CIGR Ejournal Style and Format Guidelines ARID ZONE JOURNAL OF ENGINEERING, TECHNOLOGY & ENVIRONMENT AZOJETE - CIGR Section VI Special Issue: Innovation & Technologies for Sustainable Agricultural Production & Food Sufficiency AZOJETE, December, 2018. Vol. 14(SP.i4): 237-246 Published by the Faculty of Engineering, University of Maidiguri, Maidiguri, Nigeria. Print ISSN: 1596-2490, Electronic ISSN: 2545-5818 www.azojete.com.ng Corresponding Author’s Email: adeyadey_77@yahoo.com 237 ORIGINAL RESEARCH ARTICLE DETERMINATION OF WATER PRODUCTIVITY OF CASSAVA IN IBADAN, SOUTH WESTERN NIGERIA A. M. Aderemi*1, T. A. Ewemoje2, J. O. Adedipe1, I. O. Oyewo1 and L. A. Balogun3 1. Agricultural Technology Department, Federal College of Forestry Ibadan. 2.Department of Agricultural and Environmental Engineering, University of Ibadan, Ibadan, Oyo State. 3.Department of Agricultural and Bio Environmental Engineering, Oyo State College of Agriculture and Technology, Igboora, Oyo State. ARTICLE INFORMATION Received: October, 2018 Accepted: December, 2018 Keywords: Water productivity Cassava effective rainfall Cropwat rainfall data Nigeria ABSTRACT The response of yields to the actual water (effective rainfall) used by cassava, was the main area of study of this project. A twenty data point (20 years) was processed using CROPWAT 8.0 model using fixed percentage (80%) method, the model was used to run the 20 years daily rainfall data collected from NIMET (Nigeria Meteorological Agency) Oyo State from 1994 to 2013 (20 years) while the cassava yield was collected from FAOSTAT website. The rainfall pattern for the annual period of cultivation for cassava was determined through the planting and dates of the crop. The results of the annual water productivity values show that there was a very low water productivity of 0.9kg/m3 in 2012 while 2013 recorded the highest water productivity of 2.2 kg/m3. The early planting of cassava after rainfall started in the month of March which contributed to the high yield recorded in 2010, 2011 and 2013. The poor performance of cassava in 2012 could be due to the following; the variety used, the soil type, the plant’s age at harvest, and the rainfall intensity and distribution during that particular year. The trend of the results was used to determine the alternative cost of water if the farm would be fully irrigated. It was gathered that 7000 litres of untreated water would be supplied to any farthest location at ₦ 12,000. Therefore, the cost was determined based on the yield and the water used annually. . © 2018 Faculty of Engineering, University of Maiduguri, Nigeria. All rights reserved http://www.azojete.com.ng Aderemi et al.: Determination of water productivity of cassava in Ibadan, south western Nigeria. AZOJETE, 14(sp.i4): 237-246. ISSN 1596-2490; e-ISSN 2545-5818, www.azojete.com.ng Corresponding Author ‘s: Email: adeyadey_77@yahoo.com 238 1.0 Introduction Cassava (Manihot esculenta) is extensively cultivated as an annual crop in tropical and subtropical regions for its edible starchy tuberous root, a major source of carbohydrates. Cassava is the third largest source of food carbohydrates in the tropics, after rice and maize, (FAO, 1995). Cassava is a major staple food in the developing world, providing a basic diet for over half a billion people. It is one of the most drought-tolerant crops, capable of growing on marginal soils. Nigeria is the world's largest producer of cassava, while Thailand is the largest exporter of dried cassava. Cassava is important source of food in the tropics. The cassava plant gives the third highest yield of carbohydrates per cultivated area among crop plants, after sugarcane and sugar beets. It plays a particularly important role in agriculture in developing countries, especially in sub-Saharan Africa, because it does well on poor soils and with low rainfall. Water is the most common liquid on our