This report is about field attachment which was carried out in Caritas-Kotido Diocese church organization from 13th October to 19th November 2021 The report covers the period of six weeks of field activities which included orientation, office work, documentation, field visits, monitoring groups benefiting from the projects being implemented, Training the sub-county officials of disasters management in their areas, Monitoring projects, follow up activities of the projects, conducting home visits of beneficiaries, conducting interviews with individuals and households, Dialogue meetings and writing internship report. During field work activities many issues emerged and these were needs, interest, opportunities and expectations of the community members as well as beneficiaries, team work spirit, involvement of community members in community activities, Long distance, Harsh climate, Hostility, Insecurity, monitoring community driven projects, recording cases, office work, counseling, Dialogue and interviewing Chapter four presents’ recommendations directed to the Community of Adult and Community Education and Government of Uganda. I therefore learnt that the involvement of community members, beneficiaries and stakeholders in the planning process,implementation,monitoring and evaluation and maintenance of community projects used by NGO’s and as essential in delivery services out of local knowledge and I also learnt that practical application and demonstration of theoretical work done in classroom setting needs to be planned accordingly to be easy to execute duties in the field through careful reflection before implementing the programs intended to be done.

The overall objective of the study was to determine the factors influencing labour demand in Uganda using a Multivariate Linear Regression model. The study specifically focused on establishing the relationship between GDP, Capital Formation, Final Consumption Expenditure and Labor demand. The study explained the summary (descriptive statistics) at the univariate level while pairwise correlation and Multivariate Linear Regression modelwere employed at bivariate level and multivariate level respectively. Johansen’s Cointegration test revealed the presence of a long run relationship among the variables. The Multivariate Linear Regression modelrevealed that GDP and Capital Formation have statistically significant and positive effect on Labor demand at 5% level of significance holding other factors constant. The study recommended that the government should support agriculturalists to undertake modernization in agriculture, BoU should adopt efficient inflation-adjusting and reducing strategies so as to keep the inflation rate at mild level, aim at investing in the human capital and health and should encourage the establishment of the import substitution industries in Uganda.

This report covers the works from the second industrial training, which was carried out at Span Contractors Ltd, in partial fulfilment of the requirements for the award of a Bachelor of Science Degree in Civil and Environmental Engineering. The training project was proposed mixed-use building (parking, shops and apartments) on plots 1, 3 & 5, Burton Street and 2, Johnson Street, central division, Kampala Chapter 1 gives a brief introduction of Industrial Training and its objectives, and information about Span Contractors Ltd. Chapter 2 discusses the practical work that was done during the training program. Chapter 3 discusses the lessons learnt and challenges faced during the period of industrial training Chapter 4 discusses the conclusions and recommendation

The linkages between LULC and water quality in wells are not known. This makes it difficult to control and manage quality of such water sources. Hence, linkage information is required to help the concerned authorities solve and manage water quality at source level.The overall aimof the study was to analyze the effects of the different LULC types within micro watersheds on well water quality. Specifically, the study involved determining pH, EC and TUR of water, mapping the different LULC types within micro watersheds, and determining the linkages between LULC and water quality. 15 purposely sampled wells that had data (pH, EC, TUR) from NWSC were used. Satellite images were acquired from google earth pro, downloaded using smart GIS and imported into ArcGIS 10.3.1 for classification. Unsupervised classification (20 classes) was carried out and then reclassified into 4-5 classes. WQI was obtained by determining the antilog of the product of the weightage factor and quality rating of the parameters. LCI was a ratio of area covered by a given LULCto the total area in the buffer multiplied by the pollution index. SI was obtained by summing 75% of the WQI and 25% of the LCI. Mean and standard deviation for each of the parameters were calculated in Microsoft excel to provide for the statistical analysis. Mean pH was 5.73 with a STDev of 0.39. Mean EC was 291 μS/cm with a STDev of 98.64 μS/cm. Mean TUR was 40.84 NTU with a STDev of 35.66 NTU. Mean WQI was 33.72 with a STDev of 11.21. Cropland had a LCI of 1.68,bare land (0.93), forest (0.4), water (0.29) andbuilt-up (0.13). Mean SI was 18.82.All the wells were acidic in terms of pH and the TUR couldn’t meet both the WHO and UNBS standards while the EC met both standards. This means the water was acidic and turbid. The micro watersheds were mainly covered by cropland and bare land (>70%). 75% of the wells were rated moderate topoor due to the high WQI (>25). Cropland contributed 48.87% to poor quality due to the high LCI (1.68). However, bare land contributed 27.21%, forest–11.68%, swamp-8.39%, built-up-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 precise explanation for the influence of LULC on groundwater quality. Alternative LULC patterns for buffers that had low SI was recommendedin order to mitigate poor water quality at source level.In addition, there should also be routine programs for catchment management andcommunity education. Keywords: Water quality index, Land cover index, Suitability index, LULC, Linkages