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The effects of climate change and urbanisation, such as more intense rainfall and changing land use patterns, are putting increasing pressure on urban drainage systems. This study proposes a comprehensive methodology for evaluating the effectiveness of sustainable urban drainage systems (SUDSs) in mitigating flooding and managing stormwater in both current and future scenarios. The approach integrates geospatial data, including digital elevation models (DEMs) and land use information, to delineate catchments and characterise hydrological parameters. Historical rainfall records and hydrological modelling were employed to define two baseline storm events: an extreme storm involving 422 mm of rainfall over 2 h, and an average storm involving 2.84 mm of rainfall over 1 h and 18 min. Future scenarios were developed by updating these baseline events using annual rates of change in maximum and average precipitation derived from climate projections between 2025 and 2100. The analysis incorporates seven CMIP6 climate scenarios: SSP1-1.9, SSP1-2.6, SSP4-3.4, SSP4-2.5, SSP4-6.0, SSP3-7.0, and SSP5-8.5. A stochastic simulation of 1000 storms per year was carried out using a custom-built conceptual hydrological model based on CN and developed in Python, which reflects interannual variability. The results show that extreme storm volumes could increase by up to seven times and average storm volumes by up to two and a half times. Additionally, discharge peaks could exceed baseline values by up to 20% in some years, suggesting an increased occurrence of extreme runoff events. The methodology assesses SUDS performance by comparing runoff and hydrological responses between baseline and future estimates. This framework enables vulnerabilities and adaptation needs to be identified, ensuring the long-term effectiveness of SUDSs in managing urban flood risk. Addressing uncertainties in climate and land use projections emphasises the importance of integrating SUDS assessments into wider urban resilience strategies.

Although Sustainable Urban Drainage Systems (SUDS) are widely recognised as essential components of resilient urban water management, the large-scale planning and evaluation of such systems remain challenging. This study assesses the hydrological and economic performance of SUDS in Madrid (Spain) under the SSP1-2.6 and SSP5-8.5 climate scenarios, applying a dual-scale methodology based on the Curve Number (CN) model. At the catchment scale, SUDS show substantial potential for irrigation reuse, with runoff-rich catchments reaching hydrological saturation earlier (plateau at r ≈ 0.4) and runoff-limited catchments stabilising at higher implementation levels (plateau at r ≈ 0.6). At the parcel scale, partial-coverage configurations (50% irrigation coverage) outperform full-coverage solutions (100% irrigation coverage), achieving maximum retention levels of 70% in SSP1-2.6 and 50% in SSP5-8.5 while requiring less surface area (10–15%). From an economic perspective, positive net present values (NPVs), acceptable internal rates of return (IRRs), and feasible payback periods occur only at very low retention levels (r < 0.05), with financial performance declining rapidly as storage capacity increases.

This paper presents a novel approach to assess spatial and temporal irrigation performance in urban parks and can assist park manager/operator decisions in irrigation management. First, irrigation needs are estimated by traditional irrigation scheduling and the irrigation zones with similar water needs that share the same electric valve (hydrozones) are identified. Then, irrigation performance is calculated using the relative water supply (RWS) indicator and mapped (GIS software). This approach can be adapted to various spatial and temporal scales. In this study, it was applied to the Valdebebas urban development VBB (Madrid) between the 2017 and 2019 irrigation seasons. The results for the VBB parks showed high spatio-temporal variation in irrigation performance among plant typologies within an irrigation season, which can be explained by the landscape coefficient KL variation across the parks. Likewise, this variation was also observed among the three evaluated seasons; explained among other factors by differences in irrigation management. For each hydrozone, the estimation of the NDVI index by Sentinel-2A satellite images in 2019 showed a threshold on irrigation performance. Thus, the remote sensing data together with the proposed approach can be a valuable tool for helping park managers/technicians adopt better decisions on irrigation practices.

