Saowanee Wijitkosum

Environmental Research Institute Chulalongkorn University,Phayathai Road,Pathumwan,Bangkok,10330,Thailand

Keywords:Land degradation Desertification Critical factor Medalus Triangular fuzzy numbers

A B S T R A C T This study aimed to assess land degradation sensitivity of an area contributing to desertification risk in Lam Ta Kong Watershed using Environmental Sensitivity Area Index(ESAI).Five risk factors comprised climatic,soil,geographical,land utilization and vegetation,and water resources factors together with fifteen sub-factors were used to analyze the sensitivity to land degradation.The spatial analysis was calculated using Geographic Information System(GIS)and Remote Sensing(RS)techniques.The key factors influencing land degradation risks in the watershed area were analyzed using the triangular fuzzy numbers(TFNs)method.The results showed that approximately 33% of Lam Ta Kong watershed was affected by a high desertification risk excluded the water bodies and around 24.64% of the area suffered from a moderate risk.This research pointed out that key factors causing land degradation and desertification in the watershed area were related to the soil factors,followed by climatic,geographical factors,water resources,and land utilization and vegetation,respectively.The results of this study can be used as a database for planning and implementing area-based mitigations and measures as well as for land use planning in the watershed area.

1.Introduction

Land degradation and desertification are the most critical environmental issues in many parts of the world.The problems are challenging at local,regional,and global scales(Kosmas et al.,2014).Land degradation,drought,and desertification are closely related phenomena and the problems are quite complicated(Wijitkosum,2020;Lal,2012;UNSO,1999).Persistent degradation of dryland ecosystems caused by both climatic factors and human activities,including inappropriate land use and land management,led to desertification(Lahlaoi et al.,2017;Wijitkosum,2014;Xie et al.,2015).The impacts caused by climatic factors occur slowly,but those triggered by human activities accelerate rapidly and are more severe(Wijitkosum,2016;Elsayed,2013;Ibanez et al.,2008;Sepehr et al.,2007).

Land degradation and desertification are no longer limited to arid or semi-arid areas as previously defined by the United Nations Convention to Combat Desertification(UNCCD)(United Nations Convention to Combat Desertification[UNCCD],2005).Several studies indicated that various parts of the world are at risk and vulnerable to degradation,drought,and desertification(Momirović et al.,2019;Boudjemline&Semar,2018;Taghipour-Javi et al.,2016;Lal,2012;Bouabid et al.,2010;Contador et al.,2009).Therefore,combating drought,land degradation and desertification has been an international duty since 1992(UNCCD,2005),and the importance of this issue continues.The United Nations stated Target 15.3 as part of a sustainable development goal to end desertification and restore degraded lands by 2030.To achieve this goal,it is necessary to analyze current problems,future environmental trends,and vulnerability.Desertification,land degradation and drought are the global issues that pose severe challenges to the sustainable development of all countries.Vulnerability assessment is a process which monitors and assesses an area to prepare mitigations and prevent future problems caused by land degradation and desertification(United Nations Office for Disaster Risk Reduction[UNISDR],2014).Land degradation risk assessment mainly focuses on spatial analysis since the process involves several factors unique to particular areas.

The Environmentally Sensitive Area Index(ESAI)was developed for identifying environmentally sensitive areas(ESAs)by the Mediterranean Desertification and Land Use research project(Lahlaoi et al.,2017;Greco et al.,2005;Kosmas et al.,1999;Basso et al.,1999).Although the model was created and validated under the conditions of the Mediterranean area,the model was later adapted for other areas and showed good results(e.g.Bouabid et al.,2010;Taghipour-Javi et al.,2016;Wijitkosum,2020a).The original ESAI approach(Kosmas et al.,1999)involves soil,vegetation,climate,and management indices.It is a widely used model for monitoring desertification sensitivity in many areas.Many studies conducted in Euro-Mediterranean countries were analyzed based on the ESAI model such as Sepehr et al.(2007)in Iran,Momirović et al.(2019)in Serbia,Lahlaoi et al.(2017)and Bouabid et al.(2010)in Morocco.Nevertheless,the land degradation and desertification process of an area involve several factors;therefore,many scientists modified the traditional model by adjusting the indicators.Taghipour-Javi et al.(2016)incorporated irrigation water as a factor into the model while Honardoust et al.(2011)added soil erosion and waterlogging factors as indices for assessing desertification sensitivity area in Iran.Zolfaghari et al.(2019),Wijitkosum(2016),and Wijitkosum(2014)assessed the risk of desertification without considering management factors.The adjustment of various factors was considered based on conditions of the areas and risk factors that can affect land degradation and desertification.In addition,many studies modified the model by adding many suitable sub-indices for assessing desertification risk effectively.

