Nonpoint Source Water Quality Research Articles

Identification of agricultural surface source pollution in plain river network areas based on 3D-EEMs and convolutional neural networks.

Agricultural non-point sources, as major sources of organic pollution, continue to flow into the river network area of the Jiangnan Plain, posing a serious threat to the quality of water bodies, the ecological environment, and human health. Therefore, there is an urgent need for a method that can accurately identify various types of agricultural organic pollution to prevent the water ecosystems in the region from significant organic pollution. In this study, a network model called RA-GoogLeNet is proposed for accurately identifying agricultural organic pollution in the river network area of the Jiangnan Plain. RA-GoogLeNet uses fluorescence spectral data of agricultural non-point source water quality in Changzhou Changdang Lake Basin, based on GoogLeNet architecture, and adds an efficient channel attention (ECA) mechanism to its A-Inception module, which enables the model to automatically learn the importance of independent channel features. ResNet are used to connect each A-Reception module. The experimental results show that RA-GoogLeNet performs well in fluorescence spectral classification of water quality, with an accuracy of 96.3%, which is 1.2% higher than the baseline model, and has good recall and F1 score. This study provides powerful technical support for the traceability of agricultural organic pollution.

Assessing and improving the outcomes of nonpoint source water quality trading policies in urban areas: A case study in Virginia

Nonpoint source (NPS) water quality trading (WQT) is a market-based approach to improving water quality. Past work has shown that these programs could increase localized pollutant loadings, in part by exporting water quality controls from urban to rural areas. Virginia's NPS WQT program has enabled thousands of transactions and may provide a model for other programs, but its impacts on urban water quality have not been thoroughly assessed. We quantify the impact of NPS WQT purchases in Virginia on water quality and hydrology in an urban catchment. We go on to assess outcomes of a policy alternative where buyers and sellers are collocated in the urban catchment. Simulation results show that NPS WQT increased total phosphorus (TP) loading by an average of 0.8 lbs TP/year for each 1.0 offsite credits purchased in the analyzed catchment. The TP loading increased in years with greater rainfall, such that TP loads were increased by up to 1.2 lbs TP/year for each offsite credit purchased. These loading increases may or may not be acceptable, depending on the cumulative number of purchases within an urban catchment and existing local water quality issues. In our policy alternative with buyers and sellers collocated in the catchment, we found that the TP increase from development was completely offset at the catchment scale, with a decrease of 4.3 lbs TP/year for each 1.0 credits purchased. This suggests that credits awarded for urban mitigation practices are undervalued compared with water quality requirements for credit purchasers. This undervaluation is a result of the Virginia trading program using one approach to compute the credit value for buyers and a different approach to compute the credit value for sellers. We demonstrate how using a single model to determine both buyer and seller credit values in urban areas could provide greater transparency and mitigate the risk of urban pollution hot spots. This work demonstrates the importance of consistency in the scale of pollutant load calculations between buyers and sellers for NPS WQT, and contributes novel insight into the implications of WQT for urban NPS pollution.

Inexact fuzzy-flexible left-hand-side chance-constrained programming for agricultural nonpoint-source water quality management

In this study, an inexact fuzzy-flexible left-hand-side chance-constrained programming (IFLCCP) method is proposed for optimizing an agricultural nonpoint-source water quality management problem under uncertainty. The developed method can address complex uncertainties resulted from system fuzzy flexible under various level of decision-making requirements and randomness parameters appeared on the left-hand side of the constraints, and deal with the conflict between water quality protection and agricultural system economic development. The IFLCCP model is formulated through incorporating inexact left-hand-sided chance-constrained programming into interval fuzzy flexible programming framework. The decision schemes obtained by the IFLCCP are analyzed under scenarios at different confidence level of environmental constraint. The results demonstrate that the scale of crop planting and breeding industries reduces as the confidence coefficient of environmental constraint (1-pi) increases, in order to satisfy pollutant discharge constraints, which results in the reduction of the system net benefit from scenarios 1 to 3. Meanwhile, the interval control variables λ± are introduced for quantifying the degrees of overall satisfaction for the objective function and the constraints, which get optimal adjustment to guarantee the net benefit to be as close as possible to the upper bound. The IFLCCP is able to provide management schemes with high system benefits under different levels of acceptable environmental risk, taking full consideration of decision makers' environmental management requirements. This study is a new application of the IFLCCP model to agricultural water quality management problem, demonstrating its applicability to practical environmental problems with high complexity and uncertainty.

