171 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) ISSN (Print) 2313-4410, ISSN (Online) 2313-4402 © Global Society of Scientific Research and Researchers http://asrjetsjournal.org/ The Evaluation of the Rainfall-Runoff Effects to the Variation of Hydrology of Migina Catchment in Rwanda Omar Munyanezaa*, Francois Hakorimanab, Egide Mundererec, Peace Aradukundad, Theoneste Twizeyimanae a,c,dUniversity of Rwanda, College of Science and Technology, Department of Civil, Environmental and Geomatic Engineering, P.O. Box 3900, Kigali, Rwanda bRwanda Polytechnic, Ngoma College, Department of Civil Engineering, P.O. Box 35 , Kibungo, Rwanda eRwanda Polytechnic, Ngoma college, Association of Academic Researchers, P.O.Box 35-Kibungo, Rwanda aEmail: omarmunyaneza1@gmail.com; cEmail: egide50@yahoo.fr; dEmail: aradukundap@gmail.com bEmail: francoishakori12@gmail.com eEmail: ttheoneste@gmail.com Abstract The basic implementation of agricultural development and crop production increase in marshland of Migina catchment (ca: 257.4 km2) requires strong and technical analysis of the effect and change of hydro- meteorological aspects from rainfall-runoff parameters. This paper focuses on the effect of rainfall and runoff in Migina catchment and describes in details the study of rainfall and runoff availability in Migina catchment. The study was limited to the analysis of hydrological aspects of the catchment including the water balance. Specifically the paper specifies the seasonally hydrologic variation, evaluates the performance of the catchment area on the environmental activities and studies the rainfall-runoff effect on the variation of hydrology of the catchment. The required data were collected from the thirteen (13) meteorological stations located in the catchment (Meteo-Rwanda, 2008) and historical data from other institutions like: Center of GIS of the University of Rwanda, Ministry of Agriculture (MINAGRI), Ministry of Environment and Ministry of Infrastructure (MININFRA). Arithmetic mean method was used for the determination of annual rainfall. The annual evapotranspiration has been calculated through evaporation pan at Rwasave and Gisunzu stations for data recorded from 2010 to 2012. Annual discharge was determined using rating curve method at Munyazi, Mukura and Cyihene rivers for discharge data of 2010 to 2012. Simple formulas were used in calculations, and the adjusted crop coefficient was found to be 0.66, and the annual rainfall varies with respect to weather or Climate events like Temperature increase. ------------------------------------------------------------------------ * Corresponding author. http://asrjetsjournal.org/ American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2018) Volume 48, No 1, pp 171-185 172 This can have major effects on society, economy and the environment and was found to be 1569.5mm. The results show that the Migina catchment land use is dominated by the agricultural at 70% (rice, maize and beans) and livestock activities. It is recommended to contribute to the amelioration of Agricultural activities to increase the Rwandan primary sector production and sensitize the population on Rwanda seasonal changes and good governmental catchment protection plan. Key words: Migina catchment; Rainfall analysis; Runoff analysis; Rwanda; Variation. 