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Titlebook: Climate Change Impact on Soil Erosion in Sub-tropical Environment; Application of Empir Subodh Chandra Pal,Rabin Chakrabortty Book 2022 The

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書(shū)目名稱Climate Change Impact on Soil Erosion in Sub-tropical Environment
副標(biāo)題Application of Empir
編輯Subodh Chandra Pal,Rabin Chakrabortty
視頻videohttp://file.papertrans.cn/228/227405/227405.mp4
概述Deals with different empirical and semi-empirical models which have been validated with primary field-based observation.Contains detailed and lucid methods of all empirical and semi-empirical models.E
叢書(shū)名稱Geography of the Physical Environment
圖書(shū)封面Titlebook: Climate Change Impact on Soil Erosion in Sub-tropical Environment; Application of Empir Subodh Chandra Pal,Rabin Chakrabortty Book 2022 The
描述.This work focuses on the potential impact of climate change on soil erosion in a monsoon-dominated sub-tropical region. Water-induced soil erosion due to extreme rainfall during the monsoon period is a major problem worldwide, from different environmental and socio-economic perspectives. This study region covered (South Bengal) is one of the fertile agricultural belts that produces a good amount of produce and contributes to the country‘s GDP. However, the rate of agricultural output has decreased rapidly in recent times due to a decline in soil fertility...The monsoon-dominated sub-tropical region has unique characteristics in terms of seasonal temperature fluctuations and the availability of rainfall events. The sub-tropical region is densely populated, with the majority of the population relying on rain-fed agricultural production systems. The declining rate of agricultural production has also established that soil fertility is declining and soil erosion is increasing. Numerous studies show that soil erosion is the major cause of the region‘s rapidly increasing trend of land degradation. A homeostatic mechanism cannot replace soil erosion, and a gap arises between soil erosion
出版日期Book 2022
關(guān)鍵詞land degradation; storm rainfall events; severe rainfall; rainfall scenarios; sedimentaiton; conservation
版次1
doihttps://doi.org/10.1007/978-3-031-15721-9
isbn_softcover978-3-031-15723-3
isbn_ebook978-3-031-15721-9Series ISSN 2366-8865 Series E-ISSN 2366-8873
issn_series 2366-8865
copyrightThe Editor(s) (if applicable) and The Author(s), under exclusive license to Springer Nature Switzerl
The information of publication is updating

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Potential Sediment Yield Estimation Using Machine Learning, Artificial Intelligence Techniques and ld potentiality in this region. The middle, southern and south-eastern part of this region is associated with moderate to very high sediment yield zones though it is unevenly distributed throughout this region. This sort of particular information aids decision-makers and future researchers in develo
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Christine A. Ogren,Marc A. VanOverbekerate these input data are the most difficult problems for evaluating these models. The advancement of remote sensing technology has improved the accessibility and cost-effectiveness of spatial information regarding the input parameters. The spatial data processing capabilities of “geographic informa
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