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Herr J.W.,Systech Water Resources Inc. | Vijayaraghavan K.,Environmental | Knipping E.,EPRI
Journal of the American Water Resources Association | Year: 2010

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. © 2010 American Water Resources Association.

Singh R.,Pennsylvania State University | Wagener T.,Pennsylvania State University | Van Werkhoven K.,Systech Water Resources Inc. | Mann M.E.,Pennsylvania State University | Crane R.,Pennsylvania State University
Hydrology and Earth System Sciences | Year: 2011

Projecting how future climatic change might impact streamflow is an important challenge for hydrologic science. The common approach to solve this problem is by forcing a hydrologic model, calibrated on historical data or using a priori parameter estimates, with future scenarios of precipitation and temperature. However, several recent studies suggest that the climatic regime of the calibration period is reflected in the resulting parameter estimates and model performance can be negatively impacted if the climate for which projections are made is significantly different from that during calibration. So how can we calibrate a hydrologic model for historically unobserved climatic conditions? To address this issue, we propose a new trading-space-for-time framework that utilizes the similarity between the predictions under change (PUC) and predictions in ungauged basins (PUB) problems. In this new framework we first regionalize climate dependent streamflow characteristics using 394 US watersheds. We then assume that this spatial relationship between climate and streamflow characteristics is similar to the one we would observe between climate and streamflow over long time periods at a single location. This assumption is what we refer to as trading-space-for-time. Therefore, we change the limits for extrapolation to future climatic situations from the restricted locally observed historical variability to the variability observed across all watersheds used to derive the regression relationships. A typical watershed model is subsequently calibrated (conditioned) on the predicted signatures for any future climate scenario to account for the impact of climate on model parameters within a Bayesian framework. As a result, we can obtain ensemble predictions of continuous streamflow at both gauged and ungauged locations. The new method is tested in five US watersheds located in historically different climates using synthetic climate scenarios generated by increasing mean temperature by up to 8 °C and changing mean precipitation by-30% to +40% from their historical values. Depending on the aridity of the watershed, streamflow projections using adjusted parameters became significantly different from those using historically calibrated parameters if precipitation change exceeded-10% or +20%. In general, the trading-space-for-time approach resulted in a stronger watershed response to climate change for both high and low flow conditions. © 2011 Author(s).

Camarillo M.K.,Pacific University in Oregon | Weissmann G.A.,Pacific University in Oregon | Gulati S.,Pacific University in Oregon | Herr J.,Systech Water Resources Inc. | And 3 more authors.
Environmental Monitoring and Assessment | Year: 2016

High-frequency data and a link-node model were used to investigate the relative importance of mass loads of oxygen-demanding substances and channel geometry on recurrent low dissolved oxygen (DO) in the San Joaquin River Estuary in California. The model was calibrated using 6 years of data. The calibrated model was then used to determine the significance of the following factors on low DO: excavation of the river to allow navigation of large vessels, non-point source pollution from the agricultural watershed, effluent from a wastewater treatment plant, and non-point source pollution from an urban area. An alternative metric for low DO, excess net oxygen demand (ENOD), was applied to better characterize DO impairment. Model results indicate that the dredged ship channel had the most significant effect on DO (62 % fewer predicted hourly DO violations), followed by mass load inputs from the watershed (52 % fewer predicted hourly DO violations). Model results suggest that elimination of any one factor will not completely resolve DO impairment and that continued use of supplemental aeration is warranted. Calculation of ENOD proved more informative than the sole use of DO. Application of the simple model allowed for interpretation of the extensive data collected. The current monitoring program could be enhanced by additional monitoring stations that would provide better volumetric estimates of low DO. © 2016, Springer International Publishing Switzerland.

Chen C.W.,Emeritus Systech Engineering Inc. | Herr J.W.,Systech Water Resources Inc.
Journal of Environmental Engineering | Year: 2010

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. © 2010 ASCE.

Herr J.W.,Systech Water Resources Inc. | Chen C.W.,Systech Water Resources Inc.
Transactions of the ASABE | Year: 2012

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%. © 2012 American Society of Agricultural and Biological Engineers.

