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Incentive pricing programs have potential to promote economically efficient water use patterns and provide a revenue source to compensate for environmental damages. However, incentive pricing may impose disproportionate costs and aggravate poverty where high prices are levied for basic human needs. This paper presents an analysis of a two-tiered water pricing system that sets a low price for subsistence needs, while charging a price equal to marginal cost, including environmental cost, for discretionary uses. This pricing arrangement can promote efficient and sustainable water use patterns, goals set by the European Water Framework Directive, while meeting subsistence needs of poor households. Using data from the Rio Grande Basin of North America, a dynamic nonlinear program, maximizes the basin's total net economic and environmental benefits subject to several hydrological and institutional constraints. Supply costs, environmental costs, and resource costs are integrated in a model of a river basin's hydrology, economics, and institutions. Three programs are compared: (1) Law of the River, in which water allocations and prices are determined by rules governing water transfers; (2) marginal cost pricing, in which households pay the full marginal cost of supplying treated water; (3) two-tiered pricing, in which households' subsistence water needs are priced cheaply, while discretionary uses are priced at efficient levels. Compared to the Law of the River and marginal cost pricing, two-tiered pricing performs well for efficiency and adequately for sustainability and equity. Findings provide a general framework for formulating water pricing programs that promote economically and environmentally efficient water use programs while also addressing other policy goals.

Aquifers are ubiquitous, and their water is easy to obtain with low extraction costs. On many occasions, these characteristics lead to overexploitation due to important water level declines, reduction of river base flows, enhanced seawater intrusion, and wetland affection. The forecasted increase in water demands and global warming will impact the future availability of water resources. Conjunctive use of surface and subsurface waters can help in mitigating these impacts. There are two main conjunctive use strategies: artificial recharge (AR) and alternate conjunctive use (ACU). AR stores waters that are not to be used directly in aquifers. ACU utilizes groundwater in dry periods, while surface waters are preferred in wet ones; this allows the increase of water supply with lower dam storage, economic gains, and environmental advantages. Efficient conjunctive use can prevent soil salinization and waterlogging problems in semiarid countries due to excessive recharge from irrigation return flows or other origins. Groundwater is a neglected and generally misused resource to maintain environmental conditions. When considering the solution to a water resources problem, groundwater should always be part of the design as an alternative or a complementary resource. Aquifers have large inertia, and changes in their volumes are only noticeable after years of observations. Unfortunately, groundwater observation networks are much poorer than surface ones, something that should be changed if groundwater is to come to the rescue in these times of climate change. Human and material resources should be made available to monitor, control, analyze, and forecast groundwater. [ABSTRACT FROM AUTHOR]

Socio-economic costs of drought are progressively increasing worldwide due to undergoing alterations of hydro-meteorological regimes induced by climate change. Although drought management is largely studied in the literature, traditional drought indexes often fail at detecting critical events in highly regulated systems, where natural water availability is conditioned by the operation of water infrastructures such as dams, diversions, and pumping wells. Here, ad hoc index formulations are usually adopted based on empirical combinations of several, supposed-to-be significant, hydro-meteorological variables. These customized formulations, however, while effective in the design basin, can hardly be generalized and transferred to different contexts. In this study, we contribute FRIDA (FRamework for Index-based Drought Analysis), a novel framework for the automatic design of basin-customized drought indexes. In contrast to ad hoc empirical approaches, FRIDA is fully automated, generalizable, and portable across different basins. FRIDA builds an index representing a surrogate of the drought conditions of the basin, computed by combining all the relevant available information about the water circulating in the system identified by means of a feature extraction algorithm. We used the Wrapper for Quasi-Equally Informative Subset Selection (W-QEISS), which features a multi-objective evolutionary algorithm to find Pareto-efficient subsets of variables by maximizing the wrapper accuracy, minimizing the number of selected variables, and optimizing relevance and redundancy of the subset. The preferred variable subset is selected among the efficient solutions and used to formulate the final index according to alternative model structures. We apply FRIDA to the case study of the Jucar river basin (Spain), a drought-prone and highly regulated Mediterranean water resource system, where an advanced drought management plan relying on the formulation of an ad hoc "state index" is used for triggering drought management measures. The state index was constructed empirically with a trial-and-error process begun in the 1980s and finalized in 2007, guided by the experts from the Confederación Hidrográfica del Júcar (CHJ). Our results show that the automated variable selection outcomes align with CHJ's 25-year-long empirical refinement. In addition, the resultant FRIDA index outperforms the official State Index in terms of accuracy in reproducing the target variable and cardinality of the selected inputs set. [ABSTRACT FROM AUTHOR]

