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Freshwater on small islands is generally limited and relies on rainwater and groundwater. This study aimed to assess changes in shallow groundwater quality on Pari Island, Indonesia. Pari Island is a small island with an area of 41.32 ha and belongs to a monsoon climate. Also, being a residential island, it attracts many tourists. The approach was to assess the shallow groundwater quality of ten wells during the dry and wet seasons. Changes in water quality were evaluated using traditional hydrochemical analysis methods (Schoeller, Piper, and Gibbs diagrams) and ion ratios. Shallow groundwater quality in the study area showed different responses depending on the season. Therefore, each well responded differently to changes represented by changes in water quality. The change is controlled by various factors: evaporation (or water balance), geology, aquifer characteristics, tides, wind direction, and wave height. These factors trigger the fluctuation of groundwater and seawater interface, affecting the amount of rainwater and seawater transported to the freshwater aquifer layer. This water volume transported affects the process of rock weathering, dissolution, and dilution of contaminants in shallow groundwater., (© 2022. The Author(s), under exclusive licence to Springer Nature Switzerland AG.)

Freshwater on small islands is generally limited and relies on rainwater and groundwater. This study aimed to assess changes in shallow groundwater quality on Pari Island, Indonesia. Pari Island is a small island with an area of 41.32 ha and belongs to a monsoon climate. Also, being a residential island, it attracts many tourists. The approach was to assess the shallow groundwater quality of ten wells during the dry and wet seasons. Changes in water quality were evaluated using traditional hydrochemical analysis methods (Schoeller, Piper, and Gibbs diagrams) and ion ratios. Shallow groundwater quality in the study area showed different responses depending on the season. Therefore, each well responded differently to changes represented by changes in water quality. The change is controlled by various factors: evaporation (or water balance), geology, aquifer characteristics, tides, wind direction, and wave height. These factors trigger the fluctuation of groundwater and seawater interface, affecting the amount of rainwater and seawater transported to the freshwater aquifer layer. This water volume transported affects the process of rock weathering, dissolution, and dilution of contaminants in shallow groundwater. [ABSTRACT FROM AUTHOR]

Groundwater is an important source of fresh water worldwide. Jakarta, the capital city of the Republic of Indonesia, is a large city with a population of more than 10 million and the center of the country's economy and urban development. However, Jakarta has many challenges related to groundwater management. Changes in well GWL serve as a direct indicator of the effects of groundwater evolution, and GWL time series usually contain important information about aquifer dynamics. Therefore, water managers and engineers must model and predict GWL, identify and measure groundwater resources, and maintain a balance between supply and demand. Measuring and analyzing the groundwater table (GWL) of an aquifer are an important and valuable activity in the management of groundwater resources, and information on GWL variability can be used to determine groundwater availability. Accurate and reliable groundwater level estimation is very important because it provides important information about the quantitative groundwater status of an aquifer. The main advantage of AI models is their ability to reproduce nonlinear and complex processes without a full understanding of the underlying physics. As a result, the use of AI techniques in GWL modeling continues to grow, attracting the attention of scientists around the world. Using a nonlinear autoregressive network with extrinsic input (NARX) with a timestep of 14 days, this study is aimed at predicting the volatility of Jakarta's GWL. Based on the research results, both JKT-01 and JKT-03 show a linear downward trend. On the other hand, JKT-02 and JKT-04 show a stable linear trend. GWL increases the linear trend of JKT-05. Variable results are generated by model performance. Model performance (R) varied between 0.2 and 0.9 during the training phase and between 0.2 and 0.9 during the validation phase. The overall performance of the model varies from 0.3 to 0.9. The diverse lithology and high pumping capacity in Jakarta are the reasons for the different modeling results. Forecasts for 14 days (14 timesteps) show that GWL remains constant at certain well locations, while GWL decreases at other locations. This is a consideration that stakeholders can consider to reduce the small effect of the daily GWL pattern as a result of NARX modeling. [ABSTRACT FROM AUTHOR]