TABLE OF CONTENTS
Title page
Abstracts
CHAPTER ONE: INTRODUCTION
1.1 Background of Study
1.2 Statement of the Problem
1.3 Justification
1.4 Objectives of the Study
CHAPTER TWO: LITERATURE REVIEW
2.1 Agro-hydrological Models
2.2 Soil Water Balance
2.3 Soil Water Balance Estimation using Lysimeters
2.4 The Use Agro-Hydrological Models in Soil Water Balance Estimation
2.4.1 SWAP (Soil-Water-Atmosphere) model
2.4.1.1 Soil water flow in SWAP model
2.4.1.2 Soil water balance components modules in SWAP
2.4.1.3 System boundary conditions
2.4.1.4 Basic input and output of SWAP (207d) for soil water balance
2.4.2 ISIAMOD (Irrigation Scheduling Impact Assessment Model)
2.4.2.1 Soil water balance module of ISIAMOD
2.4.2.2 Assumptions and limitation
2.4.2.3 Input and output of ISIAMOD model
2.5 Models Assessments
CHAPTER THREE: MATERIALS AND METHODS
3.1 Introduction
3.2 Description of the Study Area
3.3 Treatments and Experimental Design
3.4 Description of the Mini-Lysimeter
3.4.1 Calibration and field set-up of the lysimeters
3.5 Calibration and Field Set-up Gypsum Blocks
3.6 Rain-gauge Installation
3.7 Agronomic Practice
3.8 Data Collection
3.8.1 Field soil moisture measurement from gypsum blocks
3.8.2 Determination of crop parameters
3.8.3 Data from the lysimeter
3.8.4 Determination of field actual crop evapotranspiration (ETa)
3.8.5 Estimation of reference evapotranspiration (ETo)
3.9 Model Simulation
3.10 Model Simulation Run
3.11 Model Evaluation
CHAPTER FOUR: RESULTS AND DISCUSSION
4.1 Introduction
4.2 Field Soil Water Balance
4.2.1 Daily rainfall, deep percolation and runoff depths
4.2.2 Evapotranspiration (ET) and transpiration (T)
4.2.3 Evaporation from cropped (Ecrop) and uncropped surface (E)
4.2.4 Reference (ETo) and(ETc.) evapotranspiration
4.3 Comparison of Models Simulated and Field-measured Evapotranspiration
4.4 Comparison of Models-Simulated and Field-measured Transpiration
4.5 Comparison of Models-Simulated and Field-measured Evaporation
4.6 Comparison of Measured and Simulated Surface Runoff and Deep Percolation
4.7 Measured and Simulated Crop Yield
4.8 Comparison of the Performance of SWAP and ISIAMOD
CHAPTER FVE: SUMMARY, CONCLUSION AND RECOMMENDATION
5.1 Summary
5.2 Conclusion
5.3 Recommendation
REFERENCE
ABSTRACT
Roles of water balance components in any agro-ecological system are indispensible for most physical and physiological processes within the soil-plant-atmosphere system. The performance of two agro-hydrological models: the Soil-Water-Atmosphere-Plant (SWAP) and Irrigation Scheduling Impact Assessment model (ISIAMOD) in simulating soil water balance components (SWBC) of a cropped field under rainfed condition, was studied in a sandy clay loam soil at the Research field of the Department of Agricultural Engineering, Ahmadu Bello University, Samaru, Nigeria. A field experiment consisting of nine sets of weighing-type mini-lysimeter installed in a field of size 0.053 ha was used in the study. The experiment consisting of three treatments replicated three times. The three treatments comprise of cropped lysimeter set-up covered with plastic mulch (polythene) to measure transpiration (T) process, no-mulch cropped lysimeter setup to measure evapotranspiration (ET) process and no-cropped lysimeter set-ups to measure the process of evaporation (E). The lysimeters and the surrounding field were planted with Sammaz-28 Maize variety. The components of soil water balance which include ET, T, E, runoff (Roff) and deep percolation (Dp) were measured directly from the lysimeters. To complement the measurement of ET from the lysimeter, soil moisture depletion study was also carried on the field by installing gypsum blocks at different depths to measure soil moisture. The results showed that the performance of the two models in simulating soil water balance components as compared to the field measured values was satisfactory based on the outcome of the statistical indicators used. The statistical indicators used to compare the performance of the models are coefficient of residual mass (CRM), modelling efficiency (EF) and root mean square error (RMSE). CRM showed that ISIAMOD has the tendency of underestimating the ET, T, and Ecropby a value which ranges from 2.5 to 6.0% while SWAP has the tendency of overestimating the same components which ranges from 2.0 to 9%. The modeling efficiencies of the two models range from 84 to 90%, except for evaporation processes which ranges from of 54 to 62%. The RMSE of the two models ranges from 0.29 to 0.86. They both simulated the seasonal run-off and drainage well. The results show that two models can be used for determination of soil water balance components of cropped soil and for analyzing a better water management option for agricultural production.
CHAPTER ONE
INTRODUCTION
1.1 Background of Study
Water balance components in any agro-ecological system are indispensible for most physical and physiological processes within the soil-plant-atmosphere system, especially in arid and semi-arid regions. Quantitative water balance information is required for the development of efficient method of soil water management (Odofin, et al., 2012). The knowledge of the circulation of water in and out of the soil mass and especially in a cropped field is very crucial in the planning and operation of various soil and water management strategies. A good understanding of all the aspect of soil hydrological balance (soil water balance), that is, rainfall and or irrigation, water stored in the soil, and water losses from cropped soil due to evapotranspiration, deep percolation and runoff is of importance to appreciate the role of various soil and water management strategies in solving environmental problems and increasing agricultural production. It is a very vital tool in estimating the water need of crops (Zoabeida, 2012; Federer, 1996), irrigation scheduling by soil water accounting under different scenario (Crookston, 2011; Igbadun, 2008). Besides planning of irrigation systems, knowledge of soil water balance and hence crop water use is required when planning the various soil and water management structures such as: erosion control structures, planning and design of water harvesting structures and other soil moisture conservation techniques both during rainy and dry seasons.
Soil water balance (accounting) can be likened to a financial statement of income and expenditure. It is an account of all quantities of water added to ― a control volume of soil‖ through rainfall, irrigation or capillary rise from shallow ground water, and expended....
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