Literature DB >> 26915561

Integrating land use and climate change scenarios and models into assessment of forested watershed services in Southern Thailand.

Yongyut Trisurat1, Piyathip Eawpanich2, Risto Kalliola3.   

Abstract

The Thadee watershed, covering 112km(2), is the main source of water for agriculture and household consumption in the Nakhon Srithammarat Province in Southern Thailand. As the natural forests upstream have been largely degraded and transformed to fruit tree and rubber plantations, problems with landslides and flooding have resulted. This research attempts to predict how further land-use/land-cover changes during 2009-2020 and conceivable changes in rainfall may influence the future levels of water yield and sediment load in the Thadee River. Three different land use scenarios (trend, development and conservation) were defined in collaboration with the local stakeholders, and three different rainfall scenarios (average rainfall, climate change and extreme wet) were determined on the basis of literature sources. Spatially explicit empirical modelling was employed to allocate future land demands and to assess the contributions of land use and rainfall changes, considering both their separate and combined effects. The results suggest that substantial land use changes may occur from a large expansion of rubber plantations in the upper sub-watersheds, especially under the development land use scenario. The reduction of the current annual rainfall by approximately 30% would decrease the predicted water yields by 38% from 2009. According to the extreme rainfall scenario (an increase of 36% with respect to current rainfall), an amplification of 50% of the current runoff could result. Sensitivity analyses showed that the predicted soil loss is more responsive to changes in rainfall than to the compared land use scenarios alone. However, very high sediment load and runoff levels were predicted on the basis of combined intensified land use and extreme rainfall scenarios. Three conservation activities-protection, reforestation and a mixed-cropping system-are proposed to maintain the functional watershed services of the Thadee watershed region.
Copyright © 2016 Elsevier Inc. All rights reserved.

Entities:  

Keywords:  CLUE-s model; InVEST model; Thadee watershed; Watershed services

Mesh:

Substances:

Year:  2016        PMID: 26915561     DOI: 10.1016/j.envres.2016.02.019

Source DB:  PubMed          Journal:  Environ Res        ISSN: 0013-9351            Impact factor:   6.498


  6 in total

1.  Scenario analysis of the impacts of socioeconomic development on phosphorous export and loading from the Dongting Lake watershed, China.

Authors:  Ying Hou; Weiping Chen; Yuehua Liao; Yueping Luo
Journal:  Environ Sci Pollut Res Int       Date:  2017-09-27       Impact factor: 4.223

2.  Basin-wide Impacts of Climate Change on Ecosystem Services in the Lower Mekong Basin.

Authors:  Yongyut Trisurat; Aekkapol Aekakkararungroj; Hwan-Ok Ma; John M Johnston
Journal:  Ecol Res       Date:  2018       Impact factor: 1.917

3.  Spatio-temporal evolution and driving factors of carbon storage in the Western Sichuan Plateau.

Authors:  Mingshun Xiang; Chunjian Wang; Yuxiang Tan; Jin Yang; Linsen Duan; Yanni Fang; Wenheng Li; Yang Shu; Mengli Liu
Journal:  Sci Rep       Date:  2022-05-17       Impact factor: 4.996

4.  Integrating the SD-CLUE-S and InVEST models into assessment of oasis carbon storage in northwestern China.

Authors:  Youjia Liang; Lijun Liu; Jiejun Huang
Journal:  PLoS One       Date:  2017-02-23       Impact factor: 3.240

5.  Land-Use/Land-Cover Change from Socio-Economic Drivers and Their Impact on Biodiversity in Nan Province, Thailand.

Authors:  Yongyut Trisurat; Hiroaki Shirakawa; John M Johnston
Journal:  Sustainability       Date:  2019-01-26       Impact factor: 3.251

6.  A century of precipitation trends in forest lands of the Lower Mississippi River Alluvial Valley.

Authors:  Ying Ouyang; Jiaen Zhang; Gary Feng; Yongshan Wan; Theodor D Leininger
Journal:  Sci Rep       Date:  2020-07-30       Impact factor: 4.996

  6 in total

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