planet, essential to all life forms and it is also important for crop need. The need of water is increasing sharply throughout the world which is one of the most burning issues of current time. Fresh water resources are depleting due to global climatic changes, rash use of surface water, and misuse of ground water and fast increasing industrial pollution. World need for food and crop demand is increasing day by day because of rapid increase in population. (Bastiaanssen et al., 2000). As competition for increasingly scarce water resources intensifies, irrigation is under growing pressure to produce “more crops from fewer drops” and to reduce its negative environmental impacts, including soil salinization and nitrate contamination of drinking water. Greater use of water-saving precision technologies, such as drip and micro-irrigation, will make an important contribution to sustainable intensification. Irrigation water requirements are particularly abundant in the works under several surfaces, crop water requirements, crop yield and evapotranspiration as influenced by water accessibility, crop water modeling and irrigation scheduling techniques. Then this consistent data and evapo-transpiration (ETo) through CROPWAT model can be utilized to estimate the contribution of rainfall towards crop water requirement to determine that how much irrigation is required to enhance the productivity. CROPWAT is one of the models extensively used in the field of water management throughout the world. It is an application software used for irrigation planning and management. It facilitates the estimation of the crop evapotranspiration, irrigation schedule, crop water requirement and yield reduction under varying weather conditions (FAO, 2000). Rainfall determines the potential of any region in term of crops to be produced, farming system to be adopted, the nature and sequence of farming operations to be followed and to achieve higher agricultural productivity. The objectives of this study were therefore to estimate the effective rainfall using CROPWAT 8.0 model, evaluate the crop water productivity of cassava on annual basis https://en.wikipedia.org/wiki/Agriculture https://en.wikipedia.org/wiki/Tropical https://en.wikipedia.org/wiki/Subtropical https://en.wikipedia.org/wiki/Starch https://en.wikipedia.org/wiki/Tuberous_root https://en.wikipedia.org/wiki/Carbohydrate https://en.wikipedia.org/wiki/Rice https://en.wikipedia.org/wiki/Maize https://en.wikipedia.org/wiki/Carbohydrates https://en.wikipedia.org/wiki/Sugarcane https://en.wikipedia.org/wiki/Sugar_beet http://www.azojete.com.ng mailto:adeyadey_77@yahoo.com Arid Zone Journal of Engineering, Technology and Environment, December, 2018; Vol. 14(sp.i4): 237-246. ISSN 1596-2490; e-ISSN 2545-5818; www.azojete.com.ng 239 for the period of twenty (20) years and calculate the cost of alternative water used for cassava production for the entire period of twenty years on annual basis. Among the models, CROPWAT has been the most widely used for estimation of evapotranspiration and crop water requirement. Since there are few weather stations in the study areas, data required for the Penman-Monteith method has normally been extrapolated from representative weather stations nearby. The weather data available for this study will be processed using CROPWAT to estimate evapotranspiration and crop water requirement. 2.0 Materials and Methods The study was carried out using Ibadan (Nigeria) as a case study area. Ibadan lies approximately between latitude 7039I N and longitude 30 90I E of Nigeria and altitude 238m above the sea level (Google earth). The area lies within the southwest savannah zone of Nigeria. The average length of the dry season is about 121-151 days (October to March) during which little or no precipitation occurs. Means daily air temperatures (minimum and maximum) range between 23.60C and 33.20C. The wind speed ranges from 50.3 km/day in December to 735 km/day in April, with a north eastern to south western wind direction dominating from November through April. The soil is a medium loam, which has developed on deeply weathered Pre-Cambrian Basement Complex rocks but overlain by Aeolian drift of varying thickness (Ogunwole, 2000). 