Volume 11, Number 1 (October 2023):4949-4959, doi:10.15243/jdmlm.2023.111.4949 ISSN: 2339-076X (p); 2502-2458 (e), www.jdmlm.ub.ac.id
Open Access 4949 Research Article
The sensitivity level of landslide risk using Geographic Information System on the slopes of Mount Argopura, East Java, Indonesia
Basuki*, Nina Sulistiawati, Dimas Verdian, Zahrotun Naely
Department of Soil Science, University of Jember, Kalimantan Street No. 37 Earth Campus Tegalboto, Sumbersari 68121, Jember, East Java, Indonesia
*corresponding author: [email protected]
Abstract Article history:
Received 10 March 2023 Revised 17 May 2023 Accepted 24 May 2023
Jember is surrounded and limited by highlands such as Mount Argopura, Mount Ijen, Mount Argopura, and the southern karst mountains. In 2015-2022, the Jember area flooded during the rainy season and dried during the dry season. Changes in land cover that do not follow the science of soil preservation will cause disasters, including landslides and erosion. The purpose of this study is to assess the risk of landslides on the slopes of Mount Argopura through the Geographic Information System. The study used a field survey method that was divided into several stages, including making a working map, conducting a field survey, and analyzing the data in the laboratory. The sensitivity analysis of the landslide level used as the basis for the assessment used the relationship between the parameters of soil erodibility, soil erosion, slope and soil conservation, and slope length. The sensitivity of the level of landslide risk on Mount Argopura is divided into five classes, from very light to very heavy. The very light category covers 4.92% of the total area with erosion of 0.47 t/ha/year. The very heavy class covers 39.70% of the total area, with 1,360.79 t/ha/year erosion.
Keywords:
land conversion landslide Mount Argopura rainfall
To cite this article: Basuki, Sulistiawati, N., Verdian, D. and Naely, Z. 2023. The sensitivity level of landslide risk using Geographic Information Systems on the slopes of Mount Argopura, Indonesia. Journal of Degraded and Mining Lands Management 11(1):4949-4959, doi:10.15243/jdmlm.2023.111.4949.
Introduction
Jember is surrounded and bounded by plateaus such as Mount Argopura, Mount Ijen, Mount Raung, and the southern karst mountains (Basuki et al., 2022;
Soetriono et al., 2023). Regarding geomorphology, these conditions form watershed and catchment areas (Zhang et al., 2015; Ferrer et al., 2021; Geitner et al., 2021; Basuki et al., 2022). The air intake area is an air absorption area by infiltration from rain and is stored in the soil pores (Jourgholami et al., 2021; Stuurop et al., 2022). A healthy water catchment has vegetation and organic matter on the ground (Basuki et al., 2021).
The catchment areas provide and supply water in the downstream area continuously. When catching damaged water, the runoff is higher than the infiltration, resulting in increased surface runoff and the ability to carry more considerable material through
it (Suprayogo et al., 2020; Sugianto et al., 2022). This condition will cause floods and landslides (Ahmad et al., 2018; Ferrer et al., 2021; Geitner et al., 2021).
In 2015–2022, the Jember region experienced flooding during the rainy season and dry conditions during the dry season (Pertami et al., 2022). The Jember area that was hit by floods and caused huge losses included the sub-districts of Panti, Kaliwates, and Rambipuji, while during the dry season, the crops failed because there was no water in the sub-districts of Panti, Sukorambi, Patrang, Rambipuji, Arjasa, and Jelbuk. The Bedadung Watershed passes through Jember Regency, with its upstream divided into two places, namely Mount Raung and Mount Argopura (Ernanda et al., 2018; Alfarisy et al., 2020). Mount Argopura is part of a series of mountains in the Tapalkuda area of East Java (Basuki et al., 2022).
Mount Argopura is a mountain that is in an inactive
Open Access 4950 condition. Land use on the slopes to the top of the
mountain has been utilized for the needs of pedestrians. Land conversion often occurs from forest land into agricultural land or agricultural land into open land (Suprayogo et al., 2020; Ferrante et al., 2022). Land use change that does not follow conservation rules will cause disasters, including landslides and erosion (Sultana and Tan, 2021).
Erosion is a process that results from the carrying of soil and materials by water from one place to another and can cause losses to both those who are left behind and those who receive them (Xue et al., 2021). The resulting consequences are an indication of land damage in the area. Soil damage can cause land degradation through degradation of soil health, degradation of water holding capacity, droughts, and flooding (Endale et al., 2023; Yang et al., 2023).