Most researchers focused on the analysis of areas at risk,while the analysis of critical factors is still scarce.However,the analysis on critical risk factors was crucial to the planning of effective mitigations(Wijitkosum,2016).Many multiple mathematical models to group factors or analyze critical factors that pose a risk of desertification,land degradation,and drought were introduced such as hierarchical cluster analysis(Zolfaghari et al.,2019),Analytic Hierarchy Process(AHP)(Sa-Nguansilp et al.,2017),Fuzzy Analytic Hierarchy Process(FAHP)(Zhao et al.,2017).However,the most appropriate model for analyzing weight and data involving a large number of factors for solving environmental and disaster problems was FAHP(Wijitkosum & Sriburi,2019;Hosseini-Moghari et al.,2017;Zhao et al.,2017).FAHP(Chang,1996)was developed from the fuzzy set theory,it adopted the hierarchical model by taking into account layers of criteria and sub-criteria.

This study was conducted in Lam Ta Kong watershed,an important economic area located in the north-eastern part of Thailand.The area continually suffers from droughts for an extended period of time,especially during a dry spell and low precipitation period.This study aimed to explore a new approach for the assessment of vulnerability related to land degradation by incorporating the ESAI model together the FAHP approach with triangular fuzzy numbers(TFNs)and Geographical Information System techniques(GIS).The focus of this study was to assess the degradation sensitivity area and its critical desertification risks factors in order to propose feasible mitigations and preventive solutions base on land use management to combat desertification.

2.Methodology

2.1.Study area description

Fig.1.Lam Ta kong watershed area.

Lam Ta Kong watershed(Fig.1)is located in the latitude of 746129.500500-854329.500500 and longtitude of 1596615.963806-1671223.769666,which is a sub-basin of Mun River Basin.Lam Ta Kong is a medium size watershed with the area of 3419.90 sq km and is rectangular in shape.It has a fishbone river network which is narrow and long.Lam Ta Kong River is connected,originated in Khao Yai National Park in Pak Chong District,is connected with the watershed.The river,approximately 220 km in length,flows from the central part of Khao Yai and runs in a northeasterly direction to the Mekong River.Lam Ta Kong Reservoir,with a capacity of 314 million cubic meters(MCM),is the main source of water supporting all activities in five districts in the downstream area,including agriculture,manufacturers,and more than 83 communities(Wijitkosum & Sriburi,2008).The watershed covers six districts which is divided into two main parts:the upper watershed area situated above the reservoir and the lower watershed area below the reservoir.The upper reservoir area covers one district called Pak Chong District while the lower area covers five districts as follows Si Khiu,Sung Noen,Kham Thale So,Muang Nakhon Ratchasima and Chalearm Prakeate(Fig.1).

The majority area of Lam Ta Kong watershed was at moderate risk of physical drought(Wijitkosum,2018),and severe risk of agricultural drought(Sa-Nguansilp et al.,2017).Moreover,the volume of water runoff in the upstream area and the average amount of runoff flowing into the reservoir tended to decrease(Lamtakong Operation and Maintenance Project,2018).

The land usage in the upper area of the watershed is for natural and agricultural tourism.The urban area that is the second largest urban area in the watershed.The lower area of the watershed is facing continuous expansion of agricultural utilization and urbanization.Nakhon Ratchasima has been experiencing a rapid urban expansion which continues to the present day.According to Chotchaiwong and Wijitkosum(2019),it was apparent that the urbanization occurred between 2002 and 2016 both in economic activities and land use changes.Built-up areas increased to 56.04%which reduced the green areas to 35.53%and bare lands decreased to 4.80%.Nakhon Ratchasima still has the tendency to expand in the future from analyzing the city’s growth trend from the past.The built-up areas would reach 85.88%of the total area,its green areas would occupy 11.67%,its bare lands would take up 2.15%and 0.30%would be the water bodies.The major part of the watershed area(65%)is used for agricultural purpose.As for agricultural areas,some parts of the watershed covered with alkaline soil where is critically affected by salinization to the point that patches of salt stains are visible on the surface(Wijitkosum,2018).The distribution of salt-affected soil in the area is mainly due to the groundwater flow and deep drainage in recharge areas.

