Soil loss estimation and severity mapping using RUSLE model and GIS: a case study in Megech Watershed, Ethiopia

AbstractBackground: Soil erosion is the most serious problem that affects economic development, food security, and ecosystem services which is the main concern in Ethiopia. This study focused on quantifying soil erosion rate and severity mapping of the Megech watershed for effective planning and decision-making processes to implement protection measures. The RUSLE model integrated with ArcGIS software was used to conduct the present study. The six RUSLE model parameters: erosivity, erodibility, slope length and steepness, cover management, and erosion control practices were used as input parameters to predict the average annual soil loss and identify erosion hotspots in the watershed. Results: The RUSLE estimated 1,399,210 tons yr-1 total soil loss from the watershed with a mean annual soil loss of 32.84 tons ha-1yr-1. The soil erosion rate was varied from 0.08 to greater than 500 tons ha-1yr-1. A severity map with seven severity classes was created for 27 sub-watersheds: low (below 10), moderate (10-20), high (20-30), very high (30-35), severe (35-40), very severe (40-45) and extremely severe (above 45) in which the values are in tons ha-1yr-1. The area coverage was 6.5%, 11.1%, 8.7%, 22%, 30.9%, 13.4%, and 7.4% for low, moderate, high, very high, severe, very severe, and extremely severe erosion classes respectively. Conclusion: About 82 % of the watershed was found in more than the high-risk category which reflects the need for immediate land management action. This paper could be important for decision-makers to prioritize critical erosion hotspot areas for comprehensive and sustainable management of the watershed.

Application of Artificial Intelligence for Predicting Erosion of Biochar Amended Soils

Recently, incentives have been provided in developed countries by the government for commercial production of biochar for soil treatment, and other construction uses with an aim to reduce a significant amount of carbon emissions by 2030. Biochar is an important material for the development of circular economy. This study aims to develop a simple Artificial Neural Network (ANN) based model to predict erosion of biochar amended soils (BAS) under varying conditions (slope length, slope gradient, rainfall rate, degree of compaction (DoC), and percentage of biochar amendments). Accordingly, a model has been developed to estimate the total erosion rate and total water flow rate as a function of the above conditions. The model was developed based on available data from flume experiments. Based on ANN modelling results, it was observed that slope length was the most important factor in determining total erosion rate, followed by slope gradient, DoC, and percentage of biochar amendment. The percentage of biochar amendment was a leading factor in the total water flow rate determination as compared to other factors. It was also found that the reduction in erosion is relatively minimal during an increase in slope length up to 1.55 m, reducing sharply beyond that. At a slope length of 2 m, erosion is found to be reduced by 33% (i.e., 2.6 to 1.75), whereas the total flow rate decreases linearly from 1250 mL/m2/min to 790 mL/m2/min. The ANN model developed shows that soil biochar composite (SBC) with 5% biochar amendment gave the best results in reducing soil erosion. This study can be a helpful tool in providing preliminary guidelines for using biochar in erosion control.

Soil Erosion Assessment Using the RUSLE Model and Geospatial Techniques (Remote Sensing and GIS) in South-Central Niger (Maradi Region)

A systematic method, incorporating the revised universal soil loss equation model (RUSLE), remote sensing, and the geographic information system (GIS), was used to estimate soil erosion potential and potential area in the Maradi region of south-central Niger. The spatial trend of seasonal soil erosion was obtained by integrating remote sensing environmental variables into a grid-based GIS method. RUSLE is the most commonly used method for estimating soil erosion, and its input variables, such as rainfall erosivity, soil erodibility, slope length and steepness, cover management, and conservation practices, vary greatly over space. These factors were calculated to determine their influence on average soil erosion in the region. An estimated potential mean annual soil loss of 472.4 t/ac/year, based on RUSLE, was determined for the study area. The potential erosion rates varied from 14.8 to 944.9 t/ac/year. The most eroded areas were identified in central and west-southern areas, with erosion rates ranging from 237.1 to 944.9 t/ac/year. The spatial erosion maps can serve as a useful reference for deriving land planning and management strategies and provide the opportunity to develop a decision plan for soil erosion prevention and control in south-central Niger.

Assessing the Effect of Landuse/Land Cover (1986-2020) on Soil Loss in Alluvium Geologic Formation Using Geospatial Technology in Southern Nigeria

The occurrence of soil loss is a continuous process and occurs spatially across the earth’s surface. The study of soil loss is a necessity for proper understanding of the processes and the rate of soil loss for conservational purpose. Landsat Thematic Mapper (TM)/Enhanced Thematic Mapper Plus (ETM+)/Operational Land Imager (OLI) image data was acquired for 1986, 2003 and 2020 were used to derive the C factor of the RUSLE model while other factors of the model were kept fixed for the years considering their inability to change easily. The RUSLE model was used to determine the trend of the soil loss on the alluvium geologic formation considering their land use/land cover changes for 1986, 2003 and 2020. The rainfall erosivity of the study area had an average of 8201.45MJmmha-1h-1yr-1. The soil erodibility index of the soils obtained from Alluvium had an average of 0.150tons MJ-1 hmm-1. The slope length and steepness factor of the study area range from 0 to 2.574. the crop cover factor of for 1986 range from 0.52 to 0.87, 2003 range from 0.52 to 0.87 and 2020 range from 0.62 to 0.92. No active field conservation was found out within the study area as described by Wischmeier and Smith. The results obtained show that 1986, 2003 and 2020 had a soil loss of 1966.3, 2167.85 and 3361.14 tonha-1yr-1 respectively. The results show that the study area is experiencing an increased trend of soil loss. This result can serve as guide into understanding the past and current rate of soil loss for soil resource planning and management

