INTEGRATION OF RS/GIS FOR ESTIMATION OF SOIL EROSION IN LAM PHRA PHLOENG RESERVIOR, NAKHON RATCHASIMA

PROVINCE, THAILAND

O.Polpanich1, K. Nongpho2, K. Boonwan2, C. Chandraphabha2, M. Hakari1 and L. Samarakoon1 1 Geoinformatics Center, Asian Institute of Technology, P.O. Box 4, Klong luang, Pathumthani

12120, Thailand; Tel: +66 2 524 5580, Fax: +66 2 524 6147; Email: ornuma@gmail.com

2Protected Area Rehabilitation and Development Office, Department of National Park, Wildlife and Plant Conservation, 61 Pholyothin Road, Ladyao, Chatuchak, Bangkok 10900, Thailand;

Tel: 66 2579 3211, Fax: 66 2579 3211   

KEY WORDS: Drought, NDVI, Surface reflectance, Land surface temperature, Soil moisture index, Mongolia  ABSTRACT: Thailand is experiencing enormous landuse changes due to increasingly intensive agriculture. Lam Phra Phloeng watershed is one such example in the north-eastern part of Thailand and agricultural land in the area is losing productivity due to high rate of soil erosion and affecting marginal farmers adversely. Quantification of soil erosion thus becomes important and integration of remote sensing (RS) and GIS data with soil erosion models will be useful for this purpose. The purpose of this study was to (i) classify landuse/land cover map using ALOS/AVNIR-2 data acquired in 2006 and 2008 in Lam Phra Phloeng watershed, and (ii) estimate soil erosion in the study area using USLE model and E30 model. As the results, USLE estimated erosion rate was 52,770 ha (64%), 5,049 ha (6%), 17,748 ha (22%), 5,410 ha (7%) and 1000 ha (1%) in 2006, while in 2008 was about 50,417 ha (62%), 5,304 ha (6%), 9,968 ha (12%), 6,263 ha (8%) and 10,026 ha (12%) respectively. Erosion mostly occurred in the agricultural land use, when USLE modeling. E30 modeled erosion rate was low in 2006 as a whole watershed (81,000 ha), while 78,000 ha of the total watershed area (97%) was very low in 2008 and 3,000 ha (3%) was low erosion rate. Erosion occurrence largely found in the ridgeline of mountainous watershed in the two different years. The results are a help to policy makers, managers and planners for the appropriate land use planning, management and conservation practices in the study area for reducing the soil erosion. Land use cover change is updated available to concerned officials to take further necessary measures. 1. INTRODUCTION Lam Pra Phloeng reservoir is classified to be one of the most active agricultural areas in Thailand. Severe erosion of the areas becomes the big problem consequentlyi; the reservoir is one of the most seriously affected by soil erosion related sedimentation in Thailand. Clearing in the watershed from 1974 to 1985 reduced forest area by about 70% (from 531 sq.km to 160.25 sq.km). The dominant crops in the upper watershed are sugarcane and cassava. After the crop has been harvested the land is tilled and becomes sensitive to sheet erosion. The area suffers periodically from floods as well as droughts. Because of these rapid changes there is an increased sediment load in rivers draining into the reservoir. As a direct result the Lam Phra Phloeng reservoir has become very shallow at the point where major stream enterii. This result to

reduce the lifespan and capacity of the reservoir, caused by sediment inflow volumes generated from the upstream of the watershed and the deposition in downstream of the Lam Phra Phloeng reservoiriii. This study concerns the quantification of soil loss and its erosion rate in the reservoir using remote sensing (RS) and geographic information system (GIS). In doing empirical method, it is time and cost-consuming as well as highly intensive labor. Quantification of soil loss and its erosion by using satellite-based data is very useful because it can be simply applied in many areas and is well-translated to variations of the spatial data in timely manner. The major objective of the study is to apply high resolution images and RS/GIS technique for identifying land use land cover and compare the results of soil erosion estimation obtained from the Universal Soil Loss Erosion (USLE) and E30 model in the Lam Phra Phloeng Watershed, Nakhon Ratchasima Province. To achieve the research’s expected outputs, the specific objectives are 1) to classify land use land cover map of Lam Phra Phloeng watershed using ALOS/AVNIR-2 acquired in 2006 and 2008, 2) to estimate soil loss in the watershed by modeling the USLE and E30, and 3) to compare soil erosion results obtained from USLE and E30 model in the watershed to find out the differences of the two models. 2. STUDY AREA Lam Phra Phloeng watershed stretches approximately from 101º 29´ 6″ to 101º 54´ 28.8″ towards east and 14º 18´ 18″ to 14 º 45 ´28.8″ north in WGS 84 coordinate system with the total acreage of 819.80 square kilometer (81,980 hectares). The area is characterized by a hilly topography with undulating slope and flat areas. It is bounded by Pha Khao Phu Luang National Reserve Forest in the north and Khao Yai National Park in the south of the watershed. The elevation ranges approximately from 200 m to 1,300 m above mean sea level (MSL).

