Calibration, validation and application of AquaCrop model in irrigation scheduling for rice under northwest India

Abstract

A lot of research work regarding irrigation scheduling in rice has been carried out at global level with the objective of increasing irrigation water productivity (IWP) and sustaining grain yield. Under natural conditions rain disturb the planned irrigation treatments. One way to overcome this problem is to use rain shelters which is a costly affair, crop growth simulation models offer a good scope to conduct such studies by excluding the effect of rain. Very limited studies are available where FAO's AquaCrop model has been used to develop irrigation schedule for crops. Therefore, a study was conducted using FAO AquaCrop model to develop irrigation schedule for rice having higher IWP. The model was calibrated and validated using the experimental data of field experiments conducting during 2009 and 2010, respectively. The model underestimated the above ground dry biomass at 30 days after transplanting (DAT) in the range of 21.60 to 24.85 %. At the time of harvest the model overestimated the above ground dry biomass within the range 11.58 to 14.34 %. At harvest the values of normalized root mean square error (15.54%) suggested a good fit for the above ground dry biomass and an excellent agreement (3.34%) between observed and model predicted grain yield. The model suggested to irrigate rice transplanted in puddled loamy sand soil on every 5 th day to get higher IWP coupled with statistically similar grain yield as obtained with daily irrigation schedule.

Assessing the impact of climate change on wheat and sugarcane with the AquaCrop model along the Indus River Basin, Pakistan

“…This was necessary under rainfed conditions, as sporadic heavy rains reported along the Punjab province disturbed the planned irrigation treatments. For that reason, the present study followed the approach of Sandhu et al (2015) for rice along the Punjab region of India and that of Andarzian et al (2011) for wheat in Fig. 5.…”

“…Iran, with different irrigation scenarios according to the observed precipitation. While Sandhu et al (2015) tested four different irrigation schedules for the validation of rice with AquaCrop, this work embraced two irrigation schedules for the validation of wheat in Multan. As a result, the present study defined different irrigation schedules based on the average precipitation observed (77.8 mm) during wheat's growing season in Multan during the 2006-2015 period.…”

Simulating water productivity of paddy rice under irrigation regimes using AquaCrop model in humid and semiarid regions of Iran

“…Shrestha et al (2013) reported RMSE of 0.2 t ha −1 for grain yield simulation. Sandhu et al (2015) reported RRMSE of 15.54% in simulating biomass. Maniruzzaman et al (2015) presented 10.0 ≤ NRMSE ≤ 14.7 for biomass simulation.…”

“…AquaCrop model has been tested by several researchers for different crops and climates Geerts et al 2009;Baumhardt et al 2009;Farahani et al 2009;Hsiao et al 2009;Todorovic et al 2009;Araya et al 2010a, b;Stricevic et al 2011;Zinyengere et al 2011;Zeleke et al 2011;Mkhabela and Bullock 2012). Some researchers have been used the AquaCrop model to simulate rice yield response to water (Saadati et al 2011;Lin et al 2012;Shrestha et al 2013;Maniruzzaman et al 2015;Sandhu et al 2015). Achieving an optimal irrigation schedule with the goal of maximum water productivity is especially important in terms of water scarcity in arid and semiarid areas, and even in a humid region.…”

Calibration and Evaluation of Aquacrop for Maize <i>(Zea Mays L.)</i> under Different Irrigation and Cultivation Methods

“…There are many studies about frequency of irrigation of different types of crops in order to increase the productivity of irrigation water by using the Aquacrop model, which was conducted and confirmed by using the experimental data in 2009-2010, the value of Root Mean Square Error (RMSE) was 15.54% of biomass (Sandhu et al, 2015).…”