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The study of land subsidence has recently been expanded due to its increased occurrence and magnitude worldwide. This paper develops and applies an optimal control model of groundwater extractions under conditions of land subsidence. We include, in a traditional groundwater management model, two types of negative externalities associated with land subsidence: damage to infrastructure and to economic activities, and the loss of aquifer storage capacity. Using a two-stage optimal control method, characterized by two sub-problems corresponding to the phase before and after the occurrence of subsidence, we find the economically sustainable paths of groundwater extractions and water table levels under the existence of land subsidence impacts. The theoretical results indicate that the presence of land subsidence dictates the optimal paths of groundwater withdrawals and water table levels. The model has been applied to the Alto Guadalentín over-exploited aquifer system in the Segura River Basin of Spain. The empirical outcomes indicate that by following the optimal paths, groundwater extractions should be curtailing to avoid reaching the critical water level at which subsidence takes place. Results suggest that regional net present value of welfare over the planning period, under the two land subsidence scenarios, is reduced by nearly 1–5%, compared to the no land subsidence scenario. Furthermore, under subsidence, even with relatively small impacts of both types of externalities, groundwater optimal extractions are kept at levels that avoid these externalities. These outcomes clearly call for government intervention in order to reduce groundwater withdrawals in aquifers with propensity to face undesirable subsidence effects. • LS due to aquifers overused causes major social costs with irreversible impacts. • LS has not received proper attention by regulators and the economic damages are not accurately assessed. • This paper develops a groundwater optimization model including negative externalities of LS. • In presence of subsidence, even with small impacts, groundwater management is necessary. • The results call for government intervention to curtail groundwater withdrawals to face LS. [ABSTRACT FROM AUTHOR]

The presence of trace elements in water for domestic supply or irrigation could pose a significant toxic risk for health, due to direct consumption or bioaccumulation through the ingestion of vegetables irrigated with this water. This paper studies the presence of 41 trace elements plus nitrate and bromate in groundwater, using a multivariate statistical tool based on Principal Component Analysis and a geostatistical Kriging method to map the results. Principal Component Analysis revealed 11 significant principal components, which account for 82% and 81% of the total variance (information) respectively for the two dates analysed. Ordinary Kriging was applied to draw maps of the trace elements and PC scores. This research breaks new ground in terms of the large number of parameters used and in terms of the analysis of spatiotemporal variations in these parameters. The results obtained indicate that PC1 represents the natural quality of the aquifer (geogenic) and that there is little change in the average PC1 value between the two dates studied (June near the peak recharge point and November at the end of summer). Agriculture is the human activity that causes the greatest variations in the quality of the groundwater due to the use of fertilizers and due to watering crops with wastewater (PC7_J and PC5_N, June and November, respectively). Other elements of industrial origin, which are dangerous for human health, such as Pb, Cu and Cd, are grouped together in other principal components. The results show that the decline, or even complete absence, of natural recharge during the summer months leads to an increase in the TEs produced by human activity. This indicates that a temporary reduction in the natural recharge could worsen the quality of water resources. Based on the interpretation of the estimated maps, a synthetic map was created to show the spatial distribution of the areas affected by geogenic and anthropogenic factors. Studies with a global approach like this one are necessary in that the possible sources of pollution that could alter the quality of the groundwater and the amount of trace elements and other potentially harmful substances could increase as time goes by. The main advantage of the methodology proposed here is that it reduces the number of parameters, so simplifying the results. This makes it easier to interpret the results and manage the quality of the water. • PCA and geostatistical methods were used to establish the spatiotemporal variations in 41 trace elements. • A complex spatial relationship between anthropogenic and geogenic activities was reduced to just six categories. • The anthropogenic activity with the greatest impact on groundwater quality is agriculture. • Evaporitic rocks were the main cause of geogenic contamination of the groundwater. [ABSTRACT FROM AUTHOR]