1. Introduction The variation of hydrology is the situation changing the almost physical and environmental aspect of the region in our living land. This change is enhanced by hydro-meteorological factors like sun rays increase, temperature difference in different earth’s area, seasonal variation based on the loss and /or the precipitation abundance, [1]. The Migina catchment is the water reservoir (storage) located in the southern province of Rwanda where it recovers three districts including: Huye, Gisagara and Nyaruguru district. From many years ago, this catchment constitutes the principal water resource and contributes to the alimentation of water to several people accommodating the area. Villages in which the catchment is located; get water from several rivers within Migina catchment. Rivers:Mukura,Musizi,Akaremera,Ruvuzo,Kidobogo,Kadahokwa,Munyazi,Migina,Rwimbogo,Cyenzubuhoro,e tc are of the paramount importance for agricultural domain[1].. The precipitation of water vapor from the atmosphere occurs in many forms all over the world depending to the geographical location, the most important of which are rain and snow. The drainage in most urban communities is designed primarily to protect/control runoff from rainfall. The runoff, amount of water which is recovering the surface hydrology produced by the abundance of the rainfall, is the most important part of surface water hydrology in the determination of the hydrological and the topographical parameters of the region [2]. The land area that can contribute to the runoff at any particular location is determined by the shape and topography of the surrounding region. The potential contributing area is known as the watershed and the area within over which the rainfall occurs is called the catchment area characterized by the quantity, quality, timing and distribution of run-off [3]. 1.1 Limitation The Evaluation of the Rainfall-Runoff Effects to the Variation of Hydrology of Migina Catchment in Rwanda Covers the study of rainfall and runoff availability in Migina catchment, it specify the hydrological variation based on seasonal periodic change, evaluates the performance of the catchment area on the environmental activities and studies the rainfall-runoff effect on the variation of hydrology of the catchment. American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2018) Volume 48, No 1, pp 171-185 173 1.2 Description of study area Migina catchment is meso-scale catchment of approximately 260 km2 and coordinates ranging from 2o32‟ to 2o48‟ latitude south and from 29o40‟ to 29o48‟ longitude East, contains approximately 103,000 inhabitants [4].Migina catchment, located in early southern part of our country, as shown above, is covered by three district in which (64.12 Km2) are in eastern part of Gisagara, (52.62 Km2) in southern -western of Nyaruguru and (140.52 Km2) in north-west of Huye district. Migina catchment is divided into 5 sub-catchments according to the main rivers draining area (Munyazi-Rwabuye, Mukura, Cyihene-Kansi, Akagera and Migina). The delineation of this catchment has been done by using GIS-software, Digital Elevation Model (DM) and the Topographic Map for determination of catchment area and identifying catchment characteristics [ 5]. Fig.1 shows Migina catchment boundaries: Figure 1: Hydrological network of Migina Catchment boundaries 1.3 Migina catchment land use map The vegetation has impact on the infiltration capacity; the area densely covered by vegetation produces less amount of runoff than the bare ground place. Land cover such as forest delays runoff flow on gentle slopes giving the more time to infiltrate and to evaporate [6]. American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2018) Volume 48, No 1, pp 171-185 174 Figure 2: Migina catchment land cover and land use 2. Methodology The available data used in this study in Migina catchment were provided by