Browsing by Author "Oguntunde, Phillip G."
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Item A numerical modelling study of the hydroclimatology of the Niger River Basin, West Africa(Taylor & Francis, 2016-01-02) Oguntunde, Phillip G.; Abiodun, Babatunde J; Lischeid, GunnarAdequate water resources management at the basin level needs quality downscaling of climate change scenarios for application to impact assessment and adaptation work. This study evaluates the ability of a regional climate model (RegCM3) to simulate the present-day climate and regional water balance over the Niger River Basin (NRB). RegCM3 gives a good simulation of the NRB hydroclimatic features. The mean bias error for monthly temperature is 1.5°C, 0.3 mm d-1 for rainfall, and 0.4 mm d-1 for runoff. Moderate to high correlations (0.66– 0.95) were found between the modelled and the observed variables. RegCM3-based water cycling indices were not statistically different from the observation. Seasonal moistening efficiency (m) ranges between 19% and 37%; 66% of the available atmospheric moisture over NRB precipitates between June and September, of which 21% originates from local evaporation. The result suggests that the moisture sink period is July to October with very high precipitation efficiency over the basin. The model reproduces the hydroclimatology of the NRB and hence is a suitable tool for further studies relating to the assessment of climate change impacts on river basin water systemsItem A semi-empirical model for estimating surface albedo of wetland rice field(International Commission of Agricultural Engineering, 2007) Oguntunde, Phillip G.; Olukunle, O.J.; Ijatuyi, O.A.; Olufayo, A.A.Surface albedo plays a vital role in the evapotranspiration component of the wetland rice water balance. This paper examines the influence of the phenological stages of rice (Oriza sativa) field on observed albedo at a tropical site (Ghana) during the year 2002, with a view to parametrizing a simple albedo model suitable for inclusion in models to estimate evapotranspiration in wetland rice cropping systems. Crop management was similar for the two planting dates used in this study. Measurements were taken from 10 m x 10 m plots within rice fields. Four phenological stages were distinguished: emergence, vegetative, flowering and physiological maturity. Surface albedo (α) was measured and simulated, using a calibrated semi-empirical model, at solar zenith angles of 15°, 30°, 45°, 60°, and 75°. Leaf area index (LAI) and crop height (h) were also monitored. Generally, albedo increases from emergence to flowering for both planting dates but slightly decreases after flowering. The correlation coefficient (r) between α and LAI equals 0.985 and the correlation coefficient between α and h equals 0.908. The composed albedo model adequately predicted the observed albedos with an overall r = 0.946 and mean bias error (MBE) of 0.002. The extinction coefficient of the rice crop albedo was estimated as 0.75. Data presented are valuable inputs in agricultural water management, rice production models, and especially as vital sub-routine inputs in calculating evaporation and transpiration from wetland rice.Item Application of artificial neural network for forecasting standardized precipitation and evapotranspiration index: A case study of Nigeria(John Wiley & Sons, Inc., 2020-07) Ogunrinde, Akinwale T.; Oguntunde, Phillip G.; Fasinmirin, Johnson T.; Akinwumiju, Akinola S.The necessity to perform an accurate prediction of future characteristics of drought requires a robust and efficient technique that can deduce from historical data the stochastic relationship or dependency between history and future. In this study, the applicability of the artificial neural network (ANN) is used for forecasting the standardized precipitation and evapotranspiration index (SPEI) at 12-month timescale for five candidate stations in Nigeria using predictive variable data from 1985 to 2008 (training) and tested data between 2009 and 2015. The predictive variables are monthly average precipitation, average air temperature, maximum temperature, minimum temperature, mean speed, mean solar radiation, sunshine hours, and two large-scale climate indices (Southern Oscillation Index and North Atlantic Oscillation). From the several combinations of the input variables, training algorithms, hidden, and output transfer functions, a total of eight model runs stood out using a three-layer ANN network. The most efficient ANN model architecture had 9,8,1 as the input, hidden, and output neurons, respectively, trained using the Levenberg-Marquardt training algorithm and tansig as the activation and hidden transfer functions. Assessment on the efficiency of the model based on statistics indicate that the coefficient of determination, root mean square error, Nash-Sutcliffe coefficient of efficiency and the mean absolute error ranges between 0.51 and 0.82; 0.57 and 0.75; 0.28 and 0.79; 0.44 and 0.56, respectively, during the testing period. The output of these findings shows that ANN modeling technique can play a significant role as a data-driven model in forecasting monthly SPEI time series and drought characteristics in the study area, thereby leading to the development of an early warning system for the countryItem Assessing the Impact of Changing Climate on Crop Water Requirements in Nigeria.