The lack of detailed and reliable data on the estimates of water use has been a key limitation in informing sustainable, equitable and efficient water reallocations in the agricultural sector. Conventional water use data have been commonly obtained from surveys or agronomic models, which have limitations on accurately reflecting the actual water use. This paper integrates cutting-edge satellite-based water use data with an ensemble of four Calibrated Mathematical Programming Models (CMPM) (one Positive Multi-Attribute Utility Programming model, one Weighted Goal Programming model, and two Positive Mathematical Programming models) to assess and compare the performance of water reallocations under satellite-based versus conventional water use estimates. We apply these methods to the water-stressed Mancha Oriental Aquifer (MOA) in central Spain, where we simulate the impacts of a hypothetical temporary water reacquisition policy in 2017, the last dry year in record. We find that water use estimates obtained with conventional approaches (which range between 4916 m3/ha and 4510 m3/ha, on average) are 13–24 % lower than satellite-based estimates (5577 m3/ha on average) during the dry year. Moreover, the water reacquisition simulation using the CMPM ensemble shows that the reserve prices (25–66 % higher) and buyback costs (26–67 % higher) derived from conventional water use data approaches are consistently and significantly higher than those derived from satellite-based water use estimates for all the elements of the ensemble, suggesting that a policy informed with satellite-based data could significantly reduce the costs of the reallocation.
Private household water and energy use are closely linked, especially in areas of intermittent water supply where more than one billion people live globally. However, the demand-side Water-Energy Nexus at the household level is often overlooked in empirical econometric studies. Based on a household survey (n = 1872) on water and energy in the Pune Metropolitan Region, India, we find statistical relationships between intermittent water supply and household electricity demand. More than 90 % of the surveyed households use water storage to cope with water supply intermittency, low-income households are particularly affected. Electricity consumption for water access accounts for 27 % of total household electricity consumption. Using a Discrete-Continuous Choice model, we identify significant impacts from factors such as household size and income, electricity price, and particularly the duration of water supply and the use of large water storage on household electricity demand. Our results indicate that households with 24-h water access consume 30 % less electricity than those with 12-h daily access. Extending municipal piped water supply by 1 h per day for all households could reduce total household electricity consumption by 3 %. Our findings suggest that water supply intermittency is a massive cause of unnecessary emissions in cities around the world that has thus far received hardly any attention. The significant amount of electricity used to access water reveals a hidden water affordability problem that can be more prevalent during droughts. Our analyses highlight the demand-side Water-Energy Nexus from an econometric perspective and emphasize the importance of breaking down silos in resource management.
Improving water efficiency in the agricultural sector is essential to ensure sustainable withdrawals and supply of freshwater in a context of increasing water scarcity and human water demand. The water footprint (WF) is an established metric of resource intensity while the drivers steering WF over time remain under-researched. To advance this line of research, this paper assesses the sign and magnitude of macroeconomic, climatic, and agronomic drivers on the agricultural crop WF in 43 countries of the African continent for the period 2002–2016, using econometric panel data techniques and considering potential spatial patterns. The results reveal a significant spatial dependence in the WF across neighbouring countries. Socioeconomic factors are the most important determinant of water productivity, indicating that economic development facilitates a falling water requirement per unit of production. A negative impact of the temperature variation on the WF is also found, while the share of total land dedicated to agriculture tends to increase the crop WF in the continent. These results support designing adequate agricultural and water management policies to achieve sustainable and resilient food systems capable of adapting to anticipated population growth, climate change and other future threats to human health, prosperity and environmental sustainability in Africa.