This study aimed to examine the level of sensitivity to landslide risk on Mount Argopura through a geographic information system. The benefit of this activity is that it serves as a foundation for anticipating and responding to landslides and floods on the slopes of Mount Argopura and in downstream areas of Jember Regency.
Materials and Methods Study area
Agropura is a mountain located in East Java, Indonesia, with an altitude of 3,676 meters above sea level. The mountain is located in Lumajang, Situbondo, Probolinggo, Jember, and Bondowoso Regencies (Basuki et al., 2022). Jember Regency has villages with boundaries reaching the peak of Mount Argopura, one of which is Suci Village. The village is part of Panti Sub-district of Jember Regency. This village has a land area of 60 km2, consisting of Glundengan, Glengseran, and Gaplek sub-villages.
Most of the residents of Suci Village make their living by raising livestock and farming. In Suci Village, two areas are used as plantations, namely the Sentool plantation and the Gunung Pasang plantation, with the primary commodities being rubber and Kahyangan coffee. The research area is located at coordinates 112.59-113.65 east longitude and 7.97-8.16 south latitude (Figure 1). The average rainfall on the slopes of Mount Argopura is 3,065 mm/year, and the air humidity is 70-91%.
Figure 1. Research area.
Open Access 4951 Wet months with rainfall >200 mm occur in October-
April, while dry months with rainfall <200 mm occur in June-September (Figure 2).
Data collection
The research was conducted in March and April 2022.
The research location was the slopes of Mount Argopura and the Jember University Laboratory.
Research materials used included distilled water, working maps, field and laboratory analysis materials, GPS, altimeters, clinometers, laptops, and quantum GIS software. The research used a field survey method that was divided into several stages, including making work maps, field surveys, and analysis in the laboratory. The stages of creating a working map involve observation and area administration (Supandi et al., 2023). Survey activities included searching for data such as slope data, land use data, soil type data, rainfall data, and soil checks. Activities in the laboratory included data analysis on the results of field
activities for several parameters used as the basis for analyzing the level of landslide risk.
The landslide level sensitivity analysis used as the basis for the assessment is as follows:
KE = Er x Ed x LS x Pt x Tk ……….(1) where: KE is the mean annual landslides; the unit of vulnerability is t/ha/year, Er indicates the factor of rainfall-runoff erosivity, Ed is the soil erodibility factor; LS is the slope length and steepness factor; Pt is the cover management factor; and Tk is the supporting soil conservation practice factor.
Landslides are caused by water, and rainfall is a factor in accelerating landslides (Miao et al., 2022). Rainfall has parameters such as intensity and frequency. Higher intensity, frequency, or a combination of both can cause soil saturation and cause runoff so that it is able to transport particles above the ground (Parhizkar et al., 2021).
Figure 2. Rainfall in the research location.
The soil erosivity factor (Er) is measured through the following equation approach:
Er = 2.21 (rainfall)1.36……….(2) where: Er is calculated in years (mm).
Soil erodibility (Ed) is the level of ability or sensitivity of the soil to inhibit the release of soil particles due to the influence of the intensity and frequency of rainfall (Vaezi, Ahmadi et al., 2017). Soil erodibility is strongly influenced by physical and chemical characteristics such as organic matter, texture, clay, structure, and soil porosity (Alaboz et al., 2021). The higher the erodibility of the soil, the more soil is released for landslides. The soil erodibility factor was measured using the soil-type approach (Table 1).
Landslides are affected by slope conditions and slope length (Puga-Bernabéu et al., 2022). The potential for landslides is directly opposite the impact of the slope as well as the length of the slope. A longer slope length will cause cracks or side wedges. The slope length and slope factors (LS) are measured by calculating the percentage of slope at the study site and calculating the
value factor, as shown in Table 2. Land management has no effect on the ability of the soil to store rainwater through infiltration processes (Wang et al., 2022).
Land cover affects the strength of rainwater in breaking down soil particles and aggregates (Vaezi, Zarrinabadi et al., 2017; Parhizkar et al., 2021; Garg et al., 2022).
Table 1. Soil erodibility value (Ed).
Soil Types Index
value USDA Soil
Taxonomy (1)
Indonesian Soil Classification (2)
Andisols Andosol 0.278
Vertisols Grumusol 0.176
Alfisols Latosol 0.075
Entisols Regosol 0.301
Inceptisols Kambisol 0.156
(1) USDA (2014), (2) Subardja et al. (2014).