(Agricultural Engineering International: CIGR Journal, 2023-09-29) Ilesanmi, O. A.; Oguntunde, Phillip G.; Olubanjo, O. O.Climate change is a phenomenon most of the world is recently coming to terms with, but unfortunately, the African region is yet to fully understand and prepare for its effects. This study highlights the impact these changes experienced in the Nigerian climate system will have onCrop water requirements (CWR)for optimal productivity.Data were obtained from five global climate modelsnamely CCCMA, MIROC, ICHEC, NOAA and NCC. These data were sourced in Representative Concentration Pathway 8.5 (RCP8.5) for the 36 states including the Federal Capital Territory (FCT). The data length varies from 1985 – 2100 for historical, present and future periods. Penman Monteith evapotranspiration (ETo) calculator was used to determine CWR.Trend analysis was carried out on the rainfall, temperature data, and the CWR. This analysis showed a projected slight increase in rainfall and significant increments in temperature varying in the range of 131.18 mm to 135.3mm and 27.2oC to 29.1oC for rainfall and temperature respectively.Results also showed that CWR will increase in future and it correlated strongly with temperature and weakly with rainfall. This result implies that temperature affects CWR more withit driving up the water use of cassava, rice and soybean, thereby leading to increase in yield if adequate water is available as well as coupled with proper management practices. The study has concluded that CWR will increase as the years go by and is higher in states with higher latitudes; it is therefore recommended that farmers' crop production activities should be adapted to maximize available water efficientlyItem Calibration and validation of a soil water simulation model (WaSim) for field grown Amaranthus cruentus(International Journal of Plant Production, 2008-07-01) Fasinmirin, JT; Olufayo, AA; Oguntunde, Phillip G.A water simulation model (WaSim) to simulate the growth and development of Amaranthus cruentus as well as the components of water balance for a typical sandy-clay-loam soil of Akure has been described. Dry season experiments were carried between January and March of 2005 and 2006. Amaranthus seeds were established on the field and three irrigation water managements were imposed on the crop to determine its response to water deficit at its different phenological stages. Amaranthus growth and development, evapotranspiration (ET) and rooting depth were calibrated by fitting the most sensitive variables to obtain the corresponding model output. The model simulated crop growth and crop cover well, the coefficient of determination r2 =0.9 and the difference between simulated and measured root depth is not significant at P<0.001. The actual evapotranspiration (AET) from the model prediction and the measured value gave a fairly high coefficient of correlation r=0.7 at P<0.001. The mean bias error (MBE) and the root mean square error of yield estimates between the measured and the model prediction are -0.4444 and 1.35 respectively at P < 0.001. The model was considered effective and appropriate for daily simulation of water balance, water requirement of crops and in climate effects on crop production.Item Crop Water Productivity of Plantain (Musa Sp) in a Humid Tropical Environment.(JOURNAL OF Engineering Science and Technology Review, 2012-01-01) Akinro, A.O.; Olufayo,A.A.; Oguntunde, Phillip G.Crop water productivity defines the relationship between crop produced and the amount of water involved in producing the crop. It is a useful indicator for quantifying the impact of irrigation scheduling decisions with regard to water management. This paper presents CWP quantified from field experimental data. The field experiments were conducted for three years in a tropical region of south Western Nigeria to determine the crop water productivity (CWP) and consumptive use of plantain (musa sp) cv. Agbagba. There were four treatments and four replicates based on the level of water application. CWP were computed in terms of crop water use, water applied, and economic returns. Results showed that