Introduction to the AARSE2016 Special Issue of the South African Journal of Geomatics

No Abstrac

Spatial and temporal variation of papyrus root mat thickness and water storage in a tropical wetland system

acceptedVersio

Development and analysis of the Soil Water Infiltration Global database

In this paper, we present and analyze a novel global database of soil infiltration measurements, the Soil Water Infiltration Global (SWIG) database. In total, 5023 infiltration curves were collected across all continents in the SWIG database. These data were either provided and quality checked by the scientists who performed the experiments or they were digitized from published articles. Data from 54 different countries were included in the database with major contributions from Iran, China, and the USA. In addition to its extensive geographical coverage, the collected infiltration curves cover research from 1976 to late 2017. Basic information on measurement location and method, soil properties, and land use was gathered along with the infiltration data, making the database valuable for the development of pedotransfer functions (PTFs) for estimating soil hydraulic properties, for the evaluation of infiltration measurement methods, and for developing and validating infiltration models. Soil textural information (clay, silt, and sand content) is available for 3842 out of 5023 infiltration measurements ( ∼ 76%) covering nearly all soil USDA textural classes except for the sandy clay and silt classes. Information on land use is available for 76% of the experimental sites with agricultural land use as the dominant type ( ∼ 40%). We are convinced that the SWIG database will allow for a better parameterization of the infiltration process in land surface models and for testing infiltration models. All collected data and related soil characteristics are provided online in *.xlsx and *.csv formats for reference, and we add a disclaimer that the database is for public domain use only and can be copied freely by referencing it. Supplementary data are available at https://doi.org/10.1594/PANGAEA.885492 (Rahmati et al., 2018). Data quality assessment is strongly advised prior to any use of this database. Finally, we would like to encourage scientists to extend and update the SWIG database by uploading new data to it

Climate change and land degradation in Africa : A case study in the Mount Elgon region, Uganda

The aim of this study is to estimate and compare soil erosion, in the Mount Elgon region, eastern Uganda, during the last decade. Possible trends and changes in erosion are linked to precipitation/climate change as well as changes in land cover. Two different versions of the Revised Universal Soil loss Equation RUSLE. are implemented and compared, one using slope length and the other using flow accumulation to estimate the slope length and steepness factor LS. Comparisons of the modeled soil erosion vs. field data indicate that RUSLE based on flow accumulation is preferable. The modeling is carried out for the years 2000, 2006, and 2012, and is based on ASTER remotely sensed data, digital elevation models, precipitation data from the study area, as well as existing soil maps. No significant trends in estimated soil erosion are found to be present during the last decade. Over exploitation of land is probably compensated by improved agricultural management and no significant increase in precipitation. Even if there are reports of more intense and increasing amounts of rainfall in the area, this could not be verified, neither through the analysis of climate data, nor by trends in the estimated soil loss

Differentiated Spatial-Temporal Flood Vulnerability and Risk Assessment in Lowland Plains in Eastern Uganda

This study was conducted to map flood inundation areas along the Manafwa River, Eastern Uganda using HECRAS integrated with the SWAT model. The study mainly sought to evaluate the predictive capacity of SWAT by comparisons with streamflow observations and to derive, using HECRAS, the flood inundation maps. Changes in Land-use/cover showed by decrease in forest areas and wetlands, and conversions into farmlands and built-up areas from 1995 to 2017 have resulted in increased annual surface runoff, sediment yield, and water yield. Flood frequency analysis for 100-, 50-, 10-, and 5-year return periods estimated peak flows of 794, 738, 638, and 510 m3/s, respectively, and total inundated areas of 129, 111, 101, and 94 km2, respectively. Hazard classification of flood extent indicated that built-up areas and commercial farmlands are highly vulnerable, subsistence farmlands are moderately to highly vulnerable, and bushland, grassland, tropical high forest, woodland, and wetland areas are very low to moderately vulnerable to flooding. Results demonstrated the usefulness of combined modeling systems in predicting the extent of flood inundation, and the developed flood risk maps will enable the policy makers to mainstream flood hazard assessment in the planning and development process for mitigating flood hazards

Assessing the Dynamics of Agropastoral farmers’ Adaptive Capacity to Drought in Uganda’s Cattle Corridor

Adaptive capacity provides a pivotal role in resilience building for socio-ecological systems to overcome both natural and anthropogenic disturbances. Persistent droughts increasingly cause abrupt changes in communities’ ability to mobilize scarce resources, anticipate or respond to perceived or current effects over time. This paper examines the factors influencing agropastoral farmers’ adaptive capacity dynamics in the cattle corridor of Uganda, and quantify their relative contributions. Data analysed was derived from a household survey of 426 households randomly and purposively selected from the six districts in the cattle corridor. Agropastoral farmers' adaptive capacity was assessed using the Local Adaptive Capacity (LAC) framework and measured using Principal component Analysis (PCA). Multivariate probit regression model was used to reveal the significant factors influencing adaptive capacity. The study illustrates that farmers' adaptive capacity index was low and variable across the cattle corridor sub-regions, significant indicators were; innovations, asset base, knowledge, and information. Farmers' gender, level of education, land size, off-farm activities, and membership to savings and loan-based associations significantly changed adaptive capacity. This study enlightens stakeholders with better knowledge of adaptive capacity, its component indicators, and factors at the household level. It also provides methodological approaches for assessing adaptive capacity at local level to climate change hazards. The study recommends an integrated application of the knowledge on the underlying factors to help infer innovative approaches and avert the long-term/ expected effects of drought on the context under investigation