Nonpoint Source Water Quality Trading outcomes: Landscape-scale patterns and integration with watershed management priorities

Nonpoint source (NPS) water quality trading (WQT) has been lauded as a way to reduce water pollution while mitigating costs, but NPS WQT programs often do not account for cumulative landscape-scale impacts to hydrological and ecological processes. In this work, we parameterize the landscape-scale patterns of an emerging NPS WQT market in Virginia (n = 606 transactions) and describe potential tradeoffs and synergies. We also examine program outcomes in the context of Virginia's spatially-explicit conservation and restoration priorities, and discuss ways in which NPS WQT integrates or fails to integrate with these state-level watershed management goals. These spatial and policy analyses demonstrate novel ways to evaluate NPS WQT programs. Our results reveal how NPS WQT has influenced Virginia land management patterns in practice. Specifically, we show that this program has encouraged the transfer of water quality Best Management Practices (BMPs) from urban to rural areas. Impact sites are often far from mitigation sites, at an average of 164.6 km apart measured along the stream network and most often migrated outside the 8-digit Hydrologic Unit Code watershed boundaries. We also find opportunity for improved integration with the state-level management priorities, including that an estimated 22% of the NPS WQT mitigation site area works against state priorities (for example by converting prime farmland to forest), 9% supports state priorities, and 69% neither negates nor supports state priorities. We suggest policy and management actions that can increase the integration of NPS WQT with statewide watershed management goals, and could ultimately improve environmental returns from this fast-growing program.

A Multiarmed Bandit Approach to Adaptive Water Quality Management.

ABSTRACTNonpoint source water quality management is challenged with allocating uncertain management actions and monitoring their performance in the absence of state‐dependent decision making. This adaptive management context can be expressed as a multiarmed bandit problem. Multiarmed bandit strategies attempt to balance the exploitation of actions that appear to maximize performance with the exploration of uncertain, but potentially better, actions. We performed a test of multiarmed bandit strategies to inform adaptive water quality management in Massachusetts, USA. Conservation and restoration practitioners were tasked with allocating household wastewater treatments to minimize N inputs to impaired waters. We obtained time series of N monitoring data from 3 wastewater treatment types and organized them chronologically and randomly. The chronological data set represented nonstationary performance based on recent monitoring data, whereas the random data set represented stationary performance. We tested 2 multiarmed bandit strategies in hypothetical experiments to sample from the treatment data through 20 sequential decisions. A deterministic probability‐matching strategy allocated treatments with the highest probability of success regarding their performance at each decision. A randomized probability‐matching strategy randomly allocated treatments according to their probability of success at each decision. The strategies were compared with a nonadaptive strategy that equally allocated treatments at each decision. Results indicated that equal allocation is useful for learning in nonstationary situations but tended to overexplore inferior treatments and thus did not maximize performance when compared with the other strategies. Deterministic probability matching maximized performance in many stationary situations, but the strategy did not adequately explore treatments and converged on inferior treatments in nonstationary situations. Randomized probability matching balanced performance and learning in stationary situations, but the strategy could converge on inferior treatments in nonstationary situations. These findings provide evidence that probability‐matching strategies are useful for adaptive management. Integr Environ Assess Manag 2020;16:841–852. © 2020 The Authors. Integrated Environmental Assessment and Management published by Wiley Periodicals LLC on behalf of Society of Environmental Toxicology & Chemistry (SETAC)

Planning for water quality in OH: What role(s) for planners?

