Identifying the optimal type and locations of natural water retention measures using spatial modeling and cost-benefit analysis

Water management has shifted from solely technical and engineering approaches towards nature-based solutions (NBS), like natural water retention measures (NWRM), offering benefits beyond hydrology, such as improved well-being and biodiversity conservation. Determining the best type and location of these measures is challenging due to diverse options with varying benefits and effects depending on measure type and location characteristics. While most studies regarding the optimal allocation and implementation of NBS focus on the urban environment, this study presents a methodology for decision-makers focusing on inter-urban regions with limited data on NWRM implementation. Through hydrological modeling and cost-benefit analysis (CBA), we identify Pareto optimal NWRM sites and types, considering water quantity and quality alongside economic, environmental, and social objectives. We defined optimal locations that seek the most significant reduction of runoff, sediment, and pollutants, whilst optimal NWRM types are defined to seek the most cost-effective measures based on hydrological, ecological, and social criteria. Using the Open Non-point Source Pollution and Erosion Comparison Tool (OpenNSPECT), we simulated increased infiltration in different inter-urban areas and identified the optimal placement. The criteria for selecting suitable NWRM types for the identified areas are derived from the EU Directorate General for the Environment (DG-ENV) NWRM database. The results show different effective areas for reducing runoff, sediment, and pollutants. While one NWRM (natural bank stabilization) was identified as most beneficial for reducing sediment, several measures were selected for runoff reduction. Interestingly, measures with high potential for pollutant reduction seem to offer limited social and biodiversity benefits, suggesting conflicting objectives and highlighting the importance of accounting for multiple criteria. By employing simplified models and qualitative benefit assessments, this paper presents a practical decision-making approach to facilitate NWRM implementation in data-scarce areas.