Land cover with annual plant vegetation can reduce the strength of rainwater, and plant roots are able to absorb and store rainwater through root hairs (Tufekcioglu et 455
391 459
310 137
61
0 0 14
341 383 513
0 100 200 300 400 500 600
Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec
Rainfall (mm)
Month
Open Access 4952 al., 2018; Fujino et al., 2023). Plant management
factors were measured through the land use approach.
The value of land use is shown in Table 3.
Table 2. Slope percentage (LS).
Slope (%) Topography Index value
0-8 Flat 0.4
8-15 Sloping 1.4
15-25 Rather Steep 3.1
25-45 Steep 6.8
>45 Very Steep 9.5
Table 3. Land use (Pt).
Land use Index
value Paddy fields and rainfed rice fields 0.01
Shrubs 0.32
Moor/Field 0.47
Plantation 0.60
Forest 0.70
Conservation is an action to reduce the rate of landslides and water runoff (Moradi et al., 2015; Tang et al., 2015). Conservation measures can be taken by creating water flow barriers such as terraces, mulch, casing patterns, and types of plants in bunds (Ping et al., 2012; Zhang L. et al., 2015; Endale et al., 2023;
Supandi et al., 2023). Soil conservation factors were measured through a soil conservation technique approach (Table 4).
Table 4. Soil conservation techniques.
Soil conservation/preservation techniques
Index value
Traditional Bench Terrace 0.35
Bench Terrace, Good 0.04
Bench Terrace, Moderate 0.15
Bench Terrace, Poor 0.40
Contour Terrace, Good 0.15
Hillside Ditch Dan Field Pits 0.30 Permanent Grass Strip, Fine, Tight, and
Striped
0.04
Permanent Grass Strip, Poor 0.4
Strip Crotalaria 0.5
Contour Cropping Slope 1-3 % 0.4 Contour Cropping Slope 3-8 % 0.5 Contour Cropping Slope 8-15 % 0.6 Contour Cropping Slope 15-25% 0.8 Contour Cropping Slope >25% 0.9 Straw Mulch as much as 1 t/ha/year 0.60 Straw Mulch as much as 3 t/ha/year 0.25 Straw Mulch as much as 6 t/ha/year 0.15 Crotalaria Mulch 3 t/ha/year 0.50
Corn Mulch, 3 t/ha/year 0.35
Beds For Vegetables 0.15
Peanut Mulch 0.75
The risk of landslide susceptibility (KE) is obtained from the multiplication of the five factors of soil erosivity, soil erodibility, slope and slope length, plant management, and soil conservation. Landslide sensitivity values are classified into five categories:
very light, mild, moderate, severe, and very heavy. The class values are as in Table 5.
Table 5. Avalanche sensitivity risk level class (KE).
Class Landslide Risk Level
Amount of Soil Carried away (t/ha/year)
I Very low <15
II Low 15-60
III Moderate 60-180
IV Heavy 180-480
V Very heavy >480
Data analysis
Data were analyzed using GeoDa software, and spatial data were analyzed using ArcGIS 13.1 software.
Statistical analysis was used to relate the effect of the parameters associated with the landslide class with correlation and regression analysis. The spatial distribution of the area and landslide potential areas was carried out in Arc-GIS 13.1 software using interpolation analysis.
Results and Discussion Erosivity factor
Rain erosion is a rain factor that affects and causes soil loss. Rain characteristics that can affect erosivity include the amount of rainfall, the length of time it rains, the size of the raindrops, and the speed of the falling rain (Kinnell, 2020). Suci Village has three measuring stations, namely DAM Kr. Anom, DAM Klatakan, and DAM Pono, and one climate station, namely the Sentool climate station. Rain erosivity values were assessed based on annual average rainfall data for the period 2016-2020. Based on data processing through Excel and ArcGIS software, the Suci Village measuring station showed the distribution of different rain erosivity values, as shown in Table 6.
Table 6. Soil erosivity value.
Rain station Soil Erosivity Value (mm/year)
DAM Klatakan 3,000-3,500
DAM Kr. Anom 3,500-4,000
DAM Pono 4,000-4,500
The distribution of rain erosivity values for each station differs from 3,000 mm/year to 4,500 mm/year (Table 6). The DAM Klatakan station has an erosivity value of 3,000-3,500 mm/year, the DAM Kr. Anom station has a value of 3,500-4,000, and the DAM Pono station has a value of 4,000-4,500 mm/year. The
Open Access 4953 lowest value was found at the DAM Klatakan station,
and the highest was at the DAM Pono. The erosivity value is directly proportional to and positively correlated with the breaking strength of soil aggregates. Rainwater will fill the pores of the soil, both macro and micro, and when the pores are filled, it will cause water to be obstructed in the infiltration process and increase runoff flow (Jourgholami et al., 2021). The distribution of the erosivity of rain in the Suci Village area is shown in Figure 3.
