Centre for Integrative Ecology, School of Life and Environmental Sciences, Deakin University, VIC 3125, Australia.
Sustainability and Biosecurity, Department of Primary Industries and Regional Development, 1 Nash Street, East Perth, WA 6004, Australia.
Sci Total Environ. 2022 Jul 10;829:154360. doi: 10.1016/j.scitotenv.2022.154360. Epub 2022 Mar 11.
Worldwide food production is under ever-increasing demand. Meanwhile, climate change is disrupting rainfall and evaporation patterns, making agriculture freshwater supplies more uncertain. IPCC models predict an increased variability in rainfall and temperature over most of the globe under climate change. Yet, the effects of climate variability on water security remain poorly resolved. Here we used satellite images and deep-learning convolutional neural networks to analyse the impacts of annual averages, seasonality, climate anomaly, and temporal autocorrelation (or climate reddening) for rain and temperature on the water levels of >100,000 Australian farm dams across 55 years. We found that the risk of empty farm dams increased with warmer annual temperatures, lower yearly rainfall, stronger seasonality, reduced climate anomalies, and higher temporal autocorrelation. We used this information to develop a predictive model and estimate the likelihood of water limitations in farm dams between 1965 and 2050 using historical data and Coupled Model Intercomparison Project Phase 5 (CMIP5) at two climate change scenarios. Results showed that the frequency of empty water reserves has increased 2.5-fold since 1965 and will continue to increase across most (91%) of Australia. We estimated a 37% decline in rural areas with year-round water supplies between 1965 (457,076 km) and 2050 (285,998 km). Our continental-scale assessment documents complex temporal and spatial impacts of climate change on agricultural water security, with ramifications for society, economy, and the environment.
全球粮食生产正面临日益增长的需求。与此同时，气候变化扰乱了降雨和蒸发模式，使农业淡水供应更加不确定。政府间气候变化专门委员会（IPCC）的模型预测，在气候变化下，全球大部分地区的降雨量和温度变化将增加。然而，气候变化对水安全的影响仍未得到很好的解决。在这里，我们使用卫星图像和深度学习卷积神经网络来分析年平均值、季节性、气候异常和时间自相关（或气候变红）对雨温和温度对超过 10 万个澳大利亚农场水坝水位的影响，时间跨度为 55 年。我们发现，农场水坝空坝的风险随着年平均温度升高、年降雨量减少、季节性增强、气候异常减少和时间自相关增加而增加。我们利用这些信息开发了一个预测模型，并使用历史数据和耦合模型比较计划第 5 阶段（CMIP5）在两种气候变化情景下，估计 1965 年至 2050 年期间农场水坝的水资源限制的可能性。结果表明，自 1965 年以来，空水储量的频率增加了两倍，而且在澳大利亚大部分地区（91%）将继续增加。我们估计，在农村地区，全年供水的地区将减少 37%，从 1965 年（457,076 公里）减少到 2050 年（285,998 公里）。我们的大陆规模评估记录了气候变化对农业水安全的复杂时间和空间影响，对社会、经济和环境都有影响。