This paper presents a collaborative framework to couple historical records with expert knowledge and criteria to define a decision support system (DSS) that supports the seasonal operation of the reservoirs of the Jucar River system. The framework relies on the codevelopment of a DSS tool that is able to explicitly reproduce the decision-making processes and criteria considered by the system operators. Fuzzy logic is used to derive the implicit operating rules followed by the managers, and is based on historical decisions and expert knowledge obtained in the codevelopment process, combining both sources of information. Fuzzy regression is used to forecast future inflows based on the meteorological and hydrological variables considered by the system operators in their decisions on reservoir operation. The DSS was validated against historical records. The developed framework and tools offer the system operators a way to predefine a set of feasible ex ante management decisions, and to explore the consequences associated with any single choice. In contrast with other approaches, the fuzzy-based method used in this study is able to embed inflow uncertainty and its effects in the definition of the decisions on the system operation. Furthermore, the method is flexible enough to be applied to other water resource systems. [ABSTRACT FROM AUTHOR]

The high uncertainty associated with the effect of global change on water resource systems calls for a better combination of conventional top–down and bottom–up approaches, in order to design robust adaptation plans at the local scale. The methodological framework presented in this article introduces “bottom–up meets top–down” integrated approach to support the selection of adaptation measures at the river basin level by comprehensively integrating the goals of economic efficiency, social acceptability, environmental sustainability and adaptation robustness. The top–down approach relies on the use of a chain of models to assess the impact of global change on water resources and its adaptive management over a range of climate projections. Future demand scenarios and locally prioritised adaptation measures are identified following a bottom–up approach through a participatory process with the relevant stakeholders and experts. The optimal combinations of adaptation measures are then selected using a hydro-economic model at basin scale for each climate projection. The resulting adaptation portfolios are, finally, climate checked to define a robust least-regret programme of measures based on trade-offs between adaptation costs and the reliability of supply for agricultural demands. This innovative approach has been applied to a Mediterranean basin, the Orb river basin (France). Mid-term climate projections, downscaled from 9 General Climate Models, are used to assess the uncertainty associated with climate projections. Demand evolution scenarios are developed to project agricultural and urban water demands on the 2030 time horizon. The results derived from the integration of the bottom–up and top–down approaches illustrate the sensitivity of the adaptation strategies to the climate projections, and provide an assessment of the trade-offs between the performance of the water resource system and the cost of the adaptation plan to inform local decision-making. The article contributes new methodological elements for the development of an integrated framework for decision-making under climate change uncertainty, advocating an interdisciplinary approach that bridges the gap between bottom–up and top–down approaches. [ABSTRACT FROM AUTHOR]

Summary: Future water management will shift from building new water supply systems to better operating existing ones. The variation of water values in time and space will increasingly motivate efforts to address water scarcity and reduce water conflicts. Hydro-economic models represent spatially distributed water resource systems, infrastructure, management options and economic values in an integrated manner. In these tools water allocations and management are either driven by the economic value of water or economically evaluated to provide policy insights and reveal opportunities for better management. A central concept is that water demands are not fixed requirements but rather functions where quantities of water use at different times have varying total and marginal economic values. This paper reviews techniques to characterize the economic value of water use and include such values in mathematical models. We identify the key steps in model design and diverse problems, formulations, levels of integration, spatial and temporal scales, and solution techniques addressed and used by over 80 hydro-economic modeling efforts dating back 45-years from 23 countries. We list current limitations of the approach, suggest directions for future work, and recommend ways to improve policy relevance. [Copyright &y& Elsevier]