Management and soil conservation factors
Land use in Suci Village, Jember Regency, is divided into seven types: jungle forest, plantations, rainfed rice fields, shrubs, settlements, and rice fields. There are two plantations in Suci Village, namely the Gunung Pasang plantation and the Sentool plantation. The distribution of land use in Suci Village on the slopes of Mount Argopura is shown in Figure 3.
The results of the field survey, with the help of secondary data (processed maps) and the Avenza Maps application, found that there were several points of land use that did not match reality. In the use of the jungle itself, it was found that there was land conversion into plantations with rubber and coffee plants with a ratio of about 40% rubber and 60% coffee plants and a contour cropping system of >25%, where PT values of 0.7 and Tk values of 0.9 were obtained (Table 7).
The plantation land is also used for rubber plantations with permanent grass strips. In the paddy fields where the samples were taken, rice was planted with a Pt value of 0.01, but generally, in this area, a rotational cropping system was also used where rice fields were also used for planting corn and legumes.
The land conservation system applied there is terraces.
Medium bench because the terrace boundary is still not high from the land surface, where the Tk value is 0.15.
Figure 3. Distribution of rainfall (left) and land use (right).
Table 7. Land cover index and crop management.
Land use Land Area Pt Tk
ha %
Forest 3,580.90 60.17 0.70 0.90
Plantation 952.89 16.01 0.60 0.40
Paddy fields and rainfed rice fields 65.13 1.09 0.01 0.15
Shrubs 795.96 13.38 0.32 0.80
Moor/Field 356.32 5.99 0.47 0.50
Notes: Pt is the cover management factor, and Tk is the supporting soil conservation practice factor.
Open Access 4954 In the scrubland, there was also an unsuitable reality
where, at the sampling site, it was found that land had been cleared and planted with teak trees around 1 year old with a Pt value of 0.32 and a cropping system with conservation contour cropping techniques of 15-25%.
In the use of dry fields or fields, it was found that there was vegetation of Parasenrianthes sp. around 50% of the land, 40% of banana trees, and 10% of coconut trees from all parts of the sampling point land where PT values were obtained at 0.47 and Tk 0.5 (Table 7).
Soil erodibility factor
The soil sensitivity factor is closely related to the strength of the soil (Tufekcioglu et al., 2018). The higher the level of erodibility, the higher the level of landslide risk. Soil erodibility (Ed) can be determined by means of soil type map interpretation. In the Suci Village itself, there are two soil types (Andisols and Inceptisols) with five subgroups were found, where the Typic Hapludans and Lithic Hapludans subgroups belong to Andisols, while the Typic Dystrudepts, Andic Dystrudepts, and Typic Eutrudepts belong to Inceptisols (Figure 4). By processing data through ArcGIS and Excel and using sources of information that have been collected previously, the erodibility value is obtained, as shown in Table 8. The Ed value of the soil types in the Andisols order is 0.278, which is included in the medium-level category. In the
Inceptisols order, the Ed value of the soil type is 0.156, which is included in the low category.
Slope factor
Topography describes the earth's surface with various forms that are influenced by its forming factors (Neswati et al., 2019). Data on the slope of the slopes of Mount Argopura were obtained through DEMNAS (Digital Elevation Model Nasional) USGS 2014 data processing, which was then processed in the first stage, namely the slope, followed by reclassification according to the mapping rules of five slope levels starting from 0-8, 8-15, 15-25, 25-45, and >45 (Figure 4).
Each slope has a different area. The percentage of slope and land area were then processed to obtain the LS value, as shown in Table 9. On a slope of 0-8%
(flat), a land area of 669.17 ha (11.38%) was found in the Suci Village section with an LS value of 0.4. On a slope percentage of 8-15% (sloping), it has a land area of 715.62 (1217%) with an LS value of 1.4. On slopes of 15-25% (rather steep), there is a land area of 1.13035 ha (19.22%) with an LS value of 3.1. On a slope of 25-45%, it is on a land area of 2,488.77, or 42.32% of the land area of Suci Village, where an LS value of 6.8 is obtained. On slopes > 45%, there is a land area of 876.40 acres, or 14.90% of the area of Suci Village, with an LS value of 9.5.
