HR: 1340h
AN: H53C-0481    [Abstracts]
TI: On the Estimation of Evapotranspiration for Future Climate Change Impacts on Agricultural Water Requirements
AU: * Aloysius, N R
EM: noel.aloysius@und.edu
AF: Deptartment of Earth System Science and Policy, University of North Dakota, Grand Forks, ND 58202-9011 United States
AB: Doubling of atmospheric CO2 concentrations are likely to increase the average global temperature by two to five degrees Celsius and would cause significant changes in climate. Changes in temperature will directly impact water requirements of plants. Since agriculture is the major water consumer, accurate estimates of agricultural crop water requirements are required in order for countries to better plan their future water allocations to different sectors, especially to the agriculture sector. Changes in crop water requirements are indicated by changes in reference evapotranspiration (ET). Procedures for estimating ET should be applicable to all climatic conditions and accurate for both short and long term periods, and should not require data or information that is usually of very limited availability. This is of greater importance when it comes to planning regional and country level agricultural water requirements. Three methods to estimate monthly ET, namely Hargreaves method (ETH), Samani method (ETS) and Food and Agricultural Organization's (FAO) modified Penman-Monteith (FAOETP) method are compared with data obtained for the Indian Sub-continent. While ETH and ETS requires minimum data (minimum and maximum temperatures), FAOETP requires the estimation of net solar radiation and wind velocity in addition to the above two and is physically based. The results are compared with Penman-Monteith ET (ETP) computed from field data. Regression analyses were performed considering ETP as dependant variable and the other three ETs' as independent variables. Results indicates that FAOETP has very high correlation with ETP (average monthly R Square = 0.794, CV = 0.157) compared to ETH (average monthly R Square = 0.709, CV=0.163) and ETS (average monthly R Square = 0.458, CV=0.495). While FAOETP method gives better results and has the capability of incorporating more variables to improve its performance, ETH method is also comparable and provides a simplified procedure. Both the methods can be employed with minimum set of data.
DE: 1807 Climate impacts
DE: 1816 Estimation and forecasting
DE: 1818 Evapotranspiration
SC: Hydrology [H]
MN: Fall Meeting 2005