2.2.Factor analysis and identify factors contributing to land degradation and desertification

To identify the factors that led to land degradation and desertification in Lam Ta Kong watershed,the spatial factors leading to such problem were considered and risk factors contributing to land degradation and desertification reported in other study areas in Thailand were reviewed.Five main factors and fifteen sub-factors were identified.The main factors comprised climatic factor(three sub-factors),soil factor(five sub-factors),geographical factor(two sub-factors),land utilization and vegetation factor(two subfactors)and water resource factor(three sub-factors).

The sensitivity to land degradation was identified by combining five quality indices:climatic,soil,geographical,land utilization and vegetation,and water resources.Each sub-index,or sub-factor,was applied a quantitative classification scheme with a score of 1(best value;least sensitive to desertification),2(worst value;most sensitive to desertification),and values between 1 and 2 represented relative vulnerability(Boudjemline & Semar,2018;Kosmas et al.,1999;Sepehr et al.,2007).The classes and assigned weighting index for the index are shown in Tables 1-5.The determination of classes and assigned weighting index for factors adapt from research of Land Development Department(2004),Sepehr et al.(2007)and Wijitkosum(2016).The classes of sub-indices are optimized according to the spatial conditions and spatial data.

The climatic factors consisted of aridity index(AI),precipitation,and precipitation days.The meteorological data were obtained from eight local agrometeorological stations over a period of 26 years(1990-2016).The agrometeorological stations scattered in the watershed area.The precipitation data were analyzed with areal data using equal interval.The double mass curve model(Searcy&Hardison,1960)was used for the analysis of stability and consistency of the data(Wijitkosum & Sriburi,2019).Chomtha(2006)suggested that the AI method(Equation(1))was the most suitable method for assessing the aridity index in the northeastern region of Thailand.Penman-Monteith equation(Food and Agriculture Organization[FAO],2009)was used to calculate the reference evapotranspiration(Equation(2))(Allen et al.,1998;Wijitkosum,2014)

where AI is an aridity index,P is annual precipitation(mm),Kcis a crop coefficient,and ET0is reference evapotranspiration.

where Rn:net radiation at the crop surface(MJ m-2day-1),G:soil heat flux density(MJ m-2day-1),γ:psychrometric constant(kPa°C-1),T:mean daily temperature at 2 m height(°C),U2:wind speed at 2 m height(ms-1),es:saturation vapour pressure(kPa),ea:actual vapour pressure(kPa),es-ea:saturation vapour pressure deficit(kPa),andΔ:slope vapour pressure curve(kPa°C-1)

The classes and assigned weighting index for climatic subindices are shown in Table 1.

The soils are a crucial component of land resources,which perform many vital functions in the ecosystem(Lal,2012).Soil resources are essential for agriculture,cultivation,hydrological system,and evaporation of water in the soil.Drought and desertification have diverse effects on the soil and,on the other hand,drought and desertification are also triggered by land degradation.Therefore,soil resources are one of the essential factors in assessing the risk of land degradation,drought,and desertification(Wijitkosum,2020b;Bouabid et al.,2010;Taghipour-Javi et al.,2016).

The soil factor consisted of soil texture,soil fertility,soil drainage,soil erosion,and soil salinity.The sub-factors related to soil characteristics were taken from the Land Development Department(LDD)together with data from field research.The soil erosion index was obtained from calculating Universal Soil Loss Equation(USLE)(Wischmeier and Smith,1978)which was the most suitable equation for soil erosion in Thailand.The classes and assigned weighting index for soil sub-indices are shown in Table 2.

The geographical factor related to land degradation and desertification contained two sub-factors which were slope gradients and elevations.The data were obtained from topographic maps(1:25,000 maps)made available by the Royal Thai Survey Department,Royal Thai Armed Forces Headquarters.The slope and altitude data were derived from creating digital elevation models(DEMs).The classes and assigned weighting index for geographical sub-indices are shown in Table 3.

Table 1 Classes and assigned weighting values for different climatic sub-indices.

Table 2 Classes and assigned weighting values for different soil sub-indices.