crop water consumed varied significantly (P<0.05) among treatments. Estimated water consumed ranged from 900 mm to 1700 mm from planting to harvest depending on the irrigation water regime. Crop Water Productivity (CWP) in terms of water consumed varied from 0.91 – 1.37 kgm-3 for 2006/2007 and 0.91 – 1.41 kgm-3 in the 2007/2008 seasons respectively while CWP in terms of water applied varied from 2.82 – 3.98 kgm-3 and 2.89 – 4.04 kgm-3 in the first and second seasons respectively. The amount of irrigation water applied at the different growth stages of the crop and the growth stage response to moisture stress influenced the status of CWP. The findings indicated that plantain crops were very sensitive to lack of soil water during the total growing season.Item Environmental regulation and modelling of cassava canopy conductance under drying root‐zone soil water(John Wiley & Sons, Ltd., 2007-09) Oguntunde, Phillip G.; Alatise, Michael OSap flow was measured, with Granier-type sensors, in a crop of field-grown water-stressed cassava (Manihot esculenta Crantz) in Ghana, West Africa. The main objective of this study was to examine the environmental control of canopy conductance (gc) with a view to modelling the stomatal control of water transport under water-stressed condition. Weather variables measured concurrently with sap flow were: air temperature (Ta ), relative humidity (RH ), wind speed (u) and solar radiation (Rs). Relationship between canopy conductance (gc) and vapour pressure deficit (Dε) was curvilinear while no specific pattern was observed with Rs. Average diurnal gc decreased from 3.0 ± 0.6 to 0.7 ± 0.4 mm s−1 between 0730 and 2000 h local time (= GMT) each day. A Jarvis-type model, based on a set of environmental control functions, was parameterized for the cassava crop in this study. Model results demonstrated that gc was estimated with a high degree of accuracy based on Rs, Ta , and Dε (r2 = 0.92; F = 809.2; P < 0.0001). Dε explained about 90% (F = 2129.7;P < 0.0001) of the variations observed in gc, whereas both Rs and Ta contributed about 2% of the explained variance in gc. The aerodynamic conductance (ga ) was very high compared to gc, leading to a daily average ratio ga /gc > 100 and a decoupling factor< 0.1. Cross-validation analysis revealed a consistent good performance (r2 > 0.85) of the gc model with Dε as the only independent environmental variable. Copyright 2007 Royal Meteorological SocietyItem Evaluating a finer resolution global hydrological model’s simulation of discharge in four West-African river basins(Springer International Publishing, 2021-11) Babalola, T.E.; Oguntunde, Phillip G.; Ajayi, A.E.; Akinluyi, F.O.; Sutanudjaja, E.H.Performance evaluation of hydrological models enables their consolidation, thereby allowing for the evaluation of water resource conservation approaches. This research aims to evaluate the performance of a finer resolution version (5 arcmin) of the PCRaster Global Water Balance (PCR-GLOBWB) for discharge estimation, in four basins in data-scarce West Africa; the Niger, Komadugu-Yobe, Jama’are, and Ogun. At the Ogun, discharge simulation was validated in a proxy basin, Ouémé, which is hydrologically comparable. The model performance was evaluated using Nash–Sutcliffe efficiency (NSE), coefficient of determination (r 2 ), Kling–Gupta efficiency (KGE), RMSE—observations standard deviation ratio (RSR), percent bias (PBIAS) and visual plots. PCR-GLOBWB was found to be suitable in all four basins but yielded better performance at three of the basins; the Niger, Jama’are, and Komadugu-Yobe (NSE, KGE, and r 2 above 0.7) compared to the Ogun basin where a proxy validation approach was followed. Results at the Ogun underlined the importance of measured data in hydrological studies. Still, model performance was satisfactory in the Ogun. PCR-GLOBWB performances across the four basins, in the area, validate its reliability as a tool applicable for water resources management strategies and further investigation of impacts of climate variations on river dynamicsItem Evaluation of Evapotranspiration Prediction for Cassava Crop Using Artificial Neural Network Models and Empirical Models over Cross River Basin in Nigeria(MDPI, 2025-01-01) Eludire, Oluwadamilare Oluwasegun; Faloye, Oluwaseun Temitope; Alatise, Michael; Ajayi, Ayodele Ebenezer; Oguntunde, Phillip G.; Badmus, Tayo; Fashina, Abayomi; Adeyeri, Oluwafemi E.; Olorunfemi, Idowu Ezekiel; Ogunrinde, Akinwale T.first_pagesettingsOrder Article Reprints Open AccessArticle Evaluation of Evapotranspiration Prediction for Cassava Crop Using Artificial Neural Network Models and Empirical Models over Cross River Basin in Nigeria by Oluwadamilare Oluwasegun Eludire 1,2,Oluwaseun Temitope Faloye 3,4,*ORCID,Michael Alatise 2,Ayodele Ebenezer Ajayi 2,4,5,Philip Oguntunde 2,Tayo Badmus 1,Abayomi Fashina 6,Oluwafemi E. Adeyeri 7,*ORCID,Idowu Ezekiel Olorunfemi 8ORCID andAkinwale T. Ogunrinde 9 1 Department of Agricultural and Bioresources Engineering, Faculty of Engineering and Technology, University of Calabar, Calabar PMB 1115, Nigeria 2 Department of Agricultural and Environmental Engineering, Federal University of Technology, Akure PMB 704, Nigeria 3 Department of Water Resources Management and Agrometeorology, Federal University, Oye-Ekiti PMB 373, Nigeria 4 Institute for Plant Nutrition and Soil Science, Christian Albrecht’s University zu Kiel, Hermann Rodewaldstr. 