Uncertainty in TMDL Models

Shirmohammadi, Adel; Chaubey, Indrajeet; Bosch, David D.; Ga,; Muñoz‐Carpena, Rafael; Dharmasri, Cecil; Arabi, Mourad; Wolfe, Mary Leigh; Frankenberger, J. R.; Graff, C.; Sohrabi, Teymour

doi:10.13031/2013.20786

Cited by 29 publications

(40 citation statements)

References 0 publications

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“…In SUFI-2, during calibration, the user may specify the percentage error in the measured data, which is an independent error as it is a standard deviation added to the measured data. Here, we provided a 10% error for flow measured data and a 20% error for N and P related measurements (Harmel et al 2006).…”

Section: Swat Calibration and Quantification Of Modelling Uncertaintymentioning

confidence: 99%

“…Unfortunately, the uncertainty related to the simulated hydrological variables, especially water quality variables, when examining climate change impacts is not well known (Beven 2011), despite that some researchers (e.g. Sohrabi et al 2003;Shirmohammadi et al 2006) have advocated for quantifying this uncertainty, particularly for water quality simulations.…”

Section: Introductionmentioning

confidence: 99%

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Evaluating the Importance of Non-Unique Behavioural Parameter Sets on Surface Water Quality Variables under Climate Change Conditions in a Mesoscale Agricultural Watershed

Mehdi

Schulz

Ludwig

et al. 2017

Water Resour Manage

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The parameter uncertainty in the eco-hydrological model Soil and Water Assessment Tool (SWAT) was estimated using non-unique parameter sets for the Altmühl watershed (Bavaria, Germany). The Sequential Uncertainty Fitting Algorithm (SUFI-2) was used to calibrate SWAT. The non-unique parameter sets found were subsequently applied to SWAT concurrently with climate change simulations to determine the variables of streamflow, nitrate nitrogen (NO 3 − -N) and total phosphorus (TP). A suite of seven bias corrected climate change simulations provided reference and future climate data. The nonunique behavioural parameter sets that met an objective function of NSE >0.6 during calibration were applied to SWAT with the reference climate and with the future climate simulations. The best parameter set was also propagated through SWAT with each reference and future climate simulation in turn. Combining the non-unique behavioural parameter sets for estimating uncertainty bounds with an ensemble of climate change simulations led to a wider mean monthly spread (difference between maximum and minimum) of simulated NO 3 − -N and TP than using the best run with the future climate simulations. More monthly data was considered using the non-unique approach, resulting in statistical significances for more Water Resour Manage (2018) months of the year and overall lower interquartile ranges. The study quantifies the non-unique behavioural parameter set contributions to the modelling prediction, which assists in making more informed decisions based on available knowledge, with its limitations, of the future simulations. We outline a simple approach that can easily be replicated for similar hydrological modelling studies.

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Section: Swat Calibration and Quantification Of Modelling Uncertaintymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Evaluating the Importance of Non-Unique Behavioural Parameter Sets on Surface Water Quality Variables under Climate Change Conditions in a Mesoscale Agricultural Watershed

Mehdi

Schulz

Ludwig

et al. 2017

Water Resour Manage

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“…Accurately predicting MPN-or CFU-based standard violations from FIB loading levels should therefore involve explicit acknowledgment of how a model-predicted receiving water concentration translates into an MPN or CFU value, and then how frequently those MPN and CFU values violate standards (5,14). A review of current modeling practice, however, indicates that such an approach is seldom, if ever, implemented.…”

Section: Introductionmentioning

confidence: 99%

“…Despite a growing body of research on the role of models and model uncertainty in water resources management (7,14,24), we know of no water quality models which explicitly acknowledge how natural variability in FIB concentrations, combined with intrinsic analytic uncertainty, propagates into MPN-or CFU-based water quality standard violations and associated management decisions. The following section describes our attempt to fill this gap.…”

Section: Introductionmentioning

confidence: 99%

An Assessment of Fecal Indicator Bacteria-Based Water Quality Standards

Gronewold

Borsuk

Wolpert

et al. 2008

Environ. Sci. Technol.

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Fecal indicator bacteria (FIB) are commonly used to assess the threat of pathogen contamination in coastal and inland waters. Unlike most measures of pollutant levels however, FIB concentration metrics, such as most probable number (MPN) and colony-forming units (CFU), are not direct measures of the true in situ concentration distribution. Therefore, there is the potential for inconsistencies among model and sample-based water quality assessments, such as those used in the Total Maximum Daily Load (TMDL) program. To address this problem, we present an innovative approach to assessing pathogen contamination based on water quality standards that impose limits on parameters of the actual underlying FIB concentration distribution, rather than on MPN or CFU values. Such concentration-based standards link more explicitly to human health considerations, are independent of the analytical procedures employed, and are consistent with the outcomes of most predictive water quality models. We demonstrate how compliance with concentration-based standards can be inferred from traditional MPN values using a Bayesian inference procedure. This methodology, applicable to a wide range of FIB-based water quality assessments, is illustrated here using fecal coliform data from shellfish harvesting waters in the Newport River Estuary, North Carolina. Results indicate that areas determined to be compliant according to the current methods-based standards may actually have an unacceptably high probability of being in violation of concentration-based standards.

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“…The risk of model error thus rises with the increasing degree of uncertainty associated with the inaccurate input parameters. Therefore, incorporating uncertainty analysis due to variability in model's input parameter values has gained increasing research importance in assessing model capabilities [2].…”

Section: Introductionmentioning

confidence: 99%

BMP Evaluation for Nutrient Control in a Subtropical Reservoir Watershed Using SWAT Model

Chu¹,

Shirmohammadi²,

Lin³

et al. 2013

Proceedings of the 2013 International Conference on Remote Sensing,Environment and Transportation Engineering

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Abstract-The eutrophication problem that results from the inappropriate management in upstream watershed is prevailing among most reservoirs in Taiwan. As a result, implementation of appropriate Best Management Practices (BMPs) in upland watershed has proved to be the most effective measure to reduce or alleviate the nutrient loadings and the risk of eutrophication. This study aims to employ the uncertainty analysis and risk probability on SWAT (Soil and Water Assessment Tool) simulation for assessing the effectiveness of various BMP scenarios implemented in Feitsui reservoir watershed. The SWAT model was applied to assess the water quality impacts due to the implementation of various BMP scenarios. Five BMPs were selected and implemented on each agricultural land for overall evaluation of pollution reduction efficiency both at field and watershed scales. Finally, the effects of uncertainty in model input parameters on pollution reduction efficiency of BMPs are evaluated using constrained Monte Carlo simulation based on Latin hypercube sampling (LHS) and Orthogonal sampling (OS) schemes. Moreover, the Cumulative Distribution Functions (CDF) of average annual TP and chlorophyll a concentrations were created for further assessment on eutrophication risk. The simulation results show that the reduction of eutrophication risk approaches 13% (from 15 to 2%) for Caelson Trophic Satus Index (CTSI) methods based on implementation of 5 BMPs (a combined BMP scenario). Overall, this study concludes that incooperating uncertainty analysis in modeling will provide model output with specific probability, which not only assists the decision-maker in developing BMP and TMDL plans but also assesses the reliability of NPS pollution control strategies and risk of water quality degradation.

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Uncertainty in TMDL Models

Cited by 29 publications

References 0 publications

Evaluating the Importance of Non-Unique Behavioural Parameter Sets on Surface Water Quality Variables under Climate Change Conditions in a Mesoscale Agricultural Watershed

Evaluating the Importance of Non-Unique Behavioural Parameter Sets on Surface Water Quality Variables under Climate Change Conditions in a Mesoscale Agricultural Watershed

An Assessment of Fecal Indicator Bacteria-Based Water Quality Standards

BMP Evaluation for Nutrient Control in a Subtropical Reservoir Watershed Using SWAT Model

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