Integrated hydrologic–economic decision support system for groundwater use confronting climate change uncertainties in the Tunuyán River basin, Argentina

Abstract

This study presents an integrated hydrologic–economic model as decision support system for groundwater use and incorporates uncertainties of climate change. The model was developed with the Vensim software (Ventana Systems) for system dynamic simulations. The software permitted the integration of economic variables along with hydrologic variables, in a unified format with the aim of evaluating the economic impacts of climate change on arid environments. To test the model, we applied it in one of the upper Tunuyan River sub-basin, located in the Mendoza Province (Argentina), where irrigation comes from groundwater. The model defines the best mix of crops and the total land use required to maximize the total river sub-basin monetary income, considering as a limit the amount of water that does not exceed the natural annual aquifer recharge. To estimate the impacts of climatic changes, four scenarios were compared: the business as usual (with the number of existing wells) in a dry year with a temperature increase of 4 °C; the business as usual in a wet year with an increase in temperature of 1.1 °C; an efficient use of wells in a dry year and a temperature increase of 4 °C and an efficient use of wells in a wet year with a temperature increase of 1.1 °C. Outputs calculated by the model were: land use per crop, total sub-basin net benefit, total sub-basin water extraction, water extraction limit depending on river discharge and total number of wells required to irrigate the entire area. Preliminary results showed that the number of existing wells exceeded the optimized number of wells required to sustainably irrigate the entire river sub-basin. Results indicated that in an average river discharge year, if wells were efficiently used, further rural development would be possible, until the limit of 350 million m3 of water extraction per year was reached (650 million m3 for a wet year and 180 million m3 for a dry year). The unified format and the low cost of the software license make the model a useful tool for Water Resources Management Institutions, particularly in developing countries.