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This article in JEQ

  1. Vol. 31 No. 3, p. 937-945
     
    Received: Mar 14, 2001


    * Corresponding author(s): Faruk.Djodjic@mv.slu.se
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doi:10.2134/jeq2002.9370

A Decision Support System for Phosphorus Management at a Watershed Scale

  1. Faruk Djodjic *a,
  2. Hubert Montasb,
  3. Adel Shirmohammadib,
  4. Lars Bergströma and
  5. Barbro Uléna
  1. a Swedish Univ. of Agricultural Sciences, Division of Water Quality Management, Box 7072, S-750 07 Uppsala, Sweden
    b Univ. of Maryland, Biological Resources Engineering, College Park, MD 20742

Abstract

Phosphorus (P) is one of the main nutrients controlling algal production in aquatic systems. Proper management of P in agricultural production systems can greatly enhance our ability to combat pollution of aquatic environments. To address this issue, a decision support system (DSS) consisting of the Maryland Phosphorus Index (PI), diagnosis expert system (ES), prescription ES, and a nonpoint-source pollution model, Ground Water Loading Effects of Agricultural Management Systems (GLEAMS), was developed and applied to an agricultural watershed in southern Sweden. This system can identify critical source areas (CSAs) regarding phosphorus losses within the watershed, make a diagnosis of probable causes, prescribe the most appropriate best management practices (BMPs), and test the environmental effects of the applied BMPs. The PI calculations identified small parts of the watershed as CSAs. Only 10.4% of the total watershed area in 1995 and 5.2% of the total watershed area in 1996 were classed as “high potential P movement.” Four probable causes (high P level in soil, excessive P fertilization, stream proximity, and subsurface drainage) and three BMPs (riparian buffer strips, reduced P fertilizer application, and P fertilizer incorporation) were identified by a diagnosis and prescription expert system. The GLEAMS simulations conducted for one selected CSA field for a 24-yr period showed that the recommended BMP reduced runoff P losses by 55% and sediment P losses by 71%, if applied from the first year. Results showed that using DSS may enable us to select a proper BMP implementation strategy and to realize the beneficial effect of BMPs on a long-term basis.

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Copyright © 2002. American Society of Agronomy, Crop Science Society of America, Soil Science SocietyPublished in J. Environ. Qual.31:937–945.