C. A. Madramootoo

Estimation of Future Crop Water Requirements for 2020 and 2050, Using CROPWAT

The objective of this study was to determine the impacts of potential climate change on daily and total crop water requirements (CWR) of peaches in Southern Ontario using CROPWAT in conjunction with the climate scenarios derived from SDSM. Baseline climate is based on the 30 year-period, 1971-2000 of the mean monthly normals, and two time periods in the future centered on the decades of 2020s (2010-2039) and 2050s (2040-2069). The climate parameters of temperature, precipitation, relative humidity, sunshine duration and wind speed were downscaled using the SDSM (version 3.1) method. To determine the future crop water requirements (CWR), the CROPWAT model (FAO, 1992) was used to simulate the daily and the season total CWR and irrigation requirements for the present and the future decades. Results compared to the base climate show an increase in crop water requirements of 6.0 % (39 mm) per season using the SDSM-CGCM1 model for 2020s and 3.0% (20 mm) per season using both the SDSM-HADCM3 A2 & B2 models for 2020s. About 8 % (56 mm) increase in using the SDSM-CGCM1 and HADMC3 A2 models for 2050s, and 7.0 % (43 mm) per season. However, the irrigation requirements decreased, compared to the current situation, by 6.0 % (18 mm) (assuming 90% irrigation efficiency) using the SDSM-CGCM1 for 2020s and by 27% (81 mm) for both SDSM-HADCM3 A2 & B2 models for 2020s. While in 2050s, a decrease of 2.71% (8 mm), 21% (64 mm) and 6% (59 mm) using the SDSM-CGCM1, SDSM-HADCM3 A2 and SDSM-HADCM3 B2, respectively for 2050s.

Evaluation of Winter Freeze Damage Risk to Apple Trees in Global Warming Projections

Winter freeze damage affects fruit production regularly in the northern part of North America. This situation, which is related to climatic conditions, financially affects fruit producers and limits the affected areas to the use of cultivars that are freeze-resistant but do not always yield a sufficient market return. The purpose of this study is to conduct an experiment with a newly developed numerical model (W5L+) and its associated snow cover module to evaluate the effects of the projected climatic change on the risk of winter freeze damage to apple trees. The model W5L+ quantifies the risk of freeze damage occurrence at defined locations based on local meteorological records or projections. Risk quantification is achieved by screening daily meteorological time series with pre-identified parameters that are known to be proxies for conditions that result in freeze-damage. The model was parameterized using historical meteorological records from apple orchards in Farnham, southern Quebec, and descriptions of regional winter freeze damaging events that were recorded between 1920 and 2005. In 82% of the years studied, the model was able to identify correctly the order of magnitude of the recorded freeze events. During the same period, results suggest that extremely low temperatures and prolonged periods of low temperatures were responsible for the majority of damaging events. When used with climatic projections downscaled from a global climate model (GCM), the model predicted a decrease in freeze risk for apple trees at the Farnham orchards in the next 60 years. This trend is due to a decrease in extreme cold events as well as in prolonged periods of low temperature. The present study demonstrates the potential of the W5L+ modeling approach in studying the impact of climate change on the occurrence of damaging freezes. However, the predictions need to be verified by using the model with a large range of agro-climatic conditions and climate projections.

Assessing on-farm irrigation water use efficiency in Southern Ontario.

For high-value horticultural crop production in southern Ontario, irrigation is an essential ingredient in overcoming insufficient rainfall and achieving stabilized crop production. In a context where competition for limited water resources intensifies due to the expansion of the agricultural sector, increasing urban development and tourism, and potential climate change impacts, conserving water through efficient irrigation has become a key solution in addressing this growing challenge. The implementation of advanced soil water monitoring technologies and water budgeting methods for improved irrigation scheduling is examined with regard to water conservation and thus as a means to cope with competing demands for limited water supplies. During the 2007 growing season, soil moisture was measured using two sensors at four field sites (comprising a total of six irrigated zones as two sites include two different irrigation/production systems) in southern Ontario. Irrigation water consumption was measured by flow meters at three sites. In addition, a survey was administered to collect information on growers’ current irrigation scheduling practices. On-farm irrigation performance was assessed by comparing calculated tomato, green bell pepper, strawberry and peach water requirements (using the water budget method) with growers’ estimates of irrigation water use and with soil moisture measurements taken during the growing season. Four out of the six irrigated zones were excessively irrigated, while in one zone, water was insufficiently applied. The crop water requirements were met efficiently exclusively in one zone where tomatoes were grown. Overall, the results of this research show that by implementing advanced soil moisture monitoring technologies, growers can increase precision in water application and reduce the uncertainty in their current irrigation scheduling practices.

A Comparison of DRAINMOD and SWAT for Surface Runoff and Subsurface Drainage Flow Prediction at the Field Scale for a Cold Climate

Tile drainage reduces surface runoff, soil erosion and improves crop yields, but contributes to the loss of nutrients from agricultural fields. Therefore, it is important to accurately predict the field-scale hydrology in order to better manage water resources and ensure environmental sustainability. In this study, two widely used models, DRAINMOD and the Soil and Water Assessment Tool (SWAT), were calibrated and validated for hydrology of two tile-drained agricultural fields in the Pike River watershed of Southern Quebec. The hydrologic performance of DRAINMOD and SWAT was compared for cold-climate conditions and evaluated at seasonal and monthly time scales. Three years of hydrologic data served to calibrate and validate the model, with the year 2002/03 being used for calibration and 2004 for validation. Model predictions of surface runoff and subsurface drainage flow were compared with the measured surface runoff and subsurface drainage flow values from the two instrumented study sites. The comparison of two models was established based on their prediction accuracy. In the calibration period, DRAINMOD overestimated cumulative subsurface drainage outflow by 5 %, and SWAT underestimated cumulative subsurface drainage outflow by 26%. In the validation period, DRAINMOD was found more successful than SWAT in subsurface drainage flow prediction with R2 greater than 0.82 for both sites. Also, the prediction error statistics indicated clearly that the DRAINMOD performed well in predicting subsurface drainage outflows with different soil type in cold climatic conditions. However, the SWAT’s performance model in simulating total monthly surface runoff was better than DRAINMOD during the validation period with R2 greater than 0.88. The results of this study showed that DRAINMOD was better than SWAT at simulating field scale hydrology in most cases. Additionally, the calibration of SWAT required more effort and input data.

A Comparison of Soil Moisture Monitoring Technologies for Irrigation Scheduling

Currently, there is a range of sophisticated and user-friendly soil moisture monitoring equipment on the market which varies in cost, ease of installation/maintenance, as well the information output. However, for the most part, growers are still using antiquated methods (e.g. “feel method”) for determining when to apply water. A variety of soil moisture sensors were installed on southern Ontario farms for use in irrigation scheduling for selected horticultural crops. With the help of growers, the project assessed several of the available units for use in timely determination of irrigation need.