VERTICAL ACCURACY ASSESSMENT OF THE PROCESSED SRTM DATA FOR THE BRAZILIAN TERRITORY

This research aims to determine the vertical accuracy of the Interferometric Digital Elevation Model (DEM) obtained from the processed Shuttle Radar Topographic Mission (SRTM) data. The research compared the SRTM-GL1 (Shuttle Radar Topographic Mission-Global 1) with 30-meter resolution and the following 90-meter resolution models: (a) EMBRAPA; (b) Hydrological data and maps based on Shuttle Elevation Derivatives at multiple Scales (HydroSHEDS) (HydroSHEDS), provided by the United States Geological Survey (USGS); (c) Consultative Group for International Agricultural Research-Consortium for Spatial Information (CGIAR-CSI); and (d) Jonathan de Ferranti. The accuracy analysis considered the diverse Brazilian regions, adopting 1,087 field points from the Global Navigation Satellite System (GNSS) trackers or topography methods. The Jonathan de Ferranti model achieved the best accuracy with RMSE of 9.61m among the 90-meter resolution models. Most SRTM models at 1:100,000 scale reached Grade A of the Cartographic Accuracy Standard. However, the accuracy at the 1: 50,000 scale did not achieve the same performance. SRTM errors are linearly related to slope and the most significant errors always occur in forest areas. The 30-meter resolution SRTM showed an accuracy of around 10% better (RMSE of 8.52m) than the model of Jonathan de Ferranti with 90-meter resolution (RMSE of 9.61m)

Impacts of DEM resolution and area threshold value uncertainty on the drainage network derived using SWAT

Many hydrological algorithms have been developed to automatically extract drainage networks from DEM, and the D8 algorithm is widely used worldwide to delineate drainage networks and catchments. The simulation accuracy of the SWAT model depends on characteristics of the watershed, and previous studies of DEM resolution and its impacts on drainage network extraction have not generally considered the effects of resolution and threshold value on uncertainty. In order to assess the influence of different DEM resolutions and drainage threshold values on drainage network extraction using the SWAT model, 10 basic watershed regions in China were chosen as case studies to analyse the relationship between extracted watershed parameters and the threshold value. SRTM DEM data at 3 different resolutions were used in this study, and regression analysis for DEM resolution, threshold value and extraction effects was done. The results show that DEM resolution influences the selected flow accumulation threshold value; the suitable flow accumulation threshold value increases as the DEM resolution increases, and shows greater variability for basins with lower drainage densities. The link between drainage area threshold value and stream network extraction results was also examined, and showed a variation trend of power function y = axb between the sub-basin counts and threshold value, i.e., the maximum reach length increases while the threshold value increases, and the minimum reach length shows no relation with the threshold value. The stream network extraction resulting from a 250 m DEM resolution and a 50 000 ha threshold value was similar to the real stream network. The drainage network density and the threshold value also shows a trend of power function y = axb ; the value of b is usually 0.5.Keywords: SWAT, digital elevation model (DEM), watershed delineation, threshold valu

Erosion Relevant Topographical Parameters Derived from Different DEMs—A Comparative Study from the Indian Lesser Himalayas

Topography is a crucial surface characteristic in soil erosion modeling. Soil erosion studies use a digital elevation model (DEM) to derive the topographical characteristics of a study area. Majority of the times, a DEM is incorporated into erosion models as a given parameter and it is not tested as extensively as are the parameters related to soil, land-use and climate. This study compares erosion relevant topographical parameters—elevation, slope, aspect, LS factor—derived from 3 DEMs at original and 20 m interpolated resolution with field measurements for a 13 km2 watershed located in the Indian Lesser Himalaya. The DEMs are: a TOPO DEM generated from digitized contour lines on a 1:50,000 topographical map; a Shuttle Radar Topography Mission (SRTM) DEM at 90-m resolution; and an Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) DEM at 15-m resolution. Significant differences across the DEMs were observed for all the parameters. The highest resolution ASTER DEM was found to be the poorest of all the tested DEMs as the topographical parameters derived from it differed significantly from those derived from other DEMs and field measurements. TOPO DEM, which is, theoretically more detailed, produced similar results to the coarser SRTM DEM, but failed to produce an improved representation of the watershed topography. Comparison with field measurements and mixed regression modeling proved SRTM DEM to be the most reliable among the tested DEMs for the studied watershed