the Ministry of Natural Resources (MINIRENA) and Rwanda meteorological office. Some additional data like topographic map, DEM map, land use and land cover; crop factors were obtained from other institutions like, FAO, National University of Rwanda (NUR-CGIS Center) and others were collected manually. After getting all data, we did a detailed analysis with mass curve of rainfall, average annual precipitation, average monthly precipitation and daily quantity of precipitation in the catchment area. This has helped us to estimate the total volume of rainfall received in catchment during this period as given in eq. 1. Total Volume of rainfall (m3) is expressed below: (1) Where TR: Total rainfall (mm) and A is area of catchment (m2). In Migina meso–scale catchment, there are thirteen (13) rain gauges, five (5) river gauging stations with divers, two (2) evaporation pans, two (2) weather stations, three (3) tipping buckets and eleven (11) piezometers have been installed from April to July 2009 on two transactions. All these 13 stations were visited and coordinates were recorded as shown in Table 1. American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2018) Volume 48, No 1, pp 171-185 175 The variation of hydrology study (Migina catchment) is depending on the amount of rainfall (inflow) and outflow (evapo-transpiration-runoff) variability. The inflow: This is contributed by the rainfall falling in the catchment; it is calculated from data obtained at Ten stations; Sovu, Save, Mpare, Vumbi and C-GIS (Butare) Muyira, Kansi and Kibirizi, Rwasave by using Excel Software and the Theissen polygon method. Table 1: Stations installed in the Migina catchment Station Latitude(UTM) Longitude(UTM) Altitude(m) Period Collected data Rango 805464 9707671 1708 2010- 2011 Precipitation Mubumbano 803144 9705574 1808 2010- 2011 Precipitation Murama 800129 9699128 1720 2010- 2011 Precipitation Vumbi 800382 9709831 1824 2010- 2011 Precipitation Mpare 803030 9711007 1691 2010- 2011 Precipitation Sovu 800824 9717176 1764 2010- 2011 Precipitation Save B 808328 9718265 1770 2010- 2011 Precipitation Muyira 809227 9708819 1725 2010- 2011 Precipitation Kibirizi 809300 9706476 1712 2010- 2011 Precipitation Gisunzu 805956 9701364 1684 2010- 2011 Evaporation Rwasave 806184 9712510 1665 2010- 2011 Evaporation Kansi A 805555 9702817 1685 2010- 2011 Discharge CGIS(nur) 801485 9713790 1726 2010- 2011 Precipitation, Wind, To Munyazi- Rwabuye 806263 9713884 1662 2010- 2011 Discharge The outflow: was contributed by the discharge at the outlet of the catchment measured at Munyazi-Rwabuye station, Mukura station and the evapo-transpiration calculated from evaporation, measured by evaporation pan at Rwasave fishpond. American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2018) Volume 48, No 1, pp 171-185 176  Water balance of the catchment was given by eq. 2. STORAGES= INFLOWS - OUTFLOWS. ΔS =P - (ET + Q) (2) With ΔS: Storage, R: Runoff, ET: Evapo-transpiration and P: Precipitation. The rainfall has been determined by using arithmetic mean method as expressed in the equation 2.The monthly average rainfall has been calculated in Table 2 by using data recorded for period of 2 years (2010-2011) at 13 rain gages installed in Migina catchment. Table 2: Average depth method or arithmetic mean method for rainfall determination. Year Month Rango Mubumbano Murama Vumbi Mpare Sovu Save B P(mm) 2010 January 199.3 209.8 182.5 335.3 226.4 151.9 190.3 February 208.4 260.6 238.9 237.6 183.4 180.5 183.6 March 320.9 161.6 159.9 153 148 158 84.9 April 390.9 168.2 144.9 226.4 245.6 158.8 123.5 May 390.9 259.2 177.4 