Impact of land use land cover within a micro watershed on well water quality in Mulanda Sub-county
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The linkages between the immediate land use land cover (LULC) and water quality in wells are not known making it difficult to control and manage quality of such water sources. The aim of the study was to analyze the effects of the different LULC types within wells’ micro watersheds on the water quality. Specifically, the study involved mapping the different LULC within micro watersheds (500m), determining pH, Electrical Conductivity (EC), Turbidity (TUR) of water, and determining the linkages between LULC and water quality. The study site was Mulanda sub county, Tororo district in Eastern Uganda. Fifteen purposely sampled wells that had data (pH, EC, TUR) from NWSC were used. Acquired Google Earth Pro Satellite images, were processed by ArcGIS 10.3.1. Unsupervised classification (20 classes) was carried out and then reclassified into 5 classes. Water Quality Index (WQI) was obtained by determining the antilog of the product of the weightage factor and quality rating of the parameters. Land Cover Index (LCI) was determined as the ratio of area covered by a given LULC to the total area in the buffer multiplied by the pollution index. Suitability Index (SI) was obtained by summing 75% of the WQI and 25% of the LCI. Descriptive statistics for each of the parameters were calculated in Microsoft excel. The results showed that the mean values (standard deviation) for pH, EC, TUR and NTU were respectively 5.73 (SD 0.39), 291 µS/cm (SD 98.64 µS/cm), 40.84 NTU (SD 35.66 NTU). Mean WQI was 33.72 (SD 11.21). Cropland had a LCI of 1.68, bare land (0.93), forest (0.4), water (0.29) and built-up (0.13). Mean SI was 18.82. All water in the wells was acidic and turbid with pH and the TUR that couldn’t meet both the WHO and UNBS standards while the EC met both standards. The micro watersheds were mainly covered by cropland and bareland (>70%). 75% of the wells were rated moderate to poor due to the high WQI (>25). Cropland contributed 48.87% to poor quality due to the high LCI (1.68). Bare land contributed 27.21%, forest–11.68%, swamp-8.39%, builtup-3.79% to poor quality. The low SI (<20) showed that most wells weren’t suitable for consumption. Nevertheless, integrated remote sensing and groundwater quality gave a good explanation for the influence of LULC on groundwater quality. Alternative LULC patterns for buffers that had low SI is recommended in order to mitigate poor water quality at source level. In addition, there should also be routine programs for catchment management and community education. Hence, linkage information derived is required to guide the concerned authorities solve and manage water quality at source level.