2, 24118 Kiel, Germany 5 Institute for Fourth Industrial Revolution, SE Bogoro Centre, Afe Babalola University, Ado Ekiti 360001, Nigeria 6 Department of Soil Science and Land Resources Management, Federal University, PMB 373, Oye-Ekiti 371104, Nigeria 7 School of Energy and Environment, City University of Hong Kong, Kowloon, Hong Kong 8 Department of Civil Engineering, Lead City University Ibadan, Ibadan 200255, Nigeria 9 Key Laboratory of Ecological Safety and Sustainable Development in Arid Lands, Northwest Institute of Eco-Environment and Resources, Chinese Academy of Sciences, Beijing 100045, China * Authors to whom correspondence should be addressed. Water 2025, 17(1), 87; https://doi.org/10.3390/w17010087 Submission received: 28 August 2024 / Revised: 5 October 2024 / Accepted: 8 October 2024 / Published: 1 January 2025 (This article belongs to the Section Water, Agriculture and Aquaculture) Editorial Note: Due to an editorial processing error, this article was incorrectly included within the Special Issue Crop Evapotranspiration, Crop Irrigation and Water Savings upon publication. This article was removed from this Special Issue’s webpage on 14 February 2025 but remains within the regular issue in which it was originally published. The editorial office confirms that this article adhered to MDPI's standard editorial process (https://www.mdpi.com/editorial_process). Downloadkeyboard_arrow_down Browse Figures Versions Notes Abstract The accurate assessment of water availability throughout the cassava cropping season (the initial, developmental, mid-season, and late stages) is crucial for mitigating the impacts of climate change on crop production. Using the Mann–Kendall Test, we investigated the trends in rainfall and cassava crop evapotranspiration (ETc) within the Cross River basin in Nigeria. Reference evapotranspiration (ETo) was based on two approaches, namely Artificial Neural Network (ANN) modelling and three established empirical models—the Penman–Monteith (considered the standard method), Blaney–Morin–Nigeria (BMN), and Hargreaves–Samani (HAG) models. ANN predictions were performed by using inputs from BMN and HAG parameters, denoted as BMN-ANN and HAG-ANN, respectively. The results from the ANN models were compared to those obtained from the Penman–Monteith method. Remotely sensed meteorological data spanning 39 years (1979–2017) were acquired from the Climatic Research Unit (CRU) to estimate ETc, while cassava yield data were acquired from the International Institute of Tropical Agriculture (IITA), Ibadan. The study revealed a significant upward trend in cassava crop ETc over the study period. Additionally, the ANN models outperformed the empirical models in terms of prediction accuracy. The BMN-ANN model with a Tansig activation function and a 3-3-1 architecture (number of input neurons, hidden layers, and output neurons) achieved the highest performance, with a coefficient of determination (R2) of 0.9890, a root mean square error (RMSE) of 0.000056 mm/day, and a Willmott’s index of agreement (d) of 0.9960. There is a decreasing trend in cassava yield in the region and further analysis indicated potential average daily water deficits of approximately −1.1 mm/day during the developmental stage. These deficits could potentially hinder root biomass, yield, and overall cassava yield in the Cross River basin. Our findings highlight the effectiveness of ANN modelling for irrigation planning, especially in the face of a worsening climate change scenario.Item Evaluation of Four ETo Models for IITA Stations in Ibadan, Onne and Kano, Nigeria.