Department of Irrigation and Reclamation Engineering, Faculty of Agriculture Engineering and Technology, College of Agriculture and Natural Resources, University of Tehran, Karaj, Alborz, Iran.
Department of Geography, University of California, Santa Barbara, CA, 93016-4060, USA.
Sci Rep. 2021 Aug 31;11(1):17424. doi: 10.1038/s41598-021-96776-9.
Water is a vital element that plays a central role in human life. This study assesses the status of indicators based on water resources availability relying on hydro-social analysis. The assessment involves countries exhibiting decreasing trends in per capita renewable water during 2005-2017. Africa, America, Asia, Europe, and Oceania encompass respectively 48, 35, 43, 20, and 5 countries with distinct climatic conditions. Four hydro-social indicators associated with rural society, urban society, technology and communication, and knowledge were estimated with soft-computing methods [i.e., artificial neural networks, adaptive neuro-fuzzy inference system, and gene expression programming (GEP)] for the world's continents. The GEP model's performance was the best among the computing methods in estimating hydro-social indicators for all the world's continents based on statistical criteria [correlation coefficient (R), root mean square error (RMSE), and mean absolute error]. The values of RMSE for GEP models for the ratio of rural to urban population (PRUP), population density, number of internet users and education index parameters equaled (0.084, 0.029, 0.178, 0.135), (0.197, 0.056, 0.152, 0.163), (0.151, 0.036, 0.123, 0.210), (0.182, 0.039, 0.148, 0.204) and (0.141, 0.030, 0.226, 0.082) for Africa, America, Asia, Europe and Oceania, respectively. Scalable equations for hydro-social indicators are developed with applicability at variable spatial and temporal scales worldwide. This paper's results show the patterns of association between social parameters and water resources vary across continents. This study's findings contribute to improving water-resources planning and management considering hydro-social indicators.
水是生命中不可或缺的基本要素。本研究采用水文社会分析方法，基于水资源可用性评估指标状况。评估对象是 2005-2017 年间人均可再生水资源呈下降趋势的国家。非洲、美洲、亚洲、欧洲和大洋洲分别包含 48、35、43、20 和 5 个具有不同气候条件的国家。利用软计算方法[即人工神经网络、自适应神经模糊推理系统和基因表达编程（GEP）]对世界各大洲与农村社会、城市社会、技术与通信以及知识相关的四个水文社会指标进行了估算。基于统计标准（相关系数 R、均方根误差 RMSE 和平均绝对误差 MAE），GEP 模型在估算世界各大洲水文社会指标方面的表现优于其他计算方法。对于农村与城市人口比例（PRUP）、人口密度、互联网用户数量和教育指数参数，GEP 模型的 RMSE 值分别为（0.084、0.029、0.178、0.135）、（0.197、0.056、0.152、0.163）、（0.151、0.036、0.123、0.210）、（0.182、0.039、0.148、0.204）和（0.141、0.030、0.226、0.082），分别对应非洲、美洲、亚洲、欧洲和大洋洲。本文还开发了适用于全球不同时空尺度的水文社会指标可扩展方程。研究结果表明，社会参数与水资源之间的关联模式因大陆而异。本研究的发现有助于在考虑水文社会指标的情况下改进水资源规划和管理。
