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Groundwater overdraft gives rise to multiple adverse impacts including land subsidence and permanent groundwater storage loss. Existing methods are unable to characterize groundwater storage loss at the global scale with sufficient resolution to be relevant for local studies. Here we explore the interrelation between groundwater stress, aquifer depletion, and land subsidence using remote sensing and model-based datasets with a machine learning approach. The developed model predicts global land subsidence magnitude at high spatial resolution (~2 km), provides a first-order estimate of aquifer storage loss due to consolidation of ~17 km 3 /year globally, and quantifies key drivers of subsidence. Roughly 73% of the mapped subsidence occurs over cropland and urban areas, highlighting the need for sustainable groundwater management practices over these areas. The results of this study aid in assessing the spatial extents of subsidence in known subsiding areas, and in locating unknown groundwater stressed regions. Groundwater overdraft can lead to land subsidence and groundwater storage loss. Here, the authors develop a machine learning-based method to map subsidence globally, explore subsidence drivers, and identify regions under high groundwater stress.

In 2012, consumers paid $32 billion in overdraft fees, representing the single largest source of revenue for banks from demand deposit accounts during this period. Owing to consumer attrition caused by overdraft fees and potential government regulations to reform these fees, financial institutions have become motivated to investigate their overdraft fee structures. Banks need to balance the revenue generated from overdraft fees with consumer dissatisfaction and potential churn caused by these fees. However, no empirical research has been conducted to explain consumer responses to overdraft fees or to evaluate alternative pricing strategies associated with these fees. In this research, we propose a dynamic structural model with consumer monitoring costs and dissatisfaction associated with overdraft fees. We apply the model to an enterprise-level data set of more than 500,000 accounts with a history of 450 days, providing a total of 200 million transactions. We find that consumers heavily discount the future and potentially overdraw because of impulsive spending. However, we also find that high monitoring costs hinder consumers’ effort to track their balance accurately; consequently, consumers may overdraw because of rational inattention. The large data set is necessary because of the infrequent nature of overdrafts; however, it also engenders computational challenges, which we address by using parallel computing techniques. Our policy simulations show that alternative pricing strategies may increase bank revenue and improve consumer welfare. Fixed bill schedules and overdraft waiver programs may also enhance social welfare. This paper explains consumer responses to overdraft fees and evaluates alternative pricing strategies associated with these fees. The online appendices are available at https://doi.org/10.1287/mksc.2018.1106 .

California is currently in the midst of a record-setting drought. The drought began in 2012 and now includes the lowest calendar-year and 12-mo precipitation, the highest annual temperature, and the most extreme drought indicators on record. The extremely warm and dry conditions have led to acute water shortages, groundwater overdraft, critically low streamflow, and enhanced wildfire risk. Analyzing historical climate observations from California, we find that precipitation deficits in California were more than twice as likely to yield drought years if they occurred when conditions were warm. We find that although there has not been a substantial change in the probability of either negative or moderately negative precipitation anomalies in recent decades, the occurrence of drought years has been greater in the past two decades than in the preceding century. In addition, the probability that precipitation deficits co-occur with warm conditions and the probability that precipitation deficits produce drought have both increased. Climate model experiments with and without anthropogenic forcings reveal that human activities have increased the probability that dry precipitation years are also warm. Further, a large ensemble of climate model realizations reveals that additional global warming over the next few decades is very likely to create ∼100% probability that any annual-scale dry period is also extremely warm. We therefore conclude that anthropogenic warming is increasing the probability of co-occurring warm–dry conditions like those that have created the acute human and ecosystem impacts associated with the “exceptional” 2012–2014 drought in California.

The last 60 years has seen unprecedented groundwater extraction and overdraft as well as development of new technologies for water treatment that together drive the advance in intentional groundwater replenishment known as managed aquifer recharge (MAR). This paper is the first known attempt to quantify the volume of MAR at global scale, and to illustrate the advancement of all the major types of MAR and relate these to research and regulatory advancements. Faced with changing climate and rising intensity of climate extremes, MAR is an increasingly important water management strategy, alongside demand management, to maintain, enhance and secure stressed groundwater systems and to protect and improve water quality. During this time, scientific research—on hydraulic design of facilities, tracer studies, managing clogging, recovery efficiency and water quality changes in aquifers—has underpinned practical improvements in MAR and has had broader benefits in hydrogeology. Recharge wells have greatly accelerated recharge, particularly in urban areas and for mine water management. In recent years, research into governance, operating practices, reliability, economics, risk assessment and public acceptance of MAR has been undertaken. Since the 1960s, implementation of MAR has accelerated at a rate of 5%/year, but is not keeping pace with increasing groundwater extraction. Currently, MAR has reached an estimated 10 km3/year, ~2.4% of groundwater extraction in countries reporting MAR (or ~1.0% of global groundwater extraction). MAR is likely to exceed 10% of global extraction, based on experience where MAR is more advanced, to sustain quantity, reliability and quality of water supplies.

