Abstract. In this study we evaluated changes in land cover and rainfall in the Upper Gilgel Abbay catchment in the Upper Blue Nile basin and how changes affected stream flow in terms of annual flow, high flows and low flows. Land cover change assessment was through classification analysis of remote sensing based land cover data while assessments on rainfall and stream flow data are by statistical analysis. Results of the supervised land cover classification analysis indicated that 50.9 % and 16.7 % of the catchment area was covered by forest in 1973 and 2001, respectively. This significant decrease in forest cover is mainly due to expansion of agricultural land.By use of a change detection procedure, three periods were identified for which changes in rainfall and stream flow were analyzed. Rainfall was analyzed at monthly base by use of the Mann-Kendall test statistic and results indicated a statistically significant, decreasing trend for most months of the year. However, for the wet season months of June, July and August rainfall has increased. In the period 1973-2005, the annual flow of the catchment decreased by 12.1 %. Low flow and high flow at daily base were analyzed by a low flow and a high flow index that is based on a 95 % and 5 % exceedance probability. Results of the low flow index indicated decreases of 18.1 % and 66.6 % for the periods 1982-2000 and 2001-2005 respectively. Results of high flows indicated an increase of 7.6 % and 46.6 % for the same periods. In this study it is concluded that over the period 1973-2005 stream flow has changed in the Gilgel Abbay catchment by changes in land cover and changes in rainfall.

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Cape Verde is a semi-arid country conformed by a group of islands located off the west coast of Africa, with highly variable rainfall that appears during a single rainy season. Santiago Island, the biggest of the country, is characterized for abrupt changes of relief within small distances. The influence of geographic location and topographic parameters, such as slope gradient, exposition and elevation on the variability of rainfall in Santiago Island was studied using monthly rainfall data of 30 seasons (1981 to 2010), with daily rainfall data for 14 seasons (1997 to 2010). The number of rainfall days and the percentage of maximum daily rainfall within the monthly and seasonal totals were evaluated. Few rainy days can control the monthly and seasonal rainfall patterns of Santiago Island. Multivariate linear regressions among daily, monthly and seasonal rainfall and elevation, slope gradient, aspect, and geographic east and west coordinates as predictors were carried out. Elevation explains most of the variance in the rainfall. The coefficients of determination show an inverse relationship with the rainfall depth: moderate rainfall totals (120-150 mm monthly, 250-300 mm seasonal) produced the best correlations for seasonal and monthly rainfall, while very low (<50 mm for monthly, <200 mm for seasonal) and very high amounts (>250 mm for monthly, >350 mm for seasonal) resulted in poor correlations. Long-term mean rainfall was interpolated using ordinary kriging and kriging with external drift. In Santiago Island, high and more extreme rainfall events are less influenced by elevation, while low and medium rainfall events are significantly influenced by orography, with most of the rainfall appearing on high elevations.

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Passive sampling techniques can improve the discovery of low concentrations by continuous collecting the contaminants, which usually go undetected with classic and once-off time-point grab sampling. The aim of this study was to evaluate organochlorine pesticide (OCP) residues in the aquatic environment of the Lake Naivasha river basin (Kenya) using passive sampling techniques. Silicone rubber sheet and Speedisk samplers were used to detect residues of α-HCH, β-HCH, γ-HCH, δ-HCH, heptachlor, aldrin, heptachlor epoxide, pp-DDE, endrin, dieldrin, α-endosulfan, β-endosulfan, pp-DDD, endrin aldehyde, pp-DDT, endosulfan sulfate, and methoxychlor in the Malewa River and Lake Naivasha. After solvent extraction from the sampling media, the residues were analyzed using gas chromatography electron capture detection (GC-ECD) for the OCPs and gas chromatography-mass spectrometry (GC-MS) for the PCB reference compounds. Measuring the OCP residues using the silicone rubber samplers revealed the highest concentration of residues (∑OCPs of 81 (± 18.9 SD) μg/L) to be at the Lake site, being the ultimate accumulation environment for surficial hydrological, chemical, and sediment transport through the river basin. The total OCP residue sums changed to 71.5 (± 11.3 SD) μg/L for the Middle Malewa and 59 (± 12.5 SD) μg/L for the Upper Malewa River sampling sites. The concentration sums of OCPs detected using the Speedisk samplers at the Upper Malewa, Middle Malewa, and the Lake Naivasha sites were 28.2 (± 4.2 SD), 31.3 (± 1.8 SD), and 34.2 (± 6.4 SD) μg/L, respectively. An evaluation of the different pesticide compound variations identified at the three sites revealed that endosulfan sulfate, α-HCH, methoxychlor, and endrin aldehyde residues were still found at all sampling sites. However, the statistical analysis of one-way ANOVA for testing the differences of ∑OCPs between the sampling sites for both the silicone rubber sheet and Speedisk samplers showed that there was no significant difference from the Upper Malewa to the Lake site (P < 0.05). Finally, the finding of this study indicated that continued monitoring of pesticides residues in the catchment remains highly recommended.

