1. Introduction
Soil erosion due to land degradation negatively impacts not only natural resources but also livelihoods of people as a result of low agricultural productivity [
1,
2,
3,
4,
5]. Land degradation reduces economic yield from agricultural, forest, grass, or shrub lands, decreases soil fertility, biodiversity and ecosystem services, and ultimately farmers’ economy [
6,
7,
8]. The major factors of land degradation are soil erosion, loss of topsoil with fertility, decrease of agricultural production, poor water quality, and flooding [
6,
9,
10]. Furthermore, developing countries are currently faced with immediate concerns that relate to land degradation, freshwater shortages, food insecurity, and air and water pollution. Climate change will further exacerbate these concerns, leading to rapid water shortages, land degradation, and desertification [
11].
Generally, the negative impact of soil erosion has two kinds, including the on-site or long-term adverse impacts on soil quality and productivity, and the offsite or short-term impacts [
12,
13,
14]. Soil erosion impacts the decrease in agricultural productivity through a decrease in soil structure and reduction in effective rooting depth, loss of plant nutrients and soil organic carbon (SOC), loss of plant-available water and available water content (AWC), loss of land area, and seedling damage, resulting in serious problems such as drought stress, crust formation, compaction, and poor emergence of seedling and crop stands [
12,
15]. Lal [
16] reported that USD 40 million was annually expended for extra fertilizer cost to restore soil quality impacted by erosion in order to increase agricultural yields in the United States. Similarly, it was reported that in southern Alberta, crop yield decreased from 10% to 39%, while 5–20 cm top soil was eroded [
17]. Furthermore, soil erosion also impacts water quality [
2,
12]. Moreover, the intensive utilization of agrochemicals is an inevitable effect of increasing population pressures in Asia and Africa. The risks of the adverse consequence of erosion-induced transport of chemicals into water bodies are likely to increase [
12].
In the Cambodian context, forest clearance, LULC change, agricultural land expansion, and improper crop, soil, and water management practices resulted in land degradation [
10]. The northwestern part of Cambodia is facing severe land degradation and soil erosion [
18]. According to Chuenchum et al. [
2], FAO [
19], and Van Oost et al. [
20], over 20 t/ha/yr topsoil was eroded from agricultural land in many tropical regions and countries in Southeast Asia. For example, soil erosion of 6.5 t/ha.yr was reported in Thailand [
21] and 2 t/ha.yr in Viet Nam in 1992 [
22]. Chuenchum et al. [
2] estimated that annual soil erosion along the Mekong River ranged from 7 to 100 t/ha.yr in 2019. Cambodia shares similarities with many countries in the region (e.g., Thailand, Viet Nam, and Laos) and is impacted by soil erosion [
2,
23,
24]. Previous findings showed that the average annual soil erosion rate in Cambodia was in the range from 7 to less than 100 t/ha.yr [
2]. The problem is more serious upland due to steep topography, rapid deforestation, and agricultural expansion [
18,
24,
25,
26]. For example, a cassava field eroded around 60 to 119 t/ha/262 days in the upland area of Battambang [
27]. Another study estimated that in land with more than 30-degree slope, the soil erosion ranged from 16.3 t/ha.yr in 2002 to 27.6 t/ha.yr in 2015 due to LULC change [
25].
The spatial distribution and mapping of soil erosion in steep slopes is important information needed to develop a sustainable plan for appropriate land management, agricultural management focused on minimizing land degradation [
28]. There are several models and tools such as the Agricultural Policy/Environmental eXtender (APEX), Soil and Water Assessment Tool (SWAT), Universal Soil Loss Equation (USLE) or Revised Universal Soil Loss Equation (RUSLE), Environmental Policy Integrated Climate (EPIC), Water Erosion Prediction Project (WEPP), the Erosion Productivity Impact Calculator (EPIC), and the Agricultural Nonpoint Source (AGNPS) to estimate soil loss [
25,
28,
29,
30]. Neges et al. [
28] concluded that a combination of remote sensing and geographic information system (GIS) with other models is beneficial. For example, RUSLE is commonly used to study soil erosion in different regions around the world. The RUSLE with the integration of GIS was developed by Wischmeier and Smith [
31]. It was employed by many researchers in the Mekong regions [
2,
23,
25,
32], Thailand [
21,
33], Ethiopia [
9,
28,
34,
35,
36,
37], China [
38,
39,
40], and Nepal [
41] to predict soil erosion. The RUSLE was employed to predict soil erosion in regions when the measured data are limited [
28,
30,
31,
42]. There are five factors of the RUSLE model, namely rainfall erosivity (R), soil erodibility (K), topography (LS), cover and management (C), and support practice (P) used to estimate the long-term average erosion rate, annually [
31].
