The Impacts of Land-Use Input Conditions on Flow and Sediment Discharge in the Dakbla Watershed, Central Highlands of Vietnam

Abstract

The main objective of this study was to evaluate various land-use input conditions in terms of the performance improvement found in consequent flow and sediment simulations. The soil and water assessment tool (SWAT) was applied to the Dakbla watershed from 2000 to 2018. After the calibration and validation processes, dissimilar effects between the input conditions on the flow and sediment simulations were confirmed. It was recognized that the impact of the land use on the sediment simulation was more sensitive than with the flow simulation. Additionally, through monthly evaluation, the effects against the flow and sediment in the rainy season were larger than those in the dry season, especially for sediment simulation in the last three months from October to December. Changing land-use conditions could improve flow and sediment simulation performance better than the performance found with static land-use conditions. Updated land-use inputs should be considered in simulations if the given land-use condition changes in a relatively short period because of frequent land-use policy changes by a local government.

The evaluation of land use cover changes through the composite approach of Landsat 8 and the land use capability index for the Bedadung watershed

“…The images were analyzed using geodetic analysis and composited with band 654. Composite maps were focused on comparing colors, locations, objects, shadows, textures, sizes, patterns, and shapes (Nguyen et al, 2021;Tram et al, 2021). Land cover was analyzed using a guided classification method by focusing on the color in Landsat 8 images (Jia et al, 2014;Tassi et al, 2021).…”

Effects of local land-use policies and anthropogenic activities on water quality in the upstream Sesan River Basin, Vietnam

“…Updating land-use change information through different approaches is important when seeking to improve the accuracy of the model's performance (Moriasi et al, 2019;Wagner et al, 2019;and Aghsaei et al, 2020). In this study, a method confirmed by Tram et al (2021) was used to track the frequent and complicated local land-use policies by using R script. For the analysis, multiple land-use maps were developed on the basis of local information and policies reflected by the local land-use conditions (2005, 2010, 2015, and 2018)…”

“…Kon Tum had the lowest share of agriculture in 2016 among the five provinces in this region because of its poorer soil quality and lower agricultural productivity. An expansion of agricultural activities and a shift in cultivation toward the hillslope have been conducted in the target area since 2005 onwards (Tram et al, 2021). According to the 2010 statistical yearbook, there was an increasing tendency of agricultural land, urban areas, and forestry land with values of 39.9 %, 56.6 %, and 1.7 %, respectively, compared to 2005.…”

“…According to the 2010 statistical yearbook, there was an increasing tendency of agricultural land, urban areas, and forestry land with values of 39.9 %, 56.6 %, and 1.7 %, respectively, compared to 2005. From 2010 onward, a crop conversion policy that encouraged a move from mixed forests to rubber forests was enacted (Tram et al, 2021). Rubber trees predominated, accounting for 61.0 % (433.2 km 2 ) of the total mixed forest area (709.6 km 2 ) in Kon Tum province (Kon Tum Provincial People's Committee, 2016).…”

Evaluating Impacts of Detailed Land Use and Management Inputs on the Accuracy and Resolution of SWAT Predictions in an Experimental Watershed

“…Furthermore, previous studies investigating the difference between static and dynamic land use and management practice inputs used the earliest land use map available as the static condition and baseline scenario. As a result, they found obvious effects of land use changes on the simulation of flow, and sediment, nitrogen, and phosphorus loadings [48][49][50][51] and argued that differences in the land use input conditions could affect the long-term water quantity and quality simulation so that dynamic land use input was recommended. On the contrary, we used the land use map of 2001 (in the middle of the simulation period from 1992 to 2011) and limited management information as the static land use and management practice input for SWAT2.…”