Abstract: Combined hydro-economic models of river basins are fundamental tools for assessing management and infrastructure strategies to improve the economic efficiency of water use in a context of competition over scarce water resources. Integrated hydro-economic models have to be capable to properly reproduce the physical behavior of the system, with a realistic representation of the different surface and groundwater resources, including their interaction, and the spatial and temporal variability of resource availability. On the other hand, such models must incorporate the value of water for different urban, agricultural and industrial uses and users. Economic values for water use are defined according to the marginal residual value of water for production (for agricultural and industrial uses) or the aggregated willingness-to-pay (WTP) for urban supply and other final water uses. In this paper, we present a systematic approach to estimate the marginal economic value of surface and groundwater resources at different locations within a complex water resources system. Based on a holistic conjunctive optimization model applied to the Adra river system in Spain we asses the total and marginal opportunity costs of capacity and operation constraints, including the opportunity cost of imposing environmental constraints on water use as foreseen in future Spanish water policy following the implementation of the European Water Framework Directive. The resulting opportunity costs provide important information to water managers about economic inefficiencies of current water allocation policy or infrastructure design, and about the resource opportunity costs to be considered in the design of efficient pricing policies in regions with water scarcity issues. [Copyright &y& Elsevier]

The management of water in systems where the balance between resources and demands is already precarious can pose a challenge and it can be easily disrupted by drought episodes. Anticipated drought management has proved to be one of the main strategies to reduce their impact. Drought economic, environmental, and social impacts affect different sectors that are often interconnected. There is a need for water management models able to acknowledge the complex interactions between multiple sectors, activities, and variables to study the response of water resource systems to drought management strategies. System dynamics (SD) is a modeling methodology that facilitates the analysis of interactions and feedbacks within and between sectors. Although SD has been applied for water resource management, there is a lack of SD models able to regulate complex water resource systems on a monthly time scale and considering multiple reservoir operating rules, demands, and policies. In this paper, we present an SD model for the strategic planning of drought management in the Jucar River system, incorporating dynamic reservoir operating rules, policies, and drought management strategies triggered by a system state index. The DSS combines features from early warning and information systems, allowing for the simulation of drought strategies, evaluating their economic impact, and exploring new management options in the same environment. The results for the historical period show that drought early management can be beneficial for the performance of the system, monitoring the current state of the system, and activating drought management measures results in a substantial reduction of the economic impact of droughts. [ABSTRACT FROM AUTHOR]

Coordinated and efficient operation of water resource systems becomes essential to deal with growing demands and uncertain resources in water‐stressed regions. System analysis models and tools help address the complexities of multireservoir systems when defining operating rules. This paper reviews the state of the art in developing operating rules for multireservoir water resource systems, focusing on efficient system operation. This review focuses on how optimal operating rules can be derived and represented. Advantages and drawbacks of each approach are discussed. Major approaches to derive optimal operating rules include direct optimization of reservoir operation, embedding conditional operating rules in simulation‐optimization frameworks, and inferring rules from optimization results. Suggestions on which approach to use depend on context. Parametrization–simulation–optimization or rule inference using heuristics are promising approaches. Increased forecasting capabilities will further benefit the use of model predictive control algorithms to improve system operation. This article is categorized under:Engineering Water > Water, Health, and SanitationEngineering Water > Methods [ABSTRACT FROM AUTHOR]