2.1 Climatic Data The climatic data used for this work were obtained from the data files of Ibadan over a period of Twenty years (1994-2013) from the Nigerian Meteorological Agency (NIMET) and was imputed into CROPWAT-8.0 for windows. The weather data are being generated from the automatic weather station of the agency (NIMET), which relatively records accurate climatic data of its environments. 2.2 Cassava Yield Data The cassava yield data used for this study for the period of twenty years (1994-2013) was obtained from Food and Agriculture Organization Statistics (FAOSTAT, 2015). The data was calculated per hectare on annual basis. 2.3 Determination of Reference Crop Evapotranspiration The Reference Evapotranspiration (ETo) represents the potential evaporation of a well- watered grass crop. The water needs of other crops are directly linked to this climate parameter (Mohammed, 2009). In order to calculate reference evapotranspiration (ETo), the respective climate data should be collected from the nearest and the most representative meteorological stations. Several institutes and agencies may keep climatic records such as the Irrigation Department, the file:///C:/Users/user/Downloads/azojete143/www.azojete.com.ng Aderemi et al.: Determination of water productivity of cassava in Ibadan, south western Nigeria. AZOJETE, 14(sp.i4): 237-246. ISSN 1596-2490; e-ISSN 2545-5818, www.azojete.com.ng Corresponding Author ‘s: Email: adeyadey_77@yahoo.com 240 Meteorological Service or nearby Agricultural Research Stations and may provide information on climatic stations inside or in its vicinity (Allen et al., 1998). For this work, the data have been obtained from both the automatic weather station of NIMET and FAOSTAT. Daily climatic data of the year 1994-2013 were used. The climatic data used is rainfall data and the second data used was the cassava yield data. Although several methods exist to determine ETo, the Penman-Monteith Method has been recommended as the appropriate combination method with the climatic data; temperature, sunshine, humidity, windspeed, (FAO, 1998). The FAO Penman-Monteith method to estimate ETo is expressed as;      2 2 34.01 273 900408.0 u eeu T GR ETO asn        (1) Where: ETO = Reference evapotranspiration (mm day-1) Rn = Net radiation at the crop surface (MJ m-2 day-1) G = Soil heat flux density (MJ m-2 day-1) T = Mean daily air temperature at 2 m height (oC) µ2 = Wind speed at 2 m height (ms-1) es = Saturation vapour pressure (kPa) ea = Actual vapour pressure (kPa) Δ = Slope vapour pressure curve (kPa oC-1 ) = Psychrometric constant (kPa oC-1) For this project, The United States Department of Agriculture, Soil Conservation Service method on CROPWAT-8 was used to determine the effective rainfall on monthly basis which accumulated to annual effective rainfall. The USDA, SCS method for calculation of effective rainfall is described in a FAO publication (Dastane, 1978). The method is implemented in models for planning and management of irrigation as the CROPWAT model, where the USDA, SCS method is the default method for calculation of effective rainfall among other four methods (Marica, 2013). 