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Comprehensive analysis of evapotranspiration estimation methods and modelling actual evapotranspiration of maize (Zea mays, L.) crop under water deficient conditions for drought proofing and water savings in agriculture

Student Name: Mr Prakashkiran Suryakant Pawar
Guide: Dr. Alok Adholeya
Year of completion: 2012


The use of FAO 56 Penman-Monteith method for reference evapotranspiration (ETo) calculations to get crop water requirement or irrigation scheduling has been recommended worldwide because it provides reasonable results under wide range of climatic conditions.Various popular Penman forms of this equation like FAO 24 Penman (1977), Kimberly-Penman (1996) and Penman (1948) besides original method are used commonly all over the world including India. ‘Evapotranspiration in Irrigation and Hydrology’ Committee of the American Society of Civil Engineers (ASCE) established Task Committee has recommended standardized reference (Standardized Penman-Monteith) equation. This method performs similar to FAO 56 Penman- Monteith method using short reference crop (ETos), which was the reference used in the study. Primary objective of this study was to evaluate performance of these five popular forms of Penman versions of equations based on their daily crop ET predictions under prevailing climatic conditions of New Delhi. Attempts were also made to evaluate the theoretical performance of these popular forms according to guidelines of ASCE. In absence of reliable data required for this method or absence of well established weather station, various other methods viz.FAO 24 Radiation, Priestley-Taylor, Blaney-Criddle, Hargreaves, Turc, Makkink and Pan Evaporation are used commonly. Performance evaluation of these seven commonly used radiation and or temperature based methods based on their daily ETo predictions compared to FAO 56 Penman-Monteith method predicted ETo and lysimetric ETc was also carried out.

The crop ET (ETc) can be obtained from ETo using stage dependent crop coefficient (Kc). Various types of crop coefficients viz. single Kc, weather adjusted single Kc and dual Kc can be developed and used. Choice of Kc depends upon the precision required in the ETc calculations. Extensive review of literature revels that use of single crop coefficient is common & others types of crop coefficients are used very rarely in India. Presented study provides with this important information of application of different types of Kc and performance of above mentioned models with them. Occurrence of mild to severe water stress is common in agriculture, hence performance of these models under different water stress conditions viz. normal (no water stress), mild to moderate (moderate stress), moderate to severe stress (severe stress) and water saturated (wet) conditions has been carried out and presented. Under water stress conditions (moderate stress & severe stress) use of water stress (Ks) adjusted crop coefficient has been done.

Plant water status is one of the important factors responsible for crop growth and management of agricultural water. The crop water stress index (CWSI) based on canopy surface temperature is most often used index for detecting crop water status. Hence it is popular tool for irrigation signal in modern applications which may be evidenced from related literature survey and instrumentation developments. This study examines the application of three different forms of CWSI for Maize (Zea mays L.) crop grown in kharif (July to October) season at New Delhi, India. Crop water stress indices used in the study are Idso’s empirical model, and theoretical models based on Jackson’s and Alve’s definitions.

Another objective of the study was to find out the relationship between ET and microclimatic parameters. These relationships were developed using correlation analysis as well as by establishing stepwise multiple regression analysis under different soil moisture conditions. Then information of performance evaluation of models and analogies of ET prediction multiple parameter stepwise regression analysis were employed to derive ET prediction model under water stress conditions.

For performance evaluation of models, use of fifteen crop seasons secondary data ranging from 1976 to 1991 and two years field experiment data (2005 & 2006) of Maize (Zea mays. L) crop has done. Each crop season has required information of lysimeter ET along with other meteorological parameters and soil moisture observations. All secondary and field experimental data was evaluated for their consistency and accuracy before actual use according to guidelines mentioned in FAO 56. Statistical indicators used to evaluate performance were least root mean square difference (RMSD), mean bias error (MBE) and t-statistics.

Theoretical inter-comparison results support the adoption of a set of “standardized” equations recommended by ASCE Task Committee. Comparisons between sum-of-hourly and daily calculations shows good internal consistencies for ASCE standardized Penman-Monteith as well as by FAO 56 Penman-Monteith and Kimberly-Penman (1982, 1996) methods when used over two different time steps. It can also be concluded from performance evaluation of models using actual observations that ASCE standardized Penman-Monteith and FAO 56 Penman-Monteith is slightly superior to other models under above mentioned four water conditions and using all four types of crop coefficients. Performance evaluation of radiation and/or temperature models showed that Priestley-Taylor and FAO 24 Blaney-Criddle method can be used for ETo predictions under wide range of climatic conditions when limited data is available or reliability of data is in question.

Results of the presented study shows that the CWSI based on Alve’s definitions and empirical CWSI based on Idso’s definitions are better tools for monitoring kharif season Maize crop water stress at New Delhi. In addition to this, it may be concluded that these two definition based CWSI may be used further for irrigation scheduling using additional local information. CWSI based on Alves definition is practical tool for monitoring Maize crop water stress as it does not require estimation of crop surface resistance, while crop water stress indices based on Idso’s definitions and Jackson’s definition may become useful tools for quantifying water stress of Maize crop in New Delhi region using additional validation experiments.

It can also be concluded form the presented study that use of water stress coefficient (Ks) adjusted Kc under water stress conditions, is improving the ET predictions considerably. But use of Ks alone is not sufficient for water stress level quantification or identification of water stress on crop and better methodologies are required for water stress representation. Hence presented research has been provided with novel methodology to estimate ET under water stress conditions.

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