Developing an automatic conjunctive surface-groundwater operating system for sustainable agricultural water distribution

Abstract

Groundwater extraction from aquifers is the primary approach for supplying agricultural water demand due to the inadequate, unfair, and unreliable distribution of surface water (SW) systems. In this regard, the present study developed an automated operating system for conjunctive surface and groundwater (GW) resources. By centralized model predictive control (CMPC), an automated SW distribution system was developed in MATLAB and integrated with the groundwater modeling system (GMS) to provide an intelligent SW-GW conjunctive operating system in water scarcity scenarios. A controversial irrigation district in central Iran is selected as the test case in Iran. GW extraction from active tube-wells in the SW distribution system's territory includes 39%, 21%, 40% deep, semi-deep, and shallow. Besides, about 65% of energy consumption is related to over-exploitation in deep wells. The notable point of automating the SW system is the high capability of CMPC to control fluctuations in all canal reaches so that the dependability and adequacy of water distribution become reasonable even under severe scenarios. Intelligent SW-GW operating system led to an uprise of 0.1–2.2, 0.2–3.2, 0.4–3.9, 0.7–6.9, 1.5–9.1, and 3.8–13.5 m in the aquifer water level, respectively, within 12, 2, 36, 48, 60, and 120 months. Besides, Water extraction reduction from the aquifer after one year is about 16%, and the reduction of annual energy consumption is around 81%. The proposed method enables authorities to promote the SW distribution in practical, implementable, and step-by-step planning to reduce GW extraction from tube-wells based on actual water reduction potential.