Economic-ecological optimization model of land and resource use at farm-aggregated level

Abstract

A Farm-Level Economic Ecological Optimization Model (FLEOM) was developed in the ZEF/UNESCO Khorezm project as a land-use planning and decision-support tool at the level of farms and Water Users Associations (WUAs) to couple ecological and economic optimization of land allocation. The agronomic database for cotton, winter wheat and maize that underlines the model was established with the cropping system simulation model CropSyst using data sets, field experience and knowledge of a range of agronomic and hydrological studies on irrigation and fertilizer response, planting dates, tillage and residue management. Potential users of this tool are medium-level stakeholders such as representatives of WUAs and the local water authority. Besides, the model is intended to be a tool for scientists and for university education. The features of FLEOM are presented through simulation of four different management scenarios, each with different sets of assumptions relating to changes in socio-economic conditions: (i) business-as-usual, (ii) commodity market liberalization, (iii) ecological commodity market liberalization, and (iv) dry-year scenario. The evaluation of the scenarios demonstrates that FLEOM produces consistent and plausible outputs, and that it can be used for quite complex scenario simulations. The scenario results reveal that under conditions of a liberalized commodity market, cotton production had no comparative advantages and would completely disappear, and with it the state income from cotton exports. However, simulations also highlighted that the state procurement of cotton seems to indirectly mitigate excessive use of irrigation water and that without the state procurement system, scarcity and conflicts over irrigation water even in normal years are likely to occur. Double cropping of rice and maize as summer crops after wheat was constrained mainly by the availability of water and/or by the obligation of fulfilling the state procurement production of cotton. Despite the model being normative, the simulation results are very reasonable and thus enable a better understanding of the impacts of different cotton policies on the farm economy as well as on farmers' decisions with respect to land and water use in Khorezm. The results of this study can further contribute to the discussion on what policy options are available for promoting income and food resilience of rural producers in other areas of Uzbekistan that are prone to water scarcity, and with agronomic and economic conditions closely resembling those observed in the Khorezm region.