(Journal of Environment and Earth Science, 2014) Ilesanmi, Oluwaseun A.; Oguntunde, Phillip G.; Olufayo, Ayorinde A.Records of climatic variables (Solar radiation, Maximum and Minimum Temperature, Maximum and Minimum Relative Humidity and Wind speed) were collected from three International Institute of Tropical Agriculture (IITA) Stations namely Ibadan, Kano and Onne in Nigeria. For Ibadan, a 36-year (1973 – 2008) record was obtained, for Kano, a 29-year (1980 - 2008) record was obtained and for Onne, a 31-year (1977 - 2006) record was obtained. Evapotranspiration rates for each of the stations were estimated using the FAO-56 approach. The performance of four ET models (Blaney-Morin-Nigeria (BMN), Hargreaves-Samani, Priestly-Taylor and JensenHaise models) were evaluated with reference to FAO 56 Model making use of ET estimated from these models. The BMN model was found out to be the best model that can be applied to estimate ET in each of these stations because it has a high correlation value with the values obtained from FAO56-PM model along with favourable statistic values and it requires a considerably less number of variables for its estimation with correlation (r) values of 0.7, 0.77 and 0.75 respectively for Ibadan, Onne and KanoItem Greenhouse evapotranspiration and crop factor of Amaranthus cruentus grown in weighing lysimeters(Academic Journals, 2015-08-20) Fasinmirin, Johnson Toyin; Reichert, Jose Miguel; Oguntunde, Phillip G.; Ajayi, Ayodele EbenezerActual evapotranspiration and crop coefficient (Kc) of Amaranthus cruentus grown in weighing lysimeter was determined under a screen house. The weighing lysimeter was made of a cylindrical plastic of circular cross-sectional area of 0.076 m2 and diameter 0.3 m. Climatic variables such as solar radiation, relative humidity, air temperature and wind speed were collected for the estimation of reference evapotranspiration (ETr) using the FAO-Penman Monteith model. Actual crop evapotranspiration (ETc) was measured directly from the daily drop in the level of water in the burette that was connected to the lysimeter. Crop factor (Kc) was estimated from the ratio of ETc /ETo. The ETc of the crop rose gradually from the period of emergence (4.5 mm week -1 ) during the 1 week after planting (WAP) to a maximum value of 14.3 mm week-1 during the 7 WAP. Kc for the emergence and maturity stages of Amaranthus cruentus were 0.15 and 0.36, respectively. The highest leaf area index (LAI) and leaf coverage area were 11.39 and 0.866. The optimum soil moisture content for the highest Kc value (0.36) was 11.7%. The output of this research will be useful for farmers who are into vegetable production for enhanced productivity at farm levelsItem Impact of climate change and drought attributes in Nigeria(MDPI, 2022-11-10) Ogunrinde, A.T.; Oguntunde, Phillip G.; Akinwumiju, A.S.; Fasinmirin, J.T.; Olasehinde, D.A.; Pham, Q. B.; Linh, N. T.T.; Anh, D. T.Data from historical observatories and future simulations were analyzed using the representative concentration pathway (RCP) 8.5 scenario, which covered the period from 1951 to 2100. In order to characterize the drought, three widely used drought indicators were used: the standardized precipitation index (SPI), the reconnaissance drought index (RDI), and the standardized precipitation and evapotranspiration index (SPEI). The ensemble of the seven (7) GCMs that used RCA-4 was able to capture several useful characteristics of Nigeria’s historical climatology. Future climates were forecasted to be wetter than previous periods during the study period based on the output of drought characteristics as determined by SPI. SPEI and RDI predicted drier weather, in contrast. SPEI and RDI’s predictions must have been based on the effect of rising temperatures brought on by global warming as depicted by RCP 8.5, which would then have an impact on the rate of evapotranspiration. According to drought studies using the RCP 8.5 scenario, rising temperatures will probably cause more severe/extreme droughts to occur more frequently. SPEI drought frequency changes in Nigeria often range from 0.75 (2031–2060) to 1.80 (2071–2100) month/year, whereas RDI changes typically range from 0.30 (2031–2060) to 0.60 (2071–2100) month/year. The frequency of drought incidence has recently increased and is now harder to forecast. Since the Sendai Framework for Disaster Risk Reduction 2015–2030 (SFDRR) and the Sustainable Development Goals (SDGs) have few more years left to be completed, drastic efforts must be made to create climate-resilient systems that can tackle the effects that climate change may have on the water resources and agricultural sectors.Item Implications of trends and cycles of rainfall on agriculture and water resource in the tropical climate of Nigeria(Special Publication of the Nigerian Association of Hydrological Sciences., 2012-08-11) Alli, AA; Oguntunde, Phillip G.; Olufayo, AA; Fasinmirin, JTTrends and cycles of rainfall over Nigeria, as well as their implications for water resources and agriculture, have been studied since 1960 on annual, seasonal and monthly bases. Rainfall data of 47 years (1960 – 2006) were obtained for twenty stations over Nigeria for the evaluation of trends using the Mann-Kendall test. Auto correlation