*Corresponding author: Department of Civil Engineering, Jember University, 68121, Indonesia E-mail address: [email protected] (Indra Nurtjahjaningtyas)
doi: https://doi.org/10.21776/ub.pengairan.2023.014.02.3
Vol. 14 No. 02 (2023)
Jurnal Teknik Pengairan: Journal of Water Resources Engineering
Journal homepage: https://jurnalpengairan.ub.ac.id/index.php/jtp
Original research article
Assessment of Land Erosion Hazard in the Sampean Hulu Sub Watershed, Bondowoso Regency
Roeby Setyawan, Indra Nurtjahjaningtyas*, Entin Hidayah
Department of Civil Engineering, Engineering Faculty, Jember University, 68121, Indonesia
A R T I C L E I N F O A B S T R A C T Keywords:
Disaster;
Erosion;
Hazard;
Irrigation network;
USLE
The Sub-watershed of Sampean Hulu, located on the slopes of Mount Raung is susceptible to erosion hazards. Erosion indicators have been observed in the irrigation channels, mainly due to frequent sedimentation, which compromises the irrigation infrastructure's optimization and water distribution. To address this, erosion monitoring using the Universal Soil Loss Erosion (USLE) model, along with GIS and remote sensing techniques, is essential. It was found that the irrigation networks associated with Clangap and Tamanan rain gauges are at higher risk due to intense rainfall. Maesan and Wonosari II rain gauges cover a larger irrigation network area, highlighting the need for erosion prevention measures. The dominant soil type, Tv, with a high clay content, is highly susceptible to erosion. Flat and gently sloping slopes have a lower risk compared to steeper slopes, while very steep and steep slopes pose higher erosion risks. Paddy fields and well-managed forest plantations have lower erosion hazards, while bare land and certain agricultural practices contribute to increased erosion risks. The analysis classified the erosion hazard into five classes, with the sub-watershed being predominantly low and very low susceptible to soil erosion. Implementing conservation practices, sustainable land management, and land use regulations are crucial for erosion prevention.
1. Introduction
The Sampean Hulu Sub-watershed is located on the slopes of Mount Raung, encompasses four distinct river sections:
Clangap River, Sampean Hulu River, Pager Gunung River, and Pringjagung River. This region is primarily characterized by mixed forests with moderately steep slopes, making the soil surface susceptible to erosion hazards. The intensive land use practices in the surrounding areas have reduced soil fertility and diminished carrying capacity, increasing the risk of floods, landslides, and erosion during the rainy season [1].
Evidence of erosion indicators within the irrigation channel of the network, mainly attributed to frequent sedimentation, has been observed during routine inspections conducted by irrigation officers [2]. If left unaddressed, this sedimentation reduces the channel's capacity, compromising the optimization of the irrigation infrastructure and leading to suboptimal water distribution to the irrigated areas [3].
Therefore, it is essential to implement erosion monitoring in the operational management and maintenance of the irrigation network
.
The Universal Soil Loss Erosion (USLE) model has been widely utilized in previous studies for land erosion prediction
due to its simplicity and data accessibility [4]. The USLE model offers advantages such as reliable erosion estimates over long- term intervals (10-20 years) and requiring fewer parameters than alternative models, leading to its widespread acceptance and global application [5]. Accurate prediction of erosion risks using the USLE model relies on spatial data encompassing multiple parameters describing the watershed [6]. Integrating Geographic Information System (GIS) techniques and remote sensing allows for the extraction of topographic factors from Digital Elevation Model (DEM) data, enabling precise soil loss calculations. Consequently, integrating the USLE model with GIS and remote sensing techniques has proven an efficient tool for soil erosion assessments, as demonstrated by various researchers [4], [6]. In this study, the USLE method was applied within the administrative boundaries of 13 sub- districts, including Curah Dami, Pakem, Wringin, Grujugan, Tegal Ampel, Tlogo Sari, and partial segments of Klabang and Maesan. Severe erosion categories were observed in the sub- districts of Panti, Jelbuk, Sumber Jambe, Bangsal Sari, Arjasa, and Sukorambi [7].
