مدل مبتنی بر سیستم پشتیبانی از تصمیم گیری برای مدیریت کیفیت آب تحت عدم قطعیت ترکیبی

Water quality management is inevitably complicated since it involves a number of environmental, socio-economic, technical, and political factors with dynamic and interactive features. In planning water quality management systems, uncertainties exist in many system components and may affect the system behaviours. It is thus desired that such complexities and uncertainties be effectively addressed for providing decision support for practical water quality management. The objective of this study is to develop a model-based decision support system for supporting water quality management under hybrid uncertainties, named FICMDSS, which is based on a hybrid uncertain programming (HFICP) model with fuzzy and interval coefficients. The system provides an effective tool for the decision makers in dealing with water quality management problems and formulating desired policies and strategies. The user can easily operate the system and obtain the decision support through user-friendly graphical interfaces. The HFICP model improves upon the existing inexact programming methods through incorporation of hybrid fuzzy and interval uncertainties into the optimization management processes and resulting solutions. Results of a water quality management case study indicated that the developed FICMDSS can facilitate the decision making in planning agricultural activities for water quality management in agricultural systems. Feasible decision alternatives for cropping area, amounts of manure and fertilizer application, and sizes of livestock husbandry can be generated for achieving the maximum agricultural system benefit subject to the given water-related constraints. The user can better make the decisions for water quality management under hybrid uncertainties with the help of FICMDSS.

Water quality management is inevitably complicated since it involves a number of environmental, socio-economic, technical, and political factors with dynamic and interactive features. Nonpoint source (NPS) pollution from agricultural activities is the most significant source of water quality deterioration in agricultural lands (Cho et al., 2008, Huang and Xia, 2001, Leóna et al., 2004 and USEPA, 1992). Due to its diffuse characteristics, NPS contamination is difficult to be controlled since it is hard to isolate and quantify the contribution from individually dispersed sources (Berka, Schreier, & Hall, 2001). One effective means for NPS pollution control is to plan the related agricultural activities for causing the water quality deterioration. In planning of such water quality management systems, uncertainties exist in many system components and may affect the system behaviours. It is thus desired that such complexities and uncertainties be effectively addressed for providing decision support for practical water quality management (Chen et al., 2005, Huang et al., 2008 and Nie et al., 2008). Mathematical models can facilitate in identifying effective decision schemes for water quality management. Previously, a variety of inexact water quality management models have been developed for dealing with various types of uncertainties (Chang et al., 1997, Chen et al., 2005, Huang, 1996, Huang, 1998, Karmakar and Mujumdar, 2006, Lee and Wen, 1997, Luo et al., 2006, Nie et al., 2008, Sasikumar and Mujumdar, 1998, Sasikumar and Mujumdar, 2000, Zhang et al., 2009 and Zhang et al., 2010). They could be categorized into fuzzy programming models, stochastic programming models, and interval programming models. Due to the inherent complexities and uncertainties, these mathematical models were highly complicated and involved in a number of mathematical knowledge on uncertainty analysis, modeling formulation and solution algorithms. The decision makers often encounter difficulties in understanding the inexact modeling results and formulation of desired policies and strategies for water quality management. A decision support system (DSS) can be helpful for handling the above situations and facilitating the decision making processes. Previously, a number of decision support systems have been developed and applied in the field of environmental management (Loucks and da Costa, 1991, Recknagel et al., 1991, Ito et al., 2001, Matthies et al., 2006, Obropta et al., 2008, Quinn, 2009, Simonovic, 1996a, Simonovic, 1996b, Srinivasan and Engel, 1994 and Zhang et al., 2009). Nasiri, Maqsood, Huang, and Fuller (2007) proposed a fuzzy multiple-attribute decision support expert system to compute the water quality index for assessment and evaluation of water quality policies. Assaf and Saadeh (2008) developed an integrated decision support system to assess and evaluate alternative management plans for sewage induced degradation of surface water quality. Argent, Perraud, Rahman, Grayson, and Podger (2009) described a catchment modeling software system named E2 to improve the flexibility of the specific DSS. Kao, Pan, and Lin (2009) developed a web-based budget allocation system for regional water quality management to improve environmental sustainability. However, there was a lack of research efforts in incorporating the inexact water quality management models into the decision support systems, where the hybrid uncertainties expressed by fuzzy membership functions and interval numbers associated with the coefficients of the objective function and the constraints of the models could be effectively reflected. Therefore, the objective of this study is to develop a model-based decision support system for supporting water quality management under hybrid uncertainties, named FICMDSS, which is based on a hybrid uncertain programming (HFICP) model with fuzzy and interval coefficients. The different functions are effectively organized and integrated within an integrated decision support framework. The coefficients in the objective function can be modeled as interval numbers, and those in the constraints can be expressed by fuzzy membership functions. The HFICP model can improve upon the existing inexact programming methods through incorporation of hybrid fuzzy and interval uncertainties into the optimization management processes and resulting solutions. An agricultural water management case is proposed for demonstrating the applicability of the developed FICMDSS. Feasible decision alternatives for cropping area, amounts of manure and fertilizer application, and sizes of livestock husbandry can be generated for achieving the maximum agricultural system benefit subject to the given water-related constraints under hybrid uncertainties. This papers proceeds as follows. Section 2 describes the model development. Section 3 presents the development of FICMDSS. Section 4 describes the implementation of FICMDSS through a water quality management case study, and Section 5 concludes the paper.

A model-based decision support system (FICMDSS) has been developed for supporting water quality management in agricultural systems, which is based on the hybrid uncertain programming (HFICP) model with fuzzy and interval coefficients. The system provides an effective tool for the decision makers in dealing with water quality management problems. The user can easily operate the system and obtain the decision support through menus and buttons which allow the selection of different functions via user-friendly graphical interfaces. The system can be used for tackling the uncertainties associated with the objective function expressed by interval numbers and the constraints expressed by fuzzy membership functions. In this system, the embedded HFICP model with an interval objective is converted into a bi-objective model by simultaneously maximizing the lower and upper bounds of the interval objective. The constraints with fuzzy coefficients are transformed into deterministic ones through a fuzzy robust programming method, which enhances the robustness of the optimization processes. The conversion enables the hybrid uncertainties to be directly communicated into the optimization processes and resulting solutions, so that effective decision alternatives can be generated. Results of the case study indicated that the developed FICMDSS can facilitate the decision making in planning agricultural activities for water quality management in agricultural systems. The user can freely select the output options for the modeling results obtained from the decision support system. Optimal decision alternatives can be displayed using graphical or tabular styles. The user can better make the decisions for water quality management under hybrid uncertainties with the help of FICMDSS.