Lulseged Tamene

Mapping Soil Properties of Africa at 250 m Resolution: Random Forests Significantly Improve Current Predictions

80% of arable land in Africa has low soil fertility and suffers from physical soil problems. Additionally, significant amounts of nutrients are lost every year due to unsustainable soil management practices. This is partially the result of insufficient use of soil management knowledge. To help bridge the soil information gap in Africa, the Africa Soil Information Service (AfSIS) project was established in 2008. Over the period 2008–2014, the AfSIS project compiled two point data sets: the Africa Soil Profiles (legacy) database and the AfSIS Sentinel Site database. These data sets contain over 28 thousand sampling locations and represent the most comprehensive soil sample data sets of the African continent to date. Utilizing these point data sets in combination with a large number of covariates, we have generated a series of spatial predictions of soil properties relevant to the agricultural management—organic carbon, pH, sand, silt and clay fractions, bulk density, cation-exchange capacity, total nitrogen, exchangeable acidity, Al content and exchangeable bases (Ca, K, Mg, Na). We specifically investigate differences between two predictive approaches: random forests and linear regression. Results of 5-fold cross-validation demonstrate that the random forests algorithm consistently outperforms the linear regression algorithm, with average decreases of 15–75% in Root Mean Squared Error (RMSE) across soil properties and depths. Fitting and running random forests models takes an order of magnitude more time and the modelling success is sensitive to artifacts in the input data, but as long as quality-controlled point data are provided, an increase in soil mapping accuracy can be expected. Results also indicate that globally predicted soil classes (USDA Soil Taxonomy, especially Alfisols and Mollisols) help improve continental scale soil property mapping, and are among the most important predictors. This indicates a promising potential for transferring pedological knowledge from data rich countries to countries with limited soil data.

Soil Erosion Studies in Northern Ethiopia

Soil erosion is one of the biggest global environmental problems resulting in both on-site and off-site effects. The economic implication of soil erosion is more serious in developing countries because of lack of capacity to cope with it and also to replace lost nutrients. These countries have also high population growth which leads to intensified use of already stressed resources and expansion of production to marginal and fragile lands. Such processes aggravate erosion and productivity declines, resulting in a population–poverty–land degradation cycle. Rapid population growth, cultivation on steep slopes, clearing of vegetation, and overgrazing are the main factors that accelerate soil erosion in Ethiopia. The annual rate of soil loss in the country is higher than the annual rate of soil formation rate. Annually, Ethiopia losses over 1.5 billion tons of topsoil from the highlands to erosion which could have added about 1.5 million tons of grain to the country’s harvest. This indicates that soil erosion is a very serous threat to food security of people and requires urgent management intervention. To circumvent the impacts of erosion, it is important to know the severity of the problem and the main controlling factors. Since different portions of the landscape vary in sensitivity to erosion due to differences in their geomorphological, geological, and vegetation attributes, it is also necessary to identify high erosion risk areas in order to plan site-specific management interventions. Depending on the prevailing erosion processes and controlling factors, the efficiency of soil conservation measures may vary. This calls for the assessment of the soil conservation potential of different management practices. This study was conducted in northern Ethiopia in order to assess rates of soil loss, investigate controlling factors, and analyze spatial patterns and management alternatives. Section 5.1 reviews the impacts of soil erosion at global and regional scale. Section 5.2 discusses the magnitude of soil erosion in northern Ethiopia based on reservoir survey and Section 5.3 explores its major determinant factors. Section 5.4 applies soil erosion models to identify high erosion risk areas for targeted management intervention and Section 5.5 simulates the potentials of different land management/soil conservation techniques in reducing soil loss of selected catchments. Section 5.6 summarizes the major findings of the study. A.K. Braimoh and P.L.G. Vlek (eds.), Land Use and Soil Resources. 73

Soil Erosion Prediction Using Morgan-Morgan-Finney Model in a GIS Environment in Northern Ethiopia Catchment

Even though scientific information on spatial distribution of hydrophysical parameters is critical for understanding erosion processes and designing suitable technologies, little is known in Geographical Information System (GIS) application in developing spatial hydrophysical data inputs and their application in Morgan-Morgan-Finney (MMF) erosion model. This study was aimed to derive spatial distribution of hydrophysical parameters and apply them in the Morgan-Morgan-Finney (MMF) model for estimating soil erosion in the Mai-Negus catchment, northern Ethiopia. Major data input for the model include climate, topography, land use, and soil data. This study demonstrated using MMF model that the rate of soil detachment varied from 170 t ha−1 y−1, whereas the soil transport capacity of overland flow (TC) ranged from 5 t ha−1 y−1 to >42 t ha−1 y−1. The average soil loss estimated by TC using MMF model at catchment level was 26 t ha−1 y−1. In most parts of the catchment (>80%), the model predicted soil loss rates higher than the maximum tolerable rate (18 t ha−1 y−1) estimated for Ethiopia. Hence, introducing appropriate interventions based on the erosion severity predicted by MMF model in the catchment is crucial for sustainable natural resources management.

