COST MINIMIZATION OF NUTRIENT REDUCTION IN WATERSHED MANAGEMENT USING LINEAR PROGRAMMING¹

Abstract

Linear programming is applied to identify the least cost strategy for reaching politically specified phosphorus and total suspended solids reduction targets for the Fox‐Wolf river basin in Northeast Wisconsin. The programming model uses data collected on annualized unit reduction costs associated with five categories of sources of phosphorus and total suspended solids discharge in each of the 41 sub‐watersheds in the basin to determine the least cost management strategy. Results indicate that: (1) cost‐effective nutrient reduction requires careful selection of geographic areas and source categories to address throughout the watershed; (2) agricultural sources are the most cost‐effective to address in the basin; and (3) care should be exercised in setting nutrient reduction targets, given that there are likely to be significantly increasing marginal costs of nutrient reduction; the model predicts that lowering the most restrictive target by 33 percent would cut reduction expenditures by about 75 percent. Policy implications of the model include support for the investigation and potential development of institutional arrangements that enable cost‐effective nutrient reduction activities to occur, such as the creation of an agency with authority over a given watershed, coordinated watershed management activities, or nutrient trading programs.

Decision support for water policy: a review of economic concepts and tools

“…They evaluated the economic value of riparian buffers in reducing agricultural non-point source pollution in a midwest US watershed. Schleich & White (1997) analyzed the cost effectiveness of various measures for reducing nutrients in watersheds. They used linear programming analysis to identify the least cost strategy for reaching politically specified phosphorus and total suspended solids reduction targets for the Fox-Wolf river basin in northeast Wisconsin.…”

Managing water quality in a New York City watershed

“…This growing complexity has led to the use of different analytic concepts and models to address water management problems (e.g. Thiessen et al 1998;Schleich & White 1997;Becker & Easter 1997;Watkins et al 2000). Models can help decision makers structure knowledge and identify information gaps.…”

Agricultural nonpoint source pollution and water quality trading: empirical analysis under imperfect cost information and measurement error

“…There are a number of federal and state programs that provide either cost-sharing or full financial support for the implementation of conservation practices in agricultural areas. A primary concern in administering the limited public funds is finding the most cost effective way to allocate the conservation practices (Schleich and White 1997;Rabotyagov et al 2010). This is equivalent to solving the least-cost placement of the conservation practices under a limited budget.…”

“…Finding the optimal placement of conservation practices in a watershed is a discrete optimization problem with the search space defined by the possible combinations of the fields located in the watershed and the available conservation practices. Schleich and White (1997) were among the first to show how linear programming models can be used to identify the least-cost solution to reach the predetermined targets for a watershed in Wisconsin. Their model included both point and agricultural sources, with the latter being aggregated in subwatersheds.…”