Dam Environmental Impact Assessment in Java Island, Indonesia
Abstract
Increasing demand for water requires the improvement of water infrastructure. Dams are one of the most prominent infrastructures for water supply, especially as water demand increases. Due to its size, the dam is bound to affect the local environment, including the hydrometeorological and hydro/geological condition. The impact of dam on the local scale is supposedly dependent on several variables, namely, the height of the dam, its age, and the area of the river basin. This study studies the impact of dams on the surrounding environment by investigating 12 dams located in Java and are spread all throughout Java in particularly West Java, East Java, Central Java and lastly Jogjakarta. The dam environmental impact will be analyzed using: firstly, linear regression to determine the relationship between dams and environmental impact and secondly cluster analysis to divide the researched dams into categories. Dams in the study area could be divided into three clusters based on the similarity in height, age and river basin area. Additionally, this study finds that there is no correlation between the river basin area and both (ground) water quality and local climate. However, there was a correlation between the dam height with temperature and precipitation, as well as the dam age with Dissolved Oxygen (DO), Total Dissolved Solid (TDS) and pH. Regarding groundwater, the values of DO, TDS and pH are higher in dams located inside of groundwater basins compared to the opposite.
Keywords: dam, water demand, dam impact.
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GUO Y, HUANG Q, HUANG S, et al. Elucidating the effects of mega reservoir on watershed drought tolerance based on a drought propagation analytical method. Journal of Hydrology, 2021, 598. https://doi.org/10.1016/j.jhydrol.2020.125738
ZHAO Y, LIU S. & SHI H. Impacts of dams and reservoirs on local climate change: a global perspective. Environmental Research Letters 2021, 16(10): 104043.
CHEN J, SHI H, SIVAKUMAR B. & PEART MR. Population, water, food, energy and dams. Renewable and Sustainable Energy Reviews 2016, 56: 18-28.
Ministry of Public Works and Public Housing. 2021. https://data.pu.go.id/dataset/bendungan
LIU J, & NIYOGI D. Identification of linkages between urban heat Island magnitude and urban rainfall modification by use of causal discovery algorithms. Urban Climate, 2020, 33: 100659. https://doi.org/10.1016/j.uclim.2020.100659
ZHU G, SANG L, ZHANG Z, et al. Impact of landscape dams on river water cycle in urban and peri-urban areas in the Shiyang River Basin: Evidence obtained from hydrogen and oxygen isotopes. Journal of Hydrology, 2021, 602: 126779. https://doi.org/10.1016/j.jhydrol.2021.126779
LÜ M, JIANG Y, CHEN X. & CHEN J-L. Spatiotemporal Variations of Extreme Precipitation under a Changing Climate in the Three Gorges Reservoir Area (TGRA). Atmosphere 2018, 9(1): 24. https://doi.org/10.3390/atmos9010024
MILLER JD. Statistics for data Science: Leverage the Power of Statistics for Data Analysis, Classification, Regression, Machine Learning and Neural Network. Mumbai: Packt Publishing, 2017.
NIRWANA MB, & WULANDARI D. Comparison of Simple and Segmented Linear Regression Models on the Effect of Sea Depth toward the Sea Temperature. Enthusiasti: International Journal of Applied Statistics and Data Science, 2021, 1(2), 68-75. https://doi.org/10.20885/enthusiastic.vol1.iss2.art3
PANT A, & RAJPUT RS. Linear Regression Analysis Using R for Research and Development. In Writing Qualitative Research Paper of International Standard (pp.180-195), 2019.
https://www.researchgate.net/publication/336981868_Linear_Regression_Analysis_Using_R_for_Research_and_Development
JOHNSTONE E C, OWENS D C, LAWRIE S M, et al. (ed.). Companion to Psychiatric Studies. Churchill Livingstone; 8th edition, 2010
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