154 234.6 163.3 111.6 June 32 33.4 53.8 46.8 27.5 23.3 11.9 July 0 0 0 0 0 0 0 August 0 0 0 0 0 0 0 September 256.7 77.1 103 51 74.2 126.5 103.1 October 231 51.8 114.3 47.3 90.7 107.7 53.1 November 286.9 147.4 157.1 108.4 141.2 39.9 115.9 December 151.3 87.4 108.6 109.4 154 77.5 185.1 2011 January 196.2 100.8 101.6 97.9 118.2 118.2 98 February 239.3 144.7 89.8 74.4 132.9 192 150.8 March 220 130.5 178.2 126.9 132.4 126.9 123.7 April 481.7 174.2 130.5 137.2 174.8 131.1 158.1 May 383.1 170.6 192.3 169 204.1 136.6 205.2 ↓ June 0 0 68.7 0 0 0 144.8 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2018) Volume 48, No 1, pp 171-185 177 Year Month Muyira Kibirizi Gisunzu Rwasave Kansi A CGIS P(mm) 2010 January 213.6 148.9 219.7 134.4 147.1 183.2 195 February 280.2 167.9 253.5 288.7 288.2 221.2 230.2 March 229.4 134 161.4 205.5 194 154.2 174.2 April 196.1 142.6 181.8 112.6 138.8 179.4 185.3 May 214.8 176.3 141.1 172.2 166.3 198.6 196.9 June 11 7.7 27.5 17.9 37.5 17.2 26.7 July 0 0 0 0 0 0 0 August 0 0 0 0 0 0 0 September 66.9 59.1 79.4 106.3 97.8 71.4 97.8 October 62.3 45.8 45.9 92.1 52.3 69.9 82 November 172.3 99.8 120.5 138.4 89.8 114.8 133.2 December 70.1 103.2 119.6 107.2 93.6 91.9 112.2 2011 January 87 108.1 73.6 154.9 293.3 119.1 128.2 February 166.8 132.5 125 197.5 179.7 141.8 151.3 March 326.8 126.5 186.1 145.3 148.6 143.3 162.7 April 546.3 343.3 228.6 198.5 179.3 234.3 239.8 May 145.6 266.3 187.2 190.2 157.8 189 199.8 June 75.1 0 78.7 0 70.6 67.9 38.9 Total Average Monthly Rainfall obtained from gauges stations of the Catchment Departing from station monthly Rainfall. 130.78 The evapo-transpiration data were collected from Rwasave and Gisunzu stations by using evaporation class A pan and were calculated as given in eq. 3, 4 and 5. Er=K*Ep (3) PET=Kc*Epan (4) PET=0.66*Epan (5) Where; Er=Reservoir Evaporation Ep=Pan Evaporation American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2018) Volume 48, No 1, pp 171-185 178 Kc=pan coefficient and Kc=0.66. The runoff was calculated by using the rating curve method which shows relationship between discharge and water level at a given gauging station in time and the results are shown in Table 4. Table 3: Determination of E & ET at Rwasave and Gisunzu stations Station year Rwasave evaporation pan Gisunzu Evaporation pan Month E(mm) PET(mm) E(mm) PET(mm) 2010 January 134.4 88.7 134.4 88.7 February. 100.9 66.6 100.9 66.6 March 103.6 68.4 103.6 68.4 April 124.9 82.4 124.9 82.4 May 116.35 76.8 116.35 76.8 June 135.58 89.5 130.5 86.2 July 198 130.7 147 97 August 194 128.1 170 112.2 September 179.33 118.4 154.48 101.9 October 170.13 112.3 153.93 101.6 November 147.42 97.3 138.54 91.4 December 151.25 99.8 129.63 85.5 2011 January 154.92 102.3 116.61 76.9 February 183.54 121.2 127.03 83.8 March 181.29 119.6 141.17 93.3 April 98.0375 64.7 157.75 104.1 May 91.245 60.2 87.32 57.6 Average monthly 95.7 131.42 86.72 E &ET Average annual 1148.4 1577.04 1040.64 E &ET Note that the data described in given table helped to determine, by combination of all water balance components, the behavior of the hydrology of Migina catchment. American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2018) Volume 48, No 1, pp 171-185 179 Table 4: Discharge water level in selected station of Migina catchment Date Mukura river Kihene-Kansi river Munyazi- Rwabuye river Month& Av.Level Discharge Av.Level Discharge Av.Level Discharge Year H(m) Q(m3/s) H(m) Q(m3/s) H(m) Q(m3/s) Jan-10 0.74 0.44 0.52 0.51 - -- Feb-10 0.67 0.24 0.75 0.85 - -- Mar-10 0.61 0.18 0.5 0.39 -- --- Apr-10 0.66 0.24 0.51 0.43 -- -- May-10 0.75 0.39 0.52 0.49 0.69 0.06 