Assessing Shrub and Grassland Degradation Portfolios as Benchmarks for Potential Water Quantity Benefits: Application of the RIOS and SWAT Model to Rimac Basin, Peru

The Rimac River Basin supplies drinking water to more than ten million people in Lima, Peru, yet its hydrological regulation capacity is increasingly constrained by land degradation, with over 35% of the basin lacking vegetation cover. Nature-based solutions implemented through conservation and restoration of natural ecosystem offer a potential complement to grey infrastructure, although their basin-scale hydrological benefits remain scantily quantified. This study proposes an inverse assessment framework that uses future degraded states as hydrological benchmarks to quantify redistributed water as a proxy for the volumetric benefits that conservation or restoration could potentially provide. Degraded Andean shrubland and grasslands were identified and prioritized using the RIOS investment assessment tool, resulting in three degradation portfolios (2826; 6566; and 10,720 ha) for the 2011–2016 period. Their hydrological responses were then simulated using the SWAT model, with a focus on dry-season dynamics. The model achieved a Kling Gupta Efficiency of 46.9% and a seasonally targeted Nash–Sutcliffe efficiency of 70% during the dry season, ensuring that despite the basin anthropization, the low flow dynamics key for water security are reliably represented. Water availability indicators and flow-duration curve metrics were applied to evaluate changes in hydrological regulation. Results show that all portfolios increased dry-season streamflow relative to baseline conditions, with the largest portfolio producing a 2.39% increase, equivalent to approximately 4 hm3 during the critical June–August period. These findings indicate that degradation alters flow redistribution within the basin water cycle and suggest that conservation or restoration may reverse these effects. The intermediate and large portfolios provided the most informative benchmarks, supporting spatially explicit decision making for basin-scale water regulation.