JCCS Articles

Rainfall variability and trends over Rwanda


Sebaziga Ndakize Joseph.1,2,*, Safaris Bonfils2, Ngaina Ndiwa Joshua3, Ntwali Didier4, Mutai Bethwel Kipkoech5, Safari Kagabo Abdou2,& Rwema Michel2

1Rwanda Meteorology Agency, P.O Box 898 Kigali, Rwanda; 2University of Rwanda P.O Box 3900, Kigali, Rwanda; 3Southern Eastern Kenya University, P.O Box 170, 90200, Kitui, Kenya, 4Rwanda Space Agency, P.O Box 6205, Kigali, Rwanda & 5University of Nairobi, P.O Box 30197, 00100, Nairobi, Kenya

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Rainfall is regarded as one of the foundational concepts for comprehending climate variability and/or change. This paper aimed at examining the seasonal and annual rainfall variability and its associated trends over Rwanda between 1981 and 2017. The Coefficient of Variation (CV) was used to determine the rainfall variability. Mann-Kendall test and Sen’s slope estimator techniques were used to detect trends and to quantify the magnitude of change. High rainfall variability was observed over eastern Rwanda, around Kigali city and central plateau, while the south-western, western and the north highland revealed lower rainfall variability. Trend analysis of annual and March-May (MAM) rainfall season depicted a significant decrease of -6.7% over south-western region (Kamembe-Aero station) and -9.8% over eastern parts (Kibungo-Kazo) respectively. A significant increase in trend of 4.3% over North-western (Gisenyi-Aero station) during September-December (SOND) season was also obtained. The rest of the stations registered a non-significant trend on both seasonal and annual time scales. Spatially, areas of Kigali City, eastern and central parts of Rwanda revealed a decreasing trend whereas an increasing trend was observed over the western, northern highland, north eastern and southern region except for the areas towards the south-east. The high rainfall variability and significant nature of changing trends demand that rain-dependent sectors of the economy link climate science and policy in order to make proper planning. With proper climate homogeneity zoning, the agricultural sector in particular needs to develop effective techniques that optimize food production including water use rationalisation.

Key words: Rainfall, Rwanda, Trend, Variability, Rain-Dependent


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Analysis of Climate Change Indices in Musanze District, Rwanda


Anthony Twahirwa.1,2,*, Christopher Oludhe2, Philip Omondi2,4, Gaspard Rwanyiziri3, Joseph Sebaziga Ndakize1,3,& Sandrine Guhirwa1

1Rwanda Meteorology Agency, P.O Box 898 Kigali, Rwanda,2University of Nairobi, P.O Box 30197, 00100, Nairobi, Kenya,3University of Rwanda, P.O Box 3900 Kigali, Rwanda, & 4IGAD Climate Prediction and Application Centre, P.O. Box 10304, 00100 Nairobi, Kenya

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This study used daily rainfall, minimum temperature, and maximum temperature data from the Rwanda Meteorology Agency (Meteo Rwanda) for the years 1983 - 2016 to analyze climate change indices in the Musanze district of Rwanda. Rainfall and temperature extreme indices were determined using the methodology provided by Expert Team on Climate Change Detection Monitoring Indices (ETCCDMI). Climate Data Tool (CDT), which is R-based package developed by International Research Institute for Climate and Society (IRI) was used to compute the indices. Sen's slope estimator and the modified Mann-Kendall (m-MK) test were both applied to identify trends and determine the degree of change. The Monthly Temperature (TXx, TXn, TNx, and TNn) indices generally showed a warming in the eastern and a cooling in the western parts of the district, according to the trend results; however, the Minimum tail of temperature indices showed a slightly reduced cooling which is a sign of warm nights and hot days in highland areas of volcanic region. For the same period, the district's eastern regions have higher precipitation intensity and wetness, which gradually declines toward the middle and western regions. In addition, a considerable upward trend in the annual total precipitation for days above the 95th percentile (very wet days) and the annual count for precipitation equal or greater than 20 mm (very heavy precipitation days). Additionally, temperature indices showed a large rise in the minimum and maximum values of daily minimum temperatures, annual minimum and maximum values of daily maximum temperatures, and the percentage of days with daily maximum temperatures above the 90th percentile (warm days). In view of these evolving trends in weather and climate patterns, the study recommends local farmers and other stakeholders involved in socioeconomic activities in the district to implement the necessary climate change mitigation and adaptation measures.

Key words: Climate change, Climate Indices, Precipitation, Temperature, Musanze District


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Water Balance Evaluation for Flood Risk Reduction in the Yala River Basin, Western Kenya


Kiluva V.M.1, Wanyonyi E.S.1, Wakhungu J.W.2

1School of Disaster Management and Humanitarian Assistance, Masinde Muliro University of Science and Technology, Kakamega, Kenya

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The Yala River Basin (YRB) in Western region of Kenya has in the past experienced climate and weather extreme events that include floods. Floods have triggered loss of lives, destruction of property, outbreak of water borne diseases and siltation of arable land. This study utilized the Nedbør-Afstrømnings-Model (NAM) hydrologic model (available in the NAM Module of the MIKE 11 hydrodynamic model) on the Yala River Basin (YRB) to generate flood flows for water balance evaluation. The study utilized satellite imagery data for the period 1984-2010 sourced from the Regional Centre for Mapping of Resources for Development, rainfall (1980-2012) and river discharge (1947-2012) data sets from the Kenya Meteorological Department (KMD) and the Water Resources Management Authority (WARMA), respectively. Data quality control was statistically checked before sensitivity analysis, calibration, validation, and simulation of the flood flows. Daily water balance estimates for the Yala River Basin (YRB) over the period 1980-2010 were developed using the NAM hydrologic model. The results indicate that the mapped flood area extent varied by a value of 34.23 km2 over the period 1980-2010. The Yala River Basin (YRB) indicated an estimated inflow value of 4,814.72 MCM and outflow value of 4,578.23 MCM, with a coefficient of determination of 0.867. The difference between the inflow and outflow values was 236.49 MCM, that formed the flood flow or the water balance. This study concluded that the water balance value of 236.49 MCM was responsible for the floods recorded in the Yala River Basin (YRB) for the period 1980-2010, and it should be taken care of through flood risk reduction initiatives.

Key words: Floods, Water balance, NAM hydrologic model, Simulation, Yala River Basin


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