https://orcid.org/0000-0002-2844-9905
ABSTRACT
Climate change and land-use change are two major factors that affect the hydrologic response of a river basin. The Soil and Water Assessment Tool (SWAT) is a reliable method to model the hydrology of a river basin. The SWAT-land-use update tool offers a user-friendly interface for the incorporation of dynamic land-use changes into hydrological modeling. This paper evaluates the impacts of climate and dynamic land-use changes on the streamflow generation in the Nowrangpur catchment encompassing Indravati dam, which is a major water resources project in India. Calibrating the SWAT model involved updating land-use data from 1985 to 2015, yielding satisfactory results. The future land-use/land-cover changes were predicted using the cellular atomata-artificial neural network model. Downscaled general circulation model data from 10 climate models were utilized to predict climate change impacts up to 2100. Projections indicate increased precipitation during the months from August to December with a more pronounced increase in the mid and far future. An uptrend in maximum and minimum temperatures for all months is observed in the far future relative to the baseline period. Furthermore, the streamflow predictions indicate a near-future decrease in total annual streamflow, followed by an increase of up to 41% in the mid and far future.
HIGHLIGHTS
Impacts of changes in land use and land cover (LULC) and climate on streamflow generation in the Nowrangpur catchment are explored.
SWAT-LUT is considered to account for the dynamic LULC changes.
Cellular automata–artificial neural network model is used to obtain future projections of LULC.
Change factor method is used to downscale future climate projections from CMIP6 GCMs.
Annual streamflow is expected to decrease in the near future followed by a considerable increase in the mid and far future.
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