scholarly journals Prediction of Land Erosion Events in the Down Stream Kreung Meureubo Watershed West Aceh District

2021 ◽  
Vol 1 (4) ◽  
pp. 70-76
Author(s):  
Muhammad Ikhsan ◽  
Meylis Safriani ◽  
Cut Suciatina Silvia ◽  
Refvina Dari
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Soil Erosion ◽  
Land Cover ◽  
Erosion Rate ◽  
Land Conservation ◽  
Soil Types ◽  
Soil Erodibility ◽  
Conservation Actions ◽  
Rain Splash

This study aims to predict the occurrence of erosion in the downstream Krueng Meureubo watershed, West Aceh Regency. Erosion is the loss of topsoil due to rain splash which is analyzed as a factor of rain erosivity, but the occurrence of erosion is not necessarily calculated by the occurrence of rain alone, but many other factors, such as soil erodibility, slope and length of land, land cover and the presence or absence of land conservation efforts. the. The Krueng Meurebo watershed shows a large sediment transport, with an indication that the river is getting shallower caused by sediment deposition at the riverbed, this sediment comes from sediment carried through the process of soil erosion. The method used in analyzing the occurrence of soil erosion in this study is the USLE method and uses a Geographic Information System (GIS). The results obtained are the distribution of erosion rate values in 228 polygons, with the largest erosion rate value occurring in polygon 1 with an erosion rate of 8495.308 tons/ha/year. The smallest erosion rate occurs in polygons 30, 34, 35, 179, and 180, with an erosion rate of 0 meaning that there is no land erosion event, which occurs in organosol and glehumus and regosol soil types, land cover is settlements and water bodies. It is concluded that the occurrence of erosion in a land is very dependent on the type of soil and the type of land cover. It is recommended for land with large erosion events to take serious land conservation actions so that erosion events can be minimized and do not occur continuously which of course can cause the watershed to become critical. Conservation efforts can be carried out in various ways, one of which is by vegetative means using plants that can reduce the rate of soil erosion.

scholarly journals Estimation of Soil Erosion using USLE and GIS

2019 ◽  
Vol 8 (2) ◽  
pp. 3936-3939
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Rate ◽  
Environmental Problem ◽  
Gis Technique ◽  
Economic Imbalances ◽  
Factor C ◽  
Soil Loss Equation

Soil erosion is one of the most serious environmental problem which must be taken in to consideration to prevent economic imbalances in nature. Soil erosion not only affect the agricultural productivity but also increases level of sedimentation. The study was carried out to determine the soil erosion for the watershed which is located in Godavari middle sub basin, Nanded district, Maharashtra state (India). The universal soil loss equation (USLE) and Geographic information system (GIS) technique was used to determine soil erosion. Present study revealed that, the study area is under moderate erosion with an average soil loss 7.233 tones/ha/yr. Where as minimum and maximum erosion rate observed as 5.39 tones/ha/yr to 10.27 tones/ha/yr respectively. The various maps of USLE factors prepared in QGIS environment. Statistically significant relationship obtained between soil loss and cover management factor (C). It was observed that C factor more influences in soil loss than any other factor.

scholarly journals Impact of land-use and land-cover change on soil erosion using the RUSLE model and the geographic information system: a case of Temeji watershed, Western Ethiopia

2021 ◽  
Author(s):  
Mitiku Badasa Moisa ◽  
Daniel Assefa Negash ◽  
Biratu Bobo Merga ◽  
Dessalegn Obsi Gemeda
Keyword(s):  
Land Use ◽  
Information System ◽  
Geographic Information System ◽  
Soil Erosion ◽  
Land Cover ◽  
Water Conservation ◽  
Soil Loss ◽  
Geographic Information ◽  
Lulc Change ◽  
The Impact

Abstract The impact of land-use land-cover (LULC) change on soil resources is getting global attention. Soil erosion is one of the critical environmental problems worldwide with high severity in developing countries. This study integrates the Revised Universal Soil Loss Equation model with a geographic information system to estimate the impacts of LULC conversion on the mean annual soil loss in the Temeji watershed. In this study, LULC change of Temeji watershed was assessed from 2000 to 2020 by using 2000 Landsat ETM+ and 2020 Landsat OLI/TIRS images and classified using supervised maximum likelihood classification algorithms. Results indicate that the majority of the LULC in the study area is vulnerable to soil erosion. High soil loss is observed when grassland and forest land were converted into cultivated land with a mean soil loss of 88.8 and 86.9 t/ha/year in 2020. Results revealed that about 6,608.5 ha (42.8%) and 8,391.8 ha (54.4%) were categorized under severe classes in 2000 and 2020, respectively. Accordingly, the soil loss severity class is directly correlated with the over-exploitation of forest resources and grasslands for agricultural purposes. These results can be useful for advocacy to enhance local people and stakeholder's participation toward soil and water conservation practices.

