Laghari, Khalifa Qasim (2009) Perceptive Research on Irrigation Scheduling and Water Management. PhD thesis, Mehran University of Engineering & Technology, Jamshoro.
The growing demand and increasing fresh-water scarcity urgently require effective and sustainable management of water for irrigation to assure future requirements of food and fiber production. The sustainable management uses advanced technologies to improve water use efficiency. The computer-based irrigation models are globally accepted as most consistent management tools for efficiently using irrigation water on field. An irrigation scheduling computer model (Mehran) is developed basically as an irrigation research and management tool. The Mehran Model is an integrated decision support system (DSS), which is designed using Visual Basic-6.0 platform to compute Reference Evapotranspiration (ETo) by FAO-56 Penman-Monteith method. Crop Evapotranspiration (ETc) and irrigation schedules are computed by the model using daily soil-water balance and dual crop coefficients approaches. The model distinguishes soil texture classes and different irrigation methods, and also considers 66 regional and international crop types. The model computes soil-water profiles variation with respect to the time and existing root depth of the crop. The model interface provides multiple choices to user for designing irrigation schedules by (a) Real-time daily water balance, (b) Planning on demand system, (c) Planning rotational system, and (d) Synchronizing on demand and rotational (warabandi) systems. The model has been field tested and validated on planning and management of various irrigation schedules for cotton and wheat crops in Lower Indus Basin of Pakistan. The field experiments at management allowed depletion (MAD) level of 55, 65 and 75% were carried out for cotton crop, and at MAD level of 45, 55 and 65% for wheat crop. The daily actual crop evapotranspiration (ETca) was observed through gypsum block readings and a drainage lysimeter. The observed seasonal cotton crop actual Evapotranspirations (ETca) in the experiments were 486, 413, and 397 mm and those computed by the model were 504, 421, and 404 mm. Similarly the observed seasonal wheat crop ETc was 363, 359, and 332 mm, and those computed were 383, 369, and 355 mm. The crop water use efficiency (WUE) determined in terms of seed-cotton yield per unit of land and per unit of seasonal ETc were computed to be 6.0, 6.5, and 5.8 kg (ha mm) −1. The corresponding water use efficiencies (WUEs) for the wheat crops were obtained 14.1, 15.0 and 13.4 kg (ha mm) −1. The highest crop WUE was achieved with MAD at 65% for cotton crop and at 55% for wheat crop’s experiments. The model averagely overestimated seasonal ETc of cotton crop merely by 2.41% and 4.31% for wheat crop. Weekly root depth and daily soil-moisture measurements were carried out, which assisted in carefully monitoring effective root zone depth during experiments. When practicing either scientific or traditional irrigation scheduling in the country, a seasonal water amount of 370 mm is suggested for wheat crop, and 450 – 500 mm for cotton crop to achieve optimum yield and WUE. Statistical analysis (R2 = 93%, T–test = 2.6, and F–test = 1481) showed good correlation between the computed and actual seasonal ETc of the crops. The sensitivity analysis on weather input parameters revealed that the model is most sensitive to temperature variations on output of crop transpiration, soil evaporation and irrigation water allocation. The Mehran Model is found to be quite versatile, flexible, user–friendly, and can be successfully used as a decision support system for irrigation scheduling and management for general crops, specifically for cotton and wheat crops in the Lower Indus Basin of Pakistan.
|Item Type:||Thesis (PhD)|
|Uncontrolled Keywords:||Perceptive, Research, Irrigation, Scheduling, Water, Management, Evapotranspiration, lysimeter|
|Subjects:||Engineering & Technology (e)|
|Deposited By:||Mr. Javed Memon|
|Deposited On:||21 Jul 2010 10:37|
|Last Modified:||24 Jun 2011 11:56|
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