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Driven by the need for integrated management of groundwater (GW) and surface water (SW), quantification of GW–SW interactions and associated contaminant transport has become increasingly important. This is due to their substantial impact on water quantity and quality. In this review, we provide an overview of the methods developed over the past several decades to investigate GW–SW interactions. These methods include geophysical, hydrometric, and tracer techniques, as well as various modeling approaches. Different methods reveal valuable information on GW–SW interactions at different scales with their respective advantages and limitations. Interpreting data from these techniques can be challenging due to factors like scale effects, heterogeneous hydrogeological conditions, sediment variability, and complex spatiotemporal connections between GW and SW. To facilitate the selection of appropriate methods for specific sites, we discuss the strengths, weaknesses, and challenges of each technique, and we offer perspectives on knowledge gaps in the current science. 

Abstract Scarce and unreliable urban water supply in many countries has caused municipal users to rely on transfers from rural wells via unregulated markets. Assessments of this pervasive water re-allocation institution and its impacts on aquifers, consumer equity and affordability are lacking. We present a rigorous coupled human–natural system analysis of rural-to-urban tanker water market supply and demand in Jordan, a quintessential example of a nation relying heavily on such markets, fed by predominantly illegal water abstractions. Employing a shadow-economic approach validated using multiple data types, we estimate that unregulated water sales exceed government licences 10.7-fold, equalling 27% of the groundwater abstracted above sustainable yields. These markets supply 15% of all drinking water at high prices, account for 52% of all urban water revenue and constrain the public supply system’s ability to recover costs. We project that household reliance on tanker water will grow 2.6-fold by 2050 under population growth and climate change. Our analysis suggests that improving the efficiency and equity of public water supply is needed to ensure water security while avoiding uncontrolled groundwater depletion by growing tanker markets. 

Abstract Scarce and unreliable urban water supply in many countries has caused municipal users to rely on transfers from rural wells via unregulated markets. Assessments of this pervasive water re-allocation institution and its impacts on aquifers, consumer equity and affordability are lacking. We present a rigorous coupled human–natural system analysis of rural-to-urban tanker water market supply and demand in Jordan, a quintessential example of a nation relying heavily on such markets, fed by predominantly illegal water abstractions. Employing a shadow-economic approach validated using multiple data types, we estimate that unregulated water sales exceed government licences 10.7-fold, equalling 27% of the groundwater abstracted above sustainable yields. These markets supply 15% of all drinking water at high prices, account for 52% of all urban water revenue and constrain the public supply system’s ability to recover costs. We project that household reliance on tanker water will grow 2.6-fold by 2050 under population growth and climate change. Our analysis suggests that improving the efficiency and equity of public water supply is needed to ensure water security while avoiding uncontrolled groundwater depletion by growing tanker markets. 

In India, the second-largest sugarcane producing country in the world, accurate mapping of sugarcane land is a key to designing targeted agricultural policies. Such a map is not available, however, as it is challenging to reliably identify sugarcane areas using remote sensing due to sugarcane’s phenological characteristics, coupled with a range of cultivation periods for different varieties. To produce a modern sugarcane map for the Bhima Basin in central India, we utilized crowdsourced data and applied supervised machine learning (neural network) and unsupervised classification methods individually and in combination. We highlight four points. First, smartphone crowdsourced data can be used as an alternative ground truth for sugarcane mapping but requires careful correction of potential errors. Second, although the supervised machine learning method performs best for sugarcane mapping, the combined use of both classification methods improves sugarcane mapping precision at the cost of worsening sugarcane recall and missing some actual sugarcane area. Third, machine learning image classification using high-resolution satellite imagery showed significant potential for sugarcane mapping. Fourth, our best estimate of the sugarcane area in the Bhima Basin is twice that shown in government statistics. This study provides useful insights into sugarcane mapping that can improve the approaches taken in other regions. 

Systems models of the Food–Water–Energy (FWE) nexus face a conceptual difficulty: the systematic integration of local stakeholder perspectives into a coherent framework for analysis. We present a novel procedure to co-produce and systematize the real-life complexity of stakeholder knowledge and forge it into a clear-cut set of challenges. These are clustered into the Pressure–State–Response (PSIR) framework, which ultimately guides the development of a conceptual systems model closely attuned to the needs of local stakeholders. We apply this approach to the case of the emerging megacity Pune and the Bhima basin in India. Through stakeholder workshops, involving 75 resource users and experts, we identified 22 individual challenges. They include exogenous pressures, such as climate change and urbanization, and endogenous pressures, such as agricultural groundwater over-abstraction and land use change. These pressures alter the Bhima basin’s system state, characterized by inefficient water and energy supply systems and regional scarcity. The consequent impacts on society encompass the inadequate provision with food, water, and energy and livelihood challenges for farmers in the basin. An evaluation of policy responses within the conceptual systems model shows the complex cause–effect interactions between nexus subsystems. One single response action, such as the promotion of solar farming, can affect multiple challenges. The resulting concise picture of the regional FWE system serves resource users, policymakers, and researchers to evaluate long-term policies within the context of the urban FWE system. While the presented results are specific to the case study, the approach can be transferred to any other FWE nexus system. 

Abstract Sugar is the second largest agro-based industry in India and has a major influence on the country’s water, food, and energy security. In this paper, we use a nexus approach to assess India’s interconnected water-food-energy challenges, with a specific focus on the political economy of the sugar industry in Maharashtra, one of the country’s largest sugar producing states. Our work underscores three points. First, the governmental support of the sugar industry is likely to persist because policymakers are intricately tied to that industry. Entrenched political interests have continued policies that incentivize sugar production. As surplus sugar has been produced, the government introduced additional policies to reduce this excess and thereby protect the sugar industry. Second, although the sugar economy is important to India, sugar policies have had detrimental effects on both water and nutrition. Long-standing government support for sugarcane pricing and sales has expanded water-intensive sugarcane irrigation in low-rainfall areas in Maharashtra, which has reduced the state’s freshwater resources and restricted irrigation of more nutritious crops. Despite its poor nutritional value, empty-calorie sugar has been subsidized through the public distribution system. Third, the Indian government is now promoting sugarcane-based ethanol production. This policy has the benefit of providing greater energy security and creating a new demand for surplus sugar in the Indian market. Our analysis shows that a national biofuel policy promoting the production of ethanol from sugarcane juice versus directly from molasses may help reduce subsidized sugar for human consumption without necessarily expanding water and land use for additional production of sugarcane. 

The quantification of impervious surface through remote sensing provides critical information for urban planning and environmental management. The acquisition of quality reference data and the selection of effective predictor variables are two factors that contribute to the low accuracies of impervious surface in urban remote sensing. A hybrid method was developed to improve the extraction of impervious surface from high-resolution aerial imagery. This method integrates ancillary datasets from OpenStreetMap, National Wetland Inventory, and National Cropland Data to generate training and validation samples in a semi-automatic manner, significantly reducing the effort of visual interpretation and manual labeling. Satellite-derived surface reflectance stability is incorporated to improve the separation of impervious surface from other land cover classes. This method was applied to 1-m National Agriculture Imagery Program (NAIP) imagery of three sites with different levels of land development and data availability. Results indicate improved extractions of impervious surface with user’s accuracies ranging from 69% to 90% and producer’s accuracies from 88% to 95%. The results were compared to the 30-m percent impervious surface data of the National Land Cover Database, demonstrating the potential of this method to validate and complement satellite-derived medium-resolution datasets of urban land cover and land use.