In wastewater treatment plants (WWTPs), the stochastic nature of influent wastewater and operational and weather conditions cause fluctuations in effluent quality. Data-driven models can forecast effluent quality a few hours ahead as a response to the influent characteristics, providing enough time to adjust system operations and avoid undesired consequences. However, existing data for training models are often incomplete and contain missing values. On the other hand, collecting additional data by installing new sensors is costly. The trade-off between using existing incomplete data and collecting costly new data results in three data challenges faced when developing data-driven WWTP effluent forecasters. These challenges are to determine important variables to be measured, the minimum number of required data instances, and the maximum percentage of tolerable missing values that do not impede the development of an accurate model. As these issues are not discussed in previous studies, in this research, for the first time, a comprehensive analysis is done to provide answers to these challenges. Another issue that arises in all data-driven modeling is how to select an appropriate forecasting model. This paper addresses these issues by first testing nine machine learning models on data collected from three wastewater treatment plants located in Iran, Australia, and Spain. The most accurate forecaster, Bayesian network, was then used to address the articulated challenges. Key variables in forecasting effluent characteristics were flow rate, total suspended solids, electrical conductivity, phosphorus compounds, wastewater temperature, and air temperature. A minimum of 250 samples was needed during the model training to achieve a great reduction in the forecasting error. Moreover, a steep increase in the error was observed should the portion of missing values exceed 10%. The results assist plant managers in estimating the necessary data collection effort to obtain an accurate forecaster, contributing to the quality of the effluent. [Display omitted] • Bayesian network is benchmarked against eight AI models to predict wastewater quality. • Bayesian networks can handle missing value in input data due to probabilistic nature. • Key variables in WWTP quality and quantity were specified. • Input data quality has a huge role in successful development of data-driven models. • The prediction error sharply increases when the portion of missing data exceeds 10%. [ABSTRACT FROM AUTHOR]

Climate change has intensified the effects of habitat fragmentation in many ecosystems, particularly exacerbated in riparian habitats. Therefore, there is an urgent need to identify keystone connectivity spots to ensure long-term conservation and sustainable management of riparian systems as they play a crucial role for landscape connectivity. This paper aims to identify critical areas for connectivity under two contrasting climate change scenarios (RCP 4.5 and RCP 8.5 models) for the years 2030, 2050 and 2100 and to group these critical areas by similar connectivity in keystone spots for sustainable management. A set of analyses comprising climate analysis, drainage network analysis, configuration of potential riparian habitats, riparian habitat connectivity, data clustering, and statistical analysis within a Spanish river basin (NW Spain) were applied. The node and link connectivity would be reduced under the two climate change scenarios (≈2.5 % and 4.4 % reduction, respectively), intensifying riparian habitat fragmentation. Furthermore, 51 different clusters (critical areas) were obtained and classified in five classes (keystone spots) with similar connectivity across the different scenarios of climate change. Each keystone spot obtained by hierarchical classification was associated with one or more climate scenarios. One of these keystone spots was especially susceptible to the worst climate change scenario. Key riparian connectivity spots will be crucial for the management and restoration of highly threatened riparian systems and to ensure long-term biodiversity conservation. • Connectivity importance was reduced under different climate change scenarios. • Critical area detection for connectivity conservation is threatened by climate change. • Critical areas were classified with similar connectivity keystone spots against climate change. • Keystone spots with high PC index will be priority for conservation management. [ABSTRACT FROM AUTHOR]

Blockchain constitutes a disruptive technology that is currently changing business models and the way organizations operate. This paper explores the applicability of blockchain technology, and of distributed ledger technologies in general, to urban water supply and sanitation services in Spain. The potential of this technology for improving processes in this sector is assessed through a specific methodology of strategic analysis developed for this purpose. First, the technical, legal and managerial factors that condition the potential use of this technology to address the global, operational and governance challenges faced by urban water management are explored. Second, strategic analysis tools (e.g. value chain, factors of competition, and benchmarking) are used to model a water utility organization as a set of processes and characterize blockchain as an enabling technology with both benefits (traceability, immutability, and disintermediation) and limitations. Based on cost-benefit analysis, use cases in which the implementation of a blockchain could improve the organization's performance can be discerned. The results identify the processes and sub-processes of urban water utility management for which the use of a blockchain could improve performance: comprehensive maintenance, the management of serious incidents, and supplier management. Essentially, the methodology developed identifies management processes whose requirements are efficiently met through automation derived from blockchain solutions. Regardless of the management models currently in place in Spain, the traceability and disintermediation benefits of blockchain solutions can help to overcome governance and efficiency challenges associated with the management of urban water supply and sanitation services. • Disintermediation makes distributed ledger technology a disruptive technology. • Blockchain is an enabling technology for support processes in water management. • Strategic analysis identifies use cases where blockchain improves process management. • Smart contracts and traceability optimize the management of suppliers and incidents. [ABSTRACT FROM AUTHOR]