The Clean Water Act of 1972 requires states to develop total maximum daily loads (TMDLs) for surface waters not expected to comply with water quality standards after controls have been put in place to address point sources of pollution, typically from business and industry. These TMDLs have gained attention as nonpoint sources of water pollution are increasingly recognized as intractable challenge by localities and their states (Hoornbeek et al., 2013). Planning at a watershed geographic scale has been promoted by the U.S. EPA to address both the scientific and community based challenges faced in addressing TMDL levels. Studies have focused on the breadth of watershed groups participation, on watershed group membership typologies, on watershed plan development, as well as on implementation of plan recommendations (see, e.g., Hardy and Koontz, 2008; Koontz and Johnson, 2004; Hoornbeek et al., 2013). However, the role these planning efforts play within community based comprehensive planning, as well as the inclusion of planners in the watershed planning efforts, remains unclear.This paper uses the state of Ohio as a case study to explore the role of planning and planners with respect to nonpoint source water quality mitigation, specifically related to the Section 319 grant related funding, through watershed planning efforts. Section 319 directed watershed planning are focused on TMDL guidelines to combat nonpoint source pollution levels. Addressing water quality at the watershed planning level in Ohio is a multidimensional and complex process involving multiple stakeholders at every level of government, public and private planning entities, as well as educational institutions and the nonprofit sector. There have been at least eight watershed related planning processes in the state since the start of this century, including Section 319 and the Balanced Growth Program which also requires a watershed based plan.This paper examines interview data with state level watershed entities and survey data from Ohio planners. These sources provide insight into state watershed action plan processes and the involvement of planners in water quality protection in general and watershed level planning activities in particular. The paper begins with a discussion of the complex watershed planning setting in Ohio. It moves into the results of the survey and interviews to understand the role of planners in this environment. The paper concludes with an assessment of the potential policy implications of the results and directions for future research. The results of this paper are important to ongoing efforts to improve and protect surface water quality in the U.S.

Evaluating the risk of phosphorus loss with a distributed watershed model featuring zero-order mobilization and first-order delivery

Many semi-distributed models that simulate pollutants' losses from watersheds do not handle well detailed spatially distributed and temporal data with which to identify accurate and cost-effective strategies for controlling pollutants issuing from non-point sources. Such models commonly overlook the flow pathways of pollutants across the landscape. This work aims at closing such knowledge gap by developing a Spatially and Temporally Distributed Empirical model for Phosphorus Management (STEM-P) that simulates the daily phosphorus loss from source areas to receiving waters on a spatially-distributed grid-cell basis. STEM-P bypasses the use of complex mechanistic algorithms by representing the phosphorus mobilization and delivery processes with zero-order mobilization and first-order delivery, respectively. STEM-P was applied to a 217km2 watershed with mixed forest and agricultural land uses situated in southwestern China. The STEM-P simulation of phosphorus concentration at the watershed outlet approximated the observed data closely: the percent bias (Pbias) was −7.1%, with a Nash-Sutcliffe coefficient (ENS) of 0.80 on a monthly scale for the calibration period. The Pbias was 18.1%, with a monthly ENS equal to 0.72 for validation. The simulation results showed that 76% of the phosphorus load was transported with surface runoff, 25.2% of which came from 3.4% of the watershed area (classified as standard A critical source areas), and 55.3% of which originated from 17.1% of the watershed area (classified as standard B critical source areas). The standard A critical source areas were composed of 51% residences, 27% orchards, 18% dry fields, and 4% paddy fields. The standard B critical source areas were mainly paddy fields (81%). The calculated spatial and temporal patterns of phosphorus loss and recorded flow pathways identified with the STEM-P simulations revealed the field-scale critical source areas and guides the design and placement of effective practices for non-point source pollution control and water quality conservation.

