Effect of land use land cover changes on the rate of soil erosion in the Upper Eyiohia river catchment of Afikpo North Area, Nigeria

Obiahu, Ota Henry; Elias, Eyasu

doi:10.1016/j.envc.2020.100002

Cited by 27 publications

(20 citation statements)

References 21 publications

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“…For example, a mean soil loss rate of 404 t•km −2 •yr −1 from agricultural land was reported in the European territory of Russia [34]. In southeastern Nigeria, the mean soil loss rate from the agricultural lands of the upper Eyiobia catchment reached 11,400 t•km −2 •yr −1 [35]. Land use policy usually acts as a land-use change driver [36].…”

Section: Discussionmentioning

confidence: 99%

Changes in Cultivated Land Area and Associated Soil and SOC Losses in Northeastern China: The Role of Land Use Policies

Fang

2021

IJERPH

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Land use policy is the driving factor influencing land use; however, little research has been conducted to identify the role of agricultural policy in influencing land cultivation and associated soil and soil organic carbon (SOC) losses. The aims of this study were to explore temporal changes in cultivated land, soil erosion, and SOC loss and to identify the role of land use policy. The present study was conducted using the revised universal soil loss equation by integrating remote sensing images from 1980, 1990, 2000, and 2017. The study found that cultivated land areas increased from 275.11 thousand km2 in 1980, to 300.03 thousand km2 in 2000, and to 344.16 thousand km2 in 2010, and then decreased by 326.94 thousand km2. The mean soil loss rates changed from 590.66 t·km−2·yr−1 in 1980 to 634.25 t·km−2·yr−1 in 2010, and then decreased to 495.66 t·km−2·yr−1 in 2017. Soil loss rate increased with increasing slope gradient. The changes in SOC loss rates demonstrated the same pattern as that of soil loss, with the largest loss rate of 728.27 kg·km−2·yr−1. These changes can be explained by changed land use policy and population growth. In future land use management, reasonable implementation of soil conservation measures should be undertaken to reduce soil and SOC losses in the black soil region of northeastern China.

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Section: Discussionmentioning

confidence: 99%

Changes in Cultivated Land Area and Associated Soil and SOC Losses in Northeastern China: The Role of Land Use Policies

Fang

2021

IJERPH

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“…In addition, the erosivity of 460-582.08 MJ•mm•(ha•h•year) -1 was obtained for the Anambra state (Egbueri et al, 2022). This was contrary to 3894-4510 MJ•mm•(ha•h•year) -1 obtained for Anambra (Fagbohun et al, 2016) or 3000-6000 MJ•mm•(ha•h•year) -1 for the southern parts of the country (Salako, 2010) and 743.1-830 MJ•mm•(ha•h•year) -1 for Enugu (Nwakor et al, 2015) or 956.03-1680.64 MJ•mm•(ha•h•year) -1 for Ebonyi State (Obiahu & Elias, 2020). Furthermore, the erosivity of 60-184 MJ•mm•(ha•h•year) -1 obtained for the southeast of Nigeria (Ezemonye & Emeribe, 2012) was also too low for the region.…”

Section: Applications Of the Rusle Model In Nigeriamentioning

confidence: 97%

“…However, some studies have given contrary findings in Nigeria. Some scholars have found lower values of soil loss across Nigeria such as the eastern part (Adeola et al, 2016;Ajibade et al, 2020;Egbueri et al, 2022;Nwakor et al, 2015;Obiahu & Elias, 2020) and northern part. Additionally, Anejionu et al (2013) show that erosion hotspots in Southeastern Nigeria vary greatly from Ebonyi to Abia States such that it is the highest in Ebonyi, Enugu, and Anambra followed by Abia but least in Imo State.…”

Section: Applications Of the Rusle Model In Nigeriamentioning

confidence: 99%

“…Soil erodibility values of 0.018 and 0.13–0.39 were found in Benue, the north‐central part (Songu et al., 2021), and the Northeast, respectively (Madu & Kundiri, 2018). Erodibility values in the southeast varying from 0.05 to 0.8 were found in Anambra State (Ajibade et al., 2020), 0.23–0.35 in Enugu (Nwakor et al., 2015), 0.03–0.04 in Imo State, and 0.47–0.63 in Afikpo, Ebonyi State (Obiahu & Elias, 2020).…”

Section: State Of Rusle Modeling In Nigeriamentioning

confidence: 99%

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A review of soil erosion modeling in Nigeria using the Revised Universal Soil Loss Equation model