Modelling soil erosion response to sustainable landscape management scenarios in the Mo River Basin (Togo,West Africa)

The rural landscapes in Central Togo are experiencing severe land degradation, including soil erosion. However, spatially distributed information has scarcely been produced to identify the effects of landscape pattern dynamics on ecosystem services, especially the soil erosion control. In addition, relevant information for sustainable land and soil conservation is still lacking at watershed level. On this basis, using the LAndscape Management and Planning Tool for the Mo River basin (LAMPT_Mo), we (1) modelled soil erosion patterns in relation with land use/cover change (LUCC), land protection regime, and landforms, and (2) examined the efficiency of landscape redesign options on soil erosion amounts at basin scale. We found that Simulated historical net soil loss (NSL) for the Mo basin were approximately 26, 23, 27, and 44t/ha/yr, for 1972, 1987, 2000, and 2014, respectively. These simulated NSLs were higher than the tolerable soil loss limits for the Tropics. Steep slopes (≥15°), poorly covered lands (croplands and savannas), and riversides (distances ≤100m) are critical areas of sediment sources. The local appraisal of soil loss was in line with the simulated outputs even though quantification was not accounted for when dealing with rural illiterate people. Furthermore, results showed that the examined management measures, such as controlling the identified erosion hotspots through land protective measures, could help reduce the NSL up to 70%, to values closer to the tolerable limits for the Tropics. The model implementation in the basin showed insights for identifying erosion hotspots and targeting soil conservation planning and landscape restoration measures.

Fostering Food Security and Climate Resilience Through Integrated Landscape Restoration Practices and Rainwater Harvesting/Management in Arid and Semi-arid Areas of Ethiopia

Land degradation and rainfall variability are severe problems affecting sub-Saharan Africa. Ethiopia is one of the countries in the region which is hugely impacted by these processes. To circumvent the impacts of these problems, the country has been involved in implementing various landscape restoration and water harvesting (LRWH) practices since the 1970s. However, the success of these efforts has been limited especially at the earlier periods. The major reasons include the top-down approach followed to implementation of the LRWH practices, mismatch between landscape characteristics and recommended LRWH options, lack of appropriate monitoring and maintenance of schemes, and low adoption rate by communities due to limited economic return from the interventions. Despite these bottlenecks, however, various achievements have been recorded in some parts of the country. In those areas, the interventions have significantly changed the environmental and socio-economic conditions of the areas. Understanding the key drivers that promoted successful restoration of landscapes and water resources could help in designing appropriate technologies and their implementation mechanisms. This study aims to assess the biophysical and socio-economic conditions that need to be fulfilled for LRWH technologies to be adopted and be effective and to enhance resilience to climate/rainfall variability. We critically reviewed five successful cases in Tigray region to understand the critical elements to be considered when identifying, introducing and managing LRWH options. The results show that promotion of integrated management practices considering the whole landscape continuum is essential for LRWH options to succeed and create resilience to climate variability. It is also observed that interventions should be designed considering both agro-ecological, land use/cover, soil, geomorphological, hydrogeological, socio-economic and institutional conditions of specific landscapes/watersheds.

Assessing Soil Properties and Landforms in the Mai-Negus Catchment, Northern Ethiopia

Abstract Soil degradation is a serious environmental problem in Ethiopia. However, little information is documented on indicators such as variations in soil properties across different landforms in a catchment. This study was aimed to assess soil properties and their changes across sites with different erosion statuses, and identify landscape positions that require prior management attention in the Mai-Negus catchment, northern Ethiopia. Three types of erosion-status sites (stable, eroding and aggrading) were identified using reconnaissance surveys, and then the corresponding soil samples were collected and analyzed. The major soil properties were significantly varied (P ≤ 0.05) among the three erosion-status sites. The highest soil pH, organic carbon, total nitrogen, cation exchange capacity, iron and zinc were recorded from the aggrading sites in the reservoir and valley landforms of the study catchment. A higher bulk density was generally recorded in the eroding sites, whereas a lower value was observed in the aggrading sites. The highest sand content was observed in the eroding sites of the mountain followed by the central ridge landform. The paired mean difference and the correlation matrix of most soil properties between the different erosion statuses also showed significant differences. About 95% of the erosion-status sites were correctly classified by the discriminant function, indicating that the field survey-based classification was acceptable for decision making. On the basis of this study, suitable interventions should thus be introduced to the prioritized landforms, which are the mountain and central ridge, and eroding sites with severely degraded soil properties across the catchment.