Sedimentation in a small lake following conversion of bottomland forest to row cropping

Areas of native bottomland hardwood forest in the lower Red River basin in Louisiana were cleared for row cropping around 1970. Erosion and sediment deposition in channels and lakes presumably increased, affecting hydrologic connectivity and lake ecosystems. Sediment deposited in a representative small lake after land conversion was determined in 2000 from the distribution of cesium (137Cs) with depth. Sediment consisted of low-density clay deposited above dense silt loam. Organic carbon (C) and 137Cs profiles had lower and upper concentration maxima. The lower maxima established the circa 1970 lakebed at ≤0.9 m (3 ft) above the morphological discontinuity and from 2.1 to 1.3 m (6.9 to 4.3 ft) below the 2000 lakebed at positions midlake and halfway to the bank, respectively. The upper maxima were likely due to progressive land conversion around the lake, coupled with increasing clay content of sediment upwards to the 2000 lakebed. A quiescent settling model was used to estimate the composition of runoff water necessary to produce the depth, texture, and density of sediment above the lower 137Cs maxima. The Annualized Agricultural Nonpoint Source water quality model was calibrated to match this composition, and sediment accumulation under alternative management scenarios was calculated. Compared to conventional-till (CT) soybeans (Glycine max L.) for 30 years, CT with cover crop (CC), no-till (NT), NT with CC management, and forest might have reduced sedimentation in the lake by about 20%, 40%, 60%, and 98%, slowing changes in light penetration, temperature, turbidity, and chemistry that affect the lake ecosystem.

Assessing a fuzzy model and HSPF to supplement rainfall data for nonpoint source water quality in the Feitsui reservoir watershed

The objective of this study was to improve the use of a fuzzy model to supplement rainfall data when the watershed's meteorological station is either far away or suffers a loss of rainfall data. The fuzzy model can also supplement rainfall data when the station is nearby. The accuracy of rainfall data in the EPA's (Environmental Protection Agency) BASINS (Better Assessment Science Integrating Point and Nonpoint Sources) decision support tool is affected by the sparse meteorological data contained in BASINS. This study also assessed the improvement in stream flow prediction with the Hydrological Simulation Program-FORTRAN (HSPF) model contained within BASINS, using the hourly precipitation estimates for the Feitsui reservoir watershed. This study demonstrates that using a fuzzy model to supplement rainfall data has the potential to improve stream flow predictions, thus aiding water quality assessment in the nonpoint water quality assessment decision tool.

Nonpoint-Source Water Quality Management Under Uncertainty Through an Inexact Double-Sided Chance-Constrained Model

This study proposed an inexact double-hand-side chance-constrained programming (IDCCP) method for nonpoint-source water quality management within an agricultural system. The IDCCP model can express interval parameters and double-hand-side random variables (e.g. nitrogen requirement of crop and nitrogen content of manure) simultaneously. To handle the double-sided random variables, a linear form of sufficient conditions for the IDCCP was deduced and proved. The performance of IDCCP was testified in the water quality management study case at three individual probabilities (θi = 0.1, 0.05 and 0.01), and compared with the corresponding ILP model. The results demonstrated that, the net benefit of the agriculture system decrease with a decreasing violating probability (θi), an increasing satisfaction of constraint (1-θi), or a lower risk of the system. Although it is the first application of the IDCCP method to nonpoint-resource water quality management, the IDCCP could also be applied to other environmental issues under such uncertainties.

Inexact Left-Hand-Side Chance-Constrained Programming for Nonpoint-Source Water Quality Management

An inexact left-hand-side chance-constrained programming (ILCCP) was proposed and applied to a nonpoint-source water quality management problem within an agricultural system. The ILCCP model can reflect uncertainties presented as interval parameters (manure mass balance, crop nutrient balances, energy and digestible protein requirements, pollutant losses, water quantity constraints, technical constraints, and so on) and left-hand-side random variables (nitrogen requirement of crop i) at the same time. A non-equivalent linearization form of ILCCP was deduced and proved intuitively, which can help handle the left-hand-side random parameters in the constraints. The decision schemes through ILCCP were analyzed under scenarios at different individual probabilities (p i , denotes the admissible probability of violating the constraint i). The performance of ILCCP was also compared with the corresponding interval linear programming model. A representative nonpoint-source water quality management case was employed to facilitate the analysis and the comparison. The optimization results indicated that the net system benefit in the water quality management case would decrease with increasing probability levels on the whole. This was because that the higher constraint satisfaction of probability would lead to stricter decision space. The optimal scheme shows an obvious downtrend in the application amount of manure as the violation probability levels decreasing from scenarios 1 to 3 (p i = 0.1, 0.05 and 0.01). This demonstrates that the application amount of manure would be reduced effectively by adjusting strictness of the constraints. This study is the first application of the ILCCP model to water quality management, which indicates that the ILCCP is applicable to other environmental problems under uncertainties.