Shaping global change adaptation strategy in water resource systems requires an interdisciplinary approach to deal with the multiple dimensions of the problem. The modelling framework presented integrates climate, economic, agronomic and hydrological scenarios to design a programme of adaptation measures at the river basin scale. Future demand scenarios, combined with a down-scaled climate scenario, provide the basis to estimate the demand and water resources in 2030. A least-cost river basin optimisation model is then applied to select adaptation measures ensuring that environmental and supply management goals are achieved. In the Orb river basin (France), the least-cost portfolio selected suggests mixing demand and supply side measures to adapt to global change. Trade-offs among the cost of the programme of measures, the deficit in agricultural water supply and the level of environmental flows are investigated. The challenges to implement such interdisciplinary approaches in the definition of adaptation strategies are finally discussed. [ABSTRACT FROM AUTHOR]

• CIRFs are useful for exploring risks of system failure under climate change. • Synthetic streamflow series are generated using SA and linked to climate conditions. • Logistic regression relates system responses to climate drivers. • System failure defined according to performance (reliability) and threshold. • LR model detects climate conditions which would require adaptation. Climate Impact Response Functions (CIRFs) can be useful for exploring potential risks of system failure under climate change. The performance of a water resource system can be synthesized through a CIRF that relates climate conditions to system behavior in terms of a specified threshold of deliveries to demands or environmental flow requirements. However, in highly regulated water resource systems this relationship may be quite complex, depending on storage capacity and system operation. In this paper we define a CIRF for these types of systems through a multivariable logistic regression (LR) model where a binary variable (system response) is explained by two continuous variables or predictors (precipitation and temperature). The approach involves generating multivariate synthetic inflow time series and relating them to specific climate conditions. Next, these inflows are used as inputs in a water management model, and the outcome is coded as a binary variable (failure or its absence) depending on selected vulnerability criteria. To identify the time span before the failure event in which climate variables are relevant, we characterized drought development stages through relative standardized indices. Mean values of precipitation and temperature for the selected time span are computed and used as explanatory variables through a LR model, which is validated using data from several climate models and scenarios. Results show that the predictive capacity of LR models is acceptable, so that they could be used as screening tools to detect challenging climate conditions for the system which would require adaption actions. [ABSTRACT FROM AUTHOR]

Meta-analyses synthesise available data on a phenomenon to get a broader understanding of its determinants. This work proposes a two-step methodology. 1) Based on a broad dataset of residential water demand studies, it builds a meta-regression model to estimate mean and standard deviation of price elasticity of residential water demand. 2) The resulting meta-model serves as a basis for implementing an approach that directly simulates the range of price elasticities resulting from policy-relevant combinations of its determinants. This simulation approach is validated using the available dataset. Despite evidence of low average price elasticity, the scenarios simulated using our meta-regression estimates show that increasing block rate tariffs are associated with higher price elasticity, and stresses the importance of using state-of-the-art methodologies when evaluating the price response. This completes other methodological insights obtained from the meta-analysis itself. Policy implications on the use of pricing to bring about water savings are discussed. [ABSTRACT FROM AUTHOR]

Abstract: When linearity can be assumed (linear response of heads to stresses), stream–aquifer flow exchange can be simulated as the drainage of a number of independent linear reservoirs. This conceptual model, which can be mathematically deduced in a univocal way from an eigenvalue solution of the linear groundwater flow problem, facilitates the understanding of the physical phenomenon and the analysis of influencing factors. The number of reservoirs required to simulate stream depletion in some ideal homogeneous cases of stream–aquifer connection was analyzed in detail in a previous investigation using analytical eigenvalue solutions . However, most aquifers are heterogeneous in nature and numerical solutions must be employed to analyze whether they could also be simulated using few reservoirs. This paper presents a stochastic analysis of the influence of heterogeneity on the simulation of natural groundwater discharges in aquifers connected to rivers, as a series of linear reservoirs. A Monte-Carlo approach was employed to perform this study. The results show that, on a monthly time scale, many cases (even heterogeneous aquifers) can be simulated using just a few reservoirs with sufficient accuracy and at minimum computational cost. Therefore, this modeling technique can be useful to efficiently simulate the integrated management of complex water resources systems at the basin scale (with many aquifers, reservoirs, demands, etc.) that need to simultaneously consider surface and groundwater flow and stream–aquifer interaction. [Copyright &y& Elsevier]