Framework for mapping large-scale nature-based solutions for drought mitigation: Regional application in Flanders.

Droughts are classified as the most expensive climate disasters as they leave long-term and chronic impacts on the ecosystem, agriculture, and human society. The intensity, frequency, and duration of drought events have increased in the past and are expected to continue rising at global, continental, and regional scales. Nature-based solutions (NBS) are highlighted as effective solutions to cope with the future impacts of these events. Despite this, there has been limited comprehensive research on the effectiveness of NBS for drought mitigation, and existing suitability mapping frameworks often overlook drought-specific criteria. To address this gap, a new framework is proposed to identify areas suitable for two drought-coping NBS types at a regional scale: detention basins and managed aquifer recharge. Two multi-criteria decision-making techniques (MCDM), i.e. Boolean logic and Analytic- Hierarchy Process (AHP), were used to map suitable large-scale NBS. The new framework accounts for unique criteria to specifically address drought conditions. By incorporating climate change scenarios for both surface and groundwater, recharge, and different groundwater characteristics, it identifies suitable and sustainable locations capable of managing extreme drought events. Executed through Boolean logic at a regional scale in Flanders (Belgium), the framework's strict approach yields significant potential areas for detention basins (298.7 km²) and managed aquifer recharge (867.5 km²). Incorporating AHP with the same criteria introduces a higher degree of flexibility for decision-makers. This approach shows a notable expansion across Flanders, varying with the level of suitability. The results underscore the highly suitable potential for detention basins (2552.2 km²) and managed aquifer recharge (2538.7 km²), emphasizing the adaptability and scalability of the framework for addressing drought in the region. The comparison between potential recharge volume due to detention basin and groundwater use in the region indicated that the detention basins could partially compensate for the high water demand. Therefore, creating a framework targeting drought is vital for the sustainable management of water scarcity scenarios.

The underexposed nature-based solutions: A critical state-of-art review on drought mitigation.

Droughts are the most expensive climate disasters as they leave long-term and chronic impacts on the ecosystem, agriculture, and human society. The intensity, frequency, and duration of drought events have increased over the years and are expected to worsen in the future on a regional and planetary/global scale. Nature-based solutions (NBS) such as wetland and floodplain restorations, green infrastructures, rainwater harvesting, etc., are highlighted as effective solutions to cope with the future impacts of these events. While the role of NBS in coping with the impacts of other disasters, such as floods, has been extensively studied, there has been a lack of comprehensive review of NBS targeting drought. The following paper provides a unique critical state-of-the-art literature review of individual drought-related NBS around the world, in Europe, and particularly in Belgium, and assesses the critical differences between the NBS applied globally and in Flanders. An extensive literature review was conducted to systematically analyze NBS, listing the type, the location, the status of the implementation, and the possible recommendations proposed to optimize future NBS applications. Finally, a comparison is made between small- and large-scale applications of NBS. By analyzing all these aspects, especially the level of effectiveness and recommendations, insight was gained into the future potential of NBS and possible improvements. The research indicated a lack of scientific publications, especially in Belgium. Hence, grey literature was also included in the literature review. Only four papers included a quantitative assessment regarding the effectiveness of drought on a global level, all stating a positive impact on groundwater recharge. In contrast, at regional and country levels, the performance of NBS was not quantified. The number of large-scale implementations is low, where landscape- or watershed-scale holistic approaches to drought mitigation are still scarce. Some successfully implemented projects are only very local and have a long realization time, two aspects that limit achieving visible impact at a larger scale. Among the many NBS, wetlands are recognized as highly effective in coping with drought but are still degraded or lost despite their significant restoration potential. A common effectiveness evaluation framework shall be followed, which gives policymakers a clear view of the different NBS investment options. Furthermore, a more collaborative approach is recommended globally, including different stakeholder groups, with specific attention to the local communities. To conclude, future research should increase the evidence base and implementation of drought-mitigating NBS.

The impact of extensive agricultural water drainage on the hydrology of the Kleine Nete watershed, Belgium.

Agricultural water drainage can significantly lower groundwater levels and affect catchment hydrology. Therefore, building models with and without these features can indicate an adverse impact on the geohydrological process. Therefore, the standalone Soil Water Assessment Tool (SWAT+) model was initially developed to simulate streamflow at the Kleine Nete catchment outlet. Next, a physically based and spatially distributed groundwater module (gwflow) was integrated into the SWAT+ model and calibrated for stream discharge at the catchment outlet. Finally, the same model was calibrated for both streamflow and groundwater heads. These final model parameters are used to investigate the basin-wide hydrologic fluxes with and without including agricultural drainage systems in the model scheme. The result suggested that the standalone SWAT+ model poorly represented the stream discharge and attained low NSE values of 0.18 and 0.37 during the calibration and validation periods, respectively. Integrating the gwflow module to SWAT+ improved the model representation of stream discharge (NSE = 0.91 and 0.65 for calibration and validation periods, respectively) and groundwater heads. However, calibrating the model for only streamflow resulted in a high root mean square error (above 1 m) for groundwater head, and the seasonality is not captured. On the other hand, calibrating the coupled model for streamflow and hydraulic head reduced the root mean square error (below 0.5 m) and captured the seasonality of groundwater level fluctuations. Finally, drainage application resulted in a 50 % (from 33.04 mm to 16.59 mm) reduction in groundwater saturation excess flow and an 18.4 mm increment in drainage water to streams. To conclude, the new SWAT+gwflow model is more appropriate than the standalone SWAT+ model for the case study. Furthermore, calibrating the SWAT+gwflow model for streamflow and groundwater head has improved the model simulation, with implications for general coupled models where representing surface and groundwater in the calibration strategy is beneficial.

Multi-variable sensitivity and identifiability analysis for a complex environmental model in view of integrated water quantity and water quality modeling.

Environmental models are often over-parameterized. A sensitivity analysis can identify influential model parameters for, e.g. the parameter estimation process, model development, research prioritization and so on. This paper presents the results of an extensive study of the Latin-Hypercube-One-factor-At-a-Time (LH-OAT) procedure applied to the Soil and Water Assessment Tool (SWAT). The LH-OAT is a sensitivity analysis method that can be categorized as a screening method. The results of the sensitivity analyses for all output variables indicate that the SWAT model of the river Kleine Nete is mainly sensitive to flow related parameters. Rarely, water quality parameters get a high priority ranking. It is observed that the number of intervals used for the Latin-Hypercube sampling should be sufficiently high to achieve converged parameter rankings. Additionally, it is noted that the LH-OAT method can enhance the understanding of the model, e.g. on the use of water quality input data.