Ezeh,

Igwe,

Asare

et al. 2024

Agrosystems Geosci & Env

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Soil erosion is a severe soil degradation problem that endangers the actualization of Sustainable Development Goals. It affects agricultural production by reducing soil fertility via topsoil translocation, leading to soil quality deterioration. A review of soil erosion modeling using the Revised Universal Soil Loss Equation (RUSLE) model shows that Nigeria lags behind other developing countries like Ethiopia despite the massive improvements provided by remote sensing and geographic information system (GIS) technologies. Fewer than 50 articles were found on the Google Scholar search engine that used the RUSLE model for empirical studies on soil erosion. Only four research articles were found on the ScienceDirect website. Additionally, there were differences in the findings from studies across Nigeria. Such disparities were due to differences in the approaches used to estimate key factors in the RUSLE model. Therefore, we recommend that the Ministries of Agriculture and Environment take soil erosion research seriously by adopting proactive soil conservation and management measures. Ensemble models can be used including machine learning approaches rather than focusing mainly on structural intervention. In addition, there should be a harmonized look‐up table for the cover management factor and conservation practices factor that fairly represent the various ecoclimatic regions. The limitations to the model's use are highlighted, and a way forward is suggested.

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“…Furthermore, a quantitative assessment showing the ecosystem service value changes is rarely assessed, mostly covering the whole country, including provinces, regions, and towns [ 33 ]. In addition to examining the changing characteristics of LULC in Madagascar, there are no local or national estimates of these consequences which is essential information required in this kind of study [ 34 ]. Therefore, this study represents the first data about linking land use change to loss/gain in ecosystem services in Madagascar island.…”

Section: Introductionmentioning

confidence: 99%

Response of Ecosystem Services to Land Use Change in Madagascar Island, Africa: A Multi-Scale Perspective

Tiandraza

et al. 2023

IJERPH

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“Land Use and Land Cover Change (LULCC)” is increasingly being affected by ecosystem services value. LULCC patterns have been subjected to significant changes over time, primarily due to an ever-increasing population. It is rare to attempt to analyze the influence of such changes on a large variety of ecosystem benefits in Madagascar island. The economic value of ecosystem services in Madagascar island is evaluated throughout the period from 2000 to 2019. The expansion of the human population affects the changing value of ecosystem services directly. The PROBA-V SR time series 300 m spatial resolution cover of land datasets from the “Climate Change Initiative of the European Space Agency (ESA)” were used to measure the values of ecosystem activities and the changes in those values caused by land use. A value transfer method was used to evaluate the value of ecosystem services to land use changes on Madagascar island. The findings show that from 2000 to 2019, at the annual rate of 2.17 percent, Madagascar island’s ecosystem service value (ESV) grew to 6.99 billion US dollars. The components that greatly contributed to the total change of ESV were waste treatment, genetic resources, food production, and habitat/refugia. These components in 2000 contributed 21.27%, 20.20%, 17.38%, and 13.80% of the total ESV, and 22.55%, 19.76%, 17.29%, and 13.78% of the total ESV in 2019, respectively. Furthermore, it was found that there was a great change in LULCC. From 2000 to 2019, bare land, built-up land, cultivated land, savannah, and wetland increased while other LULCC types decreased. The sensitivity coefficient ranged from 0.649 to 1.000, <1, with forestland registering the highest values. Wetland is in the second position for the most important land cover category in Madagascar, considering the total value of the ecosystem. The value of ecosystem benefits per unit of the land area was higher on cultivated land, despite the relatively low fraction of cultivated land area across these eras. The sensitivity indices of seven land types from 2000 to 2019 were mapped to understand better the geographical distribution patterns of ESV’s “equivalent value coefficient” (VC) across various land uses. It is suggested that the ESV should be included in Madagascar’s government land-use plan to manage it effectively and efficiently with fewer negative effects on the ecosystem.

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Effect of land use land cover changes on the rate of soil erosion in the Upper Eyiohia river catchment of Afikpo North Area, Nigeria

Cited by 27 publications

References 21 publications

Changes in Cultivated Land Area and Associated Soil and SOC Losses in Northeastern China: The Role of Land Use Policies

Changes in Cultivated Land Area and Associated Soil and SOC Losses in Northeastern China: The Role of Land Use Policies

A review of soil erosion modeling in Nigeria using the Revised Universal Soil Loss Equation model

Response of Ecosystem Services to Land Use Change in Madagascar Island, Africa: A Multi-Scale Perspective

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