Figure 4. Map of the soil type (left) and the slope of the land (right).
Open Access 4955 Table 8. Map of soil subgroups and soil erodibility
index values.
Sub Grup Ed Land Area
ha %
Typic
Hapludans 0.278
(moderate)
2121.83 35.63 Lithic
Hapludans 1231.31 20.68
Typic Dystrudepts
0.156 (low)
172.69 2.90 Andic
Dystrudepts 1804.98 30.31
Typic
Eutrudepts 624.15 10.48
Note: Ed is the soil erodibility factor.
Table 9. Slope factor.
Slope Land Area Reliefs LS
ha % value
0-8 669.17 11.38 flat 0.4
8-15 715.62 12.17 sloping 1.4 15-25 1,130.35 19.22 Rather
steep
3.1 25-45 2,488.77 42.32 steep 6.8
>45 876.40 14.90 Very steep 9.5 Note: LS is the slope length and steepness factor.
Estimation of sensitivity level of landslide risk The activity of observing the level of sensitivity to landslide risk levels that were processed was based on the parameters of soil erosion, soil erodibility, slope length, and level of conservation depicted in a map, as shown in Figure 5. There are five classes of sensitivity to landslide risk levels, namely very light to very heavy. The sensitivity of the landslide risk level with very light class is 15 t/ha/year; the sensitivity level of the landslide risk with light class is 15-60 t/ha/year; the sensitivity level of the landslide risk with medium class reaches 60-180 t/ha/year; the sensitivity class for the risk level of severe landslides is 180-480 t/ha/year;
and the sensitivity class for the risk level of very heavy landslides is >480 t/ha/year.
Table 10 shows that the use of paddy fields with moderate rice and bench terraces has a sensitivity value of landslide risk (KE) of 0.47 t/ha/year, which is included in the very light category with an area of 4.92 of the area studied. The use of dry land containing
“sengon”, banana, and coconut plants on a slope of 8- 15% obtained a sensitivity value of the level of landslide risk of 166.803 t/ha/year, which is included in class III (medium). This condition can be minimized again by adding elephant grassland use on the outskirts of the land to prevent soil flow (erosion). The use of plantation land with rubber vegetation where the plant strips are not well arranged (it is suspected that there are some plants that have collapsed due to lightning or age), there is conservation of the use of elephant grass,
but this grass looks like it has just been planted so that on this land a sensitivity value of the landslide risk level of 377.208 t/ha/year is obtained, which is included in the sensitivity level of class IV landslide risk, namely the sensitivity level of the level of risk of severe landslides. This can be minimized again by processing reforestation land and adding elephant grass vegetation to each cropping strip (Kermah et al., 2018).
Figure 5. Sensitivity map of landslide risk level.
Table 10. Sensitivity of landslide risk level.
Landslide Rate (t/ha/year)
% Land Area
Avalanche Risk
Level Class
0.47 4.92 I Very low
40.34 14.01 II Low
166.80 22.25 III Moderate
377.21 19.12 IV Heavy
8,280.99 39.70 V Very heavy
Land conversion has a high impact on the sensitivity of the level of landslide risk where land use does not match land conditions (Suprayogo et al., 2020). The land use of shrubs was also found to be unsuitable in reality, where at the sampling site, it was found that land had been cleared and planted with teak trees around 1 year old with a cropping system with a contour cropping conservation technique of >25%.
This certainly caused an increase in landslide hazards where the existing land was also open and not well covered by plants so that the KE value was 2,041.632 t/ha/year, which is included in the sensitivity level of class V landslide risk, which is very heavy. In area 5,
Open Access 4956 with the use of the jungle itself, it was found that there
was a conversion of land into plantations with rubber and coffee plantations with a ratio of around 40%
rubber and 60% coffee plantations and a contour cropping system of >25%. A landslide risk level sensitivity value of 6,239.363 was obtained, which is included in the sensitivity class of landslide risk level V (very severe). At this location, the conservation of vegetation can be carried out by using elephant grass to help grip the ground.
