Tropical regions such as Java, Indonesia, still lack publication of soil water retention (SWR) information, particularly at upper Citarum watershed. The SWR is one of the critical elements in water storage and movement in the soil and very important to solve ecological and environmental problems. However, getting the access requires a lot of laboratory meas-urement that is time-consuming and expensive. Therefore, utilizing pedotransfer functions (PTFs) to estimate the water in the soil is needed. This study aims to define soil properties related to the SWR and to evaluate the performance of existing PTFs in predicting SWR. The study was carried out at agroforestry land system soil at upper Citarum watershed, Indonesia. Ten point and two continuous existing PTFs developed for tropical regions were applied in this study. Pearson's correlation (r), mean error (ME), root mean square error (RMSE), and modelling efficiency (EF) were used for evaluation. Cation exchange capacity (CEC), organic carbon (OC), bulk density (BD), and clay were considered as potential soil properties for soil water retention prediction. The performance of PTFs by MINASNY, HARTEMINK [2011] at matric potential of –10 kPaand BOTULA [2013] at matric potential of –33 kPa and –1500 kPa were recommended for point PTFs, while PTFs by HODNETT, TOMASELLA [2002] was for continuous PTFs in predicting SWR. The accuracy of the point PTFs is almost better than the continuous PTFs in predicting SWR in agroforestry land system soil at upper Citarum watershed, Indonesia.

The Semarang-Demak plain has experienced intense human intervention over the last 40 years, thereby causing land subsidence. This study aims to assess long-term conditions in the study area using the drivers-pressuresstate- impacts-response (DPSIR) framework to mitigate land subsidence. Methods include analysis of land subsidence, socioeconomic, surface, and subsurface data, as well as spatial analysis. Results show that rapid population growth and economic activities are major driving forces, manifesting as pressures exerted from overexploitation of groundwater, increasing building and infrastructure loads, and decreasing non-built areas. Groundwater overexploitation reduced the artesian pressure in the 1980s, forming depression cones of the groundwater level from 5 to 30 m below mean sea level. From 1984 to the present, the constructed areas have increased more than tenfold, with Semarang City possessing the most densely built area. Based on our findings, we propose responses consisting of surface water utilization, spatial building regulation, and rigorous groundwater and land subsidence monitoring. Moreover, we encourage the strengthening of law enforcement and inter-sectoral management to ensure the successful land subsidence mitigation.

Unlike many other countries, tropical regions such as Indonesia still lack publications on pedotransfer functions (PTFs), particularly ones dedicated to the predicting of soil bulk density. Soil bulk density affects soil density, porosity, water holding capacity, drainage, and the stock and flux of nutrients in the soil. However, obtaining access to a laboratory is difficult, time-consuming, and costly. Therefore, it is necessary to utilise PTFs to estimate soil bulk density. This study aims to define soil properties related to soil bulk density, develop new PTFs using multiple linear regression (MLR), and evaluate the performance and accuracy of PTFs (new and existing). Seven existing PTFs were applied in this study. For the purposes of evaluation, Pearson’s correlation (r), mean error (ME), root mean square error (RMSE), and modelling efficiency (EF) were used. The study was conducted in five soil types on Bintan Island, Indonesia. Soil depth and organic carbon (SOC) are soil properties potentially relevant for soil bulk density prediction. The ME, RMSE, and EF values were lower for the newly developed PTFs than for existing PTFs. In summary, we concluded that the newly developed PTFs have higher accuracy than existing PTFs derived from literature. The prediction of soil bulk density will be more accurate if PTFs are applied directly in the area that is to be studied.