Analysis of Land Suitability for the Development of Porang (Amarphopallus ancophillus ) Plants in Lewa Sub-Regency, East Sumba Regency

Lewa sub-district is one of the sub-districts in East Sumba Regency, which has dry land that can be maximized for the development of porang plants and development purposes; information on the potential of porang plantations is needed. This study aimed to determine the biophysical characteristics of the land and the land suitability class of porang plants. The analytical method used was the matching method by comparing the land characteristics and plant growth requirements and the overlay method. The matching results show that the land characteristics in Lewa Subdistrict are class S1 (Very suitable), covering an area of 26.220,209 ha and Class S2 (quite suitable), covering an area of 3.608,523 ha. Limiting factors in this area are water availability (OA) such as drainage, nutrient retention (nr) such as CEC and pH, and erosion hazards (eh) such as slope.

Manufacturing and assessing new samplers to measure wind soil erosion

Wind soil erosion is one of the most important causes of soil degradation that impede the process of sustainable agricultural development. The first step to mitigating wind erosion hazards is to find an effective and accurate way to assess its severity. Therefore, the main objective of this research was to raise and evaluate the efficiency of the new four traps to measure eroded soil, Fixed Distance trap (FD), Fixed Point trap (FP), Rotary Distance trap (RD) and Rotary Point trap (RP). The study traps RP and FP compared with the Big Spring Number Eight trap (BSNE) (traditional trap) and the traps RD and FD compared with the Bagnold trap (traditional trap). The results indicated that the order of study traps in terms of soil collection efficiency and soil retention efficiency were RD>FD>Bagnold>RP>FP>BSNE and FP>RP>RD>FD>Bagnold>BSNE, respectively. Results proved that the best traps in collecting eroded soil were RP trap followed by FP trap, compared to BSNE trap. Also, the best traps in collecting eroded soil were RD trap, followed by FD trap, compared to the Bagnold trap. The most important results showed that the relative efficiency of RP and FP traps were 181% and 159%, respectively, compared to BSNE and the relative efficiency of RD and FD traps were 186% and 172%, respectively, compared to the Bagnold trap. The study proved high accuracy of new traps in measuring soil eroded material, separating soil particles according to their size directly inside traps and determining the direction of the wind compared to traditional traps.

Modeling and Assessing Potential Soil Erosion Hazards Using USLE and Wind Erosion Models in Integration with GIS Techniques: Dakhla Oasis, Egypt

Soil erosion modeling is becoming more significant in the development and implementation of soil management and conservation policies. For a better understanding of the geographical distribution of soil erosion, spatial-based models of soil erosion are required. The current study proposed a spatial-based model that integrated geographic information systems (GIS) techniques with both the universal soil loss equation (USLE) model and the Index of Land Susceptibility to Wind Erosion (ILSWE). The proposed Spatial Soil Loss Model (SSLM) was designed to generate the potential soil erosion maps based on water erosion and wind erosion by integrating factors of the USLE and ILSWE models into the GIS environment. Hence, the main objective of this study is to predict, quantify, and assess the soil erosion hazards using the SSLM in the Dakhla Oasis as a case study. The water soil loss values were computed by overlaying the values of five factors: the rainfall factor (R-Factor), soil erodibility (K-Factor), topography (LS-Factor), crop types (C-Factor), and conservation practice (P-Factor). The severity of wind-driven soil loss was calculated by overlaying the values of five factors: climatic erosivity (CE-Factor), soil erodibility (E-Factor), soil crust (SC-Factor), vegetation cover (VC-Factor), and surface roughness (SR-Factor). The proposed model was statistically validated by comparing its outputs to the results of USLE and ILSWE models. Soil loss values based on USLE and SSLM varied from 0.26 to 3.51 t ha−1 yr−1 with an average of 1.30 t ha−1 yr−1 and from 0.26 to 3.09 t ha−1 yr−1 with a mean of 1.33 t ha−1 yr−1, respectively. As a result, and according to the assessment of both the USLE and the SSLM, one soil erosion class, the very low class (<6.7 t ha−1 yr−1), has been reported to be the prevalent erosion class in the study area. These findings indicate that the Dakhla Oasis is slightly eroded and more tolerable against water erosion factors under current management conditions. Furthermore, the study area was classified into four classes of wind erosion severity: very slight, slight, moderate, and high, representing 1.0%, 25.2%, 41.5%, and 32.3% of the total study area, respectively, based on the ILSWE model and 0.9%, 25.4%, 43.9%, and 29.9%, respectively, according to the SSLM. Consequently, the Dakhla Oasis is qualified as a promising area for sustainable agriculture when appropriate management is applied. The USLE and ILSWE model rates had a strong positive correlation (r = 0.97 and 0.98, respectively), with the SSLM rates, as well as a strong relationship based on the average linear regression (R2 = 0.94 and 0.97, respectively). The present study is an attempt to adopt a spatial-based model to compute and map the potential soil erosion. It also pointed out that designing soil erosion spatial models using available data sources and the integration of USLE and ILSWE with GIS techniques is a viable option for calculating soil loss rates. Therefore, the proposed soil erosion spatial model is fit for calculating and assessing soil loss rates under this study and is valid for use in other studies under arid regions with the same conditions.