scholarly journals Estimation of Erosion with Geographic Information Systems (GIS) in the TAHURA RADEN SOERJO Fire Areas

2020 ◽  
Vol 3 (1) ◽  
pp. 21
Author(s):  
Heri Erwantoro Timor ◽  
Tatag Muttaqin ◽  
Nugroho Tri Waskitho
Keyword(s):  
Information System ◽  
Information Systems ◽  
Geographic Information System ◽  
Geographic Information Systems ◽  
Land Cover ◽  
Surface Runoff ◽  
Erosion Rate ◽  
Visual Presentation ◽  
Geographic Information ◽  
Erosivity Index

The Ledug Block is one of the areas in TAHURA R Soerjo which is experiencing fire. The fire causes the existing land cover to change or decrease, with the reduced land cover, the land will be easily exposed to surface runoff. This study aims to calculate the erosion rate in the TAHURA R Soerjo Ledug Block using the USLE equation, visual presentation of erosion using the Goegraphic Information System (GIS). This research was conducted in December 2018 in the rehabilitation area of Tahura R Soerjo Priug Ledug Block, Pasuruan. The method used is the Geographic Information System (GIS) whose data is sourced from calculations with the USLE method. The results of the study are the rain erosivity index (R) obtained from the month rainfall in 2018. The soil at the study site in each SUL is dusty clay. The vegetation in the research location in each SUL is in the form of bushes and added to SUL 3 there are several trees. The average erosion rate is 0.034 tons / ha / year. Erosion hazard classes that occur at the research location are included in class I (very mild). Enriching the land cover by planting trees with tree stands needs to be done so that the land is tightly closed and better withstand surface runoff.

scholarly journals Effect of DEM Resolution on Erosion in Batang Kuranji Watershed

2020 ◽  
Vol 15 (2) ◽  
pp. 20
Author(s):  
Elvi Roza Syofyan ◽  
Bambang Istijono ◽  
Amrizal Saidi ◽  
Revalin Herdianto
Keyword(s):  
Soil Erosion ◽  
Land Cover ◽  
Sea Level ◽  
Erosion Rate ◽  
Class Ii ◽  
Class I ◽  
Hazard Class ◽  
Dem Resolution ◽  
Main River ◽  
Rate Calculation

Batang Kuranji Watershed is one of the region river at Indragiri - Akuaman with a total area of Watershed 224.7 km2 consisting of Batang Sungai Sapiah Sub Watershed, Batang Danau Limau Manih Sub Watershed, Batang Sungkai Sub Watershed, Batang Bukik Tindawan Sub Watershed and Batang Padang Janiah Sub Watershed. Batang Kuranji flows from upstream of the Bukit Barisan with the highest elevation + 1,605 meters above sea level at the peak of Bukit Tinjau Laut and empties into the Padang beach with a main river length of ± 32.41. DEM has an influence on the results of land erosion by affecting the slope accuracy. The higher the DEM resolution, the more precise the results of the soil erosion simulation. With the Musle method the rate of erosion occurs in the Batang Kuranji watershed, with DEM data of 8m and land cover in 2017, an erosion rate of 23.91 tons / ha / year is classified in hazard class II (light), DEM data of 30m erosion rate is 7. 70 tons / ha / year are classified in hazard class I (very mild), with DEM data of 90m erosion rate of 4.54 tons / ha / year classified in hazard I class (very light). It can be seen that the higher the DEM resolution, the more accurate the erosion rate calculation in the watershed.

scholarly journals APLIKASI PENGINDERAAN JAUH DAN SISTEM INFORMASI GEOGRAFI UNTUK PEMETAAN DAERAH BERPOTENSI TSUNAMI DI KABUPATEN KUPANG PROVINSI NUSA TENGGARA TIMUR

