Evaluating the Sustainability of Agricultural Systems by Compromise Programing: Lorestan Koohdasht Area

Agricultural sector plays a vital role in Iran’s economy but this sector has pursued an unsustainable route mostly because of land and water resources degradation resulting from inefficient use of irrigation water and intensive use of inorganic inputs. However, increasing production is not the only relevant goal in farming systems. It is important to consider the effects of agriculture on soil productivity, pollution, water and energy use efficiency, Greenhouse gas emissions and social aspects. In fact, there is a strong interest for redefining production systems looking for a balance between high productivity and the protection of the environmental services provided by these farming systems. In this regard, current study evaluated environmental, economic and social impacts of agricultural systems in Kouhdasht area as one of the important regions of Lorestan province using multi-criteria compromise programming (CP) and a set of different weights. Gross margin, direct expenses and crops acreage were the indicators considered for economic sustainability analysis. The environmental indicators were water use, EIQ (environmental impact quotient), use of fertilizer, insecticides and pesticides, soil organic carbon and crop rotation. The social indicators considered for analysis were employment and education level. The basic idea in compromise programming as a well-known multi-criteria decision-making method, is to identify an ideal solution that can be obtain from the available options. This ideal solution is a point reference for decision maker and options or alternatives are ranked based on how far they are from it. The findings of this study include the identification of a set of agricultural systems based on different views or weights. These optimal agricultural systems are compared to the current agricultural systems.

In current study a compromise programming optimization model was solved to find efficient agricultural systems, according to economic, environmental and social criteria, for crop/livestock farms. An agricultural system can be shown as a linear combination of activities. Each activity is characterized by the resources and inputs employed, the type and quantity of the output produced and the environmental impacts. Generally, eight agricultural systems corresponding to different crops and livestock production were considered for analysis. The evaluation of sustainability of agriculture requires determination of attributes or indicators covering economic, environmental and social dimensions. In fact, the concept of attribute or indicator is fundamental in multi-criteria models. In this study, three economic, six environmental and two social indicators are included as attributes. Selection of indicators was based on relevance of the indicators, the frequency of using the indicator in previous studies and availability of data. The solution of CP entailed of finding the lowest distance to the ideal for all the criteria. Decision-maker preferences were simulated using nine scenarios, which combine three distance functions (π = 1, π = 2 and π =100), and three different weights based on the importance of different dimensions.

The results showed that, based on the first weight group (environmental view) and at the low and high weight for deviations (π =1 and π = 100), wheat1 and sugar beet1 systems are the most sustainable system respectively. But sugar beet2 system is the most unstable agricultural system at all levels of π and in all areas. Overuse of groundwater for irrigation, fertilizer and pesticide in some areas further reinforced agricultural unsustainability. In the second weight group (economics view) and for π = 2, activity diversification (crop -livestock) system was more balanced than continuous crop farming. In the third weight group (equal weight to all dimensions) and for π = 2, sugar beet1 and the rain fed cultivated systems were the most sustainable. In other values of π, the sugar beet2 had the least sustainable index. The findings of this study indicate instability in Azadbakht Korapa and Cham Sangar villages in all weight groups, while Katkan village is most sustainability for π = 2. Results also showed that for π = 1, Kohnani and Eastern Tarhan rural district are most sustainable and most unsustainable rural district respectively. The lack of sustainable agricultural production in Eastern Tarhan in π = 1, was due to limited economics performance in rural district. However, in high levels of sensitivity to deviations from the ideal level, the rural district of Boluran and the Western Tarhan,are most unsustainable rural district, and North and South Kouhdasht, Golgol, Darb Gombad and Ziretang are the most sustainable rural district in the region. Finally, by putting different dimensions of sustainability, this study extracted ten independent and distinct patterns of sustainability using data mining. Farms in patterns 5 and 8 were experienced relative sustainable, and farms in the pattern 6, were unsustainable in all dimensions.

It was inferred from the results of this study that there are regional differences in agricultural sustainability in Kouhdasht. As a result, it is suggested that effective agricultural policies be adopted in accordance with local research.