Table 3 Classes and assigned weighting values for different geographical sub-indices.

Table 4 Classes and assigned weighting values for different vegetation sub-indices.

The land utilization and vegetation factor comprised land use and land cover.The remote sensing and GIS technology were integrated to classify the data and map the land utilization and vegetation factor.The data used for this factor was obtained from satellite images taken by Theos satellite with a multispectral 15-m resolution and were processed by the ArcGIS software.The georeferencing accuracy of the image was cross-checked with field research and cross-referenced with governing organization.The vegetation sub-indices were classed and weighted as shown in Table 4.

The water resource factor consisted of stream density,distance from irrigation cannel,and ground water volume.The data used for stream density and distance from irrigation canal factors were satellite images taken by Theos satellite,and from Department of Water Resource,Royal Irrigation Department,Office of Regional Irrigation Office 8.The stream density(SD)is calculated by L/A,when L is the length of the streams(km)and A is the watershed area(sq km).The distances from irrigation canal are analyzed by buffer assignment where distances are determined by class.The ground water volume data obtained from the Departmentof Groundwater Resources isdata in the form of the shape files.The classes and assigned weighting index for water resources sub-indices are shown in Table 5.

Table 5 Classes and assigned weighting values for different water resource sub-indices.

In this study,the factor analysis and spatial models,including methodology for the determination of ESAIs,were done by using GIS software supported by geographical analysis processes that enhance the precision of the output of the models.

2.3.Environmental sensitivity areas to degradation in the lam Ta kong watershed

The ESAs approach(Kosmas et al.,1999),the vulnerability to degradation method was developed to identify the pertinent problematic areas that were sensitivity to degradation(Honardoust et al.,2011;Sepehr et al.,2007).The method identified the sensitivity area through the ESAI which the index could be used to obtain an in-depth understanding of the parameters causing land degradation and desertification threats at a certain point(Kosmas et al.,2014).The ESAI contains scores to calculate the sensitivity of an area and an impact that each of the parameters has to the particular area(Lahlaoi et al.,2017;Wijitkosum,2016;Sepehr et al.,2007).In this study,the ESAs approach was adapted and modified by integrating five factors to provide an overall picture of the environmental conditions without considering the land management factor in the area.Land sensitivity to degradation was defined as the final step in an environmental quality index,classifying the watershed area into five quality indexes.The ESAI was compiled using geometric means(Equation(3)to Equation(7))which was constructed from the ESAs approach(Kosmas et al.,1999).Each quality index was calculated using the respective algorithm as shown in Table 6.

Table 6 Environmental properties related to land degradation sensitivity indices.

The spatial model created with ArcGIS 10.7v.software tools facilitated parametric entry for calculations and scores generated by ESAI approach.Each quality index,the algorithm Equation(3)to Equation(7),was generated in GIS software to produce maps showing degradation risk factors.These maps were generated from the calculation using an ESAI based on ESAs approach(Equation(8))(Kosmas,1999),computed by the spatial analysis functions.

2.4.Computational procedure of triangular fuzzy number and fuzzy analytical hierarchy process

FAHP is a method computed based on the fuzzy set theory(Zadeh,1996)and an AHP(Saaty,1980).Fuzzy set theory was designed to simulate the uncertainty of the cognitive processes of humans.The concept of fuzzy sets is a class of objects with a continuum of grades of membership that divides the evaluation results into intervals(Zadeh,1996).A fuzzy set is defined by a membership function and its membership function completely characterized all the information about a fuzzy set.It is also defined as a set of ordered pairs(Equation(9))(Amini & Nikraz,2017):

The degree of membership function was operated over the range of real numbers[0,1]that was the unit interval.A fuzzy set contains elements that have different degree of membership in it.The main characteristic of fuzziness is the grouping of individuals into classes that do not have sharply defined boundaries.A fuzzy set A is given by its membership function A:X→[0,1].

Chang(1996)proposed the TFNs to the pairwise comparisons among all criteria or factors in the dimensions of a hierarchysystem.The pairwise comparison was used to replace crisp values to eliminate vagueness of the factors by taking into account layers of criteria and sub-criteria.is a special class of the fuzzy numbers.The membership functionsare explained in Equation(10).TFNs can be defined by a triplet(l，m，u）

where 0≤l≤m≤u≤1,l stands for the lowest possible value,m presents the most possible value or the modal value,and u presents the highest possible value.The triangular membership function can be based on 10 fuzzy linguistic values(Table 7).