Figure 1. Study area
Figure 2. Research stages
Rainfall erosivity (R) Rainfall
intensity
Rain gages map
Soil type map
Land use map DEM
map
Soil erodibility
(K)
Crop Management and Soil Conservation Practices (CP) slope length
and steepness (LS)
Estimated erosion rate USLE method A = R * K * LS *CP
Erosion hazard classes Data input
GIS processing
Output
Slope
%
Flow accumulation
Flow direction
The primary objective of this research is to determine erosion hazard classes within the Sampean Hulu Sub-watershed of Bondowoso Regency by employing the integrated USLE model in conjunction with remote sensing and GIS techniques.
Additionally, this study introduces variations in the delineation of sub-watershed boundaries compared to prior investigations, ensuring a comprehensive assessment of erosion hazards within the region.
2. Method 2.1. Study area
The research area was conducted in the Sampean Hulu Sub-watershed. The total area of the study is 171.09 km2 and is located between 8°6'0" - 7°57'0" S latitude and 113°6'0" - 114°0'0" E longitude, as shown in Figure 1. The shape of the area stretches from west to east, with the western part consisting of the slopes of Mount Argopuro and the eastern part consisting of the slopes of Mount Raung. The total area of this location is 17,108.51 hectares.
2.2. Methodology
The research consists of three stages: (1) spatial data inventory, (2) data processing using ArcGIS, and (3) erosion rate calculation, as shown in Figure 2. The data inventory and processing involve collecting and analyzing various spatial data sets, including rainfall station maps and annual rainfall data, soil type maps, Digital Elevation Model (DEM) maps, and land use maps used as thematic maps. The calculation of erosion values using the USLE model includes rainfall erosivity (R), soil erodibility (K), slope length and steepness (LS), crop management, and soil conservation practices (CP), as well as determining and mapping erosion hazard classes.
2.3. Erosion Parameters of USLE 2.3.1. Rainfall erosivity (R)
The value of the rainfall erosivity factor (R) is obtained by summing up the accumulated data of annual rainfall events at the research stations, which is calculated by summing up the daily rainfall data over one year. The average annual rainfall for 10 years is used to calculate the value of the R factor. The calculation of the R factor is done using the following equation [8]:
𝑅 =
2,5𝑃100(0,075𝑃+0,73) (1) where R is the Rainfall erosivity factor (mm/year), and P is the Average annual rainfall over one year (mm/year).
The calculated values of the erosivity factor are then interpolated using the Inverse Distance Weighting (IDW) method. After conducting various tests, it was found that the IDW method is better than the Spline method for creating R factor maps [9]. The interpolation procedure results in a final output of an R factor layer in raster format, where each closed polygon contains pixel R values with varying R values. The dimension of the R pixel size follows the component tool dimension of the ArcGIS DEM map, which is 30 x 30 meters.
Table 1. K values based on soil types [10]
No Soil type K factor
1 Alluvial 0.29
2 Andosol 0.28
3 Brown forest 0.28
4 Gley 0.29
5 Granusol 0.16
6 Latosol 0.26
7 Litosol 0.13
8 Mediterranean 0.16
9 Organosol 0.29
10 Red Podsol 0.20
11 Regosol 0.31
2.3.2. Soil erodibility (K)
The distribution map of different soil types is used to interpret the soil erodibility values (K). Table 1 shows the aspects of soil erodibility (K) for the observed area. The values of the K factor for each soil type can be seen in Table 1. Then, the soil type layer is converted into a raster format, and the final result is an overlay of the K parameter in raster format with pixel dimensions of 30 x 30 meters.
2.3.3. Slope length and steepness (LS)
The LS factor calculation uses Digital Elevation Model (DEM) data from the Aster GDEM2 data source (https://asterweb.jpl.nasa.gov/gdem.asp). The DEM data is then processed to generate flow direction, flow accumulation, and slope layers. The raster calculator in ArcGIS is used to calculate the LS factor based on the equation (2) [7]:
𝐿𝑆 = (
𝐹𝑎𝑐𝑐×𝑐𝑒𝑙𝑙 𝑠𝑖𝑧𝑒22,13
)
0,4× (
sin(𝑠𝑙𝑜𝑝𝑒)0,0896
)
1,3(2) Facc is flow accumulation; cell size is used at pixel resolution (30 m), and the slope is the elevation difference of the observed area (°). The LS factor values per pixel are obtained from the processed LS raster map in raster format.
