Isiguzo Edwin Ahaneku , Kingsley Chidi Ezinna , Francis Nkemdirim Orji , George Uwadiegwu Alaneme , Ekeoma Emmanuel Chukwudi
{"title":"Spatial distribution of soil erodibility factors in erosion-prone areas in Umuahia, Southeast, Nigeria","authors":"Isiguzo Edwin Ahaneku , Kingsley Chidi Ezinna , Francis Nkemdirim Orji , George Uwadiegwu Alaneme , Ekeoma Emmanuel Chukwudi","doi":"10.1016/j.jer.2024.04.002","DOIUrl":null,"url":null,"abstract":"<div><div>This study evaluates the spatial distribution of soil erodibility factor (K) in Umuahia, Abia State, Nigeria using the Universal Soil Loss Equation (USLE) nomograph. The soils used for the study was sampled from 14 erosion prone areas in Umuahia, Southeast, Nigeria. The topsoil samples collected at depths of 0–10 cm, 10–20 cm, and 20–30 cm around the middle of each location identified with the aid of a GPS. The percentages of sand, silt, clay, moisture content, saturated hydraulic conductivity, and organic matter (OM) were all examined. The Gaussian ordinary kriging model for the determination of K-factor was compared with the Inverse Distance Weighting method. The K-factor’s coefficient of variation (CV) was 0.29 and the K-factor value of the nuggets to sill ratio (0.44) indicates a moderate spatial distribution. The Gaussian semi-variogram approach yielded the best estimate accuracy and model fitting effects, meaning that the Gaussian ordinary Kriging model is better for K-factor estimation. The root mean squared error (RMSE) was 0.0079 and the mean squared deviation ratio (MSDR) was 0.89, implying that the Gaussian model was unbiased and adequately captured the experimental variation. The K-factor values were lower in the north of the research region ranging from 0.0250 to 0.0197 Mg h MJ<sup>−1</sup> mm<sup>−1</sup> compared to east with the K-factor ranging from 0.0399 to 0.0423 Mg h MJ<sup>−1</sup> mm<sup>−1</sup>. The estimated K-factor was relatively unbiased since the root mean square error was extremely small and the mean error was nearly equal to 0. The determination of soil erodibility (k-factor) influenced by factors such as soil texture, structure, and organic matter is crucial in assessing the vulnerability of land area to soil erosion. The spatial distribution of these factors affects the k-factor at different locations in a landscape, which enables accurate estimation of k-factor. Nutrient levels impact soil erodibility and distribution. Low nitrogen limits growth, favoring erosion. Phosphorus aids stability. Optimal potassium benefits growth and erosion control. Spatial distribution is vital, emphasizing precise nutrient management for effective soil health.</div></div>","PeriodicalId":48803,"journal":{"name":"Journal of Engineering Research","volume":"13 2","pages":"Pages 1627-1637"},"PeriodicalIF":2.2000,"publicationDate":"2025-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Engineering Research","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S2307187724000920","RegionNum":4,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q3","JCRName":"ENGINEERING, MULTIDISCIPLINARY","Score":null,"Total":0}
引用次数: 0
Abstract
This study evaluates the spatial distribution of soil erodibility factor (K) in Umuahia, Abia State, Nigeria using the Universal Soil Loss Equation (USLE) nomograph. The soils used for the study was sampled from 14 erosion prone areas in Umuahia, Southeast, Nigeria. The topsoil samples collected at depths of 0–10 cm, 10–20 cm, and 20–30 cm around the middle of each location identified with the aid of a GPS. The percentages of sand, silt, clay, moisture content, saturated hydraulic conductivity, and organic matter (OM) were all examined. The Gaussian ordinary kriging model for the determination of K-factor was compared with the Inverse Distance Weighting method. The K-factor’s coefficient of variation (CV) was 0.29 and the K-factor value of the nuggets to sill ratio (0.44) indicates a moderate spatial distribution. The Gaussian semi-variogram approach yielded the best estimate accuracy and model fitting effects, meaning that the Gaussian ordinary Kriging model is better for K-factor estimation. The root mean squared error (RMSE) was 0.0079 and the mean squared deviation ratio (MSDR) was 0.89, implying that the Gaussian model was unbiased and adequately captured the experimental variation. The K-factor values were lower in the north of the research region ranging from 0.0250 to 0.0197 Mg h MJ−1 mm−1 compared to east with the K-factor ranging from 0.0399 to 0.0423 Mg h MJ−1 mm−1. The estimated K-factor was relatively unbiased since the root mean square error was extremely small and the mean error was nearly equal to 0. The determination of soil erodibility (k-factor) influenced by factors such as soil texture, structure, and organic matter is crucial in assessing the vulnerability of land area to soil erosion. The spatial distribution of these factors affects the k-factor at different locations in a landscape, which enables accurate estimation of k-factor. Nutrient levels impact soil erodibility and distribution. Low nitrogen limits growth, favoring erosion. Phosphorus aids stability. Optimal potassium benefits growth and erosion control. Spatial distribution is vital, emphasizing precise nutrient management for effective soil health.
期刊介绍:
Journal of Engineering Research (JER) is a international, peer reviewed journal which publishes full length original research papers, reviews, case studies related to all areas of Engineering such as: Civil, Mechanical, Industrial, Electrical, Computer, Chemical, Petroleum, Aerospace, Architectural, Biomedical, Coastal, Environmental, Marine & Ocean, Metallurgical & Materials, software, Surveying, Systems and Manufacturing Engineering. In particular, JER focuses on innovative approaches and methods that contribute to solving the environmental and manufacturing problems, which exist primarily in the Arabian Gulf region and the Middle East countries. Kuwait University used to publish the Journal "Kuwait Journal of Science and Engineering" (ISSN: 1024-8684), which included Science and Engineering articles since 1974. In 2011 the decision was taken to split KJSE into two independent Journals - "Journal of Engineering Research "(JER) and "Kuwait Journal of Science" (KJS).