Assessing the Hydrologic Performance of the Nonpoint Source Water Quality Assessment Decision Support Tool Using HSPF in Feitsui Reservoir Watershed

The accuracy of rainfall predictions in the EPA’s BASINS (Better Assessment Science Integrating Point and Nonpoint Sources) decision support tool is affected by the sparse meteorological data contained in BASINS. The objectives of this study were improvement of using the entropy theory to supplement the precipitation data are significant when the watershed’s meteorological station is either far away or not in a similar climatic region. When the station is nearby, using entropy theory to supplement the precipitation data produces similar results. And this study assessed the improvement of stream flow prediction of the Hydrological Simulation Program-FORTRAN (HSPF) model contained within BASINS using the hourly precipitation estimates in Feitsui reservoir watershed. Our results demonstrated consistent improvements of daily stream flow predictions in Feitsui reservoir watershed when precipitation data was incorporated into BASINS. Our analyses also showed that the stream flow improvements were mainly contributed by entropy theory to supplement precipitation data; partially due to the constraints of current BASINS-HSPF settings. However, entropy theory to supplement precipitation data did improve the base flow prediction. The entropy theory method showed 10.17 to 25.51 percent less error than the Thiessen polygon method and Arithmetic to supplement the rainfall data. And used entropy theory supplement the rainfall data to simulate stream flow that RMSE values between 58 and 182. This study demonstrates entropy theory to supplement precipitation has the potential to improve stream flow predictions, thus aid the water quality assessment in the nonpoint water quality assessment decision tool.

Assessment of Runoff and Sediment Yields Using the AnnAGNPS Model in a Three-Gorge Watershed of China

Soil erosion has been recognized as one of the major threats to our environment and water quality worldwide, especially in China. To mitigate nonpoint source water quality problems caused by soil erosion, best management practices (BMPs) and/or conservation programs have been adopted. Watershed models, such as the Annualized Agricultural Non-Point Source Pollutant Loading model (AnnAGNPS), have been developed to aid in the evaluation of watershed response to watershed management practices. The model has been applied worldwide and proven to be a very effective tool in identifying the critical areas which had serious erosion, and in aiding in decision-making processes for adopting BMPs and/or conservation programs so that cost/benefit can be maximized and non-point source pollution control can be achieved in the most efficient way. The main goal of this study was to assess the characteristics of soil erosion, sediment and sediment delivery of a watershed so that effective conservation measures can be implemented. To achieve the overall objective of this study, all necessary data for the 4,184 km2 Daning River watershed in the Three-Gorge region of the Yangtze River of China were assembled. The model was calibrated using observed monthly runoff from 1998 to 1999 (Nash-Sutcliffe coefficient of efficiency of 0.94 and R2 of 0.94) and validated using the observed monthly runoff from 2003 to 2005 (Nash-Sutcliffe coefficient of efficiency of 0.93 and R2 of 0.93). Additionally, the model was validated using annual average sediment of 2000–2002 (relative error of −0.34) and 2003–2004 (relative error of 0.18) at Wuxi station. Post validation simulation showed that approximately 48% of the watershed was under the soil loss tolerance released by the Ministry of Water Resources of China (500 t·km−2·y−1). However, 8% of the watershed had soil erosion of exceeding 5,000 t·km−2·y−1. Sloping areas and low coverage areas are the main source of soil loss in the watershed.

