Modeling the effects of future climate and land-use changes on streamflow in a headwater basin in the Brazilian Caatinga biome

Abstract

Projected climate changes integrated into future land-use changes are extremely complex and hard to estimate, especially for basins located in semiarid environments. This work aims to estimate streamflow and the future water yield using climate prediction and land-use changes in the Salgado River basin for the 2030 − 2060 period. In this study, the applicability of the Soil and Water Assessment Tool (SWAT) and Land Change Modeler models was verified to estimate flows and land use and cover for the studied basin. Calibration and validation of the SWAT model are used on a monthly basis for 1986 − 2017, with a calibration period from 1986 to 2006 and a validation period from 2007 − 2017. Land use and cover analysis is performed for the 1985 − 2000 period, and future land use and cover is predicted using the land change model for 2050. In addition, future hydrological modeling of the geographical distribution of the water yield is performed for each subbasin of the Salgado River basin from the 2030 to 2060 period. The results of land use and cover changes show that the pasture class was the one that showed the most significant increase in the basin due to recent changes in land use and cover. The results showed that the HadGEM2-ES model presented a minor difference in the representative concentration pathways (RCP) 2.6, which indicates that this model is the most suitable for rainfall-runoff simulations in the region.

Keywords:

• Hydrological modeling
• land-use change
• water yield
• semiarid region

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

This study was financed in part by the Brazilian Federal Agency for the Support and Evaluation of Graduate Education (Coordenação de Aperfeiçoamento de Pessoal de Nível Superior – CAPES) – Fund Code 001, the National Council for Scientific and Technological Development, Brazil – CNPq (Grant No. 313358/2021-4 and 309330/2021-1) and the Federal University of Paraíba.