Balancing water supply demand is vital for sustaining livelihoods. Spatial mapping and calculating water yield dynamics due to land use changes over decades are needed to manage land resources and formulate ecological protection policies. This study mapped the supply, demand, and matching status of water product service using the Integrated Valuation of Ecosystem Service and Tradeoff (InVEST) biophysical models in the Citarum Watershed (CW) in 2000, 2010, and 2020. Moreover, this study used Exploratory Spatial Data Analysis (ESDA) and Geographic Information System (GIS) techniques to study the agglomeration characteristics and evolutionary trajectories of supply–demand over two decades. The results showed that between 2000–2010 and 2010–2020, the water supply decreased by 19.01 × 10⁸ m³ (18.28%) and 12.97 × 10⁸ m³ (15.27%), respectively. However, the water demand in the same period increased by 6.17 × 10⁸ m³ (23%) and 15.74 × 10⁸ m³ (47%), respectively. Over the decades, the contribution of land use land cover (LULC) changes to variations in water supply has yielded values ranging from 2.87% to 6.37%. The analysis of the water supply–demand imbalance indicated that the entire CW experienced water shortage, and the type of spatial matching for supply and demand is dominated by a high supply and high demand class (16.09% of the total area). Based on the level of water deficit calculation, the upstream and downstream areas were identified as zones that require ecological conservation, while the middle CW area requires ecological restoration or ecological improvement.

The application of remote sensing data has been significant in modeling soil erosion. However, previous studies have fallen short in elucidating and lacked an understanding of the multifactor influencing erosion. This study addresses these limitations by employing the InVEST and the Geodetector models. Specifically, it aims (1) to delineate both spatial and temporal variations in soil erosion within the Citarum watershed from 2010 to 2020, (2) to identify the key drivers of soil erosion and unravel the underlying mechanisms, and (3) to identify the high-risk zones for soil erosion. Both models consider a range of natural predictors, including topography (slope factor), climate (precipitation factor), and vegetation cover (vegetation factor). In addition, they incorporate social parameters such as income per capita and population density, which interact with the watersheds position in the downstream, middle, and upper streams. The results reveal that, over a decade, the average soil erosion increased by 15.50×10⁶ tons, marking a 16.65 surge. The impact of factors varies significantly across different subwatershed areas. For example, fraction vegetation cover interactions influence upper- and middle-stream regions, while the downstream area is notably affected by precipitation interactions. The high-risk erosion areas in the watershed are primarily influenced by slope, precipitation, and fractional vegetation cover. In these areas, factors causing high erosion risks include slope, precipitation, and other environmental variables categorized into strata. The study highlights the varying influential factors in different watershed areas.

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.

Rapid land use and land cover (LULC) changes in densely populated watersheds pose serious challenges to the sustainability of ecosystem services (ES), yet their spatially explicit economic consequences remain insufficiently understood. This study analyzes the spatio-temporal dynamics of LULC and ecosystem service values (ESVs) in the Citarum Watershed, Indonesia, one of the country’s most critical and intensively transformed watersheds. Multi-temporal Landsat imagery from 2003, 2013, and 2023 was classified using a Random Forest algorithm, while future LULC conditions for 2043 were projected using a Multi-layer Perceptron–Markov Chain (MLP–MC) model under three scenarios: Business-as-Usual (BAU), Protecting Paddy Field (PPF), and Protecting Forest Area (PFA). ESVs were quantified at multiple spatial scales (county, 250 m grids, and 100 m grids) using both the Traditional Benefit Transfer (TBT) method and a Spatial Benefit Transfer (SBT) approach that integrates biophysical indicators with socio-economic variables. The contribution of LULC transitions to ESV dynamics was further assessed using the Ecosystem Service Change Intensity (ESCI) index. The results reveal substantial historical forest and shrubland losses, alongside rapid expansion of settlements and dryland agriculture, indicating intensifying anthropogenic pressure on watershed functions. Scenario analysis shows continued degradation under BAU, limited mitigation under PPF, and improved forest retention under PFA; although settlement expansion persists across all scenarios. Total ESV declined from USD 2641.33 million in 2003 to USD 1585.01 million in 2023, representing a cumulative loss of 46.13%. Projections indicate severe ESV losses under BAU and PPF by 2043, while PFA substantially reduces, but does not eliminate economic degradation. ESCI results identify forest and shrubland conversion to settlements and dryland agriculture as the dominant drivers of ESV decline. These findings demonstrate that integrating multi-scenario LULC modeling with spatially explicit ESV assessment provides a more robust basis for ecosystem-based spatial planning and supports sustainable watershed management under increasing development pressure.

Exploring the drivers of changes in ecosystem services is crucial to maintain ecosystem functionality, especially in the diverse Central Citarum watershed. This study utilises the integrated valuation of ecosystem service and trade-offs (InVEST) model and multiscale geographically weighted regression (MGWR) model to examine ecosystem services patterns from 2006 to 2018. The InVEST is a hydrological model to calculate water availability and evaluate benefits provided by nature through simulating alterations in the amount of water yields driven by land use/cover changes. Economic, topographic, climate, and vegetation factors are considered, with an emphasis on their essential components. The presence of a geographical link between dependent and explanatory variables was investigated using a multiscale geographic weighted regression model. The MGWR model is employed to analyse spatial impacts. The integration of both models simplified the process and enhanced its understanding. The findings reveal the following patterns: 1) decreasing land cover and increasing ecosystem services demand in the watershed, along with a decline in water yield, e.g. certain sub-districts encounter water scarcity, while others have abundant water resources; 2) the impact of natural factors on water yield shifts along vegetation > climate > topography (2006) changes to climate > vegetation > topography (2018).

The Bekasi River Basin is highly vulnerable to severe and recurrent flooding, as evidenced by significant infrastructure and environmental damage during major events. This study investigates the catastrophic floods of 2016, 2020, 2022, and 2025 by implementing the Rainfall-Runoff-Inundation (RRI) model to simulate key hydrological processes. After validation using historical water level data, the model performed effectively, achieving the highest coefficient of determination (R² = 0.75) and lowest root mean square error (RMSE = 0.66) at Cileungsi Station. In contrast, the lowest R² = 0.02, and the highest RMSE = 3.74 at Pondok Gede Permai (PGP) Station. The results reveal a concerning trend of worsening 5-year flood events, with the 2025 flood reaching a peak inundation depth exceeding 3 m and affecting an area of 2.97 km², caused by a rainfall threshold of more than 180 mm/day. Furthermore, the model shows a rapid hydrological response, with a time lag of approximately 7 h or less between peak rainfall and flood onset across three monitoring stations. Analysis indicates these severe floods were primarily triggered by heavy rainfall combined with significant land cover changes. The findings provide valuable insights for flood prediction and mitigation strategies in this vulnerable region.