Study location
This study is conducted in Batticaloa district that belongs to eastern province of Sri Lanka. The geographical coordinates of the Batticaloa district are 7°34’ N and 81°41’ E.
Selection of model
In this study, CROPWAT model was selected for the computation of crop water requirement and irrigation scheduling for rice in Batticaloa district. CROPWAT 8.0 was used to calculate reference evapotranspiration using climatic variables such as maximum and minimum temperature, sunshine hour, rainfall, relative humidity and wind speed.
CROPWAT model input data
The basic input data for CROPWAT model are the climatic parameters which are required for calculating Reference Evapotranspiration. Researchers proposed several methods to determine evapotranspiration out of which the Penman-Monteith Method (
FAO, 1998) has been recommended as the appropriate combination method to determine the crop water requirements using climatic data such as temperature, humidity, sunshine and wind speed.
FAO Penman-Monteith method (
FAO, 1998) was used in the present study for determining reference crop evapotranspiration (ET
O) since it has been reported to provide values that are very consistent with actual crop water use data worldwide
(Allen et al., 2006). Secondary data such as station data (Table 1), climate data (Table 2), rainfall data (Table 3), crop data (Table 4) and soil data (Table 5) were collected in the present study and used as input data for CROPWAT model for further analysis.
Station data
Source
Geospatial data from survey department and https://www.distancesto.com/coordinates/lk/batticaloa-latitude longitude/history/15542.html
Climate data
Following long-term meteorological data were collected from meteorological department.
· Maximum Temperature and Minimum Temperature (degree Celsius).
· Maximum Relative Humidity and Minimum Relative Humidity (%).
· Wind Speed (km/h).
· Sunshine Hours (Hours).
Rainfall data
Average monthly rainfall data were collected from meteorological department to find out the effective rainfall to calculate the crop water requirement and irrigation scheduling.
Determination of effective rainfall
Many water studies have used the CROPWAT 8.0 model to estimate monthly effective rainfall. Although the software offers several alternative methods, the method referred to as the “USDA SCS method” (USDA Soil Conservation Service method) has generally been used due to its simplicity; being only a function of monthly precipitation and not requiring local calibration. The original USDA SCS method estimates monthly effective rainfall from gross rainfall, soil water holding capacity and crop evapotranspiration. A similar study was carried out to determine the water requirement of main crops in the perumal tank irrigation command area in Cuddalore district of Tamilnadu. In the method reference crop evapotranspiration (Reference Evapotranspiration) was determined using the FAO Penman - Monteith method and the effective rainfall was calculated using USDA S.C method (
Saravanan and Saravanan, 2014). Monthly rainfall data are required to calculate the effective rainfall
(Allen et al., 1998 and
Smith, 1991). For this study, the USDA SCS method provided in the CROPWAT model was used to calculate the effective rainfall on monthly basis using the following criteria.
· When total rainfall is <250 mm, effective rainfall (ER) is given by the following equation;
ER=Total R*(125-0.2*TR)/125 .....Eq. 1
· When total rainfall is >250 mm, effective rainfall is given by the following equation;
ER=125+0.1*Total Rainfall …..Eq. 2
Crop data
The crop type, variety and development stage should be considered when assessing the evapotranspiration from crops grown in large, well-managed fields. Crop coefficient values (Kc) were taken from available published data and FAO CROPWAT 8.0 default value. Based on the published information following crop data were collected.
Soil data
The soil module is essential data input, requiring the general soil data like total available water (TAW), maximum infiltration rate, maximum rooting depth, initial soil moisture depletion. In case of calculation of rice water requirement, additional soil data are required such as drainable porosity, critical depletion for puddle cracking, water availability at planting, maximum water depth. In Batticaloa, the coastal belt of eastern province of Sri Lanka, the predominant soil group is sandy Regosols, which contain 95-98% sand with no confining horizons in its soil profile
(Bawatharani et al., 2004). Sandy regosols soil predominating the coastal belt of Batticaloa district is very low in plant nutrients especially nitrogen and poor in oher soil fertility components due to its poor retention capacity (
Premanandarajah and Prapagar, 2009). They are largely dominant in the cultivated area in this narrow strip along the sea
(Heerthihah et al., 2010).
Default value for sandy soil by FAO in the model was used in calculation of irrigation scheduling and related publications (
Central Environmental Authority, 1992) and (
Wickramasinghe and Wijewardena, 2000).