Discussion
Rainfall in the research location is in the high category, which causes high soil erosivity values (Romshoo et al., 2021). The soil erosivity is supported by the slope factor, soil type, land use, and soil conservation level (Vaezi, Zarrinabadi et al., 2017). The slope has the potential to accelerate landslides because water that is saturated in the soil is able to move more quickly to fall down, which is supported by gravity (Geitner et al., 2021). This condition is supported by correlation analysis showing a very close and directly proportional level (r = 0.946, p = 0.01). Landslide sensitivity is influenced by the level of land use, land management, and soil conservation (Xu et al., 2021). Table 11 shows that land use has a very strong correlation with land use, land management, and soil conservation and is inversely proportional (r = -0.980, p = 0.01). This means that land use in accordance with land conditions can reduce the risk of sensitivity to landslides. If land use is prioritized for plantation crops and forests, land with sloping conditions and a slope of more than 15%
will reduce the level of landslide hazard. Land management systems and conservation technology also affect the risk of landslides; this is also shown by
the correlation analysis, which shows that there is a very close relationship between land management (r = -0.980, p = 0.01) and the type of soil conservation applied (r = -0.982, p = 0.01). Land management through tillage on steep land with a slope of >25% is achieved as much as possible through minimal tillage, and the types of plants planted have deep and strong root systems. Woody plants are plants that have a taproot system that can reduce the rate of soil displacement, which causes the soil to become damaged (Asdak et al., 2018).
Utilization of plants with deep taproots will also increase soil conservation and support soil conservation technologies (Adetunji et al., 2020). This condition is consistent with the coefficient of determination of landslide sensitivity to land management (R2 = 0.9607) and a linear regression model with the equation of y = -0.76x + 5.12 (Figures 6 and 7). The erodibility value of the soil is related to the slope, soil type, crop management index (land use, conservation techniques), and whether or not the land conditions greatly affect the level of sensitivity to landslide risk (Zhang L. et al., 2015; Romshoo et al., 2021; Supandi et al., 2023). Supported by the field reality, it was found that there was a discrepancy with the conditions, namely that there were several land conversion activities. Diversion of land use is, of course, very influential on the level of sensitivity to landslide risk where plants have a function as a soil gripper and the conservation techniques or cropping systems applied aim to minimize or restrain soil melting caused by impact or water flow (Yuill et al., 2016). Soil conservation has a significant influence (p<0.01) on landslide potential with a coefficient of determination of R2 = 0.9643, and the relationship can be described in the regression model y = -0.91x + 5.81 Table 11. The correlation coefficient between parameters.
Parameters Landslides Land Use Slope Land Management
Land Use -0.989
Slope 0.946 -0.897
Land Management -0.980 0.972 -0.907
Soil Conservation -0.982 0.970 -0.897 0.989
(a) (b)
Figure 6. Relationship between landslide level versus land use (a), landslide level versus slope (b), For each graph, the regression equation and the coefficient of determination (R2) are given. Note: ** p<0.01, *p<0.05.
y = -0.87x + 5,67 R² = 0.9789 **
0 2 4 6
0 2 4 6
Landuse
Landslides Level
y = 1.1x - 0,34 R² = 0.8942 *
0 2 4 6
0 2 4 6
Slope
Landslides Level
Open Access 4957
(a) (b)
(c)
Figure 6. Relationship between landslide level versus soil of type (a), landslide level versus land management (b), and landslide level versus soil conservation (c). For each graph, the regression equation and the coefficient
of determination (R2) are given. Note: ** p<0.01, *p<0.05.
Conclusion
The study indicated that the sensitivity to the amount of danger of landslides on Mount Argopura slopes is classified into five categories, ranging from very light to very heavy. Areas with very mild landslide hazard conditions occupy 4.92% of the total area and have an erosion rate of 0.47 t/ha/year; the light category occupies 14.01% of the total area and has an erosion rate of 40.34 t/ha/year; the medium area category occupies 22.25% of the total area and has an erosion rate of 125.71 t/ha/year; and the weight group covers 19.12% of the whole area and has an erosion rate of 307.77 t/ha/year; the very heavy category covers 39.70% of the total area and has an erosion rate of 1360.79 t/ha/year.
Acknowledgments
The authors thank the laboratory technicians at the Faculty of Agriculture, University of Jember, for allowing us to analyze this research activity.
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y = 1.12x - 0.38 R² = 0.9718 **
0 1 2 3 4 5 6
0 2 4 6
Soil Type
Landslides Level
y = -0.76x + 5,12 R² = 0.9607 **
0 1 2 3 4 5
0 2 4 6
Land Management
Landslides Level
y = -0.91x + 5.81 R² = 0.9643
0 1 2 3 4 5 6
0 2 4 6
Soil Conservation
Landslides Level
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