आईएसएसएन: 2157-7617

पृथ्वी विज्ञान एवं जलवायु परिवर्तन जर्नल

खुला एक्सेस

हमारा समूह 1000 से अधिक वैज्ञानिक सोसायटी के सहयोग से हर साल संयुक्त राज्य अमेरिका, यूरोप और एशिया में 3000+ वैश्विक सम्मेलन श्रृंखला कार्यक्रम आयोजित करता है और 700+ ओपन एक्सेस जर्नल प्रकाशित करता है जिसमें 50000 से अधिक प्रतिष्ठित व्यक्तित्व, प्रतिष्ठित वैज्ञानिक संपादकीय बोर्ड के सदस्यों के रूप में शामिल होते हैं।

ओपन एक्सेस जर्नल्स को अधिक पाठक और उद्धरण मिल रहे हैं
700 जर्नल और 15,000,000 पाठक प्रत्येक जर्नल को 25,000+ पाठक मिल रहे हैं

में अनुक्रमित
  • CAS स्रोत सूचकांक (CASSI)
  • सूचकांक कॉपरनिकस
  • गूगल ज्ञानी
  • शेरपा रोमियो
  • पर्यावरण में अनुसंधान तक ऑनलाइन पहुंच (ओएआरई)
  • जे गेट खोलो
  • जेनेमिक्स जर्नलसीक
  • जर्नल टीओसी
  • उलरिच की आवधिक निर्देशिका
  • कृषि में वैश्विक ऑनलाइन अनुसंधान तक पहुंच (अगोरा)
  • सेंटर फॉर एग्रीकल्चर एंड बायोसाइंसेज इंटरनेशनल (CABI)
  • RefSeek
  • हमदर्द विश्वविद्यालय
  • ईबीएससीओ एज़
  • ओसीएलसी- वर्ल्डकैट
  • प्रोक्वेस्ट सम्मन
  • एसडब्ल्यूबी ऑनलाइन कैटलॉग
  • पबलोन्स
  • यूरो पब
  • आईसीएमजेई
इस पृष्ठ को साझा करें

अमूर्त

Integration of Geo: Spatial and RUSLE Techniques for Soil Loss Estimation and to Identify Potential Soil and Water Conservation Measures in the Northern Ethiopia

Amare Gebre Medhin Nigusse, Belete Alemu

Soil erosion is one of the most severe land degradation challenges in the Ethiopia Highlands which causes siltation of large reservoirs and decline of agricultural production and productivity. This is also happening in the lake Hayq, the northern Ethiopia resulting in series agro-ecological imbalance. Improper cultivation, deforestation and rapid population growth are the main driving forces for this natural hazard. However, scientific studies are hardly found to see the impacts happening on the study area. Hence, present study was conducted with the aim of estimating the rate of soil loss and identifies potential soil and water conservation measures to be introduced in the area. Revised Universal Soil Loss Equation (RUSLE) with an integration of geo-spatial technologies applied to address the stated objectives. The RUSLE model used six important spatial factors namely rainfall data taken from Ethiopian national metrology agency, soil data, slope length and steepness derived from Digital Elevation Model (DEM), vegetation coverage from NDVI and conservation practice implemented were used. These raster baseline maps were prepared using different soft wares derived from various sources. Finally, the raster data added to the RUSLE environment model to evaluate and estimate the soil erosion loss. Similarly, potential conservation measures identified based on social acceptance, conservation performance, labor cost for implement and maintenance. Multi-criteria decisionmaking methods used to rank the conservation measures using the principle of analytic hierarchy process. The finding of this study indicated that the minimum annual soil loss estimated was zero in the outlet area which is less than the minimum tolerable soil loss 2 metric ton/ha/yr. Whereas the maximum annual soil loss was estimated to be 76.8 ton/ha/yr in steep area which is far from the maximum tolerable soil loss (18 ton/ha/yr). Generally, the mean annual soil loss from the catchment was estimated 22.8 ton/ha/yr which accounted a total of 131,966.4 ton/ha/yr soil loss. Of the total catchment, 39.4% (1860.1 ha) of the catchment area lie from non to slightly soil loss; 34.4% (1987 ha) of the catchment under moderately soil loss; 26.2% (1514.9 ha) of the catchment estimated high to very high soil loss. This result is comparable with household’s perception. Finally, the intervention map of the study area was prepared by integration of GIS, RS and RUSLE model and multi-criteria analysis applicable for conservation planning program and sustainable land management and sound soil and water conservation measures in erosion prone areas. To conclude, the study shows the effectiveness of GIS and RS techniques together with RUSLE model in estimating soil loss which can be used as a panacea for decision making such as for water resource infrastructure planning and establishment. But, such scientific studies demanded more comprehensive, reliable and accurate input data for better outcome and decision making.