Singh R.,Pennsylvania State University | van Werkhoven K.,Systech Water Resources Inc. | Wagener T.,Pennsylvania State University | Wagener T.,University of Bristol
Hydrological Sciences Journal | Year: 2014

Robust projections of climate change impacts on regional hydrology are crucial for water resources management, especially in data-sparse regions. Impact projections have to: (a) be available at gauged and ungauged locations; (b) consider changes in watershed behaviour for different future climates and land uses; and (c) include estimates of uncertainty. We apply a novel water resources modelling framework which combines signature regionalization with the trading of space for time to obtain hydrological projections in ungauged basins and under climate change for the Olifants basin in southern Africa, a UNESCO HELP basin. We find that using statistically downscaled general circulation model (GCM) vs observed climate data leads to only slight deterioration in reliability of runoff projections for the historical period. The framework projects a decrease in regional runoff by -8.7% and -3.9% for A2 and B1 scenarios, respectively, by the end of the century, with, 80% and 67% of GCMs agreeing on the decrease in runoff, respectively. © 2013 IAHS Press.

Strinqfellow W.T.,Pacific University in Oregon | Strinqfellow W.T.,Lawrence Berkeley National Laboratory | Herr J.,Systech Water Resources Inc. | Sheeder S.,Systech Water Resources Inc. | And 4 more authors.
Proceedings - 7th International Congress on Environmental Modelling and Software: Bold Visions for Environmental Modeling, iEMSs 2014 | Year: 2014

Eutrophication of the San Joaquin River (SJR) has resulted in low dissolved oxygen (DO) conditions, which has led to a regulatory response and development of total maximum daily load (TMDL) allocations. Due to the dynamic nature of processes governing oxygen depletion in the SJR, a model was needed to help stakeholders understand the fate and transport of nutrients and oxygen-demanding substances that cause the low DO conditions. Here, the Watershed Analysis Risk Management Framework (WARMF) model was used to simulate nutrient removal and control strategies, accounting for the secondary effects of growth and transformation between sources and discharge. Using the management alternatives in the WARMF Consensus Module, simulations were run to test the global removal of nutrient inputs on downstream phytoplankton growth, a major contributor of oxygen demand in the SJR. In the simulations, removal of ammonia had the greatest impact on downstream phytoplankton, causing a 32% reduction, while removal of phosphate and nitrate caused reductions of 25% and 13%, respectively. When ammonia and nitrate were both removed, phytoplankton reduction was 62%. These model results suggest that nitrogen control programs would be more effective than phosphorus programs. Using the Data Module in WARMF, input files were modified to determine the impacts of individual tributaries and agricultural drainages. In each simulation, the contributing loads for individual inputs were removed while maintaining flow. According to the model output, the largest impact on phytoplankton occurred with the removal of mass loads from Salt Slough (32% less than baseline). The effect of removing the mass loads from Mud Slough had a slightly lower impact (26% less than baseline). The WARMF model proved useful for exploration of planning and management alternatives, providing an expert decision-making tool that is available to stakeholders.

Camarillo M.K.,Pacific University in Oregon | Stringfellow W.,Pacific University in Oregon | Stringfellow W.,Lawrence Berkeley National Laboratory | Herr J.,Systech Water Resources Inc. | And 4 more authors.
Proceedings - 7th International Congress on Environmental Modelling and Software: Bold Visions for Environmental Modeling, iEMSs 2014 | Year: 2014

A one-dimensional link-node model was used to simulate water quality conditions in the tidally-influenced, deep water ship channel (DWSC) of the San Joaquin River located in Central California. The DWSC has been plagued with low dissolved oxygen (DO) conditions for decades and is currently a focus of restoration efforts. The model was calibrated using a six-year flow and water quality data set. Model simulations were run by removing the mass loads of each of the following major sources of oxygen depletion to determine the effects: elimination of the deepened ship channel (i.e., restore to its preexisting depth), elimination of import of oxygen-demanding substances (ODS) from the San Joaquin River watershed, elimination of import of ODS from the urban tributaries, and elimination of discharge of ODS from the City of Stockton regional wastewater control facility. The model results suggest that elimination of the deepened ship channel resulted in the best projected improvement relative to the modelled baseline with a predicted 55% improvement, while reducing ODS from the watershed would likely cause a 44% improvement. These results demonstrate that there are multiple contributing factors causing low DO in the DWSC and that removal or elimination of any single variable will not result in a complete resolution of low DO events.

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