Advanced Applications of AquaCrop for Field Management and Climate Impact Assessment