Impact of reclamation on the environment of the lower mekong river basin

Yusuke Hiraga, So Kazama, Chaiwat Ekkawatpanit, Yoshiya Touge

Research output: Contribution to journalArticlepeer-review

4 Citations (Scopus)

Abstract

Study Region: In the lower Mekong River Basin, the watershed development, such as reclamation, has been rapidly erence water index (NDWI) were defined as going on. The reclamation is expected to cause many problems on this important watershed environment. Study Focus: The objective of this research is to quantitatively clarify the impact of reclamation on the watershed environment of the lower Mekong River Basin. New hydrological insights: The locations of reclamation areas were extracted using MNDWI, NDVI and NDSI derived by Landsat data. As a result, the 49 reclamation areas covering approximately 95% of all 52 reclamation areas determined by visual extraction, were extracted. Then, the multiple logistic regression model was constructed to find the tendency of the occurrence of reclamation and reproduce the occurrence of reclamation. The test of goodness of fit, such as Hosmer-Lemeshow test and Nagelkerke coefficient, shows high adaptability (R2 = 0.89) of the probability model. The probability of occurrence of reclamation could be explained by the distance from the Phnom Penh city and the distance from the river channels. Moreover, the existence of reclamation areas was incorporated into the flood-inundation model and total phosphorus transportation model changing the value of the elevation and the phosphorus loading respectively. Consequently, the inundation water level increases about 3.8 m and total phosphorus concentration increases about 0.71 mg/L around Phnom Penh in case of the reclamation of 10% of all inundation areas of Phnom Penh and Kandal province.

Original languageEnglish
Pages (from-to)143-155
Number of pages13
JournalJournal of Hydrology: Regional Studies
Volume18
DOIs
Publication statusPublished - 2018 Aug

Keywords

  • Cambodia
  • Flood inundation model
  • Multiple logistic regression
  • NDWI
  • Remote sensing
  • Watershed development

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