Abstract. Flux towers provide essential terrestrial climate, water, and radiation budget information needed for environmental monitoring and evaluation of climate change impacts on ecosystems and society in general. They are also intended for calibration and validation of satellite-based Earth observation and monitoring efforts, such as assessment of evapotranspiration from land and vegetation surfaces using surface energy balance approaches.In this paper, 15 years of Skukuza eddy covariance data, i.e. from 2000 to 2014, were analysed for surface energy balance closure (EBC) and partitioning. The surface energy balance closure was evaluated using the ordinary least squares regression (OLS) of turbulent energy fluxes (sensible (H) and latent heat (LE)) against available energy (net radiation (Rn) less soil heat (G)), and the energy balance ratio (EBR). Partitioning of the surface energy during the wet and dry seasons was also investigated, as well as how it is affected by atmospheric vapour pressure deficit (VPD), and net radiation.After filtering years with low-quality data (2004)(2005)(2006)(2007)(2008), our results show an overall mean EBR of 0.93. Seasonal variations of EBR also showed the wet season with 1.17 and spring (1.02) being closest to unity, with the dry season (0.70) having the highest imbalance. Nocturnal surface energy closure was very low at 0.26, and this was linked to low friction velocity during night-time, with results showing an increase in closure with increase in friction velocity.The energy partition analysis showed that sensible heat flux is the dominant portion of net radiation, especially between March and October, followed by latent heat flux, and lastly the soil heat flux, and during the wet season where latent heat flux dominated sensible heat flux. An increase in net radiation was characterized by an increase in both LE and H, with LE showing a higher rate of increase than H in the wet season, and the reverse happening during the dry season. An increase in VPD is correlated with a decrease in LE and increase in H during the wet season, and an increase in both fluxes during the dry season.

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The Food and Agricultural Organization of the United Nations (FAO) portal to monitor water productivity through open‐access of remotely sensed derived data (WaPOR) offers continuous actual evapotranspiration and interception (ETIa‐WPR) data at a 10‐day basis across Africa and the Middle East from 2009 onwards at three spatial resolutions. The continental level (250 m) covers Africa and the Middle East (L1). The national level (100 m) covers 21 countries and 4 river basins (L2). The third level (30 m) covers eight irrigation areas (L3). To quantify the uncertainty of WaPOR version 2 (V2.0) ETIa‐WPR in Africa, we used a number of validation methods. We checked the physical consistency against water availability and the long‐term water balance and then verify the continental spatial and temporal trends for the major climates in Africa. We directly validated ETIa‐WPR against in situ data of 14 eddy covariance stations (EC). Finally, we checked the level consistency between the different spatial resolutions. Our findings indicate that ETIa‐WPR is performing well, but with some noticeable overestimation. The ETIa‐WPR is showing expected spatial and temporal consistency with respect to climate classes. ETIa‐WPR shows mixed results at point scale as compared to EC flux towers with an overall correlation of 0.71, and a root mean square error of 1.2 mm/day. The level consistency is very high between L1 and L2. However, the consistency between L1 and L3 varies significantly between irrigation areas. In rainfed areas, the ETIa‐WPR is overestimating at low ETIa‐WPR and underestimating when ETIa is high. In irrigated areas, ETIa‐WPR values appear to be consistently overestimating ETa. The relative soil moisture content (SMC), the input of quality layers and local advection effects were some of the identified causes. The quality assessment of ETIa‐WPR product is enhanced by combining multiple evaluation methods. Based on the results, the ETIa‐WPR dataset is of enough quality to contribute to the understanding and monitoring of local and continental water processes and water management.