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Now showing items 1 - 16 of 16

  • Risk-based decision making to evaluate pollutant reduction scenarios

    Ahmadisharaf, Ebrahim   Benham, Brian L.  

    A total maximum daily load (TMDL) is required for water bodies in the U.S. that do not meet applicable water quality standards. Computational watershed models are often used to develop TMDL pollutant reduction scenarios. Uncertainty is inherent in the modeling process. An explicit uncertainty analysis would improve model performance and result in more robust decision making when comparing alternative pollutant reduction scenarios. This paper presents a risk-based framework for evaluating alternative pollutant allocation scenarios considering reliability in achieving water quality goals. We demonstrate a generic routine for the application of Generalized Likelihood Uncertainty Estimation (GLUE) to Hydrological Simulation Program-FORTRAN (HSPF) using existing softwares to evaluate two bacteria reduction scenarios from a recently developed TMDL that addressed a bacterial impairment in a mixed land use watershed in Virginia, U.S. Our probabilistic analysis showed that for reliability levels <25%, the recommended TMDL bacterial load reduction scenario had the same exceedance rate as the full reduction scenario (fully reducing all bacterial loads except wildlife), while for reliability levels between 25% and 50%, the exceedance rates for the two pollutant reduction scenarios were similar, with the TMDL recommended scenario violating the water quality criteria only slightly more often. The full reduction scenario performed better in higher reliability levels, although it could not meet the water quality criteria. Our results indicated that, in this case, achieving water quality goals with very high reliability was not possible, even with extreme levels of pollutant reduction. The risk-based framework presented here illustrates a method to propagate watershed model uncertainty and assess performance of alternative pollutant reduction scenarios using existing tools, thereby enabling decision makers to understand the reliability of a given scenario in achieving water quality goals. (C) 2019 The Author(s). Published by Elsevier B.V.
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  • Sustainability-Based Flood Hazard Mapping of the Swannanoa River Watershed

    Ahmadisharaf, Ebrahim   Kalyanapu, Alfred J.   Chung, Eun-Sung  

    An integrated framework is presented for sustainability-based flood hazard mapping of the Swannanoa River watershed in the state of North Carolina, U.S. The framework uses a hydrologic model for rainfall-runoff transformation, a two-dimensional unsteady hydraulic model flood simulation and a GIS-based multi-criteria decision-making technique for flood hazard mapping. Economic, social, and environmental flood hazards are taken into account. The importance of each hazard is quantified through a survey to the experts. Utilizing the proposed framework, sustainability-based flood hazard mapping is performed for the 100-year design event. As a result, the overall flood hazard is provided in each geographic location. The sensitivity of the overall hazard with respect to the weights of the three hazard components were also investigated. While the conventional flood management approach is to assess the environmental impacts of mitigation measures after a set of feasible options are selected, the presented framework incorporates the environmental impacts into the analysis concurrently with the economic and social influences. Thereby, it provides a more sustainable perspective of flood management and can greatly help the decision makers to make better-informed decisions by clearly understanding the impacts of flooding on economy, society and environment.
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  • Scale-dependent impacts of urban and agricultural land use on nutrients,sediment,and runoff

    Lacher, Iara L.   Ahmadisharaf, Ebrahim   Fergus, Craig   Akre, Thomas   Mcshea, William J.   Benham, Brian L.   Kline, Karen S.  