2.3.4. Crop Management and Soil Conservation Practices (CP)
The determination of the CP factor involves the use of a land use map. The land use map is obtained from the digital Indonesian Land Cover (RBI map) in vector format, which is then converted into raster format with a pixel size of 30 x 30 m. The assignment of CP factor values is determined for each pixel based on Table 2. In the land use layer, the table includes CP factor values as attribute values. Subsequently, using the
"polygon to raster" process available in GIS, the land use map layer is converted into a raster format. This process results in a land use map layer in raster format with a pixel accuracy of 30 x 30 m.
2.4. Erosion hazard classification
The determination of erosion hazard classes is done by summing up the magnitude of erosion rates using the Universal Soil Loss Equation (USLE). USLE is the most commonly used equation among other equations and dominates the calculations for predicting long-term average soil loss [11].
Table 2. Estimated CP factor values for various land uses [10]
No Land use CP
1 Irrigated rice fields 0.10
2 Rainfed rice fields 0.001
3 Fallow land 0.28
4 Plantation 0.30
5 Bare land/ grassland 0.02
6 Shrubland 0.001
7 River 1
8 Residential area 0.05
9 Lake/ reservoir 0.001
10 Forest 0.02
11 Swamp/ marshland 0.01
12 Pond 0.05
13 Sand 1
14 Airport/ port 1
15 Saline land 1
16 Factory/ building 1
Table 1. Erosion hazard classes [10]
Class Erosion level
(Ton//ha/year) Level
I 0 – 15 Very low
II 15 – 60 Low
III 60– 180 Moderate
IV 180 –480 Hight
V > 480 Very high
The USLE calculation is performed by combining the relevant factors into the following calculation equation (3) :
𝐴 = 𝑅 × 𝐾 × 𝐿𝑆 × 𝐶𝑃 (3) Where: A: calculated soil erosion (ton/ha/year) R: erosivity factor of rainfall K: erodibility factor of soil LS: slope length and stepness factor CP: conservation and vegetation factor.
Then, the resulting numerical values for erosion at each pixel are classified based on erosion hazard class criteria, as shown in Table 3.
3. Results and Discussion 3.1. Rainfall erosivity (R)
Rainfall erosivity refers to the ability of rainfall to cause soil erosion [12]. It measures the erosive power of raindrops and the energy they exert when they hit the ground [13]. Rainfall erosivity has a significant impact on erosion occurrence. By considering rainfall erosivity data from rain gauges, irrigation planners and managers can assess erosion risk and design appropriate erosion control measures in areas of the irrigation network [14]. The rainfall distribution across different rain gages helps understand the spatial variation of erosivity in the Sub-watershed of Sampean Hulu. The spatial distribution (spatial variability)of rainfall erosivity values obtained from IDW interpolation for all research areas is shown in Figure 3.
Based on the rainfall data processing obtained from 5 observation stations in the Sampean Hulu Sub-watershed. The highest R value among the listed rain gages, measuring 795 mm/ year. It serves the Kloncing, Clangap, Sanom, and Masjid
irrigation networks. The Tamanan rain gauge has an R-value of 712 mm/year with only two associated irrigation network areas: Sleya and Cocong. On the other hand, the Grujugan rain gauge has the lowest R-value of 503 mm/year. This station is associated with the Hajibas, Betekan, and Bindung irrigation networks. It indicates that the rainfall in the Clangap and Tamanan areas has a stronger potential to cause soil erosion and disrupt soil aggregates. Higher rainfall erosivity values imply that the rainfall events in that area are more intense, frequent, or have a longer duration [15]. These characteristics contribute to the higher kinetic energy of raindrops, resulting in stronger impact forces on the soil surface [16].
Moreover, the rain gages with the most covered irrigation network area are Maesan and Wonosari II, with R values of 642 and 577 mm/year, respectively. The Maesan rain gauge covers nine irrigation network areas, including Gunungsari, Sumber Andung, Sumber Pakem, Pringjagung, Pagergunung, Tarwi, Sumbersari, Letek, and Paleran. The Wonosari II serves seven irrigation network areas: Taman Lor, Kabuaran, Senudin, Sipah, Gardu, Tasnan, and Kemiri. Therefore, it is also important to prevent soil erosion to ensure this wide irrigation network can work properly [17], even though it has a lower value. The average rainfall erosivity value at the research location is 645 mm/ year.