The values in the range between the lowest and highest possible values have a membership grade between 0 and 1,with the most possible value having a membership grade of 1.The lowest and highest possible values have membership grades of 0 because they represent the lower and upper limits of the fuzzy range outside which no values belong to the fuzzy number.The membership grade for a given value in the range between the lowest possible value and the highest possible value was evaluated using linear interpolation by finding the membership grade on the straight line corresponding to a given value in the fuzzy range.

By using TFNs,via pairwise comparison,the fuzzy evaluation matrixwas constructed.where l,m and u represent a fuzzy degree of judgment.Pair-wise matrices consisted of triangular fuzzy numbers are given as Equation(11)(Wang et al.,2008).

The TFNs are known as the relative weights for each alternative under a given criterion and are also used to represent the weight of each criterion concerning the total objective.A weighted summation is then used to obtain the overall performance of each alternative.In the FAHP procedure,defuzzification is a kind of the transformation from triangular fuzzy member values to a crisp value（xcrisp）.In this study,Centroid(Center-of-gravity)Average(CA)(Yager& Filev,1994)was used for defuzzification.

To calculating the consistency ratio of each matrix,in comparison with the fuzzy using the Equation 13 and 14(Wijitkosum &Sriburi,2019),the maximum eigenvalue(λmax)is the highest values ofthat can be obtained from the priority matrix,and n is the size of the matrix.If matrix à is absolutely consistent,then the λmax=n.A different situation appears when the matrix is neither totally consistent nor contradictory.In this case,Saaty(1980)defined the consistency index(CI)as Equation 13 and if λmax＞n,Saaty(1980)defined the consistency ratio(CR)as Equation 14.

The CR is used to judge consistency,where RI is random index set for randomly generated n x n matrix..The CI calculated from a large number of randomly generated reciprocal matrices.The RI of the matrices depended on the size of the matrix of order 1×1 to 15×15(Table 8).The matrix has satisfactory consistency when CR is equal to or less than 0.1(Saaty,1996)

2.5.Analysis of factors influencing vulnerability to land degradation and desertification risk

The risk factors were filtered,prioritized,and weight by FAHP system(Fig.2).The multi-level index system was constructed based on the relationship between the factors(criteria)and the subfactors.The relative importance of criteria and sub-criteria in all five matrices were analyzed using fuzzy triangular numbers along with linguistic variables from Table 7.The relationship between the factors of the 15 sub-criteria were structured and calculated using TFNs as shown in Table 7.Fifteen pairwise comparison matrices were constructed by TFNs using Equation(11).The next step of the prioritization process was defuzzification of fuzzy values.The total fuzzy weights summations of alternatives in form of fuzzy triangular members are used for defuzzification.In the defuzzification of weight step,it’s an important process to transform the fuzzy results from the fuzzy inference system into a crisp value.In this study,the centroid average is calculated in this step.Verification of the consistency of the calculation results using the CR equation.The results will be accepted if CR is less than or equal 0.1.

Table 7 Triangular scale for fuzzy number conversion used in the pairwise comparison matrix.

Table 8 The mean consistency index of randomly generated matrices.

Following the FAHP process,the areas at vulnerability to land degradation and desertification were mapped and classified at five levels of risk;very high,high,moderate,low and very low.The spatial analysis and mapping using ArcGIS 10.7 v.software.The main factors contributing to the vulnerability of land degradation and desertification in Lam Ta Kong Watershed are represented by weight of both factors and sub-factors.

Fig.2.FAHP system for analysis of factors influencing vulnerability to land degradation and desertification.

3.Results and discussions

3.1.Areas sensitive to land degradation in lam Ta kong watershed

The majority areas of Lam Ta Kong Watershed were at a high risk of land degradation which was 33% of the total area except for water bodies,followed by,the areas at moderate risk(24.64%),areas at very high risk(6.31%),areas at low risk(22.99%),and areas at very low risk(11.38%)respectively(Fig.3).

According to spatial analyzing the environmental sensitivity area index of each factor shown in Fig.4.

