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Drainage of paved and unpaved roads has been implicated as a major contributor of overland flow and erosion in mountainous landscapes. Despite this, few watershed models include or have tested for the effect roads have on discharge and sediment loads. Though having a model is an important step, its proper application and attention to distinct landscape features is even more important. This study focuses on developing a module for drainage from a road and tests it on a nested watershed (Shanko Bahir) within a larger previously studied site (Debre Mawi) that receives overland flow contributions from a highly compacted layer of soil on an unpaved road surface. Shanko Bahir experiences a sub-humid monsoonal climate and was assessed for the rainy seasons of 2010, 2011, and 2012. The model chosen is the Parameter Efficient Distributed (PED) model, previously used where saturation-excess overland flow heavily influences discharge and sediment concentration variation, though infiltration-excess occasionally occurs. Since overland flow on unpaved surfaces emulates Hortonian flow, an adjustment to the PED model (the developed module) advances possible incorporation of both flow regimes. The modification resulted in similar modeling performance as previous studies in the Blue Nile Basin on a daily basis (NSE = 0.67 for discharge and 0.71 for sediment concentrations). Furthermore, the road while occupying a small proportion of the sub-watershed (11%) contributed importantly to the early discharge and sediment transport events demonstrating the effect of roads especially on sediment concentrations. Considerations for the dynamic erodibility of the road improved sediment concentration simulation further (NSE = 0.75). The results show that this PED modeling framework can be adjusted to include unpaved compacted surfaces to give reasonable results, but more work is needed to account for contributions from gullies, which can cause high influxes of sediment.

Abstract: Worldwide, soil erosion has greatly decreased agricultural productivity and continues unabatedly despite decades of developing sustainability and soil conservation strategies. Current strategies need integrated interdisciplinary perspectives to develop more effective measures, especially in degrading mountainous landscapes where rising sediment concentrations persist. By comparing spatio‐temporal field observations and community perceptions with the Geographic Information System (GIS)‐based universal soil loss equation (USLE), this study critically examined theorized erosion patterns (by USLE) in a degraded landscape (Shanko Bahir, Ethiopia) to improve soil conservation strategy development. Daily hydro‐sedimentological data (showing 792 mm of rainfall leading to 3·2 Mg ha−1 y−1 of sediment yield) revealed mild but variable erosion patterns in 2012. Overlooking hydrology hindered the USLE's suitability for conservation planning. For instance, the median infiltration rate (33 mm h−1) was rarely exceeded (3·5% of events), meaning runoff‐induced erosion risk were not well predicted spatio‐temporally by the USLE R‐factor. Conversely, heterogeneous local perspectives explicitly considered accumulated runoff, saturation (“the water at the top level rests on the bottom”), fertility, and gullies as drivers of erosion (“black soil breaks and forms gorges”). Additionally, they designated steeper mono‐cropped lands as at risk (incidentally also highlighted by USLE). Observational evidence showed steeper midslope areas decreasing in topsoil depth by 14 mm, flatter downslope areas by 0·8 mm, and the mild upslope areas increasing 2 mm. Operationalizing effective soil conservation strategies will require expanding beyond (USLE‐based) technical knowledge to incorporate local stakeholders and consider the main hydrological processes causing erosion in sub‐humid mountainous landscapes: saturated pathways, downslope saturation, subsurface flow, and gully formation. Copyright © 2017 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Experimental research in the Ethiopian highlands found that saturation excess induced runoff and erosion are common in the sub-humid conditions. Because most erosion simulation models applied in the highlands are based on infiltration excess, we, as an alternative, developed the Parameter Efficient Distributed (PED) model, which can simulate water and sediment fluxes in landscapes with saturation excess runoff. The PED model has previously only been tested at the outlet of a watershed and not for distributed runoff and sediment concentration within the watershed. In this study, we compare the distributed storm runoff and sediment concentration of the PED model against collected data in the 95-ha Debre Mawi watershed and three of its nested sub-watersheds for the 2010 and 2011 rainy seasons. In the PED model framework, the hydrology of the watershed is divided between infiltrating and runoff zones, with erosion only taking place from two surface runoff zones. Daily storm runoff and sediment concentration values, ranging from 0.5 to over 30 mm and from 0.1 to 35 g l−1, respectively, were well simulated. The Nash Sutcliffe efficiency values for the daily storm runoff for outlet and sub-watersheds ranged from 0.66 to 0.82, and the Nash-Sutcliffe efficiency for daily sediment concentrations were greater than 0.78. Furthermore, the model uses realistic fractional areas for surface and subsurface flow contributions, for example between saturated areas (15%), degraded areas (30%) and permeable areas (55%) at the main outlet, while close similarity was found for the remaining hydrology and erosion parameter values. One exception occurred for the distinctly greater transport limited parameter at the actively gullying lower part of the watershed. The results suggest that the model based on saturation excess provides a good representation of the observed spatially distributed runoff and sediment concentrations within a watershed by modelling the bottom lands (as opposed to the uplands) as the dominant contributor of the runoff and sediment load. Copyright © 2014 John Wiley & Sons, Ltd. [ABSTRACT FROM AUTHOR]

Excessive runoff and soil erosion in the upper Blue Nile Basin poses a threat that has attracted the attention of the Ethiopian government because of the serious on-site effects in addition to downstream effects, such as the siltation of water harvesting structures and reservoirs. The objective of the study was to evaluate and recommend effective biophysical soil and water conservation measure(s) in the Debre Mewi watershed, about 30 km south of the Lake Tana. Six conservation measures were evaluated for their effects on runoff, soil loss, and forage yield using runoff plots. There was a significant difference between treatments for both runoff and soil loss. The four-year average annual soil loss in the different plots ranged from 26 to 71 t ha −1 , and total runoff ranged from 180 to 302 mm, while annual rainfall varied between 854 mm in 2008 and 1247 mm in 2011. Soil bund combined with elephant grass had the lowest runoff and soil loss as compared to the other treatments, whereas the untreated control plot had the highest for both parameters. As an additional benefit, 2.8 and 0.7 t ha −1 year −1 of dried forage was obtained from elephant and local grasses, respectively. Furthermore, it was found that soil bund combined with Tephrosia increased soil organic matter by 13% compared to the control plot. Soil bund efficiency was significantly enhanced by combining them with biological measures and improved farmers’ perception of soil and water conservation measures. [ABSTRACT FROM AUTHOR]

Information about the spatial distribution of soil properties is necessary for natural resources modeling; however, the cost of soil surveys limits the development of high-resolution soil maps. The objective of this study was to provide an approach for predicting soil attributes. Topographic attributes and the normalized difference vegetation index (NDVI) were used to provide information about the spatial distribution of soil properties using clustering and statistical techniques for the 56 km² Gumara-Maksegnit watershed in Ethiopia. Multiple linear regression models implemented within classified subwatersheds explained 6-85% of the variations in soil depth, texture, organic matter, bulk density, pH, total nitrogen, available phosphorous, and stone content. The prediction model was favorably comparable with the interpolation using the inverse distance weighted algorithm. The use of satellite images improved the prediction. The soil depth prediction accuracy dropped gradually from 98% when 180 field observations were used to 65% using only 25 field observations. Soil attributes were predicted with acceptable accuracy even with a low density of observations (1-2 observations/2 km²). This is because the model utilizes topographic and satellite data to support the statistical prediction of soil properties between two observations. Hence, the use of DEM and remote sensing with minimum field data provides an alternative source of spatially continuous soil attributes. [ABSTRACT FROM AUTHOR]