2.4 Determination of Cassava Crop Water Productivity Water Productivity is more directly linked to overall ambitions in water-scarce or water- costly situations than in systems which are supplied with plentiful, low value water. WP is most meaningful as an indicator as water resources become increasingly scarce. Assessment may be required for the whole system or parts of it, defined in time and space with the formula below, consumedorusedwater producealAgriculturWP  (2) http://www.azojete.com.ng mailto:adeyadey_77@yahoo.com Arid Zone Journal of Engineering, Technology and Environment, December, 2018; Vol. 14(sp.i4): 237-246. ISSN 1596-2490; e-ISSN 2545-5818; www.azojete.com.ng 241 In this project, the annual agricultural yield or benefit of cassava was obtained from the FAOSTAT for the period of twenty years (1994-2013) on yearly basis and the rainfall data obtained from NIMET was processed to determine the amount of water required by the plant at that particular period of time or Water Used or Consumed. With the equation 2 above, the annual water productivity was calculated for the specified period of time. Due to the water productivity calculated, it was easy to predict the amount of water that will be needed in the cassava production annually. 2.5 Cost of Water Applied Economics of water contributes towards improved allocations of water and the costs of water used and also the full social benefits of the goods and services that water provides. In this study, the cost of the quantity of water used was determined by considering the cost of water supply by the water tankers from the Oyo State Water Corporation, Eleyele, Ibadan. It was discovered that the price for which the water is delivered depends on the distance. Therefore, for the farthest location supply of 7,000 litres of untreated water, the cooperation charges ₦12,000. With this knowledge, the quantity of water used annually from 1994 to 2013 was calculated annually. This also helps to predict and have the foreknowledge of the amount of money to be spent on irrigation or supply of water if the cassava production is on the large scale, particularly for exportation. 3.0 Results and Discussion Table1 below shows the rainfall pattern based on the planting and harvesting dates of cassava for the period of 20 years. From the rainfall pattern it was seen that it took nine (9) months for the cassava to germinate, some were assumed planted early while some were planted late based on the daily rainfall data obtained. Figures1, 2 and 3 below shows effective rainfall versus cassava yield; water productivity and cost of alternative water for irrigation respectively. file:///C:/Users/user/Downloads/azojete143/www.azojete.com.ng Aderemi et al.: Determination of water productivity of cassava in Ibadan, south western Nigeria. AZOJETE, 14(sp.i4): 237-246. ISSN 1596-2490; e-ISSN 2545-5818, www.azojete.com.ng Corresponding Author ‘s: Email: adeyadey_77@yahoo.com 242 Table 1: Rainfall pattern during cassava cultivation period Year Mar Apr May June July Aug Sept Oct Nov Dec Jan Total Rainfall (mm) (mm) (mm) (mm) (mm) (mm) (mm) (mm) (mm) (mm) (mm) (mm) 1994 - 88.9 301.2 63.6 164.0 67.0 211.5 246.6 19.5 0.0 - 1,162.3 1995 127.8 81.3 146.7 129.9 220.7 260.1 139.3 213.1 20.2 - - 1,339.1 1996 - 122.1 188.3 231.4 116.9 161.4 226.5 84.9 0.0 0.4 - 1,131.9 1997 - 141.9 104.7 154.1 63.6 98.8 151.7 170.5 1.6 9.0 - 895.9 1998 - 126.9 198.5 259.5 114.2 177.3 80.3 263.4 0.0 0.0 - 1,220.1 1999 - - 189.8 226.9 230.3 162.7 149.5 154.9 24.4 0.0 19.0 1,157.5 2000 - - 112.6 104.0 149.8 183.6 241.0 144.2 19.6 0.0 18.8 973.6 2001 - - 145.9 194.2 93.5 52.1 229.1 63.0 1.9 0.2 1.0 780.9 2002 - 79.4 116.6 189.3 180.3 168.9 62.6 254.4 74.1 0.0 - 1,125.6 2003 - 101.0 129.4 203.7 205.7 107.6 283.8 153.8 39.9 0.0 - 1,224.9 2004 - 55.0 181.4 223.6 100.6 136.5 142.0 228.5 0.7 0.0 - 1,068.3 2005 - 123.0 111.1 165.2 152.4 92.5 352.7 160.6 3.7 0.0 - 1,161.2 2006 - 67.1 107.6 167.1 98.8 104.9 148.8 188.0 256.1 4.9 - 1,143.3 2007 - 65.9 176.6 229.4 133.3 356.6 178.4 168.8 71.5 10.8 - 1,391.3 2008 - 98.7 64.9 204.3 283.5 161.9 199.7 92.9 0.0 24.7 - 1,130.6 2009 - 104.4 130.8 146.7 229.4 74.3 111.5 117.8 2.1 0.0 - 917.0 2010 131.6 70.8 204.4 167.4 107.1 205.7 256.5 240.5 101.4 - - 1,485.4 2011 38.6 36.2 68.6 143.3 140.5 308.1 244.6 163.6 0.6 - - 1,144.1 2012 38.4 214.6 221.1 145.5 87.7 104.4 190.3 182.5 15.7 - - 1,200.2 2013 37.3 67.2 105.2 124.5 126.4 10.6 128.5 163.7 29.8 - - 793.2 Figure 1: Effective rainfall versus cassava yield. 