- Tytuł:
- Spatial-temporal heterogeneity and driving factors of water yield services in Citarum river basin unit, West Java, Indonesia
- Autorzy:
-
Nahib, Irmadi
Ambarwulan, Wiwin
Sutrisno, Dewayany
Darmawan, Mulyanto
Suwarno, Yatin
Rahadiati, Ati
Suryanta, Jaka
Prihanto, Yosef
Radiastuti, Aninda W.
Lumban-Gaol, Yustisi - Powiązania:
- https://bibliotekanauki.pl/articles/27311534.pdf
- Data publikacji:
- 2023
- Wydawca:
- Polska Akademia Nauk. Czasopisma i Monografie PAN
- Tematy:
-
water yields
climate
land use land cover
InVEST Model
geographically weighted regression
socio-ecological model - Opis:
- 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.
- Źródło:
-
Archives of Environmental Protection; 2023, 49, 1; 3--24
2083-4772
2083-4810 - Pojawia się w:
- Archives of Environmental Protection
- Dostawca treści:
- Biblioteka Nauki
Artykuł