Supporting multi-objective natural small water retention measures planning: the Cherio river basin case study, Italy

Land use change entailing the introduction of Natural Small Water Retention Measures (NSWRMs), with the objective of incrementing a basin’s hydrological resilience, is a multifaceted challenge: the stakeholders involved in the decision-making process are numerous, and even the nature of the issues affecting one specific group might be linked to different hydrological processes. The need for tools capable of identifying the best NSWRMs-comprising land use scenarios by meeting the interests of multiple stakeholders is then evident.

The primary objective of this study, conducted as part of the EU-funded Optain Project (Horizon 2020–2025), is to identify the optimal levels of NSWRM implementation in the Cherio River Basin, situated in the Po Plain. The analysis integrates environmental and socio-economic performance indicators to ensure a comprehensive evaluation of the proposed measures. The basin's primary hydrological challenges are related to flooding and summer droughts. The most promising NSWRMs identified to tackle these issues in the study area are: 1) rehabilitation of terraces, 2) detention ponds at the outlets of sewer systems, 3) buffer strips, 4) river restoration, and 5) cultivation of drought-resistant crops. These measures are modeled at specific sites using the SWAT+ model, integrated with the Contiguous Object Connectivity Approach (COCOA) developed within the Optain project harmonized informatic framework.

To identify the most effective NSWRM combinations for achieving various and sometimes conflicting objectives, the SWAT+ model has been integrated with the Non-dominated Sorting Genetic Algorithm II (NSGA-II), a widely recognized Pareto-based optimization method. This algorithm is implemented through the Constrained Multi-objective Optimization of Land Use Allocation (CoMOLA) tool. The optimization process does not yield a single optimal scenario but instead generates a diverse set of Pareto-optimal solutions.

The CoMOLA setup involved an array of simulations comprising 100 individuals and 200 generations. For the evaluation, two environmental and two economic indicators were selected: 1) peak flow entity, 2) water availability during irrigation season, 3) NSWRM implementation cost, and 4) agricultural gross margin.

The resulting set of optimal alternatives provides a starting point for local decision-makers to conduct a comprehensive evaluation and select the most appropriate solutions that align with their preferences and strategic objectives.