3.1 Water Productivity The figure 2 below shows the trend of water productivity across the years (1994 - 2013). Total rainfall values was computed from the weather station for a period of twenty (20) years in order to estimate the amount of rainfall that was recorded on yearly basis. Also to know the trend of rainfall that was recorded for 20 years. Effective rainfall was computed from CROPWAT 8.0 using fixed percentage (80%) method. From the data collected, maximum rainfall was recorded in the 17th year (March 7 – November 12) with a value of http://www.azojete.com.ng mailto:adeyadey_77@yahoo.com Arid Zone Journal of Engineering, Technology and Environment, December, 2018; Vol. 14(sp.i4): 237-246. ISSN 1596-2490; e-ISSN 2545-5818; www.azojete.com.ng 243 1485.4mm, while the minimum value was recorded in the 8th year (May 10 – January 10) with a value of 780.9mm. Effective rainfall was computed in order to know the amount of water in terms of rainfall that is available for the crop (cassava). The maximum and minimum values for effective rainfall were 1037.1mm and 577.8mm respectively. Table 2: Water productivity table between 1994-2013 (20 Years) Total Effective Cassava Effective Effective Water Year Planting Harvesting Rainfall Rainfall Yield Rainfall Rainfall Prod. Date Date (mm) (mm) (Kg/Ha) (mm3/Ha) (m3) (Kg/m3) 1994 April 20th Dec. 23rd 1162.3 777.4 10592.8 7774000 7774 1.362593 1995 Mar. 15th Nov. 17th 1339.1 949.6 10667.1 9496000 9496 1.123326 1996 April 20th Dec. 22nd 1131.9 808.5 10664.6 8085000 8085 1.31906 1997 April 5th Dec. 10th 895.9 702.6 11881.8 7026000 7026 1.691119 1998 April 15th Dec. 20th 1220.1 829.2 10746.1 8292000 8292 1.29596 1999 May 5th Jan. 10th 1157.5 814.6 9599.8 8146000 8146 1.178468 2000 May 10th Jan. 17th 973.6 718.8 9700 7188000 7188 1.349471 2001 May 9th Jan. 10th 780.9 577.8 9601.2 5778000 5778 1.661682 2002 April 25th Dec. 27th 1125.6 819.8 9901.3 8198000 8198 1.20777 2003 April 15th Dec. 20th 1224.9 858.4 10402.3 8584000 8584 1.211824 2004 April 22th Dec. 28th 1068.3 769 11001.1 7690000 7690 1.430572 2005 April 16th Dec. 21th 1161.2 789 10990.2 7890000 7890 1.392928 2006 April 18th Dec. 27th 1143.3 842.2 12000.3 8422000 8422 1.424875 2007 April 16th Dec. 17th 1391.3 921 11202.6 9210000 9210 1.216352 2008 April 15th Dec. 20th 1130.6 790.8 11800.4 7908000 7908 1.49221 2009 April 19th Dec. 11th 917 702.6 11767.9 7026000 7026 1.674907 2010 March 7th Nov. 12th 1485.4 1037.1 12215.5 10371000 10371 1.177852 2011 March 27th Nov. 30th 1144.1 776.8 11210.8 7768000 7768 1.443203 2012 March 30th Nov. 27th 1200.2 870.7 7958.5 8707000 8707 0.914035 2013 March 26th Nov. 30th 793.2 644.8 13947.4 6448000 6448 2.163058 Figure 2: Water productivity file:///C:/Users/user/Downloads/azojete143/www.azojete.com.ng Aderemi et al.: Determination of water productivity of cassava in Ibadan, south western Nigeria. AZOJETE, 14(sp.i4): 237-246. ISSN 1596-2490; e-ISSN 2545-5818, www.azojete.com.ng Corresponding Author ‘s: Email: adeyadey_77@yahoo.com 244 3.2 Cost of Alternative Water Table 3: Annual water cost Cassava Effective Effective Cost of water Year Yield Rainfall Rainfall Used (Kg/Ha) (m3) (litre) (₦) 1994 10592.8 7774 7774000 13324636 1995 10667.1 9496 9496000 16276144 1996 10664.6 8085 8085000 13857690 1997 11881.8 7026 7026000 12042564 1998 10746.1 8292 8292000 14212488 1999 9599.8 8146 8146000 13962244 2000 9700.0 7188 7188000 12320232 2001 9601.2 5778 5778000 9903492 2002 9901.3 8198 8198000 14051372 2003 10402.3 8584 8584000 14712976 2004 11001.1 7690 7690000 13180660 2005 10990.2 7890 7890000 13523460 2006 12000.3 8422 8422000 14435308 2007 11202.6 9210 9210000 15785940 2008 11800.4 7908 7908000 13554312 2009 11767.9 7026 7026000 12042564 2010 12215.5 10371 