2018 ◽  
Vol 3 (2) ◽  
pp. 170-178
Author(s):  
Lidia Agustina Rumaal ◽  
Jehunias L. Tanesib ◽  
Jonshon Tarigan
Keyword(s):  
Remote Sensing ◽  
Information System ◽  
Geographic Information System ◽  
Population Density ◽  
Land Cover ◽  
Arrival Time ◽  
Land Cover Map ◽  
The Impact ◽  
Monitoring Area ◽  
Wave Arrival

Abstrak Telah dilakukan pemetaan daerah rawan tsunami berdasarkan estimasi waktu tiba gelombang dan tutupan lahan di Kabupaten Kupang Provinsi Nusa Tenggara Timur menggunakan aplikasi Penginderaan Jauh dan Sistem Informasi Geografi. Penelitian ini bertujuan untuk mengidentifikasi, memetakan daerah rawan tsunami dan tingkat kerawanannya menurut estimasi waktu tiba gelombang dan tutupan lahan sebagai upaya mitigasi dampak bencana tsunami terhadap kepadatan penduduk. Metode penelitian secara umum dibagi dalam empat tahap utama yaitu pembangunan basis data berupa pembuatan peta tutupan lahan, peta gempa dan peta batimetri. Analisis data kerawanan dari peta tutupan lahan dan etimasi waktu tiba gelombang, penyajian hasil data dalam bentuk tingkat kerawanan masing-masing peta dan analisis hasil penelitian berupa tingkat kerawanan secara kualitatif masing-masing daerah titik pantau menurut peta tutupan lahan maupun estimasi waktu tiba gelombang. Selain itu, dampak kerawanan tsunami diklasifikasikan menurut tingkat kepadatan penduduk untuk kebutuhan mitigasi sebagai berikut Kecamatan Kupang Timur, Kupang Barat, Sulamu, Amfoang Timur, Semau, Semau Selatan, Amfoang Utara, Amfoang Barat Daya, Amfoang Barat Laut dan Fatuleu Barat. Kata kunci : Peta rawan tsunami, Penginderaan Jauh, Sistem Informasi Geografi, Estimasi Waktu Tiba Gelombang  Abstract Mapping of hazard tsunami areas based on estimation of arrival time of wave and land cover in Kupang Regency of East Nusa Tenggara Province using remote sensing application and geographic information system has been done. The  aims of this research are to mapping the hazard tsunami area and tsunami vulnerability level in Kupang Regency East Nusa Tenggara according to the estimated arrival time of the wave and land cover as an effort to mitigate the impact of the tsunami disaster on population density. These generally devided into four main phase namely development of database in the form of land cover map , seismic maps and bathymetry maps, data analysis of research results in the form of qualitative vulnerability of each monitoring area according to land cover map and estimated wave arrival time. Presentation of data results in the form of vulnerability level of each map and analysis and results analysis of research the form of vulnerability level of each map and analysis of research results in the form of qualitative vulnerability of each monitoring area according to land cover map and estimated wave arrival time. And then, the impact of tsunami vulnerability is classified according to population density levels for mitigation needs as follows Kupang Timur, Kupang Barat, Sulamu, Amfoang Timur, Semau, Semau Selatan, Amfoang Utara, Amfoang Barat Daya, Amfoang Barat Laut and Fatuleu Barat. Keywords: Tsunami Hazard Map, Remote Sensing, Geographic Information System, Estimated Time of arrival Wave

scholarly journals Distribution of soil nutrients and erodibility factor under different soil types in an erosion region of Southeast China

PeerJ ◽  
2021 ◽  
Vol 9 ◽  
pp. e11630
Author(s):  
Man Liu ◽  
Guilin Han
Keyword(s):  
Soil Erosion ◽  
Soil Nutrients ◽  
Soil Ph ◽  
Major Elements ◽  
Soil Types ◽  
Soil Erodibility ◽  
Soil Evolution ◽  
Southeast China ◽  
Red Soils ◽  
K Factor