Soil erosion risk assessment on some soils of the Lubumbashi plain, D.R. Congo

peer reviewedLe contrôle de l’érosion hydrique des sols est l’une des préoccupations importantes en agriculture pluviale, notamment sous les climats tropicaux. Dans la plaine de Lubumbashi, deux sites agricoles (ferme Kasapa et le périmètre agroforestier de Mukoma) ont été étudiés en vue d’y évaluer le risque d’érosion hydrique du sol. Des cartes thématiques des différents facteurs d’érosion, tels que décrits dans l’Équation universelle de pertes de sol, ont été intégrées dans un Système d’Information Géographique, permettant ainsi de : (1) démêler leur complexité et leur interdépendance dans l’analyse des risques d’érosion et (2) cerner l’impact et la contribution de chacun d’eux aux pertes en sol. Cette démarche a permis de : (1) hiérarchiser les différentes zones de sites étudiés selon leurs degrés de sensibilité à l’érosion et (2) déterminer le taux d’érosion par le ruissellement en nappe (30,8 t/ha/an en moyenne pour la ferme Kasapa et de 3,6 t/ha/an pour le site de Mukoma). Par ordre d’importance, les facteurs décisifs qui contrôlent l’érosion hydrique dans la plaine de Lubumbashi sont : la pente, l’érodibilité des sols et la couverture végétale

Efectos del cambio de uso de suelo en la erosión de la cuenca alta del Río Mira para el periodo 1996-2017

Evaluar los efectos del cambio de uso de suelo en la erosión de la cuenca alta del río Mira para el periodo 1996-2018.El suelo es un sistema dinámico donde interactúan factores bióticos y abióticos importantes para el desarrollo de la vida en el planeta, considerado como un recurso natural finito, su capacidad de regeneración se ha reducido drásticamente en el transcurso del tiempo, debido al mal manejo por las distintas actividades antrópicas. La presente investigación tuvo como objetivo analizar los efectos del cambio de uso de suelo y erosión hídrica en la cuenca alta del río Mira para el periodo 1996-2018. Se utilizó imágenes satelitales Landsat/OLI, Sentinel 2A para el año 1996 y 2018 para evaluar el cambio espacio-temporal de la cobertura vegetal y uso de suelo, empleando el software ArcGIS 10.4, a continuación, se estimó la erosión hídrica del suelo mediante la aplicación del modelo de Ecuación Universal Revisada de Pérdida de Suelo (RUSLE) y posteriormente, se aplicó la regresión geográfica pondera para conocer la asociación espacial entre el cambio de uso de suelo y la erosión hídrica. Se obtuvo ocho (8) unidades ambientales que son: Bosque, Vegetación Arbustiva, Páramo, Pastos, Cultivos, Cuerpos de Agua, Área sin vegetación y Zona Urbana, con el coeficiente del índice kappa del 0.88% para el año 2018, durante el periodo de estudio los cultivos, área sin vegetación y zona urbana aumentaron en 25.60%, 2.38%, 0.36% respectivamente, mientras bosque, vegetación arbustiva, páramo y pasto disminuyeron en 7.32%, 18.58%, 2.18% y 10-83%. La erosión hídrica media aumentó en 6.3 t\ha\año en el periodo de estudio, sin embargo, el 68.61% del área de estudio presentó baja susceptibilidad de erosión hídrica del suelo de 0-10 t\ha\año, mientras zonas con mayor tasa de erosión superan los 200 t\ha\año corresponde al 0.01%. De acuerdo con la relación entre el cambio de uso de suelo y la erosión hídrica, existe asociación espacial entre los cultivos, área sin vegetación y vegetación arbustiva con la erosión hídrica, debido al aumento de la deforestación para establecer nuevas áreas para las actividades antrópicas.Ingenierí

Spatio-temporal appraisal of water-borne erosion using optical remote sensing and GIS in the Umzintlava catchement (T32E), Eastern Cape, South Africa.