3.2.Critical factor affecting land degradation in lam Ta kong watershed

The results(Table 9)indicated that the highest weight of the critical risk factor to land degradation was the soil factor(Fig.5),followed by the climatic factor,geographical factor,water resources factor,and land utilization and vegetation factor,respectively.The results showed consistency since the CR of all the matrices was 0.00721,CI was 0.00807,RI was 1.12,and μmaxwas 5.03228.

According to sub-factors(Table 10),soil texture had the highest impact on land degradation and desertification in Lam Ta Kong Watershed,followed by the precipitation factor,precipitation days,soil salinity,slope gradient,soil erosion,aridity index,elevation,land use,land cover,soil drainage,stream density,soil fertility,distance from the irrigation canal,and ground water volume.

Table 9 The factors affecting land degradation risk in Lam Ta Kong Watershed.

Table 10 The sub-factors affecting land degradation risk in Lam Ta Kong Watershed.

3.3.The land degradation risk factors contributing to the level of desertification risk area

Most high-risk parts are located in three areas which are the boundary between Pak Chong and Si Khiu districts,the area above the reservoir,and the area in Kham Thale So district.According to spatial analysis of factors affecting land degradation risk,the data indicated that approximately 59.46%of the high-risk area had very low fertile soil and 67.79% had very poor soil drainage.Two very high risk areas,triggered by the soil factor,were mostly located in the northern part of Kham Thale So and Muang Nakhon Ratchasima,and the central part of Pak Chong district.In Kham Tale So,the affected area suffers from soil salinity problems where salt stains are visible on soil surface with dispersion greater than 50%.This area had very low fertility with sandy soil texture and well drainage.

Fig.3.Areas sensitive to land degradation in Lam Ta Kong Watershed.

This research results were consistent with the previous research conducted by Wijitkosum(2018)indicated that soil factors were considered as driving factors of physical drought risk in Lam Ta Kong watershed.The northern part of Kham Thale So district suffered from a very high risk of desertification.Moreover,the area was also suffered from soil salinity with with＞50% visible dense salt crust.Moreover,Wijitkosum(2020b)found that areas in Kham Thale So district suffered from saline-sodic soil with strong alkaline(pH 8.5-10.20)and high level of Sodium Adsorption Ratio(34.35-1158).The soil had very low fertility and high permeability.Although this area is a plain area with very low erosion,the high soil salinity made the area uncultivable and,thus,was left barren.There was no vegetative cover excepts halophytes and salt-tolerant plants.Moreover,this area is far from natural water sources.It had an annual average precipitation date of 54 days/year.

The high-risk area caused by climatic factors(56.54%)were found in the middle and downstream areas of the watershed and at the area around the reservoir between Pak Chong and Si Khiu district where Lam Ta Kong Dam is located.These areas received a much lower amount of precipitation(<1000 mm/year)and lower precipitation days(70-90 days/y)than the upstream areas above the reservoir(1050-1100 mm/year)and in Khao Yai National Park(2002.70 mm/year).The upstream area of the watershed had more than 90 precipitation days/y.Sa-Nguansilp et al.(2017)found that the climatic factor had a high effect on agricultural drought risk in Lam Ta Kong watershed.

Furthermore,a small area of 0.10% of the watershed,located between Pak Chong and Si Khiu districts,suffers from a very high desertification risk.This is a gorge area with high elevation(800-1000 m).This area was covered with vegetation but it was very far from the water resources(＞6000 m),with very low volume of groundwater(<2 cm3/hr),and very low density of water stream(<1 km/sq km),causing this area to be at very high risk of land degradation and desertification.Water resource factors causing high land degradation risk(42.30%)were found in many parts of the watershed such as in the middle part of the watershed in Si Khiu and Kham Thale So district since these areas receive a very low volume of groundwater(＞2-10 m3/hr),with long distance water canal(＞6000 m),and very low density of water stream(<1 km/sq km).

