Optimal Best Management Practice Placement Strategies for Nonpoint Source Pollution Management in the Fei-Tsui Reservoir Watershed

Abstract

The purpose of this study was to develop a tool for the optimal placement strategy of structural best management practices (BMPs) at the watershed scale. It consists of three interacting components: a simplified BMPs simulation model, a zero-dimensional reservoir water quality model (unsteady, time-variable Vollenweider model), and an optimization model (genetic algorithms). A posttreatment program that combines BMP simulation, channel routing, reservoir water quality models, and genetic algorithms was developed. Both total suspended solids and total phosphorus were taken into account, and three types of BMPs were considered. By changing the constraints, three scenarios were analyzed in this study. The total phosphorus concentration should satisfy oligotrophic, mesotrophic, and eutrophic conditions, while the total suspended solids concentration should be kept below 25 mg=L. This study analyzes three different time-scale scenarios: short term (March 28, 2003 to April 14, 2003), long term (2002, and design storms (2-year=2-h and 5-year=4-h). Near optimal solutions found in this study were compared with former research on the Fei-Tsui Reservoir watershed. For future detailed planning and designing, decision makers or designers can adopt the BMPs placement strategies developed in this study. Several nonstructural BMPs are also suggested as sound alternatives for nonpoint source pollution control when there are topographic and land ownership problems.

Applying a Multivariate Statistical Analysis Model to Evaluate the Water Quality of a Watershed

“…The Feitsui Reservoir is the second largest reservoir in Taiwan. It is located in the upper region of the Shixi stream, which flows into the Xindian stream, and receives the effluents from six tributary streams flowing through the watershed (Hsieh et al, 2010). This reservoir has been developed with a single objective: to provide water to residents of the Taipei municipality.…”

A preference-based multi-objective model for the optimization of best management practices

“…The optimization methods have been widely applied in the water resources planning and management (Nicklow et al, 2010;Shafiee and Zechman, 2011). The Nondominated Sorting GA (NSGA-II) has become one of the most widely used multi-objective GA for the selection and placement of BMPs at the watershed scale, considering the efficiency and cost of BMPs as well as farm income (Hsieh et al, 2010;Maringanti et al, 2011;Panagopoulos et al, 2013). However, NSGA-II faces difficulties when applied to problems without any information from decision makers (Deb, 1999a).…”

Enhanced nonlinearity interval mapping scheme for high‐performance simulation‐optimization of watershed‐scale BMP placement

“…Total Maximum Daily Loads (TMDL) have been widely recognized over the past few decades as a means for expressing watershed load reductions for water quality restoration [ National Research Council , ; Faulkner , ; Conley et al ., ]. In the load reduction programs, growing emphasis has been placed on nonpoint source (NPS) control [ Veith et al ., ; Kramer et al ., ; Maringanti et al ., ; Hsieh et al ., ] using best management practices (BMPs) at both watershed and site scales [ Kaini et al ., ; Park and Roesner , ; Damodaram and Zechman , ]. Widespread application of green‐infrastructure BMPs greatly improves the possibility for water quality restoration; however, costs of BMP construction, operation, and maintenance pose challenges for widespread application [ Srivastava et al ., ; Veith et al ., ; Hsieh et al ., ; Rodriguez et al ., ].…”

“…In the load reduction programs, growing emphasis has been placed on nonpoint source (NPS) control [ Veith et al ., ; Kramer et al ., ; Maringanti et al ., ; Hsieh et al ., ] using best management practices (BMPs) at both watershed and site scales [ Kaini et al ., ; Park and Roesner , ; Damodaram and Zechman , ]. Widespread application of green‐infrastructure BMPs greatly improves the possibility for water quality restoration; however, costs of BMP construction, operation, and maintenance pose challenges for widespread application [ Srivastava et al ., ; Veith et al ., ; Hsieh et al ., ; Rodriguez et al ., ]. Given the breadth of possible management options available to implementers for NPS controls, a representative dynamic watershed simulation model of the baseline condition and a predictive BMP simulation model can be coupled to evaluate the impacts of spatially optimized BMP placement [ USEPA , ; DePinto et al ., ].…”