by fish through the food web. The model was applied to Western Lake Superior Basin of Minnesota, which has many peat lands and lakes. Topographic, land use, and soil data were used to set up the model. Meteorology and precipitation chemistry data from nearby monitoring stations were compiled to drive the model. Simulated flow and mercury concentrations for several stream stations were comparable to available data. The model was used to perform mercury total maximum daily load calculations for two contrasting drainage lakes (Wild Rice Lake and Whiteface Reservoir). The model results for wet deposition, dry deposition, evasion, watershed yield, and soil sequestration of mercury were comparable with available actual data. The model predicted lake ice cover from November to April and weak stratification in summer, typical of shallow lakes in cold regions. The simulated sulfate decrease and methylmercury increase near the lake bottom in late summer are caused by sulfate reduction and mercury methylation that occur in the surficial sediment. Simulated FMC were within the range of observed values and the R2 of correlation between the simulated and observed FMC was 0.77. Under the 1989-2004 base condition, the average simulated FMC of four-year-old walleye was 0.31 μg/g for Whiteface Reservoir and 0.15 μg/g for Wild Rice Lake. The FMC criterion in Minnesota is 0.2 μg/g. Wild Rice Lake already meets this criterion without any load reduction. The model showed that a 65% reduction in atmospheric mercury deposition will not, by itself, allow Whiteface Reservoir to meet the criterion in 15 years. Additional best management practices will be needed to reduce 50% of the watershed input. [ABSTRACT FROM AUTHOR]

Presents information on a study that enhanced an existing watershed model to simulate acid mine drainage as nonpoint source load. Methodology of the study; Results and discussion on the study; Conclusions.