10371000 17775894 2011 11210.8 7768 7768000 13314352 2012 7958.5 8707 8707000 14923798 2013 13947.4 6448 6448000 11051872 Figure 3: Cost of water The maximum yield of cassava in kg/ha was recorded to be 13,947.40 as at the 20th year (2013) which was planted on the 26th of March and harvested on the 30th of November, with an effective rainfall of 644.8mm. Based on the trend of data collected, it shows that the maximum yield was recorded when we observed low rainfall which can be linked to the cost of water that can be used in replacement for effective rainfall (irrigation). http://www.azojete.com.ng mailto:adeyadey_77@yahoo.com Arid Zone Journal of Engineering, Technology and Environment, December, 2018; Vol. 14(sp.i4): 237-246. ISSN 1596-2490; e-ISSN 2545-5818; www.azojete.com.ng 245 From the figure above, the cost of water used in replace of rainfall on yearly basis (i.e. 1994 – 2013). The maximum cost of water used was observed on year 17 (2010) with the maximum price of 17,775,894. The minimum cost of water used was observed on year 8 (2001) with the minimum price of 9,903,492. These costs are important to determine so that it could be valued along with the main cost of cassava like in the determination of virtual water. This is applicable mostly in countries like Israel where water is very scarce. When cassava is produced, the value of the cost of water used for the production is added to the selling price in case of export. Similar thing should be employed here so as to attach value to our water. Planting early in the rainy season will generally produce the highest yields as shown in Table 2. All the cassava planted early in the month of march in the 1995, 2010, 2011 and 2013 had a better yield compare to others except in some few occasions and this was due to the fact that the plants have adequate soil moisture during the most critical part of their growth cycle. However, research has shown that yields can vary according to the variety used, the soil type, the plant’s age at harvest, and the rainfall intensity and distribution during any particular year. One or more of the aforementioned factors could be responsible for the low yield in 2012. 4.0 Conclusion and Recommendation Based on the yield shown above, effective rainfall and water productivity observed to be maximum in the 20th year (2013), the cost of water was calculated to be ₦11,051,872 in which the costs is low compare to other years. This amount can be used to purchase water need for cultivation of cassava in dry season when irrigation is needed in order to obtain maximum yield. The cost of water used can also be used to calculate the concept of virtual water. It is strongly recommended that other parameters like sunshine hour, temperature etc, should also be put into consideration in determining the water productivity for the production of cassava as this will shed more light on the crop yield to water use relationship. Since the effective rainfall was determined using Cropwat 8.0 model, it is advised to use other models rainfall data for this study. It is as well recommended that federal government parastatals and research institutes should be willing to assist in researches by their willingness to release data and useful materials to assist in further research works. References Allen, RG., Pereira, LS., Raes, D. and Smith, M. 1998. Crop Evapotranspiration; Guidelines for Computing Crop Water Requirements. FAO, Irrigation and Drainage Paper No.56. Rome, Italy. pp 300. file:///C:/Users/user/Downloads/azojete143/www.azojete.com.ng Aderemi et al.: Determination of water productivity of cassava in Ibadan, south western Nigeria. AZOJETE, 14(sp.i4): 237-246. ISSN 1596-2490; e-ISSN 2545-5818, www.azojete.com.ng Corresponding Author ‘s: Email: adeyadey_77@yahoo.com 246 Bastiaanssen, WGM., David, JM. and Ian, WM. 2000. Remote Sensing for Irrigated Agriculture: Examples from Research and