Gabriel Habiyaremye

Analysis of Urban Environment: Case Study of the Spatial Integration of Rwandan Cities

This paper presents the results of the study undertaken in Rwanda to investigate the spatial integration of cities. It was revealed that the economic subordination degree appears to be very low because the economy of all cities in country depends on Kigali City, the capital of Rwanda that detains more than 70% of national economy.

An assessment of the spatial distribution of Pentecost churches in an African urban environment: A case study of Lubumbashi City in the Democratic Republic of the Congo

This paper presents the results of the study undertaken at Lubumbashi City in D.R.Congo to determine the spatial distribution and evolution of Pentecost churches in Africa urban environment. It was shown that in Lubumbashi City the Pentecost Churches were grown from 112 churches in 1990 to 280 Churches in 2008. Four Church Community groups were identified which are 8th CEPAC (19 churches), 30th CEPECO (102 churches), 45th CEP (39 churches) and RESURGENCE CHURHCES (120 churches). The last cited knew a high proliferation and grew from 24 Churches to 120 Churches in the same period. The analysis of their spatial distribution by using the Distribution Model showed that the concentration of spatial distribution is R=0.416. The study of correlation between the number of Churches, the number of population and the area by using the formula of correlation coefficient shows that no correlation exists for their distribution. The need of money, accessibility and good environment were a basis of their proliferation. Finally we addressed the advices and proposed an appropriate method to all actors in order to establish a harmony in urban environment.

FORECASTING THE PERFORMANCE OF AN OIL FIELD, COMPARISON OF VARIOUS USED METHODS: THE CASE OF SHUANGHE OILFIELD, CHINA

While being the dominant source of energy, oil has also brought affluence and power to different societies. Energy produced from oil is fundamental to all parts of society. In the foreseeable future, the majority of energy will still come from oil production. Consequently, reliable methods for forecasting that production are crucial. Petroleum engineers have searched for simple but reliable way to predict oil production for a long time. Many methods have been developed in the latest decades and one common practice is decline curve analysis. Prediction of future production of petroleum wells is important for cost-effective operations of the petroleum industry. This work presents a comparative analysis of methods used to predict the performance of Shuanghe oilfield, China. Using decline curve analysis including three different methods: Arps empirical methods, LL-model and simplified model and the new simplified model, LLModel, to crosscheck Arps exponential decline model prediction results. The results showed by the comparative analysis of predictions calculated proved LL-model to be the best predictor for Shuanghe oilfield since it takes into account more parameters than the old models used in this work. However, the subsurface information or parameters of the reservoir used in LL-model may not be available every time, therefore Arps models may apply as defined. In Shuanghe oilfield calculated average geological reserves N was estimated at 9449.41 ×104 tons, the average recoverable reserves NR were estimated to 4274.61×104 tons while the water cut was 97% and the water cut predicted by LLmodel was 96.7%; not far from water flooding curves value. The exponential decline model showed recoverable reserves NR estimated around 4685.88×104 tons of oil while the decline phase of total development was estimated around 34 years which means that if the actual production conditions remain unchanged, Shuanghe oilfield would continue producing for another 25 years from 2008.

Effects of Global Climate Change on Water Resources in Rwanda: Lake Kivu Case Study

Climate change is emerging as one of the most miscellaneous expressions of the global change nowadays. It potentially affects ecosystems including water resources. The change of climate also has significant impacts on the availability of water, as well as the quality and quantity of water that is available and accessible. Aiming at studying the effect of climate change on water resources, 25 years collected secondary data of both climatic and hydro-meteorological stations were used and Statistical analysis was performed using ORIGIN PRO 8.0 Software. The study linked the surface elevation of Lake Kivu variation with respect to climate change where the level of the lake matches to pluviometric and anomalies values. Finally, the statistical analysis could not directly link the temperature variation with that of surface water level in the lake. Climate change is real and happening now and surely affects water resources among others making an urgent need to control anthropogenic inputs into the atmosphere, one of the factors forcing climate change.

Erosion control verification: “Method of hole”

This study was undertaken to assess the erosion control verification. The intensity analysis using method of hole by capturing of water flow on mountainsides was a good indication for verification. It showed that the speed of this water was reduced from 1 hour in April 2007 to 7 hours 12 minutes in April 2008 in Rwanda where radical terraces were the main method for erosion control. In Xinjiang, the intensity of erosion varied between 7 hours 23 minutes and 10 hours 7 minutes from January to December 2009. Finally we proposed this strategy for all different parts of the whole world where erosion is still a big challenge to assess its intensity in order to preserve its consequences in the environment.

Notice of Retraction Materials on rivers around tea growing areas of Rwanda

The analysis of water samples collected in rivers streams across the tea growing areas in Rwanda by using spectroscopy technique MS Instrument has clearly indicate the presence of heavy elements (Al, As, Ba, c, Ca, Cu, Fe, H+, K, Mg, Mn, N, P, S, Si, and Zn) in water samples. The highly concentrated are: Ca (37 - 54.9), C (31.5-36.4), S: 12.9-24.1, Mg: 8.5-14.1, N: 4-11 and K: 5.3-7.8. Those with medium concentration are Si: 3.4-5.4, Cu: 1.1-2.5, Mn: 0.7-1.5, Ba: 0.5-1.03, Fe: 0.6-1 and P: 0.6-0.8. And elements with low concentration are Zn: 0.3-0.76, H+: 0.4-0.66, Al: 0.4-0.6 and As: 0.02-0.5. The pH varies between 5.5- 6.7.Water is acidic and this acidity may be caused by the use of fertilizers and pesticides with high quantity of NPK + Mg. Here we proposed the method that can be applied in order to maintain the quality of drinking water.