spectral analysis was also used to detect cycles of rainfall. The result showed dominant peaks in rainfall return at various rates. For instance, Akure, Benin, Calabar, Maiduguri and Yola stations had decreasing trends of annual rainfall at rates of 1.084, 0.03, 1.80, 0.75, and 0.12 mm/month/yr, respectively with return periods between 1-2 years and 7-10 years. Rainfall trends increased in about 75 % of the locations with return period of dominant peaks varying between 1-2 years and 15 years. Abuja recorded the highest peak of rainfall in the month of October at the rate of 4.7 mm/month/yr with return period of 1-2 years. These results indicate different spatial effects on ecosystem and agriculture. Some of the implications of these trends on agriculture and water resources vary from one station to another, depending on the trends and magnitude of return period of rainfalls. Bauchi and Minna cities are expected to experience serious desertification and complete depletion of underground water due to the effects of no change in trend of rainfall. Meanwhile, agricultural activities are expected to thrive in places like Ibadan, Gusua, Osogbo and others that have moderate increase in trends of rainfall and temperature.Item Land use effects on soil erodibility and hydraulic conductivity in Akure, Nigeria(Academic Journals, 2018-02-15) Ajibola, Yusuf Habeeb; Oguntunde, Phillip G.; Lawal, Abosede KhadijahThis research was carried out to investigate the effects of three land use categories (grazed, cropped and forest land) on soil erodibility and hydraulic conductivity. Hydraulic conductivity was determined by a steady‐state flow using a mini‐disk infiltrometer while soil erodibility was determined following the Wischmeier and Smith equation. A suction rate of 2 cm s-1 was chosen for field infiltration measurement and subsequent estimation of soil hydraulic conductivity. The USDA textural classes for the land use types in forest, cropped and grazed lands are clay, sandy clay and sandy clay loam, respectively. The mean values of the hydraulic conductivity for the land uses/land cover are: forest land (0.00162±0.002019 cms-1 ), cropped land (0.002086±0.001299 cms -1 ), and grazed land (0.002244±0.002176 cms-1 ). Highest mean bulk density (1.45 ± 0.23 g cm‐ 3 ) and the lowest mean bulk densities (0.84 ± 0.14 g cm‐ 3 ) were observed in soils of forest and grazed land, respectively. Similarly, mean total porosity values ranged between 0.43 and 0.67 cm3 cm‐ 3 . Highest organic matter was found out in the grazed soil (4.90%) as a result of the urine and excreta of the cattle. High organic matter was also observed in the forest soil (3.50%) but lower relative to grazed land. The soil erodibility was high in the sampled soils of grazed land with the value of 8.73 × 10-2 ±0.03, while the least erodibility (6.35 × 10-2 ± 0.02) was recorded in the forest land. These values indicate the eroding vulnerability of the three land uses.Item Modeling and Optimization of Maize Yield and Water Use Efficiency under Biochar, Inorganic Fertilizer and Irrigation Using Principal Component Analysis(MDPI, 2024-10-14) Faloye, Oluwaseun Temitope; Ajayi, Ayodele Ebenezer; Oguntunde, Phillip G.; Kamchoom, Viroon; Fasina, AbayomiThis study was conducted to predict the grain yield of a maize crop from easy-to-measure growth parameters and select the best treatment combinations of biochar, inorganic fertilizer, and irrigation for the maize grain yield and water use efficiency (WUE) using the Principal Component Analysis (PCA) technique. Two rates of biochar (0 and 20 t ha−1) and fertilizer (0 and 300 kg ha−1) were applied to the soil, with maize crop planted, and subjected to deficit irrigation at 60, 80, and 100% of full irrigation amounts (FIA). Maize growth parameters (number of leaves—NL, leaf area—LA, leaf area index—LAI, and plant height—PH) were measured weekly. The results showed that the developed principal component regression (PCR) from the easy-to-measure growth parameters were strong and moderate in predicting the maize yield and WUE, with coefficient of determination; r2 values of 0.92 and 0.56, respectively. Using the PCA technique, the integration of irrigation with the least amount of water (60% FAI) with biochar (20 t ha−1) and fertilizer (300 kg ha−1) produced the highest ranking on grain yield and water use efficiency. This optimization technique showed that with the adoption of the integrative approach, 40% of irrigation water could be saved for other agricultural purposes Keywords: soil amendments; irrigation; maize; leaf area index; principal component analysisItem Performance of the SunScan canopy analysis system in estimating leaf area index of maize(CIGR Journal, 2012-09-23) Oguntunde, Phillip G.; Fasinmirin, Johnson