Resource depletion and environmental pollution are increasingly a matter of concern for their adverse effects on ecosystems, human health, and the economy. Circular Economy (CE) practices can help us address these challenges. This paper proposes a composite circularity index (CI) to assess the level of implementation of CE practices. The main advantage of the proposed index is its ability to combine multiple indicators of circularity for different units operating in a given sector (given as inputs), using a 'Benefit of the Doubt' model. This new model is innovative in the manner it deals with ordinal scales and also by considering both relative and absolute performance indices. These indices are computed using mathematical programming tools, building on ideas from Data Envelopment Analysis models. Although the model can be applied to any sector, this work addresses the hotel industry in particular. The selection of indicators for this CI was based on seven blocks of the Circular Economy Action Plan and a literature review of circular practices. An application of the proposed index is performed by using data from Portuguese and Spanish hotels. The proposed CI allows the identification of the organizations with the best and worst performance in implementing the CE practices and clarifying the benchmarks they could follow to improve their level of circularity. Moreover, the index analysis also provides specific targets for improvement, indicating which circular practices should be improved for the lower performers to reach the implementation levels of the best performers. • A circularity index based on DEA and the Circular Economy Action Plan is developed. • The circularity index is customized and applied to 51 hotels in Portugal and Spain. • Targets and priorities aimed at reducing hotels' footprint are discussed. • The method proposed offers potential for application in many other sectors. • 19 hotels are efficient, and the average efficiency is 85.26% in a relative assessment. [ABSTRACT FROM AUTHOR]

Climate change is expected to increase the number of days with meteorological conditions conducive to uncontrollable wildfires. Thus, it is necessary to strengthen the capacity of wildfire-prone regions to minimize the adverse impacts of these wildfires by creating resilient landscapes. In this paper we develop a participatory multi-criteria evaluation to identify and map landscape values and prioritize areas according to these values in the Montseny Biophere Reserve (Catalonia, NE Spain). Then, we draft a wildfire management strategy to protect the areas that have been prioritized through selected fuel reduction sectors that would reduce wildfire intensity. Finally, we emphasize the added value of a participatory multi-criteria evaluation in the adaptation to and management of expected megafires. We find that the integration of landscape values through participatory multi-criteria evaluation has the potential to alter wildfire management strategies by adding fuel reduction sectors and changing their implementation order. However, the implementation of the planned fuel reduction treatments faces socioeconomic and institutional barriers that call for a deeper engagement with transdisciplinary project design and transformative science. • A participatory multi-criteria evaluation approach is applied to develop a fire management strategy. • The prioritized areas to protect against wildfires are those containing a great number and diversity of landscape values. • The fire management strategy is based on spatially targeted fuel reduction treatments. • The outcome of the evaluation determines where and in which order fuel reduction treatments should be implemented. [ABSTRACT FROM AUTHOR]

The Soil and Water Assessment Tool (SWAT) is a well-established eco-hydrological model that has been extensively applied to watersheds across the globe. This work reviews over two decades (2002–2022) of SWAT studies conducted on Mediterranean watersheds. A total of 260 articles have been identified since the earliest documented use of the model in a Mediterranean catchment back in 2002; of which 62% were carried out in Greece, Italy, or Spain. SWAT applications increased significantly in recent years since 86% of the reviewed papers were published in the past decade. A major objective for most of the reviewed works was to check the applicability of SWAT to specific watersheds. A great number of publications included procedures of calibration and validation and reported performance results. SWAT applications in the Mediterranean region mainly cover water resources quantity and quality assessment and hydrologic and environmental impacts evaluation of land use and climate changes. Nevertheless, a tendency towards a multi-purpose use of SWAT is revealed. The numerous examples of SWAT combined with other tools and techniques outline the model's flexibility. Several studies performed constructive comparisons between Mediterranean watersheds' responses or compared SWAT to other models or methods. The effects of inputs on SWAT outputs and innovative model modifications and improvements were also the focus of some of the surveyed articles. However, a significant number of studies reported difficulties regarding data availability, as these are either scarce, have poor resolution or are not freely available. Therefore, it is highly recommended to identify and develop accurate model inputs and testing data to optimize the SWAT performance. [Display omitted] • SWAT review on Mediterranean hydro-climatic studies. • Lack of SWAT assessment on Mediterranean catchments. • A comparison of data from different Mediterranean basins. • Enhancing data availability for SWAT applications. • Developing a comprehensive knowledge of Mediterranean watersheds. [ABSTRACT FROM AUTHOR]

