Please use this identifier to cite or link to this item: http://localhost:8081/xmlui/handle/123456789/14672
Authors: Hatiye, Samuel Dagalo
Keywords: Deep Percolation;Water in Irrigated Fields;Water Balance Equation;Physically Based Models
Issue Date: Apr-2016
Publisher: Dept. of Civil Engineering iit Roorkee
Abstract: Deep percolation from an irrigated field has caught less attention in many research works although it contributes to significant loss of water in irrigated fields. Deep percolation is often estimated as a residual in a water balance equation. Several methods are used to estimate deep percolation from a cropped area ranging from empirical relations to physically based models (Willis et al. 1997; Vaccaro 2007; Bethune et al. 2008; Arnold 2011; Ma et al. 2013). However, there are limited studies available concerning deep percolation from water intensive crop fields such as rice and berseem under unpuddled field conditions. The present study is concerned with the prediction and field verification of the deep percolation from water intensive crop fields. Estimation of deep percolation was made using both simple water balance and physically based model. Field observation of deep percolation was carried out using drainage type lysimeters. Both laboratory and field experiments were conducted to study the performance of the selected models in predicting deep percolation. The laboratory experiments consisted of collection of soil samples from the experimental field and determination of soil bulk density, soil particle density, soil texture, soil water retention and soil hydraulic parameters. The field experiments involved growing rice and berseem crops under varying regimes of irrigation application. Field observations of irrigation, deep percolation, soil moisture content, saturated hydraulic conductivity and crop parameters were conducted. Yield determination of each crop was also conducted to study the water saving and water productivity of each crop season. Deep percolation has been estimated using the FAO based water balance model after acquiring the necessary data for the components of the water balance. Actual evapotranspiration was computed using the data of reference evapotranspiration, crop and soil moisture stress coefficients in each crop season following FAO procedure (Allen et al. 1998). Penman Monteith approach was used to compute the reference evapotranspiration. The runoff component was only considered when the depth of input water is above the level of field boundary bunds. Groundwater contribution to the root zone has not been considered since the groundwater table in the study area is sufficiently deep. It has been observed that large volume of water is returned as deep percolation loss as physically demonstrated from lysimeter experiments. Nearly 82-87 % of the input water in rice season 1 and 77-80% input water in rice season 2 was accounted for deep percolation from the experimental field. On the other hand, approximately 62-67% of input water in berseem season 1 and 45-52% of input water was lost as deep percolation return flow. The deep percolation computed on daily basis did not agree iii with the measured values; however, deep percolation computed based on lumped time steps (weekly basis for rice) and between wetting intervals (for berseem seasons) agreed well with the field observed deep percolation. This could be due to the fact that some time is needed for drainage water to arrive at lysimeter outlets located well below the crop root zone and the model structure which assumes the deep percolation to take place on the day of irrigation or rainfall only. Consequently, it can be concluded that in application of drainage type lysimeter water balance, estimation of deep percolation from a cropped area can be made fairly well on longer time steps than shorter time intervals. Physically based model predicts deep percolation very well both on daily and lumped time steps unlike the simple water balance model. Model calibrations and validations for soil and crop parameters have been done using field observed data by employing HYDRUS-1D software package. A good agreement between model predicted and field observed deep percolation was obtained. Comparatively, the performance of the model is better in the wet season than the dry season which is attributed to the pronounced development of macropores in the dry season. Although, the physically based model predicts deep percolation well, it could not be able to capture peak deep percolation values which usually result from heavy rainfall storms. Large values of saturated hydraulic conductivity near the soil surface depict the effect of root proliferation, the activities of soil micro organisms, soil cracking which favour the formation of more macropores in the surface layers. The comparison of the two models show that the performance of the models is at par in predicting deep percolation on lumped time steps, although physically based approach showed closer relationship to the field observed deep percolation than the simple water balance model. Water saving and water productivity of different irrigation schedules have also been investigated. Large saving in irrigation water has been achieved by implementing alternative irrigation schedules when compared with the conventional irrigation practice in both rice and berseem seasons. Nominal yield reduction was observed in both crop periods due to large reduction in irrigation water which has but resulted in comparatively high water productivity.
Research Supervisor/ Guide: Hari Prasad, K. S.
metadata.dc.type: Thesis
Appears in Collections:DOCTORAL THESES (Civil Engg)

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