Globally, soil erosion by water is often reported as the worst form of land degradation owing to its adverse effects, cutting across the ecological and socio-economic spectrum. In general, soil erosion negatively affects the soil fertility, effectively rendering the soil unproductive. This poses a serious threat to food security especially in the developing world including South Africa where about 6 million households derive their income from agriculture, and yet more than 70% of the country’s land is subject to erosion of varying intensities. The Eastern Cape in particular is often considered the most hard-hit province in South Africa due to meteorological and geomorphological factors. It is on this premise the present study is aimed at assessing the spatial and temporal patterns of water-borne erosion in the Umzintlava Catchment, Eastern Cape, using the Revised Universal Soil Loss Equation (RUSLE) model together with geospatial technologies, namely Geographic Information System (GIS) and remote sensing. Specific objectives were to: (1) review recent developments on the use of GIS and remote sensing technologies in assessing and deriving soil erosion factors as represented by RUSLE parameters, (2) assess soil erosion vulnerability of the Umzintlava Catchment using geospatial driven RUSLE model, and (3) assess the impact of landuse/landcover (LULC) change dynamics on soil erosion in the study area during the period 1989-2017. To gain an understanding of recent developments including related successes and challenges on the use of geospatial technologies in deriving individual RUSLE parameters, extensive literature survey was conducted. An integrative methodology, spatially combining the RUSLE model with Systeme Pour l’Obsevation de la Terre (SPOT7) imagery within a digital GIS environment was used to generate relevant information on erosion vulnerability of the Umzintlava Catchment. The results indicated that the catchment suffered from unprecedented rates of soil loss during the study period recording the mean annual soil loss as high as 11 752 t ha−1yr−1. Topography as represented by the LS-factor was the most sensitive parameter to soil loss occurring in hillslopes, whereas in gully-dominated areas, soil type (K-factor) was the overriding factor. In an attempt to understand the impact of LULC change dynamics on soil erosion in the Umzintlava Catchment from the period 1989-2017 (28 years), multi-temporal Landsat data together with RUSLE was used. A post-classification change detection comparison showed that water bodies, agriculture, and grassland decreased by 0.038%, 1.796%, and 13.417%, respectively, whereas areas covered by forest, badlands, and bare soil and built-up area increased by 3.733%, 1.778%, and 9.741% respectively, during the study period. The mean annual soil loss declined from 1027.36 t ha−1yr−1 in 1989 to 138.71 t ha−1yr−1 in 2017. Though soil loss decreased during the observed period, there were however apparent indications of consistent increase in soil loss intensity (risk), most notably, in the elevated parts of the catchment. The proportion of the catchment area with high (25 – 60 t ha−1yr−1) to extremely high (>150 t ha−1yr−1) soil loss risk increased from 0.006% in 1989 to 0.362% in 2017. Further analysis of soil loss results by different LULC classes revealed that some LULC classes, i.e. bare soil and built-up area, agriculture, grassland, and forest, experienced increased soil loss rates during the 28 years study period. Overall, the study concluded that the methodology integrating the RUSLE model with GIS and remote sensing is not only accurate and time-efficient in identifying erosion prone areas in both spatial and temporal terms, but is also a cost-effective alternative to traditional field-based methods. Although successful, few issues were encountered in this study. The estimated soil loss rates in Chapter 3 are above tolerable limits, whereas in Chapter 4, soil loss rates are within tolerable limits. The discrepancy in these results could be explained by the differences in the spatial resolution of SPOT (5m * 5m) and Landsat (30m * 30m) images used in chapters 3 and 4, respectively. Further research should therefore investigate the impact of spatial resolution on RUSLE-estimated soil loss in which case optical sensors including Landsat, Sentinel, and SPOT images may be compared

Spatial modelling of soil and water conservation activities for a catchment in the Ethiopian Highlands

This thesis focused on the use of soil and water conservation (SWC) planning tools to address two ecosystem services (ES’s), erosion control (EC) and dry season baseflow enhancement (BF). The study site was a headwater catchment encompassing Gudo Beret town located in the central sub-humid highlands of Ethiopia. The aims of the thesis were to 1) model the current soil loss risk for the catchment, 2) to simulate a spatial allocation of recommended SWC activities throughout the catchment while giving different weights to the ES objectives, and 3) to estimate potential changes in soil loss and in the water balance as a result of those simulated activity scenarios. In the study, a number of tools and procedures were used: field observations to map erosion hotspots, participatory dialogues with focus groups, remote sensing to generate a land use/land cover (LULC) map, a water balance calculation, and GIS-based spatial modelling tools. The current soil loss risk was predicted for the Gudo Beret catchment using the Revised Universal Soil Loss Equation (RUSLE). Erosion at Gudo Beret was found to far exceed safe limits, with soil loss from rainfed cropland estimated at 47 t ha-1 yr-1 (=82). Estimates of soil loss compared favorably with measurements and estimates from other sub-humid highland catchments in Ethiopia, but are believed to have significantly under-predicted total losses due to the prevalence of gullies in the study area. The Resource Investment Optimization System (RIOS) tool was used to locate the most “responsive” sites to SWC. Three scenarios were tested in which EC and BF were weighted according to the ratios 1:1, 2:1, and 1:0. RIOS performed a spatial allocation of the activities and produced a hypothetical post-SWC LULC map to represent changes in biophysical parameters where activities were allocated. Soil loss was then estimated for the entire catchment for the hypothetical scenarios and a simplified water balance was performed for the rainfed cropland LULC class to assess the potential impact on baseflow, using the soil water storage/drainage term of the water balance as a proxy. The analysis that followed found that soil loss and soil water storage/drainage were not significantly different between the scenarios. The lack of significance between outcomes of the scenarios was attributed to low data quality for some inputs and the relatively small catchment size – both of which suppressed spatial variability which is needed to produce contrasting relative rankings for the ES objectives in RIOS. Recommendations for improving RIOS were given. Despite the results, the model’s unique approach draws attention to both the need to target multiple ES objectives in future conservation goals as well as to account for the offsite benefits of SWC