Delphinus delphis Linnaeus 1758 is considered an endangered species in the Mediterranean. The species is resident in the Bay of Algeciras - Gibraltar (southern Spain; waters partially shared with Gibraltar, UK). This area is subject to strong anthropogenic pressure, but with an input of renewed waters in its central area. During three consecutive years (March 2017–March 2020), sightings were observed concentrated along the submarine canyon that runs north to south across the bay, forming a "specular S″ with a maximum depth of 460 m. The pods of Dd showed a continuous or semi-continuous spatial distribution along the vertical axis of the submarine canyon, where they feed, mate, breed and rear calves in a well-defined area that constitutes a critical habitat. This area has been cartographically delimited, choosing the area of maximum dolphin frequency as highly vulnerable due to the possibility of collisions with small vessels (<15 m) and interactions with sport fishing activities (popping, ballooning, trolling) which constitute the main threat counting the derived impacts from noise pollution. Spatio-temporal mapping has been developed to visualize the overlapping between the dolphin groups and small vessels. Mapping analysis has shown that an international Spanish-British micro-sanctuary urgently needs to be established in order to create a protected area specifically for the common dolphins, and for other species which inhabit/use the waters between Spain and Gibraltar. Coordinates and a delimited surface area have been proposed in this paper. [Display omitted] • Algeciras Bay concentrates common dolphins and boats in its central and deepest area. • The continuous presence of dolphins over the submarine canyon could be related to the existence of the canyon. • A statistical and cartographic study of common dolphin and boat sightings is carried out. • Sport fishing boats and propeller boats are a threat to dolphins. • The creation of an international micro-sanctuary for common dolphins is proposed. [ABSTRACT FROM AUTHOR]

Mediterranean forests and fire regimes are closely intertwined. Global change is likely to alter both forest dynamics and wildfire activity, ultimately threatening the provision of ecosystem services and posing greater risks to society. In this paper we evaluate future wildfire behavior by coupling climate projections with simulation models of forest dynamics and wildfire hazard. To do so, we explore different forest management scenarios reflecting different narratives related to EU forestry (promotion of carbon stocks, reduction of water vulnerability, biomass production and business-as-usual) under the RCP 4.5 and RCP 8.5 climate pathways in the period 2020–2100. We used as a study model pure submediterranean Pinus nigra forests of central Catalonia (NE Spain). Forest dynamics were simulated from the 3rd National Forest Inventory (143 stands) using SORTIE-nd software based on climate projections under RCPs 4.5 and 8.5. The climate products were also used to estimate fuel moisture conditions (both live and dead) and wind speed. Fuel parameters and fire behavior were then simulated, selecting crown fire initiation potential and rate of spread as key indicators. The results revealed consistent trade-offs between forest dynamics, climate and wildfire. Despite the clear influence exerted by climate, forest management modulates fire behavior, resulting in different trends depending on the climatic pathway. In general, the maintenance of current practices would result in the highest rates of crown fire activity, while management for water vulnerability reduction is postulated as the best alternative to surmount the increasingly hazardous conditions envisaged in RCP 8.5. • We simulate forest, climate, and wildfire dynamics under RCPs 4.5 and 8.5. • We forecast wildfire hazard in terms of crown fire potential and rate of spread. • Current management practices will not be able to surmount the increased hazard. • Management for water vulnerability reduction is postulated as the best alternative. [ABSTRACT FROM AUTHOR]

