MODELLING WATER PRODUCTIVITY OF MAIZE CROP UNDER DEFICIT IRRIGATION USING AquaCrop MODEL

MODELLING WATER PRODUCTIVITY OF MAIZE CROP UNDER DEFICIT IRRIGATION USING AquaCrop MODEL

By: Eng. KAPKWANG, Charles ChepkewelKAPKWANG, Charles Chepkewel

Prof. Emmanuel C. Kipkorir -Prof. Emmanuel C. Kipkorir - UoE UoE Date: 4Date: 4thth July 2014 July 2014

Introduction

NIB, 3-4/07/2014«MODELLING CROP WATER PRODUCTIVITY UNDER DEFICIT IRRIGATION USING AquaCrop MODEL.» slide 2

Irrigation - is significant & essential in arid environments used to increase crop water productivity in semiarid & humid regions.

Kenya's total irrigated area is about 80,000 ha. Both public & private small-scale irrigation is still less than 50,000 ha. This is still very small as compared to the estimated potential of more than 300,000 ha (Carter, 1994).

Anticipated that Kenya agricultural sector will compete with domestic & industry for the increasingly scarce water resources, yet is under pressure to produce more food and fibre with less water to satisfy the food needs of its fast growing population.

Pressure on arable land is high & future increase in agricultural production depends on the possibilities of increasing yield levels per ha, as well as bringing unused & marginal lands under cultivation.

Study Area


Scheme Layout

NIB, 3-4/07/2014«MODELLING CROP WATER PRODUCTIVITY UNDER DEFICIT IRRIGATION USING AquaCrop MODEL.»

slide 4

Background of the Problem


Sustainability of irrigated agriculture in Eldume irrigation scheme is at risk:

Watershed degradation along river Molo resulting in reduced river flows hence decreasing supply available for irrigation & irrigation costs are rising.

Due to unpredictable & uneven rainfall patterns.More frequent droughts & floods due to low/high-variable rainfall &

high evaporation rates. Inadequate optimization strategy in irrigation i.e. when & how much

to irrigate, for each water application. Optimizing control & scheduling parameters in irrigation is considered as a nested problem to the farmers.

Water deficits have negatively affected food security because of declining levels of production particularly maize which forms the basis of applying AquaCrop model in simulating maize crop yield under deficit irrigation in ASAL environments.

Justification of the Research


Threat to food security & agricultural productivity adequate for its fast increasing population esp. ``arid & semi-arid lands’’ under irrigation.

Need of utilization of abandoned land reclamation as result of water scarcity.

Need for water mgt strategies to solve declining maize crop yield due to water stress.

Dissemination of knowledge & understanding of short season maize variety irrigation schedule to water engineers, farmers associations, government agencies on mgt of limited water resource.

Research ObjectivesResearch Objectives

Slide 8

Broad ObjectiveTo establish the performance of maize crop yield under water deficit

irrigation schedules in order to enhance future water use efficiency & planning.

Specific Objectives To conduct an on-field experiment of maize crop grown in a semi-arid climate with treatments of

different water stress levels. To calibrate and validate the AquaCrop model for Eldume irrigation scheme based on maize field trials. To apply the Aquacrop model to simulate the scenarios of crop yield under water stress conditions on

maize production in Eldume irrigation scheme. To apply the SPSS model to test the statistical significance of the AquaCrop model in modeling crop

water productivity in a semi-arid irrigation system. To utilize Excel Optimization Model to determine the best irrigation interval/events in the system for

future maize crop irrigation water mgt.

NIB, 3-4/07/2014 CROP WATER PRODUCTIVITY UNDER DEFICIT IRRIGATION USING AquaCrop MODEL.»

Methodology- AquaCrop Input Parameters


slide 8

Climate data- Collected from HOBO meteorological weather station (KARI –MARIGAT) (Rainfall, Max & Min Temp, Relative Humidity, wind speed )

Reference Evapotranspiration – FA0 56 Penman Monteith Equation-Use of ETo calculator software

Crop Inputs - Canopy cover measurements – Use of Meter rule - measured on weekly basis

Soil input - Soil textural class – Soil Sampling ( 4 sampling points) – hydrometer method in Laboratory & involved determining percentage proportion of sand, silt and clay)

Pedo-transfer functions generated by soil texture triangle to evaluate moisture retained at field capacity and permanent wilting point, hydraulic conductivity & bulk density.

Irrigation water applied – Use of Parshall flume measurements (head measurements & timing to compute Q – Discharge (m^3/s) and Volume applied (m^3).

Climatic data collection-Hobo weather station (Marigat)


slide 9

Field Trial Plots Details Layout Showing Irrigation Furrows & Feeder Canals.


slide 10

On-Field experiment (34 days after sowing).

Physical characteristics of the

5 days Irrigation Interval

Physical characteristics of the

7 days Irrigation Interval


On-Field experiment –(Crop Input) cont’d

Physical characteristics of the 10 days irrigation interval

Physical characteristics of the 12 days irrigation interval


slide 12

On-Field experiment -Soil input

Soil sampling at the experimental site

Laboratory results- Soil bulk properties calculator (K.E.Saxton et al., 1986)


slide 13

.

Installation of Portable Parshall flume for water measurement


slide 14

Crop Parameters and program settings calibrated for Eldume irrigation maize crop


Input parameters and Program Settings for Calibration

Soil Inputs Climate Inputs


slide 16

Field Trial Simulation Results

Simulation results for 5 days Irrigation Interval

Simulation results for 7days Irrigation Interval


slide 17

AquaCrop Yield Simulation results (cont’d)




Simulated Canopy Cover (%) and Linear regression plot for treatment 1.








Maize crop production, crop water productivity & water use efficiency


slide 23

Comparison of Simulated Vs Observed aboveground biomass for 5, 7, 10 & 12 days irrigation intervals


Comparison of Simulated Vs Observed grain yield for 5, 7, 10 & 12 days irrigation intervals


slide 25

Validation of the AquaCrop model

Results of combined observed and simulated model output.

Validation of observed & simulated yield in a single plot.


Dependent Variable: Observed grain yield (ton/ha)


slide 27

Pair wise comparisons: Dependent variable of observed grain yield (ton/ha)


slide 28

Estimated marginal means of observed grain yield(ton/ha)


slide 29

Treatments Scenario analysis

Full supply scenario (100%) Water supply of 75%


Scenario analysisWater supply of 50%

Water supply of 25%


Scenarios summary results of area, water & benefits under 0%, 25%, 50% and 75% water shortage for the four treatments.


Conclusion


The variation of irrigation water from the non-water stressed to severe water stressed experimental blocks indicates that maize production depends majorly on the amount of water supplied to the crops throughout the season.

AquaCrop model accurately predicted the simulation of the system reasonably well as it resulted in a linear relationship of an increased/decreased yield for maize crop.

The model gave more reliable estimates of crop yield, however results indicated a decline from 6.183 ton/ha to 3.015 ton/ha for a non-water stressed to severely water stressed treatment indicating a water deficit scenario.

Based on optimal maize crop revenue collected, the best irrigation interval good for practice at Eldume irrigation scheme was the 7 days interval with 13 irrigation events per season.

Recommendation


slide 34

Construction of water reservoirs due to water deficit for sustainable irrigation systems.

Conservation of the environment to curb watershed degradation especially on the country’s water towers & along river sources.

Efforts towards use of crop water modeling tools in research to eliminate the current problems of food insecurity.

THANK YOU

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MODELLING WATER PRODUCTIVITY OF MAIZE CROP UNDER DEFICIT IRRIGATION USING AquaCrop MODEL

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