Agricultural Adaptation to Reconcile Food Security and Water Sustainability Under Climate Change: The Case of Cereals in Iran

Abstract

In this study, we simulate the crop yield and water footprint (WF) of major food crops of Iran on irrigated and rainfed croplands for the historical and the future climate. We assess the effects of three agricultural adaptation strategies to climate change in terms of potential blue water savings. We then evaluate to what extent these savings can reduce unsustainable blue WF. We find that cereal production increases under climate change in both irrigated and rainfed croplands (by 2.6–3.1 and 1.4–2.3 million t yr−1, respectively) due to increased yields (6.6%–78.7%). Simultaneously, the unit WF (m3 t−1) tends to decrease in most scenarios. However, the annual consumptive water use increases in both irrigated and rainfed croplands (by 0.3–1.8 and 0.5–1.7 billion m3 yr−1, respectively). This is most noticeable in the arid regions, where consumptive water use increases by roughly 70% under climate change. Off‐season cultivation is the most effective adaptation strategy to alleviate additional pressure on blue water resources with blue water savings of 14–15 billion m3 yr−1. The second most effective is WF benchmarking, which results in blue water savings of 1.1–3.5 billion m3 yr−1. The early planting strategy is less effective but still leads to blue water savings of 1.7–1.9 billion m3 yr−1. In the same order of effectiveness, these three strategies can reduce blue water scarcity and unsustainable blue water use in Iran under current conditions. However, we find that these strategies do not mitigate water scarcity in all provinces per se, nor all months of the year.

Reduced Runoff in the Upper Yangtze River Due To Comparable Contribution of Anthropogenic and Climate Changes

“…There are various methods available for calculating ET 0 (R. G. Allen et al., 1998; Monteith, 1965; Penman, 1948; Priestley & Taylor, 1972; Thornthwaite, 1948). In this study, the FAO Penman‐Monteith method was adopted for estimating ET 0 due to its straightforward implementation and widespread usage (Karandish et al., 2022; X. Liu, Peng, et al., 2017; X. Liu, Xu, et al., 2017; Mutziger et al., 2005). Although Federer et al.…”