Land Use and Land Cover Scenarios for Optimum Water Yield and Sediment Retention Ecosystem Services in Klong U-Tapao Watershed, Songkhla, Thailand

Jamroon Srichaichana,Yongyut Trisurat,Suwit Ongsomwang

doi:10.3390/su11102895

Jamroon Srichaichana, Yongyut Trisurat + Show 1 more

Open Access

https://doi.org/10.3390/su11102895

Copy DOI

Abstract

The Klong U-Tapao watershed is the main source of water supply for agriculture, industry, and household consumption of the Songkhla province and it frequently contributes serious problems to lowland areas, particularly flood and soil erosion. Therefore, land use and land cover (LULC) scenario identification for optimum water yield and sediment retention ecosystem services are necessary. In this study, LULC data in 2010 and 2017 were firstly classified from Landsat data using random forests classifiers, and they were then used to predict LULC change during 2018 –2024 under three different scenarios by CLUE-S model. Later, actual LULC data in 2017 and predictive LULC data of three scenarios were further used to estimate water yield and sediment retention services under the InVEST and LULC scenario for optimum water yield and sediment retention ecosystem services were finally identified using the ecosystem service change index (ESCI). The result of the study showed the major increasing areas of LULC types during 2010–2017 were rubber plantation and urban and built-up area while the major decreasing areas of LULC classes were evergreen forest and miscellaneous land. In addition, the derived LULC prediction of three different scenarios could provide realistic results as expected. Likewise, water yield and sediment retention estimation of three different scenarios could also provide expected results according to characteristics of scenarios’ definitions and climates, soil and terrain, and LULC factors. Finally, LULC of Scenario II was chosen for optimum water yield and sediment retention ecosystem services. In conclusion, the integration of remote sensing technology with advanced classification methods and geospatial models can be used as proficient tools to provide geospatial data on water yield and sediment retention ecosystem services from different scenarios.

Highlights

Water yield is the sum of runoff from the landscape [1,2]
High water yield is an ecosystem service, as is surface runoff, which is dependent on the vegetation cover under a given land use; over-surface runoff is not an appropriate situation as an ecosystem service [5,6]
Approximately 192o.f0262 km2 of rubber plantations were transformed to oil palm plantation as the result of government policy (Ministry17o7f.75Akgmri2courl7tu.3r9e% ainn2d01C0 oanodpceorvaetrievdeasr,ea20o1f 245)4. .0N1ekvme2rothr e10le.5s6s%, aanbdo1u4t2.7537%kmo2 form5.i9s3c%elilna2n0e1o7us land (129.21 km(Fi2g)uarned3).2I0n%adodfiteivone,rtghreedeenrifvoerdeosvtserianll2a0cc1u0ra(6cy3.a3n3dkKmap2)pawheartecoceoffinvcieenrttefdoricnlatossirfiuebdbtheermpalatinc tations

Summary

Introduction

Water yield is the sum of runoff from the landscape [1,2]. The relative water volume in a given landscape affects the quality of ecology in the area [3]. Changes in the landscape that affect the annual average water yield can increase or decrease land productivity. Replacing forests on slope land or mountainous areas with rubber plantations results in water retention in the subsoil layer and decreases water discharge in the dry season and increases evapotranspiration [4]. Cultivated land leads to larger average amounts of surface runoff and higher water loss from the reduced evapotranspiration in the wet season. The water yield is reflected as cumulative surface runoff measured at a specific location; it is not the desired type of regulation of water flow with yield and quality. High water yield is an ecosystem service, as is surface runoff, which is dependent on the vegetation cover under a given land use; over-surface runoff is not an appropriate situation as an ecosystem service [5,6]

Results

Discussion

Conclusion