3.2. Soil erodibility (K)
Soil erodibility is the inherent susceptibility of soils to erosion by water and wind [18]. It measures how easily erosive forces can detach and transport soil particles. In this study, the interpretation of soil erodibility is performed by the soil type, which consists of eutrik regosol (Re), molik andosol (Tm), okrik andosol (To), dan vitric andosol (Tv) as shown in Figure 4. Different soil types have varying degrees of erodibility due to their textures [19].
The dominant soil type in the study area is Tv, with a K value of 0.28, covering approximately 43.68% of the total area, which is 7474.42 hectares. This K value is the same as the Tm soil type, which covers the second largest area, 5037.48 hectares, or 29.44%. Both of them are classified as sensitive in terms of erosion susceptibility, along with To soil type. This type covers an area of 3685.58 hectares, representing 21.54% of the total area, with the lowest K value of 0.19. Conversely, the Re soil type encompasses an area of 912.03 hectares, which represents 5.33% of the total area. However, based on the observed points and the location of the irrigation network in the Sampean Hulu Sub-watershed, even though Re has the highest soil erodibility value, there is no issue in terms of irrigation infrastructure. Re soil area is located in the highlands, thus there is no irrigation network. Therefore, soil erosion management can focus on other such as areas with Tv soil type. The Tv soil type is characterized by a high content of clay components, which makes it highly susceptible to erosion [20]. This fine texture in the soil has low cohesion and is easily detached and transported by water or wind [21]. Fine-textured soils have a larger surface area, making them more prone to erosion due to smaller particles can be easily dislodged and carried away by the erosive forces of water into the irrigation network.
Figure 3. Rainfall erosivity map (R)
Figure 4. Map of soil erodibility (K)
3.3. Slope length and steepness (LS)
LS is a topographic factor used in erosion modeling, particularly in the USLE methods. LS represents the combined effect of slope length and slope steepness on soil erosion [22].
Slope length refers to the horizontal distance along the slope from the origin of runoff to the point where it exits the field or reaches a defined outlet. Slope steepness, on the other hand, measures the degree of inclination or the angle of the slope. It represents the vertical rise of the slope per unit of horizontal distance. This study's slope steepness is classified into five classes: flat, gently sloping, sloping, steep, and very steep [20],
as shown in Figure 5. The LS values are calculated from the flow accumulation and slope (steepness) obtained from the Digital Elevation Model (DEM) data.
The study area is dominated by flat, gently sloping slopes with steepness ranging from >8 to 8 to 15. These areas cover 5272 and 5080 hectares, or approximately 30.82% and 29.70%
of the study area. These slopes generally have a lower soil erosion risk than steeper slopes [4]. It is less prone to erosion than steeper slopes due to water runoff's reduced speed and energy [23]. Furthermore, the sloping, steep, and very steep only happened in 16.19%, 12.08%, and 11.21% of the total area, 2769, 2066, and 1917 hectares.
Figure 5. Slope steepness map (LS)
Figure 6. Land use map The LS value of these classes ranges from 15-25, 25, 45, to >45.
Very steep slopes are highly vulnerable to soil erosion due to their extreme inclination [24], resulting in rapid water runoff and high erosive forces [25]. Although they only stand on smaller land, areas with steep slope conditions must be assessed to prevent the irrigation network from clogging.
3.4. Crop Management and Soil Conservation Practices (CP)
Crop management and soil conservation practices (CP) refer to various techniques and strategies implemented in agricultural practices to mitigate soil erosion and maintain soil
health. CP values represent the effectiveness of specific crop management and soil conservation practices in reducing soil erosion [4]. This study classified nine land uses: secondary dryland forest, shrubland, forest plantation, plantation, rainfed agriculture, mixed rainfed agriculture, paddy fields, settlements, and bare land, as shown in Figure 6.
Paddy fields cover 6905.46 hectares or 40.36% of the total area. This land use has a CP factor value of 0.01. Forest plantations become the second largest land use area with 3512.77 hectares or 20.53%. The CP value of forest plantation is 0.001, like secondary dryland forest and shrubland with 1639.48 and 621.83 hectares or 9.58 and 3.63% of the total area.
Figure 7. Soil erosion hazard classes map It indicates that these areas are well-managed for soil
conservation practices, effectively reducing soil erosion [26].
