نتایج جستجو برای: erosivity

تعداد نتایج: 371  

Journal: :Data 2023

This paper describes the data gathered for a published in Earth-Science Reviews (DOI: 10.1016/j.earscirev.2023.104339) to address problem of studies using incorrect equations calculate rainfall erosivity (R factor), which can lead issues related land degradation, soil productivity loss, and biodiversity loss. The aim was locate articles containing create relational database that could be used p...

Journal: :International Journal of Academic Research in Business and Social Sciences 2018

Journal: :Han-guk toyang biryo hakoeji 2021

It is important to form and maintain ridges for air permeability within the upland crop root zone in Saemangeum reclaimed land with poor drainage. The ridge area, however, difficult be maintained due high content of sand silt, which are susceptible water erosion. This study was conducted investigate reduction height maize growth as affected by rainfall characteristics through application mainte...

Introduction: Soil erosion is the most important factor in damaging and decreasing the productivity of agricultural soils. Moreover, as the transfer of sediments rich in nutrients through the soil leads to soil erosion and in turn to the decrease in the dams’ reservoirs’ storage capacity, bringing about adverse economic and eco-environmental consequences such as damage to land resources and dec...

Journal: :Earth surface dynamics 2022

Abstract. Rainfall erosivity values are required for soil erosion prediction. To calculate the mean annual rainfall (R), long-term high-resolution observed data required, which often not available. overcome issue of limited availability in space and time, four methods were employed evaluated: direct regionalisation R, 5 min rainfall, disaggregation daily into time steps, a regionalised stochast...

Journal: :Remote Sensing 2021

Monitoring urban area expansion through multispectral remotely sensed data and other geomatics techniques is fundamental for sustainable planning. Forecasting of future land use cover (LULC) change the years 2034 2050 was performed using Cellular Automata Markov model current fast-growing Epworth district Harare Metropolitan Province, Zimbabwe. The stochastic CA–Markov modelling procedure valid...

Journal: :International Journal of Environment, Agriculture and Biotechnology 2017

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