Many researchers [
2,
23,
30] used the combination of GIS and remote sensing with the RUSLE model to estimate soil erosion in Mekong regions. However, these studies were not conducted over long time periods, using cover and management factor (C) estimated using NDVI based on the satellite images. Nut et al. [
25] estimated soil erosion and mapped soil risks in Stung Sangkae catchment, Cambodia. However, the cover and management factor (C) and supported practice (P) were extracted from existing LULC, made by Japan International Cooperation Agency (JICA) in 2002 and Mekong River Commission (MRC) in 2015 during the estimation of soil loss using RUSLE.
In our recent study [
26], we evaluated LULC changes and its drivers in Battambang province from 1998 to 2018. However, we did not quantify the impact of LULC on soil erosion. A complete picture of assessing the impact of LULC on soil erosion for a long-term period in the entire Battambang province is not well understood and needs attention. It is important to thoroughly understand the estimates and pattern of soil erosion risk for developing better agricultural management practices, improved land use policies, and efficient management of natural resources in order to rehabilitate the land. In this regard, this research study for assessing the impact of LULC on soil erosion in the year 1998, 2008, and 2018 was carried out in the entire Battambang province of Cambodia using a combination of GIS, remote sensing data, and RUSLE model. The study attempted to answer three specific questions: (1) How did the spatial distribution pattern of soil erosion change from 1998 to 2018? (2) What was the long-term annual average soil loss rate? (3) Where are the prioritized zones of soil erosion risk for planning and implementation of conservation measures? To answer these questions, we used Landsat 5 TM and Landsat 8 OLI images to produce LULC maps. These were used to estimate C factor, and the combination between LULC and slope was used to predict P factor.
4. Discussion
The study used the Landsat 5 TM and Landsat 8 OLI images to produce LULC in 1998, 2008, and 2018. C factor and P factor were computed based on LULC and the combination between LULC and slope, respectively. In addition, soil data of the Soil Grids database of ISRIC-World Soil Information, DEM data, rainfall data, and satellite image were combined together to estimate soil loss in Battambang province. Overall, during the period from 1998 to 2018, the agricultural land experienced an increase of 54% equal to 287,600 ha (
Table 4). This aligns with the estimation of World Bank (2015) which showed that a large share of past agricultural growth was driven by the expansion of cultivated areas from 2004 to 2012. On average, farmland increased annually by 4.7% over 2004–2012 due to deforestation [
69,
70]. They found that the forest cover declined dramatically to −79% (−284,500 ha) over 20 years. Similarly, Kong et al. [
24] indicated that the forest cover of northwest of Battambang declined to 65% between 2006 and 2016. There was increase in built-up area due to population growth, infrastructure, and socioeconomic development [
71,
72,
73,
74]. The growth of migration of poor and landless farmers who accessed agricultural lands impacted LULC [
24,
75].
Soil erodibility, runoff rate, and soil exposure to erosion, as analyzed under the standard unit of plot condition, are defined as the K factor [
76]. The highest K factor in our study was found at the upland areas and mountains, which is in agreement with others [
2,
77]. Overall, there were five different soil erosion severity classes (
Table 9). This number of categories was based on Soil Erosion Standard Document–Technological Standard of Soil and Water Conservation (SD238–87) [
78], and was used by the study [
2] for soil erosion prediction in the Mekong Lancang region, including Cambodia, as it does not have soil erosion classification. As in our study, the soil erosion severity classes were also reported in the Mekong Lancang region in 2019 [
2]. In the previous research [
2,
23,
79], RUSLE with GIS and remote sensing data were used to estimate soil loss.
Our results showed that the mean annual soil loss was 2.92 t/ha.yr in 1998, 4.20 t/ha.yr in 2008, and 4.98 t/ha.yr in 2018. Whereas the total annual soil loss was 3.49 million tons in 1998, 5.03 million tons in 2008, and 5.93 million tons in 2018. These results were in line with the finding of Nut et al. [
25], which predicted that the soil loss would range from 3.1 t/ha.yr in 2002 and 7.6 t/ha.yr in 2015 in Stung Sangkae catchment of Cambodia. Chuenchum et al. [
2] estimated the soil erosion rate in the Mekong Lancang region ranging from 7 to 10 t/ha.yr with an average of 5.35 t/ha.yr. Suif et al. [
80] and Thuy and Lee [
23] found that the annual mean of soil loss rate was 5 t/ha.yr in the Mekong Lancang. Similarly, losses were observed in the tropical conditions of Africa, for example, a study by Marondedze et al. [
81] in Zimbabwe and Lufafa et al. [
82] in Lake Victoria basin estimated an annual average soil loss of 5 t/ha/yr. Our results are also in accordance with previous studies made by [
2,
25,
83], which showed that natural vegetation enables one to reduce and to protect against soil erosion, especially in cultivated land. Additionally, we analyzed the potential soil erosion (assuming C factor and P factor equal 1) and actual soil erosion (actual C factor and P factor) in order to assess the C factor and P factor’s abilities to reduce and protect soil erosion (
Figure 9 and
Figure 10). The results illustrated that the potential soil erosion was 2.65 to 4.25 times higher than the actual soil erosion due to the effect of the C and the P factor. This was similar to the finding of Chuenchum et al. [
2], who reported that the C and P factors could reduce the rate of soil erosion from 2.5 to 7 times.