Jun-10 0.66 0.25 0.45 0.31 0.66 0.05 Jul-10 0.61 0.17 0.39 0.26 0.53 0.03 Aug.2010 0.55 0.09 0.33 0.18 0.5 0.01 Sept.2010 0.52 0.09 0.32 0.19 0.48 0.02 Jan.2011 0.4 0.23 0.52 0.44 0.61 0.08 Feb.2011 0.67 0.24 - - -- -- Mar.2011 0.61 0.18 - - 0.7 0.14 3. Results and discussion 3.1. Investigation of hydrological data analysis From the data collected at Muyira, Mubumbano, Save, Sovu, Rango, Kansi, Kibirizi, Mpare, Vumbi, Murama, Gisunzu, Rwasave and C-GIS stations. The total rainfall volume in m3 is then determined by multiplying the monthly rainfall (mm) for all stations by corresponding area of the Migina catchment (257.4 km2). The chart shows that the maximum rainfall in Migina catchment was 230.2mm (in February2010) and 239.8mm (in April2011), the minimum is 0mm (July&August2010) and 38.9mm (June2011). So in general, the rainfall varies periodically.From the evaporation (crop) coefficient Kc (Ke) =0.66 (Table 6) and soil water stress coefficient Ks=0.83 [7], we determine the adjusted coefficient as shown in eq. 6. (climateprediction.net, 2012) Kadj=(∑Ks*Kc)/n (6) Table 5: Annual average rainfall volume in the Migina catchment Year 2010 Year 2011 Month 1 2 3 4 5 6 7 8 9 10 11 12 1 2 3 4 5 6 P(mm) 195 230 174 185 196 26 0 0 97 82 133 112 128 151 162 239 199 38 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2018) Volume 48, No 1, pp 171-185 180 Months Rainfall P(mm) Rainfall in m3 P(m3)=P(mm)*Area(m2),with 260km2 Jan-10 195 50700000 Feb-10 230.2 59852000 Mar-10 174.2 45292000 Apr-10 185.3 48178000 May-10 196.9 51194000 Jun-10 26.7 6942000 Jul-10 0 0 Aug-10 0 0 Sep-10 97.8 25428000 Oct-10 82 21320000 Nov-10 133.2 34632000 Dec-10 112.2 29172000 Jan-11 128.2 33332000 Feb-11 151.3 39338000 Mar-11 162.7 42302000 Apr-11 239.8 62348000 May-11 199.8 51948000 Jun-11 38.9 10114000 Monthly Average 130.7 34 005 111.1 Annual Average 1 569.5 408 061 333.3 Ra in fa ll P( m m ) Time (Months) 0 50 100 150 200 250 300 Rainfall P(mm) Variation in Migina Catchment Rainfall P(mm) Figure 3: Monthly average rainfall variation in Migina catchment American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2018) Volume 48, No 1, pp 171-185 181 Table 6: Crop adjusted coefficient Table 7 shows that the evapo-transpiration at Rwasave is monthly varied and the monthly average rainfall is 52.6mm with the annual average rainfall of 631.2mm which is different from 917mm/year what found by Bizirema 2011. This difference shows that it varies with respect to period and used method. The diagram of monthly evaporation and evapo-transpiration variation is drawn below: & E va p or at io n (m m E va p ot ra n sp ir at io n (m m Time(Months) 0 20 40 60 80 100 120 140 EVAPORATION EVAPOTRANSPIRATION Figure 4: Evaporation-evapo-transpiration variability in the Migina (Rwasave evaporation pan) Crop Kc&Ke Kadj=(Kc*Ks)/n Rice 1 0.83 Sorghum 0.25 0.21 Tomatoes 0.22 0.18 Beans 0.76 0.63 Soybeans 0.95 0.78 Cotton 0.5 0.41 Maize 0.2 0.17 Sugarcane 0.8 0.66 Banana 0.65 0.53 Cassava 1.05 0.87 Forest 1 0.83 Sweet potatoes 0.9 0.75 Open ground 0.3 0.25 Kadj= (7.1/13)=0.55 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2018) Volume 48, No 1, pp 171-185 182 Table 7: Actual evapo-transpiration in the Migina catchment. Months Rwasave Evaporation pan Gisunzu Evaporation pan Eref(mm) AET=Eref*Kadj (mm) AET(m3)= Eref(mm) AET=Eref*K (mm) AET(m3)= AET*A(m2) AET*A(m2) Jan-10 88.7 48.8 12 688 000 88.7 48.8 12 688 000 February 66.6 36.6 9 516 000 66.6 36.6 9 516 000 March 68.4 37.6 9776000 68.4 37.6 9776000 April 82.4 45.3 11778000 82.4 45.3 11778000 May 76.8 42.3 10998000 76.8 42.3 10998000 June 89.5 49.3 12818000 