Using an improved SWAT model to simulate hydrological responses to land use change: A case study of a catchment in tropical Australia

Land use change is one of the dominant driving factors of watershed hydrological change. Thus, hydrological responses to land use changes require detailed assessments to ensure sustainable management of both water resources and natural ecosystems. The Soil and Water Assessment Tool (SWAT) model has been widely used to simulate the impacts of land use change on water balance. However, the original SWAT model has poor performance in estimating the leaf area index (LAI) of different vegetation types for tropical areas. The objective of this study was to simulate the impact of different land use change scenarios (deforestation, afforestation and urbanization) on the water balance, using an improved SWAT model with vegetation growth calibrated from MODIS LAI data. The North Johnstone River catchment in wet tropical eastern Australia was selected as the case study area. Results showed that the modified SWAT model was able to reproduce smoothed MODIS LAI with NSE >= 0.59 (NSE < 0 for default SWAT), R-2 >= 0.70 (R-2 <= 0.66 for default SWAT), and vertical bar PBIAS vertical bar <= 2.5% (vertical bar PBIAS vertical bar >= 42% for default SWAT), and to predict monthly streamflow well with NSE >= 0.92 (NSE >= 0.90 for default SWAT), R-2 >= 0.94 (R-2 >= 0.90 for default SWAT). It is noted that SWAT-T had vertical bar PBIAS vertical bar <= 10% while vertical bar PBIAS vertical bar <= 5% for default SWAT. Land use change impacted all hydrological variables, with the impact on surface runoff being the most notable at yearly scale (8.9%, 5.7%, - 9.5% and 15.9% for scenario 1, 2, 3 and 4, respectively). Absolute changes of surface runoff under land use change scenarios differed across months, with the most notable absolute change occurring during the wet season (December to May) (1.2 similar to 6.6 mm, 1.0 similar to 3.5 mm, - 7.3 similar to -1.1 mm and 3.0 similar to 9.0 mm for scenario 1, 2, 3 and 4, respectively). Urbanization increased surface runoff (5.7% and 15.9% for scenario 2 and 4, respectively) and decreased lateral runoff (- 0.7% and - 1.3%) and groundwater (-0.9% and - 3.5%), but produced no clear change in total runoff (0.2% and 0.2%), actual evapotranspiration (- 0.3% and - 0.3%), and soil water (0.5% and 0.7%) at the annual time scale. Furthermore, afforestation could decrease surface runoff (- 9.5% for scenario 3) and soil water (- 2.0%), increase evapotranspiration (1.7%), and lead to slight changes (absolute values <= 0.8%) in other hydrological variables at the annual time scale. A strong positive correlation (r >= 0.94) was observed between annual rainfall and total runoff for forest-evergreen, range-grasses, and urban land use. Forest-evergreen generally produced less total runoff than range-grasses and urban land use under conditions of the same rainfall, terrain slope, and soil texture. In addition, urban land use generally produced more surface runoff and less lateral runoff and groundwater than forest-evergreen and range-grasses under the same conditions. These results contribute important information for development of effective adaptation strategies and future policy plans for sustainable water management in tropical eastern Australia.