Associations between the quality of street space and the attributes of the built environment using large volumes of street view pictures

In this study, we focus on the quality of street space which has attracted high attentions. We discover associations between the quality of street space and built environment attributes through an ordered logistic model using massive street view pictures (SVPs) and data on street location, form, function and attributes. Before ascertain which built environment factors influence the quality of street space, we checked the concordance of the experts’ scores, as well as correlations between different dimensions through Kappa analysis and drew the distribution map of street space quality. We found that the value of intersection over union is 85.61% for scoring the street space quality by different people. The spatial quality of more than 75% streets are in the middle level with no obvious polarisation observed in the central area of Qingdao. In addition, for street quality index, all variables are statistically significant. The sequence is as follows: near-line rate > D/H ratio > slope > length of street > distance to administrative center > POIs diversity. The D/H ratio, near-line rate, slope length of street, distance to administrative center and POIs diversity have various associations on every dimension of street quality. They can prove useful for drafting more appropriate policy measures aimed at improving street quality.

Water Erosion in the Moulouya Watershed and its Impact on Dams' Siltation (Eastern Morocco)

The Moulouya watershed presents high risks of water erosion. The dams built on this river lose each year, by siltation, a volume of water of about 10 M m3 (Lahlou, 1994). This worrying rate shows that water erosion can hinder the socio-economic development of the basin if soil protection and siltation measures are not taken. This study defines the areas most threatened by water erosion to protect them as a priority. Using a GIS and the Universal Earth Loss Equation (USLE), we mapped soil losses. The adopted model determines soil loss from erosivity of rainfall, soil erodibility, inclination and slope length, soil cover, and erosion control practices. The possible origins of the deposits alluviating the dams are related to the products of alteration of the Secondary's carbonate formations and the Tertiary and Quaternary formations. The modalities of the transport of deposits of banks of the network of Moulouya are mainly by a suspension. The specific degradation in the Moulouya watershed is estimated at 214 t/km2/year. Precipitation intensity, steep slopes and deforestation are responsible for these losses.

Soil loss vulnerability: the case study of Aghien lagoon watershed outskirts Abidjan city (Côte d'Ivoire)

Aghien lagoon is a source of fresh water outskirts of Abidjan city in the south of Côte d'Ivoire. For a better understanding of its functioning, we proposed to estimate its main tributaries (Bété and Djibi) soil loss during 2016 and 2017 as part of our research activities in the lagoon watershed in order to evaluate its vulnerability face to soil loss. The methodological approach is based on USLE (Universal Soil Loss Equation) incorporated into GIS (Geographic Information Systems). This equation takes into account five key factors: the erosivity of rainfall, the soil erodibility, the topographic factor integrating slope length and steepness, the cover-management factor and the support practice factor. The combination of these factors made it possible to obtain soil loss maps of the lagoon main tributaries. The analysis of them revealed that soil loss varying mostly between 0 and 250 t ha−1 yr−1 in 2016 and 2017. With regard to the two years, the vulnerability of the lagoon face to soil loss is “low” category. In fact, the soil loss class ranging from 0 to 20 t ha−1 yr−1 occupies more than 60 % of the two sub-basins area in 2016. This trend increased in 2017 with equivalent of 71 % of the area. On the over hand, the “very high” vulnerability ranging from 250 to 1050 t ha−1 yr−1, occupied in 2016, only 0.01 % of the area. In 2017, this category of vulnerability increased in intensity, occupying 0.05 % of it. Ultimately, the increasing observed in 2016 and 2017 seems to be related to annual rainfall of respectively 1553 and 2198 mm. The case study of Aghien lagoon, soil loss vulnerability can be improved by taking account a long time series of rainfall and land use data.

Study on hydrodynamic characteristics and influence factors of asphalt pavement runoff

A hydrodynamic model is developed for rainfall runoff on asphalt pavement using two-dimensional shallow water equations. A simple yet precise expression is presented to compute flow velocity in order to alleviate the problems associated with numerical instabilities due to small water depths of thin sheet flow. The developed model performed well against measured data and numerical results in two segments. Then, the model is applied to study the influence of highway horizontal alignment, drainage manner, rainfall pattern, surface roughness and geometric parameters on pavement runoff. The results demonstrate that: (i) the influence of highway horizontal alignment on pavement runoff is nonsignificant, while that of drainage manner and the pavement surface roughness is significant. Great differences are observed in flow depth under concentrated drainage and overflow drainage conditions, especially in the area beyond 6 m away from the highway center axis; (ii) remarkable differences in maximum flow depth and peak runoff are presented under uneven and even rainfall conditions, while no great differences are found under three uneven rainfall conditions (front type, center front type and back front type); (iii) the sensitivity of the geometric parameters to the maximum flow depth from strong to weak is cross slope, width, slope length, and longitudinal slope under overflow drainage condition; while that is width, slope length, longitudinal slope and cross slope under concentrated drainage condition.