This study assesses the adoption and operational effectiveness of Environmental Management Systems (EMSs) in Italian wineries, focusing on ISO 14001:2015. It evaluates commitment, planning, communication strategies, emergency preparedness, and employee training practices. Using a comprehensive survey-based methodology, the research elucidates the dynamics of EMS implementation across various scales of winery operations. The research reveals a strong commitment among wineries to environmental objectives such as waste reduction and efficient electricity and water use. However, significant deficiencies were identified in EMS policy implementation, emergency preparedness, and the uptake of ISO 14001:2015 certification, with larger wineries showing more robust engagement in environmental training than smaller ones. The study incorporates five key performance indicators (KPIs) and a predictive model using logistic regression and Random Forest to analyze the likelihood of ISO 14001 certification based on the analyzed variables. The model highlights established processes, environmental policies, and frequent reviews as significant predictors of certification. These findings contribute original value by identifying critical leverage points and barriers affecting EMS effectiveness within the wine sector. The research uncovers nuanced interactions between the scale of operations and management engagement influencing EMSs’ success. It proposes novel, survey-based KPIs essential for assessing EMS performance in wineries, demonstrating their practical utility in pinpointing areas for improvement. The research limitations include potential biases from varying participation rates among surveyed wineries, affecting extrapolation to the broader Italian wine industry. Despite these limitations, the study provides substantive practical implications, suggesting that wineries can enhance both environmental sustainability and a competitive edge by addressing gaps in EMS implementation.

Detailed modelling of water dynamics at the catchment is of paramount importance for the optimal management and allocation of water resources. The main objective of this work is to present a set of QGIS-based routines for processing easily available geographical information to deliver inputs for integration into hydrological models developed in the Python environment. We present QGIS processes that deliver open format exchangeable files with physical information required for hydrological modelling, allowing a better tailoring of hydrological modelling tasks compared to other blinded existing models. We present the general framework by processing spatial information and running a set of hydrological models in different cases studies in the Spanish Ebro River basin, proving the utility of the proposed method for applying complex and tailored hydrological simulations.

Tipping bucket rain gauges (TBR) are widely used worldwide because they are simple, cheap, and have low-energy consumption. However, their main disadvantage lies in measurement errors, such as those caused by rainfall intensity (RI) variation, which results in data underestimation, especially during extreme rainfall events. This work aims to understand these types of errors, identifying some of their causes through an analysis of water behavior and its effect on the TBR mechanism when RI increases. The mechanical biases of TBR effects on data were studied using 13 years of data measured at 10 TBRs in a mountain basin, and two semi-analytical approaches based on the TBR mechanism response to RI have been proposed, validated in the laboratory, and contrasted with a simple linear regression dynamic calibration and a static calibration through a root-mean-square error analysis in two different TBR models. Two main sources of underestimation were identified: one due to the cumulative surplus during the tipping movement and the other due to the surplus water contributed by the critical drop. Moreover, a random variation, not related to RI, was also observed, and three regions in the calibration curve were identified. Proposed calibration methods have proved to be an efficient alternative for TBR calibration, reducing data error by more than 50% in contrast with traditional static calibration.

Hydrologic processes acting on catchments are complex and variable, especially in mountain basins due to their topography and specific characteristics, so runoff simulation models and water management are also complex. Nevertheless, model parameters are usually estimated on the basis of guidelines from user manuals and literature because they are not usually monitored, due to the high cost of conventional monitoring systems. Within this framework, a new and promising generation of low-cost sensors for hydrologic monitoring, logging, and transition has been developed. We aimed to design a low-cost, open-hardware platform, based on a Raspberry Pi and software written in Python 3, for measuring, recording, and wireless data transmission in hydrological monitoring contexts. Moreover, the data are linked to a runoff model, in real time, for flood prevention. Complementarily, it emphasizes the role of the calibration and validation of soil moisture, rain gauges, and water depth sensors in laboratories. It was installed in a small mountain basin. The results showed mean absolute errors of ±2.2% in soil moisture, ±1 mm in rainfall, and ±0.51 cm in water depth measurements; they highlight the potential of this platform for hydrological monitoring and flood risk management.

