Determinants of Watershed Performance in a Tropical Catchment Using Structural Equation Modeling in the Lahumoko Watershed, North Buton, South East Sulawesi, Indonesia

Watershed performance in tropical regions is increasingly challenged by land use change, socio¬economic pressures, and governance limitations. While many studies emphasize biophysical drivers, integrated empirical assessments incorporating institutional and social dimensions remain limited. This study investigates the determinants of watershed performance in the Lahumoko Watershed, Southeast Sulawesi, Indonesia, using covariance-based Structural Equation Modeling (SEM). Five latent exogenous variables are land use, biophysical conditions, social factors, economic factors, and institutional capacity, were modeled to explain watershed performance as the endogenous construct. Primary data were collected through structured questionnaires administered to key stakeholders, complemented by secondary spatial and hydrological data. The SEM results indicate that biophysical conditions exert the strongest direct influence on watershed performance, followed by land use and institutional capacity. Social factors show a moderate but significant effect, whereas economic factors influence watershed performance mainly through indirect pathways. The model demonstrates satisfactory goodness-of-fit statistics (RMSEA ≤ 0.08; CFI and TLI ≥ 0.90). These findings underscore the necessity of integrated watershed management strategies that combine ecological restoration, sustainable land use planning, and institutional strengthening. The results provide empirical evidence to support policy interventions aimed at improving watershed sustainability in tropical developing regions.

watershed performance; land use change; institutional capacity

1. Asdak, C. (2018). Hidrologi dan pengelolaan daerah aliran sungai (Edisi revisi). Gadjah Mada University Press. [Google Scholar] [Crossref]

2. Chen, L., Pu, Y., Zhu, K., Guo, C., Wang, Y., & Shen, Z. (2024). Integrating best management practices with dynamic water environmental capacity for optimal watershed management. Journal of Environmental Management, 371, 123264. [Google Scholar] [Crossref]

3. Darmawan, A., et al. (2024). Assessing future land-uses under planning scenarios: A case study of the Brantas River Basin, Indonesia. Environmental Challenges, 15, 100873. [Google Scholar] [Crossref]

4. FAO. (2011). The state of the world's land and water resources for food and agriculture. Food and Agriculture Organization of the United Nations. [Google Scholar] [Crossref]

5. Fornell, C., & Larcker, D. F. (1981). Evaluating structural equation models with unobservable variables and measurement error. Journal of Marketing Research, 18(1), 39–50. [Google Scholar] [Crossref]

6. Hair, J. F., Black, W. C., Babin, B. J., & Anderson, R. E. (2019). Multivariate data analysis (8th ed.). Cengage. [Google Scholar] [Crossref]

7. Kahirun, K., Baco, S. L., Muhsimin, M., Qadri, S., & Ardi, A. (2024). Land use change and carbon stocks in the Toari Watershed. Journal La Lifesci, 5(4), 369–381. [Google Scholar] [Crossref]

8. Liu, J., Dietz, T., Carpenter, S. R., Alberti, M., Folke, C., Moran, E., Pell, A. N., Deadman, P., Kratz, T., Lubchenco, J., Ostrom, E., Ouyang, Z., Provencher, W., Redman, C. L., Schneider, S. H., & Taylor, W. W. (2007). Complexity of coupled human and natural systems. Science, 317(5844), 1513–1516. [Google Scholar] [Crossref]

9. Ostrom, E. (2009). A general framework for analyzing sustainability of social-ecological systems. Science, 325(5939), 419–422. [Google Scholar] [Crossref]

10. Pahl-Wostl, C. (2019). The role of governance modes and meta-governance in the transformation towards sustainable water governance. Environmental Science & Policy, 91, 6–16. [Google Scholar] [Crossref]

11. Pambudi, A. S. (2019). Watershed management in Indonesia: A regulation, institution and policy review. The Indonesian Journal of Development Planning, 3(2), 185–202. [Google Scholar] [Crossref]

12. Perdinan, P., Tjahjono, R. E. P., Infrawan, D. Y. D., Aprilia, S., Adi, R. F., Basit, R. A., Wibowo, A., Kardono, & Wijanarko, K. (2024). Translation of international frameworks and national policies on climate change, land degradation, and biodiversity to develop integrated risk assessment for watershed management in Indonesia. Watershed Ecology and the Environment, 6, 1–12 [Google Scholar] [Crossref]

13. Perera, T. A. N. T. T., Piyadasa, R. U. K., Gunarathna, M. H. J. P., & Kumar, D. N. (2024). SWAT model to simulate hydrological responses to land use and land cover changes in a tropical catchment: A study in Sri Lanka. Groundwater for Sustainable Development, 26, 101251. [Google Scholar] [Crossref]

14. Wahyunto, et al. (2023). Modelling land use/land cover projection using different scenarios in the Cisadane Watershed, Indonesia: Implication on deforestation and food security. Egyptian Journal of Remote Sensing and Space Science, 26(2), 273–283. [Google Scholar] [Crossref]

15. Wiwoho, B. S., Phinn, S., & McIntyre, N. (2023). Characterizing watersheds to support land-use planning in Indonesia: A case study of Brantas tropical watershed. Ecohydrology & Hydrobiology, 23(4), 635–649. [Google Scholar] [Crossref]

16. Zhang, et al. (2021). Relating land-use/land-cover patterns to water quality in watersheds based on structural equation modeling. CATENA, 206, 105514. [Google Scholar] [Crossref]

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