Furthermore, the results were also confirmed with a household survey in 2021 by the authors. The results showed that all respondents claimed that during 20 years from 1998 to 2018, soil fertility declined significantly.
Figure 13 presented that 44%, 35%, and 7% of respondents reported that the soil fertility was in fair decline, strong decline, and very strong decline, respectively. However, according to the focus group discussion, the agricultural yield only slightly declined due to more use of chemical fertilizer than before. The chemical fertilizer consumption is increasing remarkably, and the local farmers spend more on chemical fertilizer. Similarly, other researchers confirmed that the soil loss made agricultural productivity decrease. The soil erosion could decrease corn productivity by 12% to 21% in Kentucky, 0–24% in Illinois, 25%–65% in Georgia, and 21% in Michigan, USA [
84,
85,
86]. Additionally, Jie [
87] reported that food production would decrease by 40% if the current rate of soil loss in China continues over the next 50 years.
The spatial distribution of soil loss under LULC classes varied in 1998, 2008, and 2018 (
Table 10). The soil erosion rate change in the study area during 1998–2018 was correlated with an increase or decrease of erosion based on LULC classes. For instance, the annual soil loss across agricultural land increased significantly from 1,909,348 (54.76%) to 4,267,439 tons (71.91%) from 1998 to 2018 (
Table 10). In contrast, the soil erosion under forest cover and grassland was the lowest. These results are in agreement with those of Chuenchum et al. [
2,
34] in the Mekong Lancang, Nut et al. [
25] in Cambodia, Niacsu et al. [
83] in Romania, and Gashaw et al. [
88,
89] in Ethiopia, who reported that the soil erosion rate broadly increased or decreased based on vulnerable LULC classes.
The agricultural land was the largest contributor to the total soil loss in Battambang province. Similar observations were made by other researchers; Nut et al. [
25] in Stung Sangkae catchment of Cambodia, Fu et al. [
90] in southeastern Washington State in USA, and Karamage et al. [
91] in Rwanda, Africa, in which 81.5%, 92.8%, and 95% of total soil loss, respectively, was observed in agricultural land.
The study also found that forest cover, grassland, and shrubland were converted to agricultural land. They are also susceptible to soil erosion.
Table 10 presented that the soil erosion under these areas was 45.24% in 1998, 28.17% in 2008, and 27.21% in 2018, respectively, while the soil erosion under cropping land was the highest, when compared to other layers. This finding also agreed with those of other researchers such as Nut et al. [
25], Pimentel and Kounang [
92], and Patric [
93], who claimed that the rate of erosion under agricultural land is more than that of these areas due to vegetation cover. If the agricultural land expansion is still occurring from the conversion of forest cover and grassland, and the poor agricultural practice still continues, the soil erosion will increase significantly. This would affect the farmers, who are facing the high expenses of chemical fertilizers in order to obtain higher agricultural yields. Hence, on-farm conservation agriculture practices (CAP), water conservation and management, agroforestry practices, vegetation cover restoration, and the creation of slope terraces should be applied to enhance sustainable land management, minimize damage to the environment, and function as adaption/mitigation measures against climate change [
25,
72]. Additionally, referring to consultation with local government, the local people understood the impact of soil erosion and CA project, especially the Appropriate Scale Mechanization Consortium (ASMC) project, which was implemented in Battambang province with the aim of focusing on scaling up conservation agricultural (CA) machineries through proper technologies and cropping systems and was actively pursued during Phase I [
94].
5. Conclusions
Our results showed that the agricultural land, built-up area, water feature, shrubland, and barren land significantly increased, while the forest cover and grassland rapidly declined from 1998 to 2018 in the study region. As a result, the total annual soil loss increased from 3.48 to 5.93 million t/ha.yr between 1998 and 2018. The highest soil loss occurred in the uplands or mountains due to steep slopes and rapid deforestation. The agricultural land expansion significantly contributed to the total soil loss. Increasing soil erosion is a major challenge for the livelihood of people as it results in poor soil fertility and low crop productivity. Our research finding would be useful to agricultural experts or policy makers for developing strategies for reducing the rate of soil erosion in the high-risk zones (steep slope and low vegetation). There is an urgent need to mitigate and protect against soil erosion for sustainable, inclusive, resilient agriculture and water management. Measures to improve vegetation cover, use of conservation agriculture practices (CAP), along with water and soil conservation, management, agroforestry practices, vegetation cover restoration, the creation of slope terraces, and the use of direct sowing mulch-based cropping (DMC) systems should be considered. In addition to biophysical technologies, emphasis should be place on socioeconomic innovations, training producers, building social capital, and enhancing the capacity for agricultural extension.