T; Abiolu, Oluremi ARapid and reliable estimates of leaf area index (LAI) are important for studies of exchanges of energy and gases in the biosphere-atmosphere continuum. This paper evaluates the field performance of SunScan canopy analysis system for rapid estimation of LAI. Direct and indirect measurements of LAI were made in a maize (Zea mays L.) field at four phenological stages (emergence, vegetative, flowering and physiological maturity) at a tropical site in Ghana during the Glowa Vota Project field campaign (www.glowa-volta.de). Similar measurements were repeated in early and late planting seasons with similar crop management practices. The result showed a generally good performance of this sensor at all the phenological stages. Average LAI from the sensor (LAIS ), ranged from 0.40–4.45, and was consistently higher than the actual LAI, which varied from 0.31–4.22, respectively for both seasons. Regression between LAI and LAIS showed a range of significant correlations with R2 > 0.74 for all the stages and seasons. With combined datasets for all stages and the two plantings, a simple regression model was fitted to estimate LAI from LAIS with R2 = 0.97 and standard error of 0.23 (P < 0.0001). The evaluated sensor yielded a good and reliable LAI estimates under maize canopy.Item Precipitation variability in West Africa in the context of global warming and adaptation recommendations(Springer International Publishing, 2020-05-27) Quenum, Gandome M.L.D.; Klutse, Nana A.B.; Alamou, Eric A; Lawin, Emmanuel A; Oguntunde, Phillip G.It is commonly accepted that the Earth’s climate is changing and will continue to change in the future. Rising temperatures are one of the direct indicators of global climate change. To investigate how the rising global temperature will affect the spatial pattern of rainfall in West Africa, the precipitation and potential evapotranspiration variables from ten Global Climate Models (GCMs) under the RCP8.5 scenario were driven by the Rossby Centre regional atmospheric model (RCA4) from the COordinated Regional Climate Downscaling EXperiment (CORDEX) and analyzed at four specific global warming levels (GWLs) (i.e., 1.5 C, 2.0 C, 2.5 C, and 3.0 C) above the preindustrial level. This study utilized three indices, the precipitation concentration index (PCI), the precipitation concentration degree (PCD), and the precipitation concentration period (PCP) over West Africa to explore the spatiotemporal variations in the characteristics of precipitation concentrations. Besides, the analysis of the effect of the specified GWLs on the Consecutive Dry Days (CDD), Consecutive Wet Days (CWD), and frequency of the intense rainfall events allowed to a better understanding of the spatial and temporal patterns of extreme precipitation in West Africa. Results reveal that, for the projections simulations and at each GWL, the rainfall onset starts one month earlier in the Gulf of Guinea in response to the control period. To encourage adaptation to the various changes in climate in general, and particularly in respect of rainfall, this study proposes several adaptation methods that can be implemented at the local (country) level, as well as some mitigation and adaptation strategies at the regional (West African) levelItem Rainfall variability at regional and local scales in the Ouémé upper valley in Benin(International Journal of Science and Advanced Technology, 2012-06) Lawin, Emmanuel Agnidé; Afouda, A.; Oguntunde, Phillip G.; Gosset, M.; Lebel, T.In West Africa, many climatic simulations show that significant changes to deal with will be exacerbation of climatic extremes (droughts, floods etc.). In the case of the Ouémé Upper Valley region where agricultural activities are essentially dependent on precipitations, it’s important to analyze impacts of climate fluctuations on the rainfall pattern. Two spatial scales have been considered to access the rainfall pattern variability in that region: especially the regional one and the local one. A seasonal rainfall analysis has been made with observed or regionalized daily rainfall data for 1950-2005 period. Dry and wet composite analysis of the rainfall signal shows that the pluviometric shortage of dry years is amplified after the “monsoon onset”. On the same way, dry years are characterized by early monsoon withdrawal which might have started since 1970. Furthermore, the years after 1970 show a shift lag in rainfall. The length of these lags depends on spatial scale. Rainfall maximum are earlier observed. The early monsoon withdrawal and the shift lag in rainfall revealed should have several consequences on agricultural production, especially on some crops yield.Item Re-examination of the BMN model for estimating evapotranspiration(Scientific