Possible Applications, Agriculture Water Management, 46:137-155. Dastane, NG. 1978. Effective Rainfall in Irrigated Agriculture; Irrigation and Drainage Paper 25; Food and Agriculture Organisation: Rome, Italy. Food and Agriculture Organization (FAO) 2000. CROPWAT, a Computer Program for Irrigation Planning and Management. Author; Smith, M. Irrigation and Drainage Paper 256; pp 340-570. Food and Agriculture Organization of the United Nations (FAO) 1995. "Dimensions of Need: An Atlas of Food and Agriculture" Marica, A. 2013. Short Description of the CROPWAT Model. http://agrometcost.bo.ibimet.cnr.it/fileadmin/cost718/repository/cropwat.pdf. (April 15, 2013) Mohammed N. 2009. Simulation of Maize Crop under Irrigated and Rainfed Conditions with CROPWAT. ARPN Journal of Agricultural and Biological Science. Vol. 3: No. 2. pp 200-241. Ogunwole, 2000. A Critical Evaluation of Traits of Improving Yields in Water-Limited Environments. ARPN Journal of Agricultural and Biological Science Vol. 4; pp 107-149. http://www.fao.org/docrep/u8480e/U8480E01.htm http://www.fao.org/docrep/u8480e/U8480E01.htm http://agrometcost http://www.azojete.com.ng mailto:adeyadey_77@yahoo.com 1.0Introduction Cassava (Manihot esculenta) is extensively cultiva Cassava is a major staple food in the developing w Water is the most common liquid on our planet, ess As competition for increasingly scarce water resou Irrigation water requirements are particularly abu Among the models, CROPWAT has been the most widely 2.0Materials and Methods The study was carried out using Ibadan (Nigeria) a 2.1 Climatic Data The climatic data used for this work were obtained 2.2 Cassava Yield Data The cassava yield data used for this study for the 2.3 Determination of Reference Crop Evapotranspir The Reference Evapotranspiration (ETo) represents In order to calculate reference evapotranspiration For this work, the data have been obtained from bo Although several methods exist to determine ETo, t The FAO Penman-Monteith method to estimate ETo is (1) Where: ETO = Reference evapotranspiration (mm day-1) Rn = Net radiation at the crop surface (MJ m-2 day G = Soil heat flux density (MJ m-2 day-1) T = Mean daily air temperature at 2 m height (oC) µ2 = Wind speed at 2 m height (ms-1) es = Saturation vapour pressure (kPa) ea = Actual vapour pressure (kPa) Δ = Slope vapour pressure curve (kPa oC-1 ) = Psychrometric constant (kPa oC-1) For this project, The United States Department of 2.4 Determination of Cassava Crop Water Productiv Water Productivity is more directly linked to over In this project, the annual agricultural yield or 2.5 Cost of Water Applied Economics of water contributes towards improved al In this study, the cost of the quantity of water u 3.0Results and Discussion Table1 below shows the rainfall pattern based on t Figures1, 2 and 3 below shows effective rainfall v Table 1: Rainfall pattern during cassava cultivati Year Mar Apr May June July Aug Sept Oct Nov Dec Jan Total Rainfall (mm) (mm) (mm) (mm) (mm) (mm) (mm) (mm) (mm) (mm) (mm) (mm) 1994 - 88.9 301.2 63.6 164.0 67.0 211.5 246.6 19.5 0.0 - 1,162.3 1995 127.8 81.3 146.7 129.9 220.7 260.1 139.3 213.1 20.2 - - 1,339.1 1996 - 122.1 188.3 231.4 116.9 161.4 226.5 84.9 0.0 0.4 - 1,131.9 1997 - 141.9 104.7 154.1 63.6 98.8 151.7 170.5 1.6 9.0 - 895.9 1998 - 126.9 198.5 259.5 114.2 177.3 80.3 263.4 0.0 0.0 - 1,220.1 1999 - - 189.8 226.9 230.3 162.7 149.5 154.9 24.4 0.0 19.0 1,157.5 2000 - - 112.6 104.0 149.8 183.6 241.0 144.2 19.6 0.0 18.8 973.6 2001 - - 145.9 194.2 93.5 52.1 229.1 63.0 1.9 0.2 1.0 780.9 2002 - 79.4 116.6 189.3 180.3 168.9 62.6 254.4 74.1 0.0 - 1,125.6 2003 - 101.0 129.4 203.7 205.7 107.6 283.8 153.8 39.9 0.0 - 1,224.9 2004 - 55.0 181.4 223.6 100.6 136.5 142.0 228.5 0.7 0.0 - 1,068.3 2005 - 123.0 111.1 165.2 152.4 92.5 352.7 160.6 3.7 0.0 - 1,161.2 2006 - 67.1 107.6 167.1 98.8 104.9 148.8 188.0 256.1 4.9 - 1,143.3 2007 - 65.9 176.6 229.4 133.3 356.6 178.4 168.8 71.5 10.8 - 1,391.3 2008 - 98.7 64.9 204.3 283.5 161.9 199.7 92.9 0.0 24.7 - 1,130.6 2009 - 104.4 130.8 146.7 229.4 74.3 111.5 117.8 2.1 0.0 - 917.0 2010 131.6 70.8 204.4 167.4 107.1 205.7 256.5 240.5 101.4 - - 1,485.4 2011 38.6 36.2 68.6 143.3 140.5 308.1 244.6 163.6 0.6 - - 1,144.1 2012 38.4 214.6 221.1 145.5 87.7 104.4 190.3 182.5 15.7 - - 1,200.2 2013 37.3 67.2 105.2 124.5 126.4 10.6 128.5 163.7 29.8 - - 793.2 Figure 1: Effective rainfall versus cassava yield. 