Trade-offs and synergies in the water-energy-food nexus: The case of sugarcane farming in Maharashtra, India

Sugarcane cultivation is a major agricultural sector in Maharashtra, India, contributing significantly to the state’s economy and rural livelihoods. It is a leading state in terms of average production and recovery, with a sixfold increase in its cultivated area from 0.89% in 1960-61 to 5.34% in 2022-23. However, sugarcane is a highly water-intensive crop with a water productivity of 4.48 kg/m³ in the state. About 79.5% of the total sugarcane of Maharashtra is cultivated in drought-prone regions of the state. High profitability, provision of electricity subsidies and Fair and Remunerative Prices (FRP), and a high number of sugar mills are the main factors behind sugarcane cultivation in Maharashtra that have resulted in many environmental consequences. Sugarcane is regarded as an ideal crop for providing both food and bioenergy (ethanol) production due to its large biomass yield in both solid and liquid forms. However, the sustainable management of water, energy, and food (WEF) resources is challenged by the rapid expansion of water-intensive sugarcane, which depletes the water resources and decreases irrigation and production of major food crops. The inherent interactions among the WEF systems result in trade-offs as well as synergies under various policies and decisions.

To address these challenges, we developed an integrated model to investigate the complex interdependencies within the WEF nexus in sugarcane farming using a system dynamic modeling approach. The model is developed using Vensim with a causal loop diagram (CLD) effectively represents the interconnections and cause-effect dynamics among WEF systems. The model is applied to a case study in the district of Maharashtra state, India. The primary data is collected through a survey of farming households. By incorporating data on water availability, energy consumption, crop productivity, and socio-economic factors, the model evaluates the impacts of various management practices and policy interventions. The sensitivity of the model output to the input parameters is analyzed using a one-at-a-time analysis, while the Monte Carlo technique is used for uncertainty assessment and to test the validity of the model. Furthermore, future scenarios are analyzed to assess the impacts of different socio-economic and climatic drivers on WEF resource dynamics. The model highlights the varying degrees of sensitivity, trade-offs, and synergies within the WEF systems under various drivers, including energy-intensive irrigation, food security constraints, and promoting bioenergy production through supportive policies.