Tomato crop is grown worldwide and is considered a mass consumer product. In Ecuador, tomato growers face two major issues: water scarcity and water mismanagement, which cause a reduction in the framers’ gross income and ecosystem services. This paper is aimed at finding an optimal irrigation scheduling in greenhouse tomato crop to achieve a balance among production, fruit quality and water use efficiency. Thus, two experiments were settled. In the first experiment, four water doses (80, 100, 120 and 140% ETc) and two irrigation frequencies (one and two irrigations per day) were compared. The second experiment evaluated the two best water doses of the first one (100 and 120% ETc) and four irrigation frequencies (one and two irrigations per day, one irrigation every two days, one irrigation every three days). Each experiment monitored the variables for tomato production (plant height, stem diameter, fruits per plant, yield) and tomato quality (pH, total soluble solids, titratable acidity). The study concluded that water doses affected more than irrigation frequency to fruit quality and production. The dose of 100% ETc, applied in one irrigation per day, is suggested to obtain a balance between production, fruit quality and water use efficiency.

A method for determining the optimal Sustainable Urban Drainage Systems (SUDs) combination at city scale is presented in this paper. A comprehensive set of SUDs categories comprising infrastructures aimed at either detaining and locally reusing or infiltrating precipitation are considered. A volumetric water balance is proposed for modelling hydrological processes in urban catchments. A multi-criteria approach combining a cost function and aims for both recharging aquifers and limiting runoff contribution to water courses is proposed to find the optimal SUDs combination. The water balance was run with each possible SUDs combination and the optimal set of SUDs was found. The method was applied to the Metropolitan Area of San Luis Potosí (Mexico). The optimal solutions in this case clearly promoted surface runoff detention and reuse over porous pavements and green roofs but they were sensitive to the considered costs. The SUD requirements to potential new urban developments for each catchment to comply with the original hydrological aims were also studied. The method requires customizing the cost function and using representative climatic data.

Increasing water scarcity is encouraging the use of unconventional water resources. In recent years, the European Union has launched numerous initiatives to promote and facilitate water reuse for agricultural irrigation. Today, the use of reclaimed water for agriculture has become an alternative, reliable and safe source of water supply and an indispensable water planning tool, especially in the area of southern Europe. However, water reuse for irrigation is currently far below its potential. Numerous barriers prevent its development and call for a detailed analysis of the different aspects affecting reclaimed water reuse, through an integrated and multidisciplinary approach. A multidisciplinary research team from Universidad Politécnica de Madrid, consisting of agronomists, hydrologists, chemists and agricultural economists, will work on the RECLAMO Project (https://blogs.upm.es/reclamo/), with the aim of providing solutions and recommendations aimed at promoting the full development and use of reclaimed water for irrigation in areas of Spain with marked water stress. For this purpose, project activities will be developed in two selected case studies (the Segura Basin, leader in water reuse in Spain and the Guadiana Basin, with success stories, but low levels of water reuse) and organised according to five axes: 1) development of a comprehensive knowledge-base covering the regulatory, technical, socio-economic and environmental aspects of reclaimed water reuse in agriculture; 2) participatory development of future scenarios exploring possible strategies, barriers and opportunities, in relation to the expansion of the use of reclaimed water for irrigation; 3) impact analysis of the strategies identified at different scales (crop, farm, (sub-)basin), through the development of an integrated modelling platform (hydrologic-agronomic-economic models); 4) Development of a roadmap and policy recommendations to achieve the full development and use of reclaimed water reuse for irrigation; 5) Dissemination of knowledge and promotion of science-policy-society dialogue. To this end, RECLAMO will collaborate closely with experts and stakeholder groups that will play a key role in the project in co-creating the scenarios and modelling tools and validating the results. The project will also seek for synergies and complementarities with other similar projects and explore new ways of collaborating with companies and research groups that allow research to continue and expand beyond the spatial and temporal limits of the project. RECLAMO’s results will promote an integrated approach to the sustainable management of water resources in water-stressed areas, including reclaimed water management. The integrated modelling platform developed in the project will allow policy-makers and water users to benefit from an improved understanding of the interactions between the social, economic and environmental aspects of water systems, in the context of climate and socio-economic change that will lead to better informed decision-making to address future water challenges. In addition, RECLAMO is expected to contribute to raising awareness about the use of reclaimed water reuse in agriculture as a safe and sustainable practice and to improve its social acceptance by producing science-based knowledge that provide evidence on the benefits derived from its use.