Figure 1 Location map of Lam Phra Phloeng watershed obtained from the Department of National Park Wildlife

and Plant Conservation

3. MATERIALS AND METHODOLOGY Data used for the study included: 1) ALOS/AVNIR-2 acquired on 3 September 2006 and 16 November 2008, supported by Japan Aerospace Exploration Agency (JAXA)

2) Field measurement data such as average annual rainfall by 23 stations in the watershed as year of 2006 and 2008, obtained from Royal Irrigation Department and Land Development Department. 3) Ground information of recognizable land features for land use classification conducted from the field visit 4) Topographic map at scale 1:50,000, obtained from the Royal Thai Survey Department. 5) Soil map, contour map and reservoir boundary were obtained from the Land Development Department and Royal Thai Survey Department at a scale of 1:50,000. Universal Soil Loss Equation (USLE) and E30 model were comparatively applied to carry out the soil erosion assessment. The research methodology presents in the Figure 2.

Figure 2 Comparative study of the USLE and E30 model in the Lam Phra Phloeng watershed, Thailand

The USLE model for estimating soil erosion requires parameters, namely, rainfall (R), soil erodibility (K), slope length (LS), vegetation cover and management (C) and support practice (P). Annual mean rainfall from 23 rain gauge stations available around the study area was used to estimated the value of R. The K-value was obtained from nomograph method calculated by the Land Development Department (LDD). Contour interval at 20 m was used to generate DEM for calculating LS-value. Land use map obtained from ALOS/AVNIR-2 provided the information of C- and P-value. The results is calculated as the mean annual soil loss in ton per hectare per year.

Figure 3 is the model input parameters used in USLE computation

R-factor K-factor LS-factor C-factor P-factor

USLE model is defined as: A (ton/ha/yr) = R K LS C P Where, A is the soil loss is ton/ha/yr, R is the rainfall-runoff erosivity factor in MJ mm/ha/h/yr, K is the soil erodibility factor in t h/MJ mm, LS is the slope length and steepness factor, C is the vegetative cover factor and P is the conservation support-practice factor. The E30 model is mainly governed by annual rate of soil erosion at 30° slope and vegetation cover. ALOS/AVNIR-2 images of 2006 and 2008 were used to calculate the Normalized Difference Vegetation Index (NDVI) for obtaining the vegetation cover, while slope factor was obtained from DEM. Result of E30 model is defined as rate of soil erosion in millimeter per year.

E30 model is defined as E = 9.0

3030 ⎟

⎟

⎠

⎞

⎜⎜

⎝

⎛

SSE

Where, E = rate of soil erosion (mm/yr), E30 = rate of soil erosion at 30° slope (defined as below), S = gradient of the point under consideration and S30 = tan (30°)

( ) ( ) ( ) ( )⎥⎦

⎤⎢⎣

⎡+−⎟

⎠⎞

⎜⎝⎛

−−

= soillossLoginNDVNDVIxinNDVaxNDVsoillossLogsoillossLogE maxIm

ImImmaxmin

30

4. RESULTS AND DISCUSSION On-screen digitizing using GIS-based visual interpretation with verification of land cover features conducted from field visit was analyzed to classify land use of the Lam Phra Phloeng watershed as map shown in Figure 4. There was slightly change in the watershed between 2006 and 2008. The area was mostly converted to crop land. About 0.50 percent of orchard was replaced by crop land, 0.17 percent of dry evergreen to crop land and 0.04% of forest plantation to crop land.

