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Rational coastal groundwater planning is of great significance to freshwater supply for sustainable social-economic development, and to environmental protection in case of seawater intrusion (SI). Quantifying the relation among groundwater quality, quantity, and the related social-economic benefits in a coastal region with intense spatio-temporal variation in groundwater abstraction is helpful to the restoration of the coastal aquifer, and the practical policymaking. However, due to the comprehensive reality involving interdisciplinary principles, it is usually difficult to integrate all the main attributes of groundwater resources into a mono-policymaking process, which might lead to biased decisions, producing a series of adverse impacts on the environment and the social economy. This study thereby develops a combined simulation-optimization model (S-O model) in the coastal part of Longkou City, China, for striking the balance among the three main attributes of groundwater, i.e., the groundwater quantity, groundwater quality or its environmental function, and its related economic yield involving the agricultural and industrial sectors. It is seen that the industrial sector contributed over 80% of the economic yield by consuming over 10% of the total groundwater resource, and the massive agricultural use of groundwater was mainly responsible for the SI. The results of the multi-objective optimization provided practical alternative schemes for groundwater abstraction in terms of maximizing economic yield and minimizing SI. Moreover, the decision discrepancy caused by partial management only considering the groundwater quantity and quality would lower the water use efficiency, and then cause unacceptable economic losses for the enterprises and the government. Our research highlights that the interdisciplinary management of groundwater resources based on the S-O model could significantly improve practicability in groundwater policymaking, and provides a typical reference for the other developing regions facing difficulty in groundwater management during coastal urban planning and economic transformation., (Copyright © 2022. Published by Elsevier Ltd.)

Hydrometric information collected by monitoring networks is fundamental for effective management of water resources. In recent years, entropy-based multi-objective criterions have been developed for the evaluation and optimization of hydrometric networks, and copula functions have been frequently used in hydrological frequency analysis to model multivariate dependence structures. This study developed a dual entropy-transinformation criterion (DETC) to identify and prioritize significant stations and generate candidate network optimization solutions. The criterion integrated an entropy index computed with mathematical floor function and a transinformation index computed with copula entropy through a tradeoff weight. The best fitted copula models were selected from three Archimedean copula families, i.e., Gumbel, Frank and Clayton. DETC was applied to a streamflow monitoring network in the Fenhe River basin and two rainfall monitoring networks in the Beijing Municipality and the Taihu Lake basin, which covers different network classification, network scale, and climate type. DETC was assessed by the commonly used dual entropy-multiobjective optimization (DEMO) criterion and was compared with a minimum transinformation (MinT) based criterion for network optimization. Results showed that DETC could effectively prioritize stations according to their significance and incorporate decision preference on information content and information redundancy. Comparison of the isohyet maps of two rainstorm events between DETC and MinT showed that DETC had advantage of restoring the spatial distribution of precipitation., (Copyright © 2019 Elsevier Inc. All rights reserved.)