Analysis of Soil Erodibility Factor for Hydrologic Processes in Kereke Watershed, North Central Nigeria

: Soil erodibility factor plays essential role in determining how susceptible soil is to hydrological processes such as detachment and removal by rainfall and runoff that could influence soil erosion and sediment entrainment by flooding in an area. This paper therefore determined the erodibility k-value of soil in the Kereke watershed with the purpose of assessing its susceptibility to hydrological processes. Data was collected on some soil properties such as soil texture, soil structure, soil organic matter content, soil carbon content, soil porosity, soil bulk density, soil moisture content and soil erodibility k-value. The systematic sampling procedure was used to select thirty-two settlements which served as catchment areas for data collection; from which thirty-two soil samples were collected for analysis. Tables and graph were used to present the data, and percentages were used to depict variations in the data set. Results of the study shows that the soil samples have high percent sand particles (71.6%), moderate amount of clay particles (15.7%), silt(12.7%), organic carbon (0.6%), organic matter (1.1%), bulk density (1.4 gcm-3 ), porosity (45.2%), moisture content (14.0%) and low soil erodibility k-value of 0.018. The soil erodibility k-value in the study area was considered to be low, and therefore the soils are moderately erodible. This probably accounts for the moderate intensity of soil erosion channels and entrained sediments by flooding observed in the study area. It is therefore recommended that soil management practices should be encouraged by farmers especially planting of cover crops, shifting cultivation and fallowing system. This will allow nutrients gain and improved bulk density to limit soil erodibility capacity and good soil management in the area. Key words: Soil erodibility factor, hydrological processes, Kereke watershed, North Central Nigeria

Use of Visible and Near-Infrared Reflectance Spectroscopy Models to Determine Soil Erodibility Factor (K) in an Ecologically Restored Watershed

This study aimed to assess the ability of using visible and near-infrared reflectance (Vis–NIR) spectroscopy to quantify soil erodibility factor (K) rapidly in an ecologically restored watershed. To achieve this goal, we explored the performance and transferability of the developed spectral models in multiple land-use types: woodland, shrubland, terrace, and slope farmland (the first two types are natural land and the latter two are cultivated land). Subsequently, we developed an improved approach by combining spectral data with related topographic variables (i.e., elevation, watershed location, slope height, and normalized height) to estimate K. The results indicate that the calibrated spectral model using total samples could estimate K factor effectively (R2CV = 0.71, RMSECV = 0.0030 Mg h Mj−1 mm−1, and RPDCV = 1.84). When predicting K in the new samples, models performed well in natural land soils (R2P = 0.74, RPDP = 1.93) but failed in cultivated land soils (R2P = 0.24, RPDP = 0.99). Furthermore, the developed models showed low transferability between the natural and cultivated land datasets. The results also indicate that the combination of spectral data with topographic variables could slightly increase the accuracies of K estimation in total and natural land datasets but did not work for cultivated land samples. This study demonstrated that the Vis–NIR spectroscopy could be used as an effective method in predicting K. However, the predictability and transferability of the calibrated models were land-use type dependent. Our study also revealed that the coupling of spectrum and environmental variable is an effective improvement of K estimation in natural landscape region.

Estimation of Soil Erosion in the Chaohu Lake Basin through Modified Soil Erodibility Combined with Gravel Content in the RUSLE Model

It is generally acknowledged that soil erosion has become one of the greatest global threats to the human–environment system. Although the Revised Universal Soil Loss Equation (RUSLE) has been widely used for soil erosion estimation, the algorithm for calculating soil erodibility factor (K) in this equation remains limited, particularly in the context of China, which features highly diverse soil types. In order to address the problem, a modified algorithm describing the piecewise function of gravel content and relative soil erosion was used for the first time to modify the soil erodibility factor, because it has been proven that gravel content has an important effect on soil erosion. The Chaohu Lake Basin (CLB) in East China was used as an example to assess whether our proposal can improve the accuracy of soil erodibility calculation and soil erosion estimation compared with measured data. Results show that (1) taking gravel content into account helps to improve the calculation of soil erodibility and soil erosion estimation due to its protection to topsoil; (2) the overall soil erosion in the CLB was low (1.78 Mg·ha−1·year−1) the majority of which was slight erosion (accounting for 85.6%) and no extremely severe erosion; and (3) inappropriate land use such as steep slope reclamation and excessive vegetation destruction are the main reasons for soil erosion of the CLB. Our study will contribute to decision-makers to develop soil and water conservation policies.

Estimation of the soil erodibility factor of a peri-urban catchment by group method of data handling and enhanced particle swarm optimization method

Soil erosion has become a major deterrent in any watershed management program. The erodibility of the soil from the river banks has degraded watersheds all over the world. That is why in any watershed development programmers’ erodibility of soil becomes a significant design parameter. However, there is lack of efficient simulation model for estimation of soil erosion. The existing models are location sensitive and mostly empirical nature in the present investigation, the authors tried to estimate the soil erodibility factor of the USLE method with the help of Enhanced PSO. The data for development of model is generated by Normalized Design of Experiment method which assumes that maximum and minimum value can be represented by I and O respectively. The same model was developed with the help of GMDH also. As per the model matrices of GMDH model shows better reliability. The selected model was applied to predict soil erodibility factor for 21 no’s of location in west Tripura region. From the prediction and comparison with the actual data it was found that the selected models have an accuracy of 99.8% in predicted model and 89.8% in case study.

Influence of soil specimen preparation on results of its organic matter content laboratory determination

Paper deals with influence of soil specimen preparation on values of its organic matter content, determined by laboratory tests. Totally 54 specimens of soils CG, CL, CI and CH from Lipnik, Międzyrzecze and Nieboczowy, Poland were tested. To obtain values of soils organic matter content, the oxidation method introduced in the Polish Standard PN-88/B-04481 was applied. The tests were carried out for particles smaller than 2 mm. For every sample, 3 specimens (every with a mass about 10 g of dry soil) were prepared by such a way that the first one is taken from whole sample after drying about 200 g of wet soil. The second and third one were taken from 50 g of remaining sample mass after taking the first one. As an oxidizing agent, the 30% hydrogen peroxide solution was used. The results show that values of organic matter content of soils range from 0.03% to 2.74%. The largest difference in values of organic matter content, caused by specimen preparation, was 0.38% (absolute difference), corresponding to relative difference 15.86%. The smallest difference was null. Mentioned difference causes negligible difference in soil erodibility factor K hence negligible difference in soil erosion rate in mentioned locations.