    We coupled a spatially-explicit land use/land cover (LULC) change model, Dinamica EGO, (Environment for Geoprocessing Objects), with the Chesapeake Bay Watershed Model (CBWM) to project the impact of future LULC change on loading of total nitrogen (TN), total phosphorous (TP) and total suspended solids (TSS) as well as runoff volume in the watersheds surrounding Virginia's Shenandoah National Park in the eastern United States. We allowed for the dynamic transition of four LULC classes, Developed, Forest, Grasses (including both pasture and hayfields) and Crops. Using 2011 as a baseline scenario and observed differences in LULC between 2001 and 2011, we estimated the temporal and spatial patterns of LULC change as influenced by physiographic and socio-economic drivers 50 years in the future (2061). Between transitions of the four LULC classes, the greatest absolute change occurred between the gain in total Developed land and loss in total Forest. New Developed land was driven primarily by distance to existing Developed land and population density. Major findings on the effect of LULC change on watershed model outputs were that: the impact of LULC change on pollutant loading and runoff volume is more pronounced at finer spatial scales; increases in the area of Grasses produced the greatest increase in TP loading, while loss of Forest increased TN, TSS, and runoff volume the most; and land-river segments with a greater proportion of Developed or a smaller proportion of Forest in the 2011 scenario experienced a greater change in runoff than other land-river segments. Results of this study illustrate the potential impact of projected LULC change on nutrient and sediment loads which can adversely impact water quality. Studies like this contribute to a broader understanding of how ecosystem services such as freshwater respond to LULC change, information relevant to those in planning and watershed management. (C) 2018 Published by Elsevier B.V.
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  • Spatial probabilistic multi-criteria decision making for assessment of flood management alternatives

    Ahmadisharaf, Ebrahim   Kalyanapu, Alfred J.   Chung, Eun-Sung  

    Flood management alternatives are often evaluated on the basis of flood parameters such as depth and velocity. As these parameters are uncertain, so is the evaluation of the alternatives. It is thus important to incorporate the uncertainty of flood parameters into the decision making frameworks. This research develops a spatial probabilistic multi-criteria decision making (SPMCDM) framework to demonstrate the impact of the design rainfall uncertainty on evaluation of flood management alternatives. The framework employs a probabilistic rainfall-runoff transformation model, a two-dimensional flood model and a spatial MCDM technique. Thereby, the uncertainty of decision making can be determined alongside the best alternative. A probability-based map is produced to show the discrete probability distribution function (PDF) of selecting each competing alternative. Overall the best at each grid cell is the alternative with the mode parameter of this PDF. This framework is demonstrated on the Swannanoa River watershed in North Carolina, USA and its results are compared to those of deterministic approach. While the deterministic framework fails to provide the uncertainty of selecting an alternative, the SPMCDM framework showed that in overall, selection of flood management alternatives in the watershed is "moderately uncertain". Moreover, three comparison metrics, F fit measure, kappa statistic, and Spearman rank correlation coefficient (rho), are computed to compare the results of these two approaches. An F fit measure of 62.6%, kappa statistic of 15.4-45.0%, and spatial mean rho value of 0.48, imply a significant difference in decision making by incorporating the design rainfall uncertainty through the presented SPMCDM framework. The SPMCDM framework can help decision makers to understand the uncertainty in selection of flood management alternatives. (C) 2015 Elsevier B.V. All rights reserved.
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  • Spatial probabilistic multi-criteria decision making for assessment of flood management alternatives

    Ahmadisharaf, Ebrahim   Kalyanapu, Alfred J.   Chung, Eun-Sung  

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  • Calibration and Validation of Watershed Models and Advances in Uncertainty Analysis in TMDL Studies

    Ahmadisharaf, Ebrahim   Camacho, Rene A.   Zhang, Harry X.   Hantush, Mohamed M.   Mohamoud, Yusuf M.  

    Watershed models are widely used in total maximum daily load (TMDL) studies to predict the impacts of pollutant discharges on the biochemical functioning and assimilative capacity of water bodies. The reliability of a TMDL is therefore tightly linked with the predictive capability of these models. While there has been an increasing availability and application of watershed models for TMDL studies, guidelines for model evaluation, including recommendations for an appropriate selection and implementation of calibration, validation, and uncertainty analysis strategies, remain at present limited. The ASCE Environmental and Water Resources Institute (EWRI) TMDL Analysis and Modeling Task Committee was established in part to identify existing and emerging challenges encountered by water resources professionals during any phase of a TMDL development and to produce documentation to address these challenges. This paper reviews existing approaches for model calibration, validation, and uncertainty analysis, including recommendations to establish baseline modeling practices to obtain a satisfactory watershed model.
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  • Calibration and Validation of Watershed Models and Advances in Uncertainty Analysis in TMDL Studies

    Ahmadisharaf, Ebrahim   Camacho, René A.   Zhang, Harry X.   Hantush, Mohamed M.   Mohamoud, Yusuf M.  

