Forecasting the long-term impacts of land use and cover changes on runoff coefficient and flood hydrograph: a case study of the Upper Citanduy Basin, Indonesia - Irawan, Pengki; Setiawan, Junaedi (Journal of Degraded and Mining Lands Management, 2025)
Land use and land cover (LULC) change significantly affects hydrological processes in ungauged basins, where data limitations hinder accurate analysis and modeling. This study assesses the long-term impacts of LULC changes on the runoff coefficient (RC) and flood hydrograph in the Upper Citanduy Basin, Indonesia, using data from 2014, 2019, and 2024 to project future scenarios through 2029. The Cellular Automata-Artificial Neural Network (CA-ANN) model through the MOLUSCE plugin in QGIS was used for LULC forecasting, achieving high accuracy (Kappa>0.9). The results indicate a 16.97% increase in the composite runoff coefficient from 2014 to 2029, primarily driven by the conversion of agricultural land into built-up areas. This increase was most pronounced in the early years, stabilizing as urbanization and land degradation effects moderated. HEC-HMS simulations using Synthetic Unit Hydrograph (SUH) methods, including Nakayasu, Snyder, and Clark SUHs, revealed that peak discharges for lower return periods (RP) in the future could approach or exceed those of higher RPs in the past. For instance, the 5-year RP peak discharge in 2029 (2.137 m³ s?¹) closely resembles the 25-year RP in 2019 (2.165 m³ s?¹). Similarly, the 5-year RP in 2024 (1.794 m³ s?¹) is comparable to the 10-year RP in 2014 (1.768 m³ s?¹), while the 5-year RP in 2019 (1.727 m³ s?¹) is nearly the same as the 2-year RP in 2029 (1.734 m³ s?¹). These findings underscore the need for sustainable land-use planning and adaptive flood management to mitigate hydrological impacts in ungauged basins.