Tanachaichoksirikun, Pinit

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Tanachaichoksirikun, Pinit
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pinit.ta@kmitl.ac.th

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    Item type:Publication,
    Impact of climate change on soil erosion in the lam phra phloeng watershed
    (2020-12-01)
    Sirikaew, Uba
    ;
    Seeboonruang, Uma
    ;
    Tanachaichoksirikun, Pinit
    ;
    Wattanasetpong, Jatuwat
    ;
    Chulkaivalsucharit, Virun
    Soil erosion plays a vital role in reducing reservoir capacity. The Lam Phra Phloeng (LPP) dams were built for flood protection and irrigation. However, they have experienced reservoir sedimentation, and the capacity of the reservoir has decreased. The surrounding soil surface was easily eroded and transported by heavy rainfall and surface runoff to streams and eventually into the reservoir. Understanding this soil erosion and sedimentation is necessary for preventing further decline of reservoir capacity and water management. This research aims to estimate long-term average annual soil erosion and predict sediment yield in the reservoir due to climate change. The methodology is determined soil loss parameters and sediment yield using the Universal Soil Loss Equation (USLE) with the Sediment Delivery Ratio (SDR). The USLE and SDR methods differed from field data, with an average absolute error of 4.0%. The Global Climatic Model, Institute Pierre Simon Laplace-Climate Model version 5A (IPSL-CM5A-MR), with Representative Concentration Pathways (RCP) 2.6, 4.5, and 8.5, was downscaled and analyzed to forecast future rainfall in the watershed. The high intensity of rainfall contributed to higher soil erosion, in RCP 8.5. Interestingly, the high and very high-risk areas increased, but the moderate risk area declined, indicating that the moderate risk area should be a priority in land management. However, the heavy rainfall and high slope gradient led to a slight increase in the soil erosion in some areas because the land covers were evergreen and deciduous forest. The prediction of sediment yield was positively correlated with the intensity of rainfall in the central part of the watershed, because the rainfall and runoff led the sediment to the river and streams, indicating that the land cover should be managed to prevent capacity decline.
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    Item type:Publication,
    Identifying Water Source Locations on a Data-Limited Small Island Using GIS and the Factor Index Method
    (2026-06-01)
    Seeboonruang, Uma
    ;
    Horpeancharoen, Witthawin
    ;
    Sirikaew, Uba
    ;
    Tanachaichoksirikun, Pinit
    ;
    Chulkaivalsucharit, Virun
    This study presents an integrated methodological framework for identifying potential freshwater source locations on data-limited small islands by combining Geographic Information Systems (GIS), the Soil and Water Assessment Tool (SWAT), and the Factor Index Method. The analytical workflow begins with processing spatial data (topography and land use) in a GIS environment to delineate initial watersheds. These inputs are then coupled with the SWAT model to simulate key hydrological output variables, such as surface runoff and stream network geometry, without requiring extensive historical streamflow data. The simulated outputs are subsequently reintegrated into the GIS environment to derive spatial attributes for each sub-basin. Subsequently, the Factor Index Method is applied to evaluate and rank the sub-basins using five key criteria: watershed area ratio, stream length ratio, slope, land use, and location accessibility. The analysis identified eight optimal sites, with field surveys confirming that four of these locations closely aligned with natural stream networks and existing spring-fed ponds. The results demonstrate that this approach can accurately delineate hydrological features and prioritize monitoring locations without extensive field data. By validating geospatial predictions through ground-truthing, this framework reduces the need for costly and time-consuming fieldwork. It enhances planning precision, supports efficient resource allocation, and can serve as a replicable model for sustainable water resource management on other small islands with similar data constraints.