Figure 4 Land use cover change in 2006 and 2008 The USLE estimated erosion rate was very low, low, moderate, severe and very severe for the two different years (2006 and 2008). These rates were quantified in terms of area as 52,770 ha (64%), 5,049 ha (6%), 17,748 ha (22%), 5,410 ha (7%) and 1000 ha (1%) in 2006, while in 2008 was about 50,417 ha (62%), 5,304 ha (6%), 9,968 ha (12%), 6,263 ha (8%) and 10,026 ha (12%)

respectively. Areas of very severe erosion are generally associated with rugged topography and minimal soil cover when USLE model performing. It mostly occurred in the agricultural land use. Erosion severity increased in 2008. Theoretically, it might have higher intensity of rainfall in 2008 than 2007, while others performance factors remaining the same. This may increase erosion rate in 2008 as changes in the kind of vegetation cover in the watershed can also affect erosion rates. Another influenced factor may be the watershed’ soil type as it was mainly sand and silt-loam. This soil type was was characterized as low erodible capacity to erosion.

Figure 5 Soil erosion map obtained from USLE As result from E30 model shown in Figure 6, the variation of NDVI in 2006 was similar to 2008. Low erosion rate in 2006 occurred in the watershed as a whole (81,000 ha), while 78,000 ha of the total watershed area (97%) was very low in 2008 and 3,000 ha (3%) was low erosion rate. Erosion occurrence was mostly predicted in the ridgeline of mountainous watershed in the two different years. Along the ridgeline, it expressed vastly severe comparing with other areas of the watershed. Consider the effect of slope length based on several previous studies, it has greatly influence soil erosion in the sloping upland area. Figure 6 presents soil erosion estimation map obtained from E30 model.

Figure 6 Soil erosion map obtained from E30 model

5. CONCLUSION The study concludes that ALOS/AVNIR-2 images with a-10 meter spatial resolution provides high information for land use land cover classification in the Lam Phra Phloeng watershed, particularly for delineating different forest types. Although ALOS/AVNIR-2 is such high multi-spectral image, the difficulty of identifying small patches of farmland is remaining. It is better to digitize on-screen with help of land features knowledge and expertise. Also, there is a limitation of cloud cover and its shadow that distorts to ground feature information in the multi-spectral images. Could masking is a must to remove some distortions of cloud cover pixels. Integration of RS/GIS technique is very effective tool to monitor and assess soil loss, land use pattern and its change because of its cost-effectiveness. From the study, no significant land use change was found in the watershed in the two different years (2006 and 2008) due to short span of time. USLE had estimated higher soil erosion rate in the watershed whereas E30 model estimated low erosion rate which is close to reality. However, there are some limitations of using E30 model as it requires actual measurement of annual soil loss (mm/yr) in the study area under different land use and land cover. Application of USLE model is difficulty in the retrieval of rainfall-runoff erositivity to perform R-factor in the study area. DEM used for calculating slope length was problematic, especially when soil erosion is not experimented at the plot study. 6. ACKNOWLEDGEMENT First and foremost, we would like to thank to our supportive contributor for this project, Japan Aerospace Exploration Agency (JAXA) for their financial support and providing us with a good opportunity to participate in the space technology application in the mini-project. We also would like to thank the Royal Thai Survey Department and Land Development Deportment for providing us spatial datasets to complete this project. Also, we would like to this opportunity to thank to Geoinformatics Center, Asian Institute of Technology, for their valuable guidance, advice and facilities to work on this project. i Phetprayoon,  T.,  S.  Sarapirome, C. Navanugraha,  and  S. Wonprasaid. 2009.  Surface Runoff  Estimation Using 

Grid‐Based Curve Number Method in the Upper Lam Phra Phloeng Watershed, Thailand. Paper presented in ACRS 

2009, Beijing, China. ii Heijnis, Hendrik, A. Sawadzki, K. Srisuksawad and K. Lorsirirat. 2003. Lam Phra Phloeng Dam, Thailand – A high 

resolution  record of human activity and climate variability. Presented  in Human‐environment  Interactions: Past 

and Present (Posters), Geological Society of America, 25 July 2003. iii Lorsirirat, K. and related. Effect of Land use Change on Soil Erosion and Sedimentation at Lam Phra Phloeng 

Reservoir  in  Northeastern  Thailand.  Accessed:  http://www.jsece.or.jp/event/conf/abstruct/2008/pdf/2008R5‐

002.pdf, 20 September 2010.