Calibrating and validating AquaCrop model for maize crop in Northern zone of Nigeria

Farmers in the northern Guinea Savannah ecological zone of Nigeria have been experiencing declining crop yield due to erratic water supply. In recent times, research on better water management and interaction between effects of climate, soil and field management on crop production is fast gaining grounds with the use of models. Models can be used to predict the impact of long-term climate variability, thus providing an opportunity of better techniques compared with the traditional multi-location trials. This study presents the calibration and validation of AquaCrop model for drip irrigated maize (Zea mays). Calibration was done using data of 2013, while validation across seasons was done with data of 2014. The modelling efficiency of grain yield, biomass yield and crop water use were 81%, 90%, and 85% when calibration was done, while during the validation the modelling efficiency were 86%, 74% and 50%, respectively. This indicates a good fit between the simulated output and measured data. The model has a tendency to over-predict grain and biomass yield at harvest by 3%-4%, under-predict seasonal evapotranspiration by 2%, and over-predict grain water productivity by 3% and biomass water productivity by 24% according to the coefficient of residual mass. The AquaCrop model high reliability for the simulations indicates it can be useful for on-the-desk assessing of the impact of irrigation scheduling protocols when properly calibrated

Models for predicting pore space indices of an irrigated lowland rice soil in a Sudan Savanna of Nigeria

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Susceptibility of wheat to water deficit at three growth stages

The grain yield of wheat (Triticum aestivum L.) to different water deficit levels at three stages of growth was obtained from field measurements conducted at the Aahmadu Bello University Farm, Samaru-Zaria. Also, the suitability of a time-based characterisation of water deficit for crop susceptibility determination was tested against a plant-based one. The plant-based measure of crop water stress, as caused by water deficit, was calculated as the product of relative evapotranspiration deficit and the duration. The crop susceptibility was the relative grain yield reduction due to a given crop water stress. The results showed that the level of water deficit determines the relative crop susceptibilities to water stress for the crop growth stages considered. Also, the relationship between time intervals (irrigation frequency as a measure of water deficit) and a plant-based water deficit varied during the crop growth season. Thus, the sole use of a time-based characterisation of water deficit for the determination of crop susceptibilities at defined growth stages is found to be unsuitable. However, since the local farmers may find it difficult to use the more sophisticated plant-based water deficit characterisation, a relationship between the plant-based and time-based water deficit characterisation for the different crop growth stages was established. Therefore, the plant-based water deficit characterisation can easily be estimated using the established relationship and the appropriate irrigation scheduling determined

A method for estimating crop actual evapotranspiration

The reliability of Rhenals and Bras (1981) model in estimating actual evapotranspiration in Samaru for a wheat crop was tested and result is herein presented. This model incorporates climate, crop and soil characteristics factors in estimating actual evapotranspiration. Actual evapotranspiration values estimated using the model were compared with actual evapotranspiration amounts estimated from open pan evaporation data. The mean difference between the average aily evapotranspiration obtained by Rhenals and Bras (1981) model and those from open pan evaporation data was 0.20 mmday-1 and was not statistically significant at 0.05 level of significance. The tested model is found reliable in estimating the crop actual evapotranspiratio

Performance evaluation of selected crop yield-water use models for wheat crop

Crop yield-water use models that provide useful information about the exact form of crop response to different amounts of water used by the crop throughout its growth stages and those that provide adequate information for decisions on optimal use of water in the farm were evaluated. Three crop yield models: Jensen (1968), Minhas et al., (1974) and Bras and Cordova (1981) additive type models were studied. Wheat (Triticum aestivum) was planted at the Institute for Agricultural Research Farm during the 1995/96 and 1996/97 irrigation seasons of November to March. The data collected from the field experiments during the 1995/96 planting season were used to calibrate the models and their stress sensitivity factors estimated for four selected growth stages of the wheat crop. The ability of the model to predict grain yield of wheat with the estimated stress sensitivity factors was evaluated by comparing predicted grain yields by each model with those obtained in the field during the 1996/97 season. The three models performed fairly well in predicting grain yields, as the predicted results were not significantly different from the field measured grain yield at 5% level of significance

Structuring and Characterisation of the Medical Infusion set as emitter for Low-Cost Drip Irrigation System

The medical infusion set was re-structured to serve as a point source emitter for low-cost drip irrigation systems. The re-structured device, here referred to as ‘medi-emitter’, was subjected to laboratory tests to evaluate its hydraulic characteristics. A calibration experiment, relating flow rate and level of emitter opening, gave a discharge range of 0-533 lhr-1 as the emitter flow regulator was gradually opened to its maximum. The peak discharge of 533 lhr-1 was recorded under a pressure of only 49.05 kPa. This makes the medi-emitter particularly suitable for low-cost drip systems that operate under gravity flow with low pressures often less than 58.86 KPa. The exponent values of the emitter flow functions ranged from 0.610 to 1.038, thus characterising the device as a laminar emitter. The laminar characteristic increases progressively with closure of the flow regulator. Manufacturer’s coefficient of variation of the medi-emitter was 0.065. Measured coefficient of variation and deviation from nominal flow were between 5 and 19%. The energy head loss coefficient of the emitter ranged from 1.48 to 28.25, which is within the range of common water outlets widely in use. Discharge through the medi-emitter was found to increase with rise in water temperature, although these variations were insignificant at 95% probability level. The influence of temperature on discharge was stronger at lower levels of emitter opening. The emitter gave average soil wetting diameters of 0.679, 0.924 and 1.07 m for sand, loam and clay soils respectively, under a discharge of 2 lhr-1. These values are comparable to those of conventional emitters. Results from this research reveal the potential of the medical infusion set to adequately serve as emitter for low-cost drip irrigation systems, particularly because it is widely available even in most rural communities

Prediction of long dry spells for appropriate cropping system in Gusau Northwestern Nigeria

The objective of this study was to predict the probabilities of occurrences of long dry spells and their lengths during the planting period in rainfed farming season for future planning in Gusau and its environs North-Western Nigeria. Markov chain and probability distribution models were used to help predict in advance the longtime dry spells occurrences in the study area. Daily rainfall amount for each year was used to determine the probabilities of wet and dry days at different orders of Markov Chain. Gamma distribution was used with the help of INSTAT plus statistical package to estimate the length of dry spells in May, June and July. The early season dry spells were determined to occur usually between the first and the last decades of May. The Longest dry spells for the month of May were determined to be 26, 25 and 21 days in 2020, 2022 and 2030 respectively. Low frequencies of dry spells are to be anticipated in June with only 10 days in 2026 and July with only 12 days in 2024. The month of May from 2011 to 2020 with mean dry days of measured and predicted data were found to be 14 and 15 days respectively while coefficient of variation (CV) of 0.3, shows a stable dry spell in the coming years in May. The R between the observed and the predicted values were averagely good, mean error (ME) -1.25,-1.00 and 1.63 between the longest monthly observed and predicted dry spell were less than all the observed data. The root mean square error (RMSE) indicated that the month of June has the highest measure of precision 3.18, followed by the month of July4.46 and May 5.50. Since, early season rainfall is uncertain and erratic than the mid-season, early planting of moisture sensitive crop like maize in Gusau without supplementary irrigation would be highly risky