The dam of Beni Haroun is the largest in Algeria, and its transfer structures feed seven provinces (wilayas) in the east-ern part of Algeria. Due to its importance in the region, it has now become urgent to study its watershed as well as all the parameters that can influence the water and solid intakes that come into the dam. The Soil and Water Assessment Tool (SWAT) model is used to quantify the water yields and identify the vulnerable spots using two scenarios. The first one uses worldwide data (GlobCover and HWSD), and the second one employs remote sensing and digital soil mapping in order to determine the most suitable data to obtain the best results. The SWAT model can be used to reproduce the hydrological cycle within the watershed. Concerning the first scenario, during the calibration period, R2 was found between 0.45 and 0.69, and the Nash–Sutcliffe efficiency (NSE) coefficient was within the interval from 0.63 to 0.80; in the validation period, R2 lied between 0.47 and 0.59, and the NSE coefficient ranged from 0.58 to 0.64. As for the second scenario, during the calibration period, R2 was between 0.60 and 0.66, and the NSE coefficient was between 0.55 and 0.75; however, during the validation period, R2 was in the interval from 0.56 to 0.70, and the NSE coefficient within the range 0.64–0.70. These find-ings indicate that the data obtained using remote sensing and digital soil mapping provide a better representation of the wa-tershed and give a better hydrological modelling.

Many countries, including Indonesia, face severe water scarcity and groundwater depletion. Monitoring and evaluation of water resources need to be done. In addition, it is also necessary to improve the method of calculating water, which was initially based on a biophysical approach, replaced by a socio-ecological approach. Water yields were estimated using the Integrated Valuation of Ecosystem Services and Trade-offs (InVEST) model. The Ordinary Least Square (OLS) and geographic weighted regression (GWR) methods were used to identify and analyze socio-ecological variables for changes in water yields. The purpose of this study was: (1) to analyze the spatial and temporal changes in water yield from 2000 to 2018 in the Citarum River Basin Unit (Citarum RBU) using the InVEST model, and (2) to identify socio-ecological variables as driving factors for changes in water yields using the OLS and GWR methods. The findings revealed the overall annual water yield decreased from 16.64 billion m3 year-1 in the year 2000 to 12.16 billion m3 year-1 in 2018; it was about 4.48 billion m3 (26.91%). The socio-ecological variables in water yields in the Citarum RBU show that climate and socio-economic characteristics contributed 6% and 44%, respectively. Land use/Land cover (LU/LC) and land configuration contribution fell by 20% and 40%, respectively.The main factors underlying the recent changes in water yields include average rainfall, pure dry agriculture, and bare land at 28.53%, 27.73%, and 15.08% for the biophysical model, while 30.28%, 23.77%, and 10.24% for the socio-ecological model, respectively. However, the social-ecological model demonstrated an increase in the contribution rate of climate and socio-economic factors and vice versa for the land use and landscape contribution rate. This circumstance demonstrates that the socio-ecological model is more comprehensive than the biophysical one for evaluating water scarcity.