Background Soil erosion can affect the distribution of soil nutrients, which restricts soil productivity. However, it is still a challenge to understand the response of soil nutrients to erosion under different soil types. Methods The distribution of soil nutrients, including soil organic carbon (SOC), soil organic nitrogen (SON), and soil major elements (expressed as Al2O3, CaO, Fe2O3, K2O, Na2O, MgO, TiO2, and SiO2), were analyzed in the profiles from yellow soils, red soils, and lateritic red soils in an erosion region of Southeast China. Soil erodibility K factor calculated on the Erosion Productivity Impact Calculator (EPIC) model was used to indicate erosion risk of surface soils (0∼30 cm depth). The relationships between these soil properties were explored by Spearman’s rank correlation analysis, further to determine the factors that affected the distribution of SOC, SON, and soil major elements under different soil types. Results The K factors in the red soils were significantly lower than those in the yellow soils and significantly higher than those in the lateritic red soils. The SON concentrations in the deep layer of the yellow soils were twice larger than those in the red soils and lateritic red soils, while the SOC concentrations between them were not significantly different. The concentrations of most major elements, except Al2O3 and SiO2, in the yellow soils, were significantly larger than those in the red soils and lateritic red soils. Moreover, the concentrations of major metal elements positively correlated with silt proportions and SiO2 concentrations positively correlated with sand proportions at the 0∼80 cm depth in the yellow soils. Soil major elements depended on both soil evolution and soil erosion in the surface layer of yellow soils. In the yellow soils below the 80 cm depth, soil pH positively correlated with K2O, Na2O, and CaO concentrations, while negatively correlated with Fe2O3 concentrations, which was controlled by the processes of soil evolution. The concentrations of soil major elements did not significantly correlate with soil pH or particle distribution in the red soils and lateritic red soils, likely associated with intricate factors. Conclusions These results suggest that soil nutrients and soil erodibility K factor in the yellow soils were higher than those in the lateritic red soils and red soils. The distribution of soil nutrients is controlled by soil erosion and soil evolution in the erosion region of Southeast China.

scholarly journals Estimation of soil loss using remote sensing and GIS-based universal soil loss equation in northern catchment of Lake Tana Sub-basin, Upper Blue Nile Basin, Northwest Ethiopia

2020 ◽  
Vol 9 (1) ◽  
Author(s):  
Veera Narayana Balabathina ◽  
R. P. Raju ◽  
Wuletaw Mulualem ◽  
Gedefaw Tadele
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Soil Erosion ◽  
Soil Loss ◽  
Erosion Rate ◽  
Soil Erodibility ◽  
Lake Tana ◽  
Erosion Rates ◽  
Soil Erosion Rate ◽  
Soil Loss Equation

Abstract Background Soil erosion is one of the major environmental challenges and has a significant impact on potential land productivity and food security in many highland regions of Ethiopia. Quantifying and identifying the spatial patterns of soil erosion is important for management. The present study aims to estimate soil erosion by water in the Northern catchment of Lake Tana basin in the NW highlands of Ethiopia. The estimations are based on available data through the application of the Universal Soil Loss Equation integrated with Geographic Information System and remote sensing technologies. The study further explored the effects of land use and land cover, topography, soil erodibility, and drainage density on soil erosion rate in the catchment. Results The total estimated soil loss in the catchment was 1,705,370 tons per year and the mean erosion rate was 37.89 t ha−1 year−1, with a standard deviation of 59.2 t ha−1 year−1. The average annual soil erosion rare for the sub-catchments Derma, Megech, Gumara, Garno, and Gabi Kura were estimated at 46.8, 40.9, 30.9, 30.0, and 29.7 t ha−1 year−1, respectively. Based on estimated erosion rates in the catchment, the grid cells were divided into five different erosion severity classes: very low, low, moderate, high and extreme. The soil erosion severity map showed about 58.9% of the area was in very low erosion potential (0–1 t ha−1 year−1) that contributes only 1.1% of the total soil loss, while 12.4% of the areas (36,617 ha) were in high and extreme erosion potential with erosion rates of 10 t ha−1 year−1 or more that contributed about 82.1% of the total soil loss in the catchment which should be a high priority. Areas with high to extreme erosion severity classes were mostly found in Megech, Gumero and Garno sub-catchments. Results of Multiple linear regression analysis showed a relationship between soil erosion rate (A) and USLE factors that soil erosion rate was most sensitive to the topographic factor (LS) followed by the support practice (P), soil erodibility (K), crop management (C) and rainfall erosivity factor (R). Barenland showed the most severe erosion, followed by croplands and plantation forests in the catchment. Conclusions Use of the erosion severity classes coupled with various individual factors can help to understand the primary processes affecting erosion and spatial patterns in the catchment. This could be used for the site-specific implementation of effective soil conservation practices and land use plans targeted in erosion-prone locations to control soil erosion.

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