Development of deficit irrigation for maize crop under drip irrigation in samaru-nigeria

In the past, outcome of any water management strategy could only be known after field experiment, in recent times, means of evaluating the implications of irrigation schedules without field experiment is fast gaining grounds with the use of models.  This research work present a scenarios studies for different developed irrigation scheduling options for a drip irrigated maize crop at the Institute for Agricultural Research (IAR) irrigation farm Samaru-Nigeria during 2013 and 2014 cropping season using a computer-based model.  Aqua Crop was calibrated and validated with data obtained from the field, it was further used to generate scenario of different irrigation scheduling outcome. Grain and biomass yields, harvest index, seasonal evapotranspiration and crop water productivity were determined.  The general trend of the results suggests that skipping regular irrigations may be advantageous if such is done at grain-filling stage, though most of the time this stage is intercepted by rain in the study area.  The scenario studies showed that the peak grain and biomass yield value of 3273 and 10492 kgha-1 was recorded when 20 mm water application depth (WAD) with 3-day irrigation interval applied across all the growth stages; the irrigation water productivity with respect to grain and biomass yield were 0.83 and 2.65 kg m-3 respectively.  The possible consequences of a developed irrigation scheduling on the crop and its environment, could be analysed without necessarily going to the field.  The Aqua Crop model is useful for on-the-desk assessing of the impact of irrigation schedulling protocols.

ASSESSMENT OF CONCENTRATION STATUS OF SOME HEAVY METALS IN WATER ALONG RIVER DILIMI, JOS NORTH, PLATEAU STATE-NIGERIA

Aim: This study was carried out to assess concentration status of someheavy metals in water along River Dilimi, Nigeria. The Nigerian inland waterbodies have been subjected to various forms of degradation due topollution. River Dilimi in Jos North of Plateau state capital is one of suchendangered inland water bodies. Activities around and in the river has ledto discharge of various heavy metal pollutants into the aquaticenvironment rendering water unsuitable for its intended purposes.Methodology and Results: Six (6) water samples were collected at theupper, centre and lower section of the river at the 20 and 120 cm depth, for every six (6) weeks making a total of eighteen (18) samples, Analyzed atNigerian Institute of Mining and Geosciences, Jos. The water samplescollected were pre-treated with few drops of concentrated Nitric acid, anddigested with Aqua-regia in the ratio of 3:1 for an hour. Different standardsolutions were prepared for AAS analysis under Beer-Lambert method ofmetal analysis using Atomic Absorption Spectrophotometer (AAS). Thedata obtained were subjected statistical analysis. The results obtained fromanalyzed water samples were alarming, iron, lead, cadmium andManganese were above the recommended threshold by 277, 6,400, 1,233and 580% accordingly, while zinc and copper were within permissible limit.Conclusion, significance and impact study: River Dilimi can be said to behighly concentrated with hazardous metals of concern like Fe, Pb, Cd andMn. This as a result of bioaccumulation will affect human and animalhealth, aquatic life and crop productivity

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