86.2 47.4 12324000 July 130.7 71.9 18694000 97 53.4 13884000 August 128.1 70.5 18330000 112.2 61.7 16042000 September 118.4 65.1 16926000 101.9 56.1 14586000 October 112.3 61.8 16068000 101.6 55.9 14534000 November 97.3 53.5 13910000 91.4 50.3 13078000 December 99.8 54.9 14274000 85.5 47.1 12246000 Jan-11 102.3 56.3 14638000 76.9 42.3 10998000 February 121.2 66.7 17342000 83.8 46.1 11986000 March 119.6 65.8 171080000 93.2 51.3 13338000 April 64.7 35.6 9256000 104.1 57.3 14898000 May 60.2 33.2 8632000 57.6 31.7 8242000 Monthly Average 95.7 52.6 21442353 86.72 55.5 11100471 Annual Average 1148.4 631.2 257308235 1040.64 666.1 133205647 Ev ap or at io n (m m )& E va po tr an sp ir at io n( m m Time in Months 0 20 40 60 80 100 120 Evaporation Evapotranspiration Figure 5: Evaporation-evapo-transpiration variability in Migina (Gisunzu-evaporation pan). American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2018) Volume 48, No 1, pp 171-185 183  Figure 4 shows that from Rwasave, the evaporation and evapo-transpiration are monthly varied. The maximum evapo-transpiration was 71.9mm (in July2010) and 66.7mm (Feb 2011), the minimum was 36.6mm (in February 2010) and 33.2mm ( in May 2011).The evapo-transpiration from Gisunzu station is drawn in Figure 5. 3.2. Effect of seasonal hydrological variation on catchment’s environment The variation of hydrology of the catchment depends on availability and/or scarcity of rainfall, runoff and storage quantity. The stored water determines how much water table is raised on. This has a strong effect on crop rooting zone and favors the time-period for agricultural activity. Table 8: Seasonal variation of the hydrology in Migina catchment Seasons in Rain season1 Dry season1 Rain season2 Dry season2 Annually Catchment balance Year (Sept- November) (December- February) March- May June- August) Rainfall P(mm) 325.2 391.7 1158.7 65.6 2001.9 Evapo- transpiration 273.3 293.1 525.3 354.2 1445.9 ETC(mm) Runoff 4.5x10-3 33.5x10-3 28.9x10-3 23x10-3 89.9x10-3 Q(mm) Change in Storage(mm) 150.69 59.26 633.4 -288.6 554.75 Change in Storage(m3) 39179 400 15 407 600 164 684 000 -75 036 000 144235000 Table 8 shows that when rainfall increases, it increases either runoff or infiltration capacity contrary to its decreasing, so is the hydrology variation. This variation affects not only the hydrology but also the environment in general through flooding, drainage capacity requirements and the hydraulic structures for the public health safety and agricultural purpose. 3.3. Generation rating curve To establish a relationship between discharge and water levels for Munyazi/Rwabuye river in Migina catchment, several discharge measurements were carried out at the gauging stations at different water levels. Munyazi River from January 2010 to March 2011, the corresponding discharge is determined by eq. 7. Y=01.009X0.183 (7) American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2018) Volume 48, No 1, pp 171-185 184 Where Y represents water level and X represents discharge. Figure 6: Water Level Vs Discharge at Munyazi-Rwabuye gauging station Figure 7: Munyazi river discharge measurement and rainfall records (photo taken by eng. Theoneste T. on 28/12/2017, 10:00am) 4. Concluding remarks The hydro-meteorological data in Rwanda are scarce in time and space with many data gaps due to historical challenges (genocide war, poor filing and data management system). Based on data taken from 2009 to 2011 at different stations installed in Migina catchment (214 km2) and different visits done to the area in which the research has been conducted, the analysis has been