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Groundwater markets improve the agricultural economy by transferring water entitlements from low-efficient users to high-efficient ones to maximize productivity. Aiming at developing an efficient groundwater market, the environmental effects of the market mechanism should be assessed, and a reliable method for monitoring water consumption needs to be employed. Toward this end, this paper proposes three annual smart groundwater market mechanisms to maximize water net benefits, minimize groundwater withdrawal, and precisely measure water consumption in agricultural fields. To guarantee the aquifer's safe yield in each mechanism, a groundwater simulation model (i.e., Groundwater Modeling System (GMS)) is used to control groundwater table drawdown at the end of the planning horizon. In addition, the fields' evapotranspiration (ET) is estimated using Surface Energy Balance Algorithm for Land (SEBAL) and Mapping Evapo Transpiration at high Resolution with Internalized Calibration (METRIC) algorithm to measure the net groundwater consumption during the market. In this regard, we evaluated the algorithms' performances using observed data from a local lysimeter. They are applied to the Nough plain in Iran to assess the effectiveness of the proposed market framework. The findings illustrate their efficiency in recovering approximately 80% (23.33 million cubic meters (MCM)) of groundwater loss due to overexploitation in the study area and increasing the users' annual benefits by 10.6% compared to the non-market condition. In addition, results imply that the METRIC model approximates daily crop ET with a higher accuracy level than the SEBAL model with RMSE, MAE, and Percentage Error of 0.37 mm/day, 0.32 mm/day, and 14.92%, respectively. This research revealed that the proposed market framework is a powerful tool for reallocating water entitlements and increasing water productivity in arid and semi-arid regions. • A groundwater market is proposed to promote economic and environmental situation. • The uncertainty of available water is incorporated in the proposed methodolgoy • Designed market mechanisms recover nearly 85% of groundwater loss in the study area. • The market framework raises the economic benefit by 128.7 billion rials annually. • METRIC algorithm approximates daily crop evapotranspiration with RMSE of 0.37 mm. [ABSTRACT FROM AUTHOR]

Understanding the complexity and feedbacks among food, energy, and water (FEW) systems is key to making informed decisions about sustainable development. This paper presents qualitative representation and quantitative system dynamics simulation of the water resources system in the Qazvin Plain, Iran, taking into account the energy intensity of water supply and interconnected water use sectors (e.g., urban, industrial, and agricultural). Qazvin Plain faces water resources challenges that are common to arid/semi-arid areas, including frequent droughts, declining surface water and groundwater, and increased urban and agricultural water demand. A system dynamics model is developed using historical data (2006–2016) to investigate the effects of anticipated dynamics of integrated water and energy sectors in the next two decades. The results of policy scenarios (2020–2039) demonstrate that the continuation of the existing management policies will cause severe damage to the water and energy sectors, pushing the system towards water resources limits to growth. An annual groundwater table decline of nearly 1 m is anticipated, indicating significant overshoot of the plain's natural recharge capacity, which may lead to the depletion of recoverable groundwater in the plain within the next three decades. The groundwater table decline will cause energy consumption of water supply to increase by about 32% (i.e., 380 GWh) to maintain irrigated agriculture. It is critical to implement a combination of water demand and supply management policies (e.g., net agricultural water savings and recycling treated wastewater) to delay the problem of water limits to growth in the region. • We present a system dynamics of model integrated water and energy sectors in an agricultural region. • The model facilitates evaluation of water management policies using a food-energy water nexux approach. • Policies that facilitate net agricultural water savings and water reuse can delay groundwater depletion. [ABSTRACT FROM AUTHOR]

Today, an increase in the drought and water shortage all around the world is a challengeable threat for different governments and international committees. Water supply chain aims to manage the water consumption and to control the water shortage. Contrary to most of previous studies focused on the forward directions of the water supply chain, this paper also considers the reverse logistics known as a Closed-Loop Supply Chain (CLSC). Hence, an integrated Water Supply and Wastewater Collection System (WSWCS) under uncertainty is proposed. Furthermore, regarding the trend of sustainable development, the environmental dimensions and social benefits of the integrated WSWCS are contributed. To meet the standards of the sustainable development in developing countries, a case study in Iran is applied to a novel multi-objective stochastic optimization model based on triple bottom lines of sustainability. Having already been employed to similar optimization problems, the Social Engineering Optimizer (SEO) has been never applied in this research area. Another innovation of this study is to introduce an improved multi-objective SEO to solve this complicated model. Eventually, with regards to an extensive comparison contributing to the Pareto-based metrics and different sensitivities, some managerial implications are concluded as the main findings. • Developing a novel multi-objective stochastic optimization model to design a sustainable water supply network. • Considering triple bottom lines of sustainability for an integrated water supply and wastewater collection system. • Applying the life cycle assessment method to estimate the sustainability aspects. • Solving the case study of Urmia Lake by an improved social engineering optimizer. [ABSTRACT FROM AUTHOR]