3.1Water Productivity The figure 2 below shows the trend of water produc Total rainfall values was computed from the weathe Table 2: Water productivity table between 1994-20       Total Effective Cassava Effective Effective Water Year Planting Harvesting Rainfall Rainfall Yield Rainfall Rainfall Prod.   Date Date (mm) (mm) (Kg/Ha) (mm3/Ha) (m3) (Kg/m3) 1994 April 20th Dec. 23rd 1162.3 777.4 10592.8 7774000 7774 1.362593 1995 Mar. 15th Nov. 17th 1339.1 949.6 10667.1 9496000 9496 1.123326 1996 April 20th Dec. 22nd 1131.9 808.5 10664.6 8085000 8085 1.31906 1997 April 5th Dec. 10th 895.9 702.6 11881.8 7026000 7026 1.691119 1998 April 15th Dec. 20th 1220.1 829.2 10746.1 8292000 8292 1.29596 1999 May 5th Jan. 10th 1157.5 814.6 9599.8 8146000 8146 1.178468 2000 May 10th Jan. 17th 973.6 718.8 9700 7188000 7188 1.349471 2001 May 9th Jan. 10th 780.9 577.8 9601.2 5778000 5778 1.661682 2002 April 25th Dec. 27th 1125.6 819.8 9901.3 8198000 8198 1.20777 2003 April 15th Dec. 20th 1224.9 858.4 10402.3 8584000 8584 1.211824 2004 April 22th Dec. 28th 1068.3 769 11001.1 7690000 7690 1.430572 2005 April 16th Dec. 21th 1161.2 789 10990.2 7890000 7890 1.392928 2006 April 18th Dec. 27th 1143.3 842.2 12000.3 8422000 8422 1.424875 2007 April 16th Dec. 17th 1391.3 921 11202.6 9210000 9210 1.216352 2008 April 15th Dec. 20th 1130.6 790.8 11800.4 7908000 7908 1.49221 2009 April 19th Dec. 11th 917 702.6 11767.9 7026000 7026 1.674907 2010 March 7th Nov. 12th 1485.4 1037.1 12215.5 10371000 10371 1.177852 2011 March 27th Nov. 30th 1144.1 776.8 11210.8 7768000 7768 1.443203 2012 March 30th Nov. 27th 1200.2 870.7 7958.5 8707000 8707 0.914035 2013 March 26th Nov. 30th 793.2 644.8 13947.4 6448000 6448 2.163058 Figure 2: Water productivity 3.2 Cost of Alternative Water Table 3: Annual water cost   Cassava Effective Effective Cost of water Year Yield Rainfall Rainfall Used   (Kg/Ha) (m3) (litre) (₦) 1994 10592.8 7774 7774000 13324636 1995 10667.1 9496 9496000 16276144 1996 10664.6 8085 8085000 13857690 1997 11881.8 7026 7026000 12042564 1998 10746.1 8292 8292000 14212488 1999 9599.8 8146 8146000 13962244 2000 9700.0 7188 7188000 12320232 2001 9601.2 5778 5778000 9903492 2002 9901.3 8198 8198000 14051372 2003 10402.3 8584 8584000 14712976 2004 11001.1 7690 7690000 13180660 2005 10990.2 7890 7890000 13523460 2006 12000.3 8422 8422000 14435308 2007 11202.6 9210 9210000 15785940 2008 11800.4 7908 7908000 13554312 2009 11767.9 7026 7026000 12042564 2010 12215.5 10371 10371000 17775894 2011 11210.8 7768 7768000 13314352 2012 7958.5 8707 8707000 14923798 2013 13947.4 6448 6448000 11051872 Figure 3: Cost of water The maximum yield of cassava in kg/ha was recorded From the figure above, the cost of water used in r These costs are important to determine so that it However, research has shown that yields can vary a 4.0Conclusion and Recommendation Based on the yield shown above, effective rainfall It is strongly recommended that other parameters l It is as well recommended that federal government References Allen, RG., Pereira, LS., Raes, D. and Smith, M. 1 Bastiaanssen, WGM., David, JM. and Ian, WM. 2000. Dastane, NG. 1978. Effective Rainfall in Irrigated Food and Agriculture Organization (FAO) 2000. CROP Food and Agriculture Organization of the United Na Marica, A. 2013. Short Description of the CROPWAT Mohammed N. 2009. Simulation of Maize Crop under I Ogunwole, 2000. A Critical Evaluation of Traits of