Joint climate and land cover change can significantly alter catchment hydrologic response, e.g., in terms of runoff and sediment delivery, and thus key determinants for downstream hydropower outcomes. While many studies highlight climate risk for hydropower operation, it is less clear how climate and landuse change together will impact hydropower outcomes, if managing landuse can reduce those impacts, and how to prioritize effective investments in the face of uncertainty about the future climatic drivers. In this study, we use Chaglla Dam, Peru’s third largest electricity generator, to develop an ensemble approach to identify parts of Chaglla’s contributing area with consistent changes in runoff and sediment under climate change. Those areas could then be targeted for maintaining or restoring natural land cover to increase baseflow and decrease sediment. We use SWAT to model catchmen...

Surface water resources in Peru are heterogeneously distributed in three drainage areas (Pacific, Titicaca, and Atlantic), and their quantification is relevant for planning in economic activities such as water supply and agriculture. However, their continuous monitoring at national scale becomes difficult due to the low stream gauges density and short streamflow records. The aim of this work is to generate a database of simulated monthly streamflows at a national scale from January 1981 to December 2016, applying the parsimonious GR2M model in a semi-distributed approach, under a parameter regionalization scheme. For this, 3594 sub-basins (~300 km2) located in the three drainage areas were tested. These sub-basins were first grouped in 14 calibration regions based on a sensitivity analysis of the runoff ratio (RR) and runoff variability (RV) indexes derived from the GR2M outputs. The mod...

Quantification of the surface water offer is crucial for its management. In Peru, the low spatial density of hydrometric stations makes this task challenging. This work aims to evaluate the hydrological performance of a monthly water balance model in Peru using precipitation and evapotranspiration data from the high-resolution meteorological PISCO dataset, which has been developed by the National Service of Meteorology and Hydrology of Peru (SENAMHI). A regionalization approach based on Fourier Amplitude Sensitivity Testing (FAST) of the rainfall-runoff (RR) and runoff variability (RV) indices defined 14 calibration regions nationwide. Next, the GR2M model was used at a semi-distributed scale in 3594 sub-basins and river streams to simulate monthly discharges from January 1981 to March 2020. Model performance was evaluated using the Kling–Gupta efficiency (KGE), square root transferred...

Surface water resources in Peru show high spatio-temporal variability, being the prediction of streamflow at ungauged sites, one of the fundamental challenges today. This research presents a methodology for regional parameter estimation at national scale using SWAT (Soil and Water Assessment Tools) model, with the goal of estimating the streamflow for three hydrographic regions in Peru: the Pacific, Titicaca and Amazonas. Hydrological models were calibrated using observed discharge data which is sparse and poorly distributed over Peru. In this context, we design a regional parameter estimation following the next steps: i) First, a regionalization of 3394 hydrological response units (HRU) in the whole country were built through Ward’s hierarchical cluster criterion, in which 14 calibration regions were defined. ii) A calibration procedure to obtain the best calibration parameters was ma...