done to determine monthly and annual rainfall, runoff, evapotranspiration and change in storage and the results were presented in various tables. Some of materials used in data collection, shape files of Migina catchment were presented through different figures. Photos taken in different media during the field works were presented and the results were interpreted on different charts. The interpretation and analysis done through all catchment show that total monthly and annual average rainfall in the Migina catchment are respectively 130.78mm and 408 033 600m3. Total monthly and annual runoff are 2247.44m3and 26 968.5m3. Total monthly and annual evapo-transpiration are respectively 32542823.4m3 and 390 513 882.4m3 and by using equation 10, the total annual storage of the catchment is found to be 17 492 American Scientific Research Journal for Engineering, Technology, and Sciences (ASRJETS) (2018) Volume 48, No 1, pp 171-185 185 749.1m3. 5. Recommendations It is recommended to contribute to the amelioration of Agricultural activities to increase the Rwandan primary sector production and sensitize the population on Rwanda seasonal changes and good governmental catchment protection plan. Acknowledgements This work was conducted in collaboration with a number of staff from the University of Rwanda and Rwanda polytechnic (Kigali and Ngoma colleges). The work was financially supported by a Student Funding Agency of Rwanda (SFAR) awarded to the second author through University of Rwanda. Authors thank the Rwanda Meteorological Agency, the Rwanda Water and Forestry Authority and the UR Center of GIS for providing data used in this study. References [1] F. Ufiteyezu, Prediction of Migina River Discharge in Contribution to hydrometeorology in Rwanda, NUR, 2010 [2] F.O.K. Anyemedu, Hydraulic structure, published lecture notes, National University of Rwanda (NUR), Butare, 2008. [3] K.C. Patra, Hydrology &Water Resource Engineering ,2nd Ed. Amsterdam, 1999. [4] J. Nyirajana, Rainfall and Runoff Relationship in Migina catchment, NUR-Butare, 2011. [5] W. C. William, Groundwater Resources Evaluation, 1995. [6] R. Dusangwe, Hydrologic Cycle in Karubanda Marshland, NUR-Butare, 2011. [7] [Online], Available: www.meteorwanda.gov.rw. (2008, August wednesday). Home. Retrieved November Monday, 2008, from http:// www.meteorwanda.gov.rw: 00-1244-3-11 [Accessed Apr. 18, 2012]. [8] [Online], Available: www.climateprediction.net. (2012, April Wednesday). Home. Retrieved Wednesday, 2012, from www.climateprediction.net [Accessed May 11, 2012]. The rainfall has been determined by using arithmetic mean method as expressed in the equation 2.The monthly average rainfall has been calculated in Table 2 by using data recorded for period of 2 years (2010-2011) at 13 rain gages installed in Migina c... Table 6: Crop adjusted coefficient Figure 5: Evaporation-evapo-transpiration variability in Migina (Gisunzu-evaporation pan).  Figure 4 shows that from Rwasave, the evaporation and evapo-transpiration are monthly varied. The maximum evapo-transpiration was 71.9mm (in July2010) and 66.7mm (Feb 2011), the minimum was 36.6mm (in February 2010) and 33.2mm ( in May 2011).The eva... 3.2. Effect of seasonal hydrological variation on catchment’s environment [7] [Online], Available: www.meteorwanda.gov.rw. (2008, August wednesday). Home. Retrieved November Monday, 2008, from http:// www.meteorwanda.gov.rw: 00-1244-3-11 [Accessed Apr. 18, 2012]. [8] [Online], Available: www.climateprediction.net. (2012, April Wednesday). Home. Retrieved Wednesday, 2012, from www.climateprediction.net [Accessed May 11, 2012].