Environmental Economics (May 2024)

Assessing payment for ecosystem services to improve lake water quality using the InVEST model

  • Supriyanto Supriyanto,
  • Dwi Nowo Martono,
  • Hayati Sari Hasibuan,
  • Djoko Mulyo Hartono

DOI
https://doi.org/10.21511/ee.15(1).2024.12
Journal volume & issue
Vol. 15, no. 1
pp. 149 – 173

Abstract

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Payment for ecosystem services is a conservation strategy designed to offer farmers financial incentives for managing land to provide ecological benefits without disturbing livelihoods. However, the distribution of spatial financial feasibility is challenging when implementing this strategy on watershed scale. This study aimed to develop payment for ecosystem services model to improve quality in lake water catchment. The model estimated incentive values based on the costs of farmers’ losses, water yields, and pollution loads. The potential loss was calculated by determining the income of farmers in lake water catchment spent on land conversion from intensive agriculture to agroforestry. Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) modeling tool was used to calculate water yield and pollution load. The model was tested with case study approach at Lake Rawa Pening in Indonesia, consisting of nine sub-basins and 75 village administrations. The results showed that the reference compensation for farmers was 1,255.97 USD/ha/year. Considering the spatial distribution of water yields, the incentive for each village varied widely from 891.54 USD/ha/year to 1,557.06 USD/ha/year, even within the same sub-basin. Ten villages had an incentive above 1,450.00 USD/ha/year. However, considering the water pollution load, 26 villages had an incentive above 1,450.00 USD/ha/year with a maximum of 2,024.17 USD/ha/year. Therefore, village boundary should be an analysis unit for determining spatial incentive feasibility rather than a sub-basin boundary. Moreover, the level of water pollution load can become an additional variable to justify the amount of incentives received by farmers.

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