and Academic Publising (http://journal. sapub. org/ijaf), 2012-02-06) Ilesanmi, Oluwaseun Ayodele; Oguntunde, Phillip G.; Olufayo, Ayorinde A.y re-examined the BMN model making use of the Sigma Plot software (based on the Levenberg – Marquardt algorithm) to generate modified versions of the BMN model that are specific for Ibadan, Kano and Onne and one version which applicable across the country, correcting some perceived shortcomings of the BMN. Records of climatic variables (Solar radiation, Maximum and Minimum Temperature, Maximum and Minimum Relative Humidity and Wind speed) were collected from three International Institute of Tropical Agriculture (IITA) Stations in Ibadan, Kano and Onne. For Ibadan, a 36-year (1973 – 2008) record was obtained, for Kano, a 29-year (1980 - 2008) record was obtained and for Onne, a 31-year (1977 - 2006) record was obtained. Evapotranspiration rates for each of the stations were then estimated using the FAO56-PM model. ETo estimates from the FAO56-PM model were thereafter used to recalibrate the BMN model, generating new model constants for Ibadan, Kano, Onne and a model combining the climatic characteristics of the three stations. The re-calibrated BMN model had higher correlation values of 0.74, 0.79 and 0.75 for Ibadan, Onne and Kano respectively when compared with the FAO-56 model than the Original BMN model when compared with the FAO56-PM model with values of 0.7, 0.77 and 0.75 respectively for Ibadan, Onne and Kano.Item The late onset of the 2015 wet season in Nigeria(American Meteorological Society, 2016-12-01) Kamoru A Lawal,; Abatan, Abayomi A.; Angélil, Oliver; Olaniyan, Eniola; Olusoji, Victoria H.; Oguntunde, Phillip G.; Lamptey, Benjamin; Abiodun, Babatunde J.; Shiogama, Hideo; Wehner, Michael F.; Stone, Dáithí A.This fifth edition of explaining extreme events of the previous year (2015) from a climate perspective continues to provide evidence that climate change is altering some extreme event risk. Without exception, all the heat-related events studied in this year’s report were found to have been made more intense or likely due to human-induced climate change, and this was discernible even for those events strongly influenced by the 2015 El Niño. Furthermore, many papers in this year’s report demonstrate that attribution science is capable of separating the effects of natural drivers including the strong 2015 El Niño from the influences of long-term human-induced climate change. Other event types investigated include cold winters, tropical cyclone activity, extreme sunshine in the United Kingdom, tidal flooding, precipitation, drought, reduced snowpack in the U.S. mountain west, arctic sea ice extent, and wildfires in Alaska. Two studies investigated extreme cold waves and monthly-mean cold conditions over eastern North America during 2015, and find these not to have been symptomatic of human-induced climate change. Instead, they find the cold conditions were caused primarily by internally generated natural variability. One of these studies shows winters are becoming warmer, less variable, with no increase in daily temperature extremes over the eastern United States. Tropical cyclone activity was extreme in 2015 in the western North Pacific (WNP) as measured by accumulated cyclone energy (ACE). In this report, a study finds that human-caused climate change largely increased the odds of this extreme cyclone activity season. The 2015 Alaska fire season burned the second largest number of acres since records began in 1940. Investigators find that human-induced climate change has increased the likelihood of a fire season of this severity. Confidence in results and ability to quickly do an attribution analysis depend on the “three pillars” of event attribution: the quality of the observational record, the ability of models to simulate the event, and our understanding of the physical processes that drive the event and how they are being impacted by climate change. A result that does not find a role for climate change may be because one or more of these three elements is insufficient to draw a clear conclusion. As these pillars are strengthened for different event types, confidence in the presence and absence of a climate change influence will increase. This year researchers also link how changes in extreme event risk impact human health and discomfort during heat waves, specifically by looking at the role of climate change on the wet bulb globe temperature during a deadly heat wave in Egypt. This report reflects a growing interest within the attribution community to connect attribution science to societal impacts to inform risk management through “impact attribution.” Many will watch with great interest as this area of research evolves in the coming years.