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Modelling and dynamic water analysis for the ecosystem service in the Central Citarum watershed, Indonesia

Suryanta Jaka, Nahib Irmadi, Ramadhani Fadhlullah, Rifaie Farid, Suwedi Nawa, Karolinoerita Vicca, Cahyana Destika, Amhar Fahmi, Suprajaka

Journal of Water and Land Development

2024

no. 60

122--137

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).

Spatial-temporal heterogeneity and driving factors of water yield services in Citarum river basin unit, West Java, Indonesia

Nahib Irmadi, Ambarwulan Wiwin, Sutrisno Dewayany, Darmawan Mulyanto, Suwarno Yatin, Rahadiati Ati, Suryanta Jaka, Prihanto Yosef, Radiastuti Aninda W., Lumban-Gaol Yustisi

Archives of Environmental Protection

2023

Vol. 49, no 1

3--24

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.

Cellular Automata Markov Method, an Approach for Rice Self-Sufficiency Projection

Sutrisno Dewayany, Ambarwulan Wiwin, Nahib Irmadi, Turmudi, Suryanta Jaka, Windiastuti Rizka, Kardono Priyadi

Journal of Ecological Engineering

2019

Vol. 20, nr 6

117--125

This article discusses the ability of the Cellular Automata (CA) Markov method to project rice sufficiency by considering the conversion of massive rice fields, such as the ones in Indonesia. The conversion of rice fields into land use for non-farming due to the rapidly growing population, industry and economic needs is increasingly affecting the rice self-sufficiency. With the development of remote sensing techniques, such as CA Markov, which has been used for years in spatial change projection, there is a need to assess the rice field conversion and its impact on the rice field self-sufficiency. The process is not solely based on CA Markov but also includes an object-based classification method utilising multi-temporal spot image data to derive land use maps, CA Markov for rice field conversion projection and rice self-sufficiency assessment, which was developed by assessing the availability of rice, consumption and production. Using the Indramayu district as the study area, the results indicate that within the next 20 years, the rice field area will decrease, and the impact on rice self-sufficiency will be 5.34 for Business as usual (BAU) and 0.47 when considering population growth. The previous research validated the results and indicated the efficiency of this method for rice self-sufficiency projection. Moreover, a management assessment was also conducted and indicated that in order to maintain rice self-sufficiency, innovation in the planting and seed systems as well as in farmers’ welfare management, such as incentives and subsidies, local food diversification systems and innovative food technique development to support food diversification, should be considered.