Streamflow Prediction Using the SCS-CN Method Coupled to the Geographic Information Systems in the Huallaga River Basin, Peru Under Climate Change.

This research evaluates the daily streamflows in the Huallaga river basin using the Curve Number method coupled to geographic information systems (GIS). The methodology includes the analysis of land cover, soil types, geomorphology, digital elevation model, time series analysis of historical records in hydrometeorological stations, development of precipitation-runoff model coupled to GIS, model calibration, and daily flow prediction. In addition, daily precipitation from 19 Global Climate Models for emission scenarios RCP 4.5 and 8.5 was used to assess changes in streamflow for the period 2020-2080, including the bias correction and downscaling. Peruvian Interpolated data of SENAMHI's Climatological and Hydrological Observations (PISCO) were assessed to complete the observed historical data along the basin. Likewise, daily flow records of 04 hydrometric stations distributed along the Huallaga River were used for the model calibration and validation. The results show that the model provides adequate estimates of daily direct runoff using the Curve Number method that can help improve decision-making in the water resources planning and management of Peruvian basins. The projected changes in precipitation show an average increase greater than 40 mm/year for the RCP 4.5 and RCP 8.5 scenarios. In general, an increase in flows in wet season and a reduction in flows in the dry season are expected for both scenarios.