The effects of cattle manure and inorganic N‐fertilizer application on soil organic carbon (SOC), bulk density, macro‐aggregate stability and aggregate protected carbon were determined on clay and sandy soils of the Murewa smallholder farming area, Zimbabwe. Maize was grown in four fields termed homefields (HFs) and outfields (OFs) because of spatial variability induced by management practices and with the following fertility treatments: control (no fertility amelioration), 5, 15 and 25 t/ha cattle manure + 100 kg/ha N applied annually for seven consecutive years. The addition of cattle manure resulted in significant (P < 0.01) increases in SOC, macro‐aggregate stability and aggregate protected carbon in clay soils from at least the 5 t/ha cattle manure rate and was comparable between HFs and OFs on clay soils. Aggregate protected carbon in clay soils was significantly higher from the 15 and 25 t/ha cattle manure rates compared to the 5 t/ha cattle manure treatment. In contrast, only SOC was significantly (P < 0.05) increased with the addition of cattle manure on the sandy soils, while bulk density, macro‐aggregate stability and aggregate protected carbon were not significantly changed. Bulk density was also not significantly (P > 0.05) different on the clay soils. A significant and positive linear relationship (r2 = 0.85) was found between SOC and macro‐aggregate stability, while an r2 value of 0.82 was obtained between SOC and aggregate protected carbon on the clay soils. However, no regressions were performed on data from the sandy soils because of the lack of significant changes in soil physical properties. Application of cattle manure and inorganic N‐fertilizer significantly increased (P < 0.05) maize grain yield on both soil types. Results show that inorganic N‐fertilizer combined with cattle manure at 5–15 t/ha per yr is necessary to increase maize yields and SOC on sandy soils in Murewa, while at least 15 t/ha per yr cattle manure is required on the clay soils to improve physical properties in addition to maize yields and SOC.

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The Global warming effect has had negative impacts on water resources in Zimbabwe due to erratic rainfall patterns. The overall effect leads to reduction in power generation on hydropower stations as a result of low water levels. Water level monitoring at hydro power generation reservoirs is thus of utmost importance. Currently employed in situ based water level monitoring techniques are less efficient and do not provide the synoptic coverage of the lake. We present the relationship between factors (natural and anthropogenic) affecting water levels and the measured water levels. The factors were derived from remote sensed data. To ascertain the most significant factors contributing to water level and electricity generation fluctuations, correlation and regression were used. The regression models generated were used to design an application. The application automated the processing satellite imagery. From the automated extraction of rainfall data and land use/cover classification water level monitoring was achieved.

A GIS-based approach for identifying suitable sites for rainwater harvesting (RWH) technologies was developed and applied in Kasungu District, Malawi. Data were obtained from reports, socio-economic survey documents of the area and maps. Field surveys were conducted in the villages of Chipala Extension Planning Area (EPA), in order to identify and evaluate the performance of existing RWH interventions, and determine factors for locating suitable areas for RWH. Observed soil moisture content was used to assess the water retention performance of the prevalent RWH technologies: contour tied ridging and soil mulching. A GIS-based Soil Conservation Service Curve Number (SCS-CN) method was used to map runoff potential for areas with RWH technologies, using physical factors of rainfall, land use, soil type and slope to estimate runoff potential. This was then integrated in a GIS database, with social-economic factors in the form of household income level and environmental factors, including impacts of implementing RWH, to determine the suitability of land areas for RWH in Kasungu District. One way analysis of variance (ANOVA) was used to test the impact of identified technologies by comparing the moisture content measurements for each of the identified technologies at 5% level of significance. The ANOVA results showed a statistically significant difference in the moisture measurements for the three technologies identified (P < 0.05). The RWH suitability map for the study area showed that 0.2% of the area considered had very high potential, 33.5% high, 55.9% moderate, 10.1% marginal and 0.3% not suitable for in-field RWH. The model was verified by locating the existing RWH on the suitability map obtained from GIS: 81% of RWH were located in the highly and moderately suitable areas whilst only 13% were located in areas of low suitability. Hence the developed model can reliably be used to predict potential areas for RWH.

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