The management of environmental flows is of paramount importance in regulated water resources systems to preserve river ecosystems. This work proposes a methodology to assess habitat alteration in river basins altered by management activities. The methodology is based on the joint application of a basin management model (SIMGES, AQUATOOL) and a model to estimate habitat time series (CAUDECO). CAUDECO is based on the weighted useable areas of the species in their different vital stages that, in turn, depend on the flows in each river stretch and the biological periods of the species. The final output is an indicator of habitat alteration, which is defined ad hoc for this work to relate the habitat suitability under regulated and natural regimes. The methodology was applied to a case study in north-western Spain: the Órbigo River basin. The results in the current management scenario highlight that the ecological flows improve the habitat suitability of several species with respect to natural regime conditions. For instance, the mean values of the habitat time series in the Órbigo River for the brown trout and bermejuela under regulated conditions are 69.6% and 88%; whereas in natural regime they are equal to 55.1% and 72.9%, respectively. Based on these results, eight additional scenarios of ecological flows were tested and their effects on both habitat alteration and water demand reliability were quantified and discussed. It was found that increases in the ecological flows up to 30% do not affect the reliability of water demands and reduce habitat alteration (i.e., lead to values of the habitat alteration indicator closer to 1) for all species present in the river basin. These results highlight that the methodology and indicator of habitat alteration proposed in this paper are useful to support the management of regulated river basins, since they allow assessing the implications of ecological flows on both habitat suitability and reliability of water demands. • A methodology is proposed to assess habitat alteration in regulated basins. • The methodology is applied to the Órbigo River basin (north-western Spain). • Environmental flows can improve habitat suitability compared to natural conditions. • Increases in environmental flows reduce habitat alteration for all species. • Rises in environmental flows up to 30% do not affect the reliability of water demands. [ABSTRACT FROM AUTHOR]

Despite major recent advances in socio-hydrology and hydroeconomics research, interdisciplinary methods and models for water policy assessment remain largely concealed to the academic arena. Most river basin authorities still base decision-making on inputs from hydrologic Decision Support Systems (DSS), and have limited information on the economic costs that water policies may impose on the economy. This paper presents a time-variant hierarchical framework that connects a hydrologic module and an economic module by means of two-way feedback protocols. The hydrologic module is designed to fit the AQUATOOL DSS, the hydrologic model used by Spanish river basin authorities to inform decision-making at a basin scale; while the economic module is populated with a Positive Multi-Attribute Mathematical Programming (PMAMP) model that represents the behavior and adaptive responses of irrigators. The proposed hierarchical framework is used to assess the economic repercussions of strengthening irrigation quotas so to achieve minimum environmental flows in the Douro River Basin (Spain) under climate change. Results show that reductions in agricultural water allocations to meet environmental flow requirements create nonlinear incremental profit and employment losses in irrigated agriculture that are on average low to moderate (between −4% and −12.9 % for profit, and between −4.6 % and −12 % for employment, depending on the scenario). During extreme droughts, the abrupt reductions in water availability and agricultural allocations can test farming systems past the breaking point and lead to catastrophic profit and employment losses (>80 %). • Water authorities have limited information on the economic costs of environmental flows. • We couple a microeconomic model with the widely used DSS AQUATOOL. • The coupling relies on a modular, protocol-based, time-variant hierarchical framework. • Water restrictions create nonlinear incremental profit and employment losses. • Extreme droughts test farming systems past breaking point and catastrophic losses. [ABSTRACT FROM AUTHOR]

This paper examines the resistance to shocks (economic, political, outbreaks etc.) of the ecological footprint in EU-5 countries over the period 1961–2016. The aim of the study is to determine whether the ecological footprint tends to return to the average with advanced econometric analysis. Efforts to move towards carbon neutrality, which increased after the Paris Agreement, are important for the countries in our analysis. To achieve our aim, we primarily used traditional and one-break unit root tests, followed by the novel SOR unit root test, which considers both sharp and smooth breaks to achieve robust results. The econometric findings show that EF and its six components (i.e., carbon, cropland, grazing land, forest, built-up land and fishing grounds) all contain unit root except the built-up land footprint for Spain and the grazing land and forest footprint for the United Kingdom. Our study provides policymakers with important information for implementing policies to reduce environmental pollution and achieve the target of carbon neutrality. • This study applies SOR unit root test, which considers both sharp and smooth breaks. • The results confirm efforts to move towards carbon neutrality in EU-5 countries. • The study contemplates policy recommendations aimed to reach carbon neutrality. [ABSTRACT FROM AUTHOR]