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Welcome to EUSpace, The Institutional Repository of Elizade University. A collection of theses, articles,books, videos, images, lectures, papers, data sets, and all types of digital content originating from Elizade University, Nigeria. This repository is managed by the University Library
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Recent Submissions
Hydrotope-based protocol to determine average soil moisture over large areas for satellite calibration and validation with results from an observation campaign in the Volta
(IEEE, 2008-05-16) Friesen, Jan; Rodgers, Charles; Oguntunde, Philip G.; Hendrickx, Jan M.H.; Giesen, Nick van de
In West Africa, which is an extremely moisturelimited region, soil water information plays a vital role in hydrologic and meteorologic modeling for improved water resource planning and food security. Recent and upcoming satellite missions, such as SMOS and MetOp, hold promise for the regional observation of soil moisture. The resolution of the satellites is relatively coarse (> 100 km2 ), which brings with it the need for large-scale soil moisture information for calibration and validation purposes. We put forward a soil moisture sampling protocol based on hydrotopes. Hydrotopes are defined as landscape units that show internally consistent hydrologic behavior. This hydrotope analysis helps in the following ways: 1) by ensuring statistically reliable validation via the reduction of the overall pixel variance and 2) by improving sampling schemes for ground truthing by reducing the chance of sampling bias. As a sample application, we present data from three locations with different moisture regimes within the Volta Basin during both dry and wet periods. Results show that different levels of reduction in the overall pixel variance of soil moisture are obtained, depending on the general moisture status. With respect to the distinction between the different hydrotope units, it is shown that under intermediate moisture conditions, the distinction between the different hydrotope units is highest, whereas extremely dry or wet conditions tend to have a homogenizing effect on the spatial soil moisture distribution. This paper confirms that well-defined hydrotope units yield an improvement at pixel-scale soil moisture averages that can easily be applied.
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.
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 Ebenezer
Actual 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 levels
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 Kano
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 country