Conversely, bare land has the highest CP value of 0.70. The highest CP value implies a high susceptibility to soil erosion due to the absence of conservation practices and less soil cover [27]. However, the area covered by bare land is relatively small, with 197.77 hectares, representing approximately 1.16%
of the total area. The rest of the area consists of 0.29%, 14.66%, 1.97%, and 7.82% of plantation, rainfed agriculture, and mixed rainfed agriculture, or approximately 48.93, 2508.24, and 336.99 hectares with a CP value of 0.20, while the settlements have a CP value of 0.35. Land cover and conservation practices play a crucial role in reducing erosion by preserving the integrity of the soil and reducing the risk of erosion by mulching, intercropping, crop rotation, and terracing [28].
3.5. Soil Erosion Hazard Classes
The erosion factor values are crucial in determining the erosion hazard classes within an area. These values are derived from various erosion variables, including Rain Erosivity (R), Soil Erodibility (K), Slope Length AND Steepness (LS), and Crop Management and Soil Conservation Practices (CP). Each factor contributes to the overall erosion potential of the land and helps assess the severity of erosion hazards. Combining these erosion factors can determine erosion hazard classes, as shown in Figure 7.
Using the USLE method, the erosion hazard classification (ton/ha/year) is determined into five classes based on Table 3.
The very high, high, moderate, low, and very low erosion hazard class covers an area of 1759.48, 1234.43, 1551.02, 5469.21, and 7010.10 hectares, accounting for 10.34%, 7.25%, 9.11%, 32.13% and 41.18% of the total area. It indicates that the Sampean Hulu sub-watershed is more dominant and less susceptible to soil erosion.
Based on the mapping, even a moderate rainfall erosivity value of 577 mm/year can contribute to a very high erosion hazard level. This highlights the significance of considering
high erosivity values and other factors, such as land cover and soil type in assessing erosion risks. The combination of moderate rainfall erosivity, susceptible land uses, and erodible soils can lead to high and very high erosion hazards [29]. Land uses with low CP values, such as secondary dryland forests, shrubland, and forest plantations, are associated with lower erosion hazards. On the other hand, land use with higher CP values, such as plantations, rainfed agriculture, mixed rainfed agriculture, settlements, and bare land, contribute to increased erosion hazards. This finding is consistent with the study by [30], which emphasizes that land uses lacking strong root systems, such as rainfed agriculture, mixed rainfed agriculture, bare land, and settlements with high CP values are susceptible to erosion. Therefore, implementing conservation agricultural practices, promoting sustainable land management practices, and implementing land use regulations and policies are important to create more resilience to erosion [31]. Additionally, the presence of Andosol soil type, characterized as organic soils in the surface layer, strongly influences the occurrence of very high erosion.
Organic soils are more susceptible to erosion, contributing to a higher erosion rate [32]. It is important to consider the erodibility of Andosol soils when implementing soil conservation measures in the area. Contour farming, terracing, cover cropping, conservation tillage, and mulching can be a solution for farmers and land owners or managers to reduce soil erosion effectively [33]. This will worsen if the incident occurs in an area that slopes to a very steep slope. As the slope steepness increases, the surface runoff erodes the soil more rapidly, and longer slopes result in a larger volume of soil being transported by runoff. Flat slopes pose a lower erosion hazard than steep slopes [34]. However, vegetation planting, soil conservation techniques, or soil bioengineering techniques can prevent the irrigation area from erosion and network blocking [35] in the Sampean Hulu Sub-watershed.
4. Conclusion
Erosion hazards in the Sampean Hulu Sub-watershed are crucial due to the extensive area and mixed forest character with moderately steep slopes. Sedimentation in the irrigation channels further exacerbates the issue, compromising water distribution and necessitating erosion monitoring in the irrigation network's management and maintenance. The land uses lacking strong root systems, such as rainfed agriculture, mixed rainfed agriculture, bare land, and settlements, contribute to higher erosion hazards. Conservation agricultural practices, sustainable land management, and land use regulations are vital in mitigating erosion hazards.
Furthermore, the presence of Andosol soil type, being organic and susceptible to erosion, emphasizes the need to consider soil conservation measures. Sloping to very steep slope conditions poses higher erosion hazards, but implementing vegetation planting, soil conservation techniques, and soil bioengineering can help prevent erosion and maintain the functionality of the irrigation network. A comprehensive approach involving multiple strategies, including land management practices, soil conservation measures, and erosion monitoring, is necessary to mitigate erosion hazards and ensure sustainable land use in the Sampean Hulu Sub- watershed.
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