Desertification is triggered by combination problems including land degradation,drought,and mismanagement of land(Bestelmeyer et al.,2015;Farajzadeh&Egbal,2007;Li et al.,2006).Drought and land degradation are closely reversible inter-linked.There is an important link with soil resources,in which the change of soil properties,both physical and biological,is a result of climate change and human activities(Keesstra et al.,2018;Lahlaoi et al.,2017;Wijitkosum,2016;Lal,2012).Soil resources are the main factor influencing the sensitivity of land degradation,desertification,and drought.The reasons how soil resource affected land degradation and desertification can be explained in various ways.For instance,persistent soil erosion problems in an area affects soil functions causing land degradation and severe land degradation may trigger desertification.While soil erosion is a result of many factors,such as land usage and changing in land use(Wijitkosum,2012;García-Ruiz,2010;Zhou et al.,2008),changes in soil structure Wijitkosum,(2020a).Geng et al.(2017)found that soil erosion along the slope of the area affected the spatial variation in soil fertility and soil texture.In addition,fine soil particles can be easily transported both by wind and water(Geng et al.,2017;Li et al.,2015).The texture of soil resulted in the water holding capacity and drainage.Soil fertility is one of the essential factors affecting soil structure and soil function,which shows the quality of soil in the area.The fertile soil supports the activities of soil microbes and the growth of plant roots which will result in the reduction of soil erosion.In addition,the area will have high fertility and more accumulation of organic carbon in the soil causing the soil to reduce the risk of deterioration(Lal,2012;Zhou et al.,2008).

Soil salinity is an important factor affecting vegetation cover and land use which leads to soil erosion(Kosmas et al.,2014;Biroudian et al.,2006).The problematic saline soil in the study area occurred from its geological structure of the area which there is a rock salt is beneath the soil surface.The rock salt contributes directly to the saline soil on the top surface.In the study area,the laying of the rock salts that are close to the soil surface affects the evaporation and brings the saline solution to the soil surface easily.This process especially occurs during the dry season and in areas without plants to cover the soil surface.Saline soil greatly affects land use,especially in agriculture and ecosystem functions.

Nevertheless,the degradation of land,droughts and desertification is a complex process which involved various risk factors.Desertification is a sub-set of land degradation and specifically refers to the decline in quality and functionality of soil,vegetation,water,biota,and climate in dry regions.Moreover,there is a correlation between the risk factors that cause the problem.

According to the vulnerability to desertification assessment,the problem is closely related to many environmental factors such as climate,soil,geographical,vegetation,and water resource,all of which contribute to the evolution and characterization of different degradation levels.The traditional ESAI approach,proposed by Kosmas et al.(1999)for different areas sensitivity to desertification,was computed from four quality indices including climatic,soil,vegetation and management quality.These indices consist of various factors affecting land degradation and desertification,and area management factors.The indices were weighted in the relation to its impact and contribution to the process of land degradation and desertification.They were grouped into their uniform class with weight indices that assigned to each class.The analysis process depends on the classification of the data in different quality indices.

Fig.4.Sensitivity area index in lam Ta kong watershed.

Fig.5.Soil factors in the Lam Ta Kong Watershed.

Previous research studies showed the popular use of traditional quality indices(e.g.Momirović et al.,2019;Lahlaoi et al.,2017;Bouabid et al.,2010).As the ESAI approach also allows changes in factors that are appropriate for the local condition(Wijitkosum,2016),many studies used a different number of quality indices and also a different number of factors in each quality index(e.g.Taghipour-Javi et al.,2016;Honardoust et al.,2011).The analysis results will provide an overview of the level of degradation,land and desertification risk and area sensitivity to desertification based on the concept of land management.However,in determining measures to prevent and resolve the desertification problems,the area should be analyzed and evaluated based on the real-life situation(Wijitkosum,2020).The area should be untreated and has not been managed in order to provide a realistic overall analysis.The analysis should involve critical factors or weight factors that make the area more sensitive to desertification.The analysis will enable local authorities to plan and implement preventive and corrective measures.Wijitkosum(2020a)indicated that rehabilitation of the degraded area using cause-specific measures at its source point resulting in a significant decrease in deterioration and desertification risk.Therefore,it is necessary to identify the risks or critical factors causing land degradation and desertification.

Funding

This research was partial supported by the“Innovation in Increasing the Organic Carbon in Soil for Sustainable Agricultural Purpose in Saline Soil Areas:First Year Pilot Project at the Lam Ta Kong Watershed”,Ratchadaphisek Somphot Endowment Fund 2014,Chulalongkorn University(CU-57-090-IC).

Acknowledgement

This research is funded by the“Innovation in Increasing the Organic Carbon in Soil for Sustainable Agricultural Purpose in Saline Soil Areas:First Year Pilot Project at the Lam Ta Kong Watershed”,Ratchadaphisek Somphot Endowment Fund 2014,Chulalongkorn University(CU-57-090-IC).