Using the Soil and Water Assessment Tool (SWAT) to Assess Material Transfer in the Layawan Watershed, Mindanao, Philippines and Its Implications on Payment for Ecosystem Services


  •  Leo Kris Palao    
  •  Moises Dorado    
  •  Kharmina Paola Anit    
  •  Rodel Lasco    

Abstract

Soil and water are the most important resources in the watershed. The alterations on the quantity and quality of these resources do not only have on-site impacts, but are experienced by off-site communities as well. To assess the material transfer and identify critical sub-basins in the Layawan Watershed, Mindanao, Philippines; the Soil and Water Assessment Tool (SWAT) Model was used. The model was also used to investigate changes in land use. Results show that a 4% reduction in sediment concentration and sediment yield in the critical sub-basins will be achieved if the community-based watershed management plan is implemented. On the other hand, there will be a 106% increase in sediment concentration and sediment yield if forests are cleared for utilization, primarily for agriculture, in the critical sub-basins. Modeling sediment yield and sediment concentration is important to help policy makers, environmental managers, and development agencies predict the impact of activities on soil and water quality, as well as guide them in the implementation of payments for ecosystem services (PES) schemes. The quantification of ecosystem services has been a major challenge surrounding the success of PES. In the Layawan Watershed, it is shown that land change use will not likely affect water quantity, it will, however, heavily impact water quality. Modeling provides an avenue to manage watersheds effectively and efficiently. SWAT running on open source GIS could help budget-constrained government units and development agencies to better predict the impact of programs and projects on watersheds.


This work is licensed under a Creative Commons Attribution 4.0 License.
  • Issn(Print): 1913-9063
  • Issn(Onlne): 1913-9071
  • Started: 2008
  • Frequency: bimonthly

Journal Metrics

Google Scholar Citations

Google-based Impact Factor (2017): 3.25

h-index (2017):  33

i10-index (2017): 81

h5-Index (2017): 18

h5-Media (2017): 25

Contact