Using the Soil and Water Assessment Tool to Estimate Achievable Water Quality Targets through Implementation of Beneficial Management Practices in an Agricultural Watershed

Runoff from crop production in agricultural watersheds can cause widespread soil loss and degradation of surface water quality. Beneficial management practices (BMPs) for soil conservation are often implemented as remedial measures because BMPs can reduce soil erosion and improve water quality. However, the efficacy of BMPs may be unknown because it can be affected by many factors, such as farming practices, land-use, soil type, topography, and climatic conditions. As such, it is difficult to estimate the impacts of BMPs on water quality through field experiments alone. In this research, the Soil and Water Assessment Tool was used to estimate achievable performance targets of water quality indicators (sediment and soluble P loadings) after implementation of combinations of selected BMPs in the Black Brook Watershed in northwestern New Brunswick, Canada. Four commonly used BMPs (flow diversion terraces [FDTs], fertilizer reductions, tillage methods, and crop rotations), were considered individually and in different combinations. At the watershed level, the best achievable sediment loading was 1.9 t ha(-1) yr(-1) (89% reduction compared with default scenario), with a BMP combination of crop rotation, FDT, and no-till. The best achievable soluble P loading was 0.5 kg ha(-1) yr(-1) (62% reduction), with a BMP combination of crop rotation and FDT and fertilizer reduction. Targets estimated through nonpoint source water quality modeling can be used to evaluate BMP implementation initiatives and provide milestones for the rehabilitation of streams and rivers in agricultural regions.

Application of nitrogen and phosphorus criteria for streams in agricultural landscapes

Efforts to control eutrophication of water resources in agriculturally dominated ecosystems have focused on managing on-farm activities to reduce nutrient loss; however, another management measure for improving water quality is adoption of environmental performance criteria (or 'outcome-based standards'). Here, we review approaches for setting environmental quality criteria for nutrients, summarize approaches developed in Canada for setting 'ideal' and 'achievable' nutrient criteria for streams in agricultural watersheds, and consider how such criteria could be applied. As part of a 'National Agri-Environmental Standards Initiative', the Government of Canada committed to the development of non-regulatory environmental performance standards that establish total P (TP) and total N (TN) concentrations to protect ecological condition of agricultural streams. Application of four approaches for defining ideal standards using only chemistry data resulted in values for TP and TN spanning a relatively narrow range of concentrations within a given ecoregion. Cross-calibration of these chemically derived standards with information on biological condition resulted in recommendations for TP and TN that would likely protect aquatic life from adverse effects of eutrophication. Non-point source water quality modelling was then conducted in a specific watershed to estimate achievable standards, i.e. chemical conditions that could be attained using currently available and recommended management practices. Our research showed that, taken together, short-term achievable standards and ultimate ideal standards could be used to set policy targets that should, if realized, lower N and P concentrations in Canadian agricultural streams and improve biotic condition.

Improving Voluntary Environmental Management Programs: Facilitating Learning and Adaptation

Environmental planners and managers face unique challenges understanding and documenting the effectiveness of programs that rely on voluntary actions by private landowners. Programs, such as those aimed at reducing nonpoint source pollution or improving habitat, intend to reach those goals by persuading landowners to adopt behaviors and management practices consistent with environmental restoration and protection. Our purpose with this paper is to identify barriers for improving voluntary environmental management programs and ways to overcome them. We first draw upon insights regarding data, learning, and adaptation from the adaptive management and performance management literatures, describing three key issues: overcoming information constraints, structural limitations, and organizational culture. Although these lessons are applicable to a variety of voluntary environmental management programs, we then present the issues in the context of on-going research for nonpoint source water quality pollution. We end the discussion by highlighting important elements for advancing voluntary program efforts.

Science, technology and policy for Water Pollution Control at the Watershed Scale: Current issues and future challenges

Water is a critical resource, and the shortage of freshwater resources worldwide will only become more critical as the world population increases and climate changes. The management of water resources provides a myriad of challenges, and, in light of advances in science, technology and policy making, now requires an integrated approach to be successful. Eutrophication and algal blooms are one of the most common and serious threats to the safety and security of water resources; however, despite advances in science and policy, the socio-economic consequences of the impact of such events on systems are still not well known. The economic cost of managing water quality issues is enormous, and can only benefit from the development of more integrated water management strategies. Research into areas related to water resources, such as management, policy, non-point source pollutants, wastewater, nutrients and water quality has increased significantly over the past 20 years, and will continue to increase as stakeholders and managers strive to develop more environmentally, socially, and economically sustainable water resource management plans. This perspective paper also presents a summary of a selection of research that formed part of the deliberations of the International Symposium on Science, Technology and Policy for Water Pollution Control at the Watershed Scale, held in April 2009.