Global food consumption drives irrigation for crops, which depletes aquifers in some regions; here we quantify the volumes of groundwater depletion associated with global food production and international trade. International food trade causes water depletion (Dalin 21403, Phys Letter) International trade is increasingly transporting 'hidden' resources and environmental factors from one country to another. For example, the water used to produce a spear of asparagus eaten in London might come from irrigation in South America. Similarly, pollution generated in China might be traceable to consumer demand in the United States. Carole Dalin et al . now extend this idea to the non-renewable groundwater that is consumed for agricultural trade. They find that 11 per cent of groundwater extraction is linked to agricultural trade, with Pakistan, the United States and India accounting for two-thirds of the global totals. The research reveals the degree to which food consumption in one country can lead to groundwater depletion in others, highlighting the need to better consider issues of sustainability and equity in the international food trade. Recent hydrological modelling 1 and Earth observations 2 , 3 have located and quantified alarming rates of groundwater depletion worldwide. This depletion is primarily due to water withdrawals for irrigation 1 , 2 , 4 , but its connection with the main driver of irrigation, global food consumption, has not yet been explored. Here we show that approximately eleven per cent of non-renewable groundwater use for irrigation is embedded in international food trade, of which two-thirds are exported by Pakistan, the USA and India alone. Our quantification of groundwater depletion embedded in the world’s food trade is based on a combination of global, crop-specific estimates of non-renewable groundwater abstraction and international food trade data. A vast majority of the world’s population lives in countries sourcing nearly all their staple crop imports from partners who deplete groundwater to produce these crops, highlighting risks for global food and water security. Some countries, such as the USA, Mexico, Iran and China, are particularly exposed to these risks because they both produce and import food irrigated from rapidly depleting aquifers. Our results could help to improve the sustainability of global food production and groundwater resource management by identifying priority regions and agricultural products at risk as well as the end consumers of these products.

We explore dynamics of limited attention in the $35 billion market for checking overdrafts, using survey content as shocks to the salience of overdraft fees. Conditional on selection into surveys, individuals who face overdraft-related questions are less likely to incur a fee in the survey month. Taking multiple overdraft surveys builds a \"stock\" of attention that reduces overdrafts for up to two years. The effects are significant among consumers with lower education and financial literacy. Individuals avoid overdrafts by making fewer low-balance debit transactions and cancelling automatic recurring withdrawals. The results raise new questions about consumer financial protection policy.

We present PCR-GLOBWB 2, a global hydrology and water resources model. Compared to previous versions of PCR-GLOBWB, this version fully integrates water use. Sector-specific water demand, groundwater and surface water withdrawal, water consumption, and return flows are dynamically calculated at every time step and interact directly with the simulated hydrology. PCR-GLOBWB 2 has been fully rewritten in Python and PCRaster Python and has a modular structure, allowing easier replacement, maintenance, and development of model components. PCR-GLOBWB 2 has been implemented at 5 arcmin resolution, but a version parameterized at 30 arcmin resolution is also available. Both versions are available as open-source codes on https://github.com/UU-Hydro/PCR-GLOBWB_model (Sutanudjaja et al., 2017a). PCR-GLOBWB 2 has its own routines for groundwater dynamics and surface water routing. These relatively simple routines can alternatively be replaced by dynamically coupling PCR-GLOBWB 2 to a global two-layer groundwater model and 1-D–2-D hydrodynamic models. Here, we describe the main components of the model, compare results of the 30 and 5 arcmin versions, and evaluate their model performance using Global Runoff Data Centre discharge data. Results show that model performance of the 5 arcmin version is notably better than that of the 30 arcmin version. Furthermore, we compare simulated time series of total water storage (TWS) of the 5 arcmin model with those observed with GRACE, showing similar negative trends in areas of prevalent groundwater depletion. Also, we find that simulated total water withdrawal matches reasonably well with reported water withdrawal from AQUASTAT, while water withdrawal by source and sector provide mixed results.

Lower prices produce higher demand... or do they? A bank's direct marketing to holders of \"free\" checking accounts shows that a large discount on 60% APR overdrafts reduces overdraft usage, especially when bundled with a discount on debit card or autodebit transactions. In contrast, messages mentioning overdraft availability without mentioning price increase usage. Neither change persists long after the messages stop. These results do not square easily with classical models of consumer choice and firm competition. Instead, they support behavioral models where consumers underestimate and are inattentive to overdraft costs, and firms respond by shrouding overdraft prices in equilibrium.

Soil carbon (C), nitrogen (N) and phosphorus (P) are important soil properties linked to nutrient limitation and plant productivity in terrestrial ecosystems. Up to 90% of the Yellow River Delta (YRD), China has been affected by soil salination due to groundwater overdraft, improper irrigation, land use and land cover change. The objective of this study is to evaluate the impact of different plant communities on soil quality in a saline-alkaline system of the YRD. We investigated the vertical distribution and seasonal variation of soil C, N, and P, and C:N ratio by choosing four dominant plant communities, namely, alfalfa grassland (AG), Chinese tamarisk (CT), locust forest (LF) and cotton field (CF). The results showed that the concentrations of soil organic carbon (SOC) and total nitrogen (TN) in CT and LF were always higher than that in AG and CF, especially in the topsoil layer (p<0.05), then gradually decreased with soil depth increasing (p<0.05). The C:N ratio was generally lower, and the average C:N ratio was higher in LF (11.55±1.99) and CT (11.03±0.47) than in CF (10.05±1.25) and AG (9.11±1.11) (p<0.05). The available phosphorus (AP) was highest in CT in Spring, while it was highest in CF in Summer and Autumn. It is worth noting that the soil AP concentrations were always low, particularly in AG (< 6.29 mg kg-1) and LF (< 4.67 mg kg-1), probably linked to P poorly mobile in the saline-alkaline region. In this study, soil nutrients in natural plant communities are superior to farmland, and are significantly affected by the types of plant community; therefore, we suggest that protection of natural vegetation and development of optimal vegetation are critical to restoring land degradation in the YRD.