ANALISIS TINGKAT BAHAYA EROSI PADA VEGETASI KEBUN KARET PADA BERBAGAI KELERENGAN DI SUB DAS BATI-BATI DAS MALUKA PROVINSI KALIMANTAN SELATAN

The danger level of erosion at each land closure and Slopes has different results. It is important to know the handling of erosion hazards later. The purpose of this study is to calculate the amount of erosion due to changes in land closures and to know the level of erosion hazard (TBE) of rubber plantations on various slopes in Sub Das Bati – Bati Das Maluka. The research method is purposive random sampling. Sample points taken based on soil type, slopes class, vegetation, and land cover are adjusted to the land units of the land unit map (overlay). Soil sampling using ring samples and soil drills will then be tested. Land cover and marbles are closely related to erosion values. The highest erosion value is in Land Unit (LU) 38 with an erosion value of 73.64 tons/ha/yr, while the lowest value is at LU 7 with an erosion value of 6.34 tons/ha/yr. The degree of erosion hazard is related to the soil solum. Erosion hazard level in all land units and land cover indicates grade II-S (medium) is present at LU 38 while light (I-SR) is on, LU 37, LU 50, and LU 59, and very light (0-SR) is on LU 7 and LU 34.Tingkat bahaya erosi pada masing-masing penutupan lahan dan kelerengan mempunyai hasil yang berbeda. Hal ini penting untuk mengetahui penanganan bahaya erosi nantinya. Tujuan dari penelitian ini ialah untuk menghitung besarnya jumlah erosi akibat perubahan penutupan lahan serta mengetahui tingkat bahaya erosi (TBE) vegetasi kebun karet pada berbagai kelerengan di Sub Das Bati-Bati Das Maluka. Metode penelitian dilakukan secara purposive random sampling. Titik sampel yang diambil berdasarkan jenis tanah, kelas kelerengan, vegetasi, dan tutupan lahan yang disesuaikan dengan unit lahan dari peta satuan lahan (overlay). Pengambilan sampel tanah menggunakan ring sample dan bor tanah yang kemudian akan dilakukan pengujian. Tutupan lahan dan kelerengan erat kaitannya dengan nilai erosi. Nilai erosi tertinggi berada pada Unit Lahan (UL) 38 dengan nilai erosi sebesar 73,64 ton/ha/thn, sedangkan nilai terendah ada pada UL 7 dengan nilai erosi sebesar 6,34 ton/ha/thn. Tingkat bahaya erosi berhubungan dengan solum tanah. Tingkat bahaya erosi pada semua unit lahan dan tutupan lahan, menunjukkan TBE kelas II-S (sedang) terdapat pada UL 38 sedangkan TBE ringan (I-SR) ada pada, UL 37, UL 50, dan UL 59 serta TBE sangat ringan (0-SR) ada pada UL 7 dan UL 34.

A NEW STORM IMPACT MATRIX COMBINING BOTH COASTAL FLOODING AND EROSION HAZARDS

Coastal zones are often threatened by storms that elevate water levels and increase the wave energy impacting the shoreline. These storm conditions result in coastal flooding and erosion hazards for communities, threatening lives, properties and infrastructure. Coastal impact Early Warning Systems (EWSs) are currently used to alert authorities of potential impacts prior to advancing storms. Effective EWSs provide important windows of opportunity to undertake mitigating actions to minimize the damage caused by a storm.Recorded Presentation from the vICCE (YouTube Link): https://youtu.be/-U6uEHfLizA

A Review on Assessing and Mapping Soil Erosion Hazard Using Geo-Informatics Technology for Farming System Management

Soil erosion is a severe threat to food production systems globally. Food production in farming systems decreases with increasing soil erosion hazards. This review article focuses on geo-informatics applications for identifying, assessing and predicting erosion hazards for sustainable farming system development. Several researchers have used a variety of quantitative and qualitative methods with erosion models, integrating geo-informatics techniques for spatial interpretations to address soil erosion and land degradation issues. The review identified different geo-informatics methods of erosion hazard assessment and highlighted some research gaps that can provide a basis to develop appropriate novel methodologies for future studies. It was found that rainfall variation and land-use changes significantly contribute to soil erosion hazards. There is a need for more research on the spatial and temporal pattern of water erosion with rainfall variation, innovative techniques and strategies for landscape evaluation to improve the environmental conditions in a sustainable manner. Examining water erosion and predicting erosion hazards for future climate scenarios could also be approached with emerging algorithms in geo-informatics and spatiotemporal analysis at higher spatial resolutions. Further, geo-informatics can be applied with real-time data for continuous monitoring and evaluation of erosion hazards to risk reduction and prevent the damages in farming systems.