NASA‐Modified Precipitation Products to Improve USEPA Nonpoint Source Water Quality Modeling for the Chesapeake Bay

The USEPA has estimated that over 20,000 water bodies within the United States do not meet water quality standards. One of the regulations in the Clean Water Act of 1972 requires states to monitor the total maximum daily load, or the amount of pollution that can be carried by a water body before it is determined to be "polluted," for any watershed in the United States (Copeland, 2005). In response to this mandate, the USEPA developed Better Assessment Science Integrating Nonpoint Sources (BASINS) as a decision support tool for assessing pollution and to guide the decision-making process for improving water quality. One of the models in BASINS, the Hydrological Simulation Program-Fortran (HSPF), computes continuous streamflow rates and pollutant concentration at each basin outlet. By design, precipitation and other meteorological data from weather stations serve as standard model input. In practice, these stations may be unable to capture the spatial heterogeneity of precipitation events, especially if they are few and far between. An attempt was made to resolve this issue by substituting station data with NASA-modified/NOAA precipitation data. Using these data within HSPF, streamflow was calculated for seven watersheds in the Chesapeake Bay Basin during low flow periods, convective storm periods, and annual flows. In almost every case, the modeling performance of HSPF increased when using the NASA-modified precipitation data, resulting in better streamflow statistics and, potentially, in improved water quality assessment.

Possibilistic Stochastic Water Management Model for Agricultural Nonpoint Source Pollution

Agricultural activities are the main contributors of nonpoint source water pollution within agricultural systems. In this study, a possibilistic stochastic water management (PSWM) model is developed and applied to a case study of water quality management within an agricultural system in China. This study is a first application of hybrid possibilistic chance-constrained programming approach to nonpoint source water quality management problems within an agricultural system. Hybrid uncertainties with the synergy of fuzzy and stochastic implications are effectively characterized by the PSWM model with the following advantages: (1) it improves upon the existing possibilistic and chance-constrained programming methods through direct incorporation of fuzziness and randomness within a general optimization framework; (2) it will not lead to more complicated intermediate models and thus have lower computational requirements; (3) its solutions offer flexibility in interpreting the results and reflect the interaction...

Assessing the hydrologic performance of the EPA’s nonpoint source water quality assessment decision support tool using North American Land Data Assimilation System (NLDAS) products

The accuracy of streamflow predictions in the EPA’s BASINS (Better Assessment Science Integrating Point and Nonpoint Sources) decision support tool is affected by the sparse meteorological data contained in BASINS. The North American Land Data Assimilation System (NLDAS) data with high spatial and temporal resolutions provide an alternative to the NOAA National Climatic Data Center (NCDC)’s station data. This study assessed the improvement of streamflow prediction of the Hydrological Simulation Program-FORTRAN (HSPF) model contained within BASINS using the NLDAS 1/8 degree hourly precipitation and evapotranspiration estimates in seven watersheds of the Chesapeake Bay region. Our results demonstrated consistent improvements of daily streamflow predictions in five of the seven watersheds when NLDAS precipitation and evapotranspiration data was incorporated into BASINS. The improvement of using NLDAS data is significant when the watershed’s meteorological station is either far away or not in a similar climatic region. When the station is nearby, using NLDAS data produces similar results. The correlation coefficients of the analyses using NLDAS data were greater than 0.8, the Nash–Sutcliffe (NS) model fit efficiency greater than 0.6, and the error in the water balance was less than 5%. Our analyses also showed that the streamflow improvements were mainly contributed by NLDAS precipitation data and that the improvement from using NLDAS evapotranspiration data was not significant; partially due to the constraints of current BASINS-HSPF settings. However, NLDAS evapotranspiration data did improve the baseflow prediction. This study demonstrates NLDAS data has the potential to improve stream flow predictions, thus aid the water quality assessment in the EPA nonpoint water quality assessment decision tool.