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Predicting the water requirement, soil moisture distribution, yield, water productivity of peas and impact of climate change using SALTMED model

Marwa, M.A.; El-Shafie, A.F.; Dewedar, O.M.; Molina-Martinez, J.M.; Ragab, R.. 2020 Predicting the water requirement, soil moisture distribution, yield, water productivity of peas and impact of climate change using SALTMED model. Plant Archives, 20 (Suppl. 1). 3673-3689.

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Abstract/Summary

It’s important to study the effect of climate change on crops and water supplies, during this critical period of water scarcity and increasing food demand. These changes include evapotranspiration, which will affect crop growth and water requirement. This research work explores the impacts of climate change on water requirements, soil moisture distribution, yield and water productivity of peas. Two consecutive field trials were conducted during the 2017 and 2018 growth seasons of peas in El Nubaria zone, Egypt, on sandy soil conditions. Two irrigation schedules were studied, the first is irrigation at 30% depletion of field capacity, FC, the second schedule irrigation used actual weather station data under drip irrigation system. Under both irrigation schedules, measured and observed data were used for calibration and validation of the SALTMED model. The model was tested to study the impact of the future scenarios (RCPs, 4.5 and 8.5) for 2040, on water requirements, soil moisture content, yield and water productivity of peas, for the same study conditions. The field data indicated there was a high uniformity of soil moisture distribution under the 30% depletion of FC irrigation schedule, compared with the irrigation schedule using weather station data, for both seasons. The highest yield was (2.7 and 3.3 t ha-1) for 2017 and 2018 seasons, respectively, under the 30% depletion of FC irrigation schedule. The highest water productivity was (0.95 and 1.07 kg m-3) with total applied of water (2840 and 3070 m3 ha-1) for 2017 and 2018 seasons, respectively, with irrigation at 30% depletion of FC. The calibration and validation of SALTMED model indicated there were a slight variations between the observed and simulated results, with high coefficients of determination, RMCE and CRM values for total dry matter, productivity, water productivity and soil moisture under both irrigation schedules and for both seasons. The predicted data using SALTMED model showed the crop water requirements will increase for RCPs, 4.5 and 8.5 scenarios of 2040. The predicted yield and water productivity tend to decrease in 2040 under both scenarios. In general, SALTMED model is a good tool for predicting total dry matter and yield and can run with different scenarios and under different conditions.

Item Type: Publication - Article
UKCEH and CEH Sections/Science Areas: UKCEH Fellows
ISSN: 0972-5210
Additional Information. Not used in RCUK Gateway to Research.: Freely available via Official URL link.
Additional Keywords: irrigation scheduling, weather station data, water productivity, peas, SALTMED simulation model, climate change
NORA Subject Terms: Agriculture and Soil Science
Related URLs:
Date made live: 27 Apr 2020 12:30 +0 (UTC)
URI: http://nora.nerc.ac.uk/id/eprint/527569

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