Spatio-seasonal variation of water quality influenced by land use and land cover in Lake Muhazi.

peer reviewedUnderstanding the influence of land use/land cover (LULC) on water quality is pertinent to sustainable water management. This study aimed at assessing the spatio-seasonal variation of water quality in relation to land use types in Lake Muhazi, Rwanda. The National Sanitation Foundation Water Quality Index (NSF-WQI) was used to evaluate the anthropogenically-induced water quality changes. In addition to Principal Components Analysis (PCA), a Cluster Analysis (CA) was applied on 12-clustered sampling sites and the obtained NSF-WQI. Lastly, the Partial Least Squares Path Modelling (PLS-PM) was used to estimate the nexus between LULC, water quality parameters, and the obtained NSF-WQI. The results revealed a poor water quality status at the Mugorore and Butimba sites in the rainy season, then at Mugorore and Bwimiyange sites in the dry season. Furthermore, PCA displayed a sample dispersion based on seasonality while NSF-WQI's CA hierarchy grouped the samples corresponding to LULC types. Finally, the PLS-PM returned a strong positive correlation (+ 0.831) between LULCs and water quality parameters in the rainy season but a negative correlation coefficient (- 0.542) in the dry season, with great influences of cropland on the water quality parameters. Overall, this study concludes that the lake is seasonally influenced by anthropogenic activities, suggesting sustainable land-use management decisions, such as the establishment and safeguarding protection belts in the lake vicinity

Geospatial Analysis for Heavy Metals and Water Quality Assessment in Bugesera Agricultural Wetlands of Rwanda

Agricultural wetlands are crucial ecosystems for provision of food, water purification, soil retention, nutrients cycling, to name few. However, they are more exposed to heavy metals deposition generating ecological concerns. Therefore, spatially explicit study for water quality and heavy metals’ contents in wetlands to reveal metal contamination sources are key steps for sustainable utilization of water resources in irrigated wetlands. Water samples were collected from surface water alongside the Gashora river. Three sampling sites (Karugenge, Karumuna and Muzi) were selected as the show high occurrence of flooding in wetland. A Global Positioning System (GPS) was used to obtain positional data where surface water samples were collected. A point (vector) database was developed for the attributes of soil, water, and associated parameters. The Photometric, calcination, titration and atomic adsorption spectrometer machines were used to detect the heavy metals. The application of GIS analysis through interpolation using Kriging was used to generate the predictive maps. Principal Components Analysis techniques was used to correlate water quality parameters for similarities and dissimilarities through cluster analysis. All statistical analyses were performed using STATA 13.0 and ArcGIS 10.5 was used to generate prediction maps. The study findings on water quality analysis shows that the ranges of heavy metals were Ca, Mg, Na, K, Cu, Zn, Mn, Pb, Cd and Cr concentration were 3.9–23; 10–22; 2–11; 10.6 –20.6; -7– 210; 0.63– 0.81; 110–160; 0.37–12; 0.15– 0.78; and 0.23–4.4ppm while for water quality analysis, the ranges for pH, EC, TDS, TH, SAR, MAR, KR and SSP concentration were 7–7.8; 190–300; 130–200; 55 –150; 26– 110; 47– 73; 8.2–72 and 35–60 respectively. The greatest heavy metals show maximum values compared to Rwanda national and international permissible limits for irrigation. Thus, there is a need of water treatment to reduce the harmfulness effect to plant and human being

A Spatial and Temporal Assessment of Vegetation Greening and Precipitation Changes for Monitoring Vegetation Dynamics in Climate Zones over Africa

Vegetation is vital, and its greening depends on access to water. Thus, precipitation has a considerable influence on the health and condition of vegetation and its amount and timing depend on the climatic zone. Therefore, it is extremely important to monitor the state of vegetation according to the movements of precipitation in climatic zones. Although a lot of research has been conducted, most of it has not paid much attention to climatic zones in the study of plant health and precipitation. Thus, this paper aims to study the plant health in five African climatic zones. The linear regression model, the persistence index (PI), and the Pearson correlation coefficients were applied for the third generation Normalized Difference Vegetation Index (NDVI3g), with Climate Hazard Group infrared precipitation and Climate Change Initiative Land Cover for 34 years (1982 to 2015). This involves identifying plants in danger of extinction or in dramatic decline and the relationship between vegetation and rainfall by climate zone. The forest type classified as tree cover, broadleaved, deciduous, closed to open (>15%) has been degraded to 74% of its initial total area. The results also revealed that, during the study period, the vegetation of the tropical, polar, and warm temperate zones showed a higher rate of strong improvement. Although arid and boreal zones show a low rate of strong improvement, they are those that experience a low percentage of strong degradation. The continental vegetation is drastically decreasing, especially forests, and in areas with low vegetation, compared to more vegetated areas, there is more emphasis on the conservation of existing plants. The variability in precipitation is excessively hard to tolerate for more types of vegetation