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  • Integrating flood hazard into site selection of detention basins using spatial multi-criteria decision-making

    Ahmadisharaf, Ebrahim   Tajrishy, Masoud   Alamdari, Nasrin  

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  • A Coupled Probabilistic Hydrologic/Hydraulic Modelling Framework to Investigate the Uncertainty of Flood Loss Estimates

    Ahmadisharaf, Ebrahim   Kalyanapu, Alfred J.  

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  • Two-Phase Monte Carlo Simulation for Partitioning the Effects of Epistemic and Aleatory Uncertainty in TMDL Modeling

    Mishra, Anurag   Ahmadisharaf, Ebrahim   Benham, Brian L.   Gallagher, Daniel L.   Reckhow, Kenneth H.   Smith, Eric P.  

    A two-phase Monte Carlo simulation (TPMCS) uncertainty analysis framework is used to analyze epistemic and aleatory uncertainty associated with simulated exceedances of an in-stream fecal coliform (FC) water quality criterion when using the Hydrological Simulation Program-FORTRAN (HSPF). The TPMCS framework is compared with a single-phase or standard Monte Carlo simulation (SPMCS) analysis. Both techniques are used to assess two total maximum daily load (TMDL) pollutant allocation scenarios. The application of TPMCS illustrates that cattle directly depositing FC in the stream is a greater source of epistemic uncertainty than FC loading from cropland overland runoff, the two sources specifically targeted for reduction in the allocation scenario. This distinction is not possible using SPMCS. Although applying the TPMCS framework involves subjective decisions about how selected model parameters are considered within the framework, this uncertainty analysis approach is transparent and the results provide information that can be used by decision makers when considering pollution control measure implementation alternatives, including quantifying the level of confidence in achieving applicable water quality standards.
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  • Two-Phase Monte Carlo Simulation for Partitioning the Effects of Epistemic and Aleatory Uncertainty in TMDL Modeling

    Mishra, Anurag   Ahmadisharaf, Ebrahim   Benham, Brian L.   Gallagher, Daniel L.   Reckhow, Kenneth H.   Smith, Eric P.  

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  • Generalized Likelihood Uncertainty Estimation and Markov Chain Monte Carlo Simulation to Prioritize TMDL Pollutant Allocations

    Mishra, Anurag   Ahmadisharaf, Ebrahim   Benham, Brian L.   Wolfe, Mary Leigh   Leman, Scotland C.   Gallagher, Daniel L.   Reckhow, Kenneth H.   Smith, Eric P.  

    This study presents a probabilistic framework that considers both the water quality improvement capability and reliability of alternative total maximum daily load (TMDL) pollutant allocations. Generalized likelihood uncertainty estimation and Markov chain Monte Carlo techniques were used to assess the relative uncertainty and reliability of two alternative TMDL pollutant allocations that were developed to address a fecal coliform (FC) bacteria impairment in a rural watershed in western Virginia. The allocation alternatives, developed using the Hydrological Simulation Program-FORTRAN, specified differing levels of FC bacteria reduction from different sources. While both allocations met the applicable water-quality criteria, the approved TMDL allocation called for less reduction in the FC source that produced the greatest uncertainty (cattle directly depositing feces in the stream), suggesting that it would be less reliable than the alternative, which called for a greater reduction from that same source. The approach presented in this paper illustrates a method to incorporate uncertainty assessment into TMDL development, thereby enabling stakeholders to engage in more informed decision making.
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  • A probabilistic framework for comparison of dam breach parameters and outflow hydrograph generated by different empirical prediction methods

    Ahmadisharaf, Ebrahim   Kalyanapu, Alfred J.   Thames, Brantley A.   Lillywhite, Jason  

    This study presents a probabilistic framework to simulate dam breach and evaluates the impact of using four empirical dam breach prediction methods on breach parameters (i.e., geometry and timing) and outflow hydrograph attributes (i.e., time to peak, hydrograph duration and peak). The methods that are assessed here include MacDonald and Langridge-Monopolis (1984), Von Thun and Gillette (1990), Froehlich (1995), 2008). Mean values and percentiles of breach parameters and outflow hydrograph attributes are compared for hypothetical overtopping failure of Burnett Dam in the state of North Carolina, USA. Furthermore, utilizing the probabilistic framework, the least and most uncertain methods alongside those giving the most critical value are identified for these parameters. The multivariate analysis also indicates that lone use of breach parameters is not necessarily sufficient to characterize outflow hydrograph attributes. However, timing characteristic of the breach is generally a more important driver than its geometric features. (C) 2016 Elsevier Ltd. All rights reserved.
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  • A probabilistic framework for comparison of dam breach parameters and outflow hydrograph generated by different empirical prediction methods

    Ahmadisharaf, Ebrahim   Kalyanapu, Alfred J.   Thames, Brantley A.   Lillywhite, Jason  

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  • Evaluating the Effects of Inundation Duration and Velocity on Selection of Flood Management Alternatives Using Multi-Criteria Decision Making

    Ahmadisharaf, Ebrahim   Kalyanapu, Alfred J.   Chung, Eun-Sung  

    Impacts of flood management alternatives are mostly assessed by inundation depth. Other inundation parameters such as velocity and duration are rarely taken into consideration. In this paper, a multi-criteria decision making (MCDM) based framework is used to analyze the effects of inundation velocity and duration on evaluation of flood management alternatives. The framework incorporates a two-dimensional (2D) flood model, Flood2D-GPU and a spatial MCDM (SMCDM) method, Spatial Compromise Programming (SCP). Flood2D-GPU is employed to simulate floods and SCP is applied to rank a set of flood management alternatives. Assessment of flood management options is conducted with multiple different weight set scenarios. First, alternatives are ranked without consideration of inundation velocity and duration. Then, the importance of these parameters increases and the alternatives are ordered in each weight set and a GIS map showing the best alternative in each grid cell is generated in each case. Best alternative maps (BAMs) are compared to investigate the impacts of inundation velocity and duration on selection of best strategy using F fit measure and κ analysis. The framework applicability is illustrated on the Swannanoa River watershed located in the state of North Carolina, US. Case study results indicate up to 49.7 % change of BAM by taking into account inundation velocity and duration. The presented approach addresses the change in selection of flood management strategies resulted by considering other inundation parameters rather than inundation depth. This can potentially reduce the uncertainties associated with the decisions made without consideration of inundation velocity and duration.
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  • Projecting land use change impacts on nutrients,sediment and runoff in multiple spatial scales:Business-as-usual vs. stakeholder-informed scenarios

    Ahmadisharaf, Ebrahim   Lacher, Iara L.   Fergus, Craig   Benham, Brian L.   Akre, Thomas   Kline, Karen S.  

    While the impact of land use/land cover (LULC) change on watersheds has been extensively studied, little attention has been given to the variability of this impact with respect to the projected LULC scenarios at a range of spatial scales. Here, a spatial LULC change model was coupled with the Chesapeake Bay Watershed Model to investigate LULC change impact on nutrients (nitrogen and phosphorous) and sediment loads and runoff volume in northwestern Virginia, U.S. Using 2011 as the baseline scenario, we examined four stakeholder-informed future (50 years hence) LULC scenarios, which differed in projection of population growth and planning strategy, along with a 'business-as-usual' (BAU) scenario, which projected historical LULC trends into the future. Four LULCs-Developed, Forest, Grasses and Crops-were dynamically transitioned. The difference in projected nutrient and sediment loads and runoff volume between the LULC scenarios was greater at finer spatial scales, where planning decisions are most commonly made. The LULC change scenario with reactive planning and high population growth resulted in the largest increase in runoff volume, while the scenario with reactive planning and low population growth showed the largest increase in modeled nutrient and sediment loads. These results suggested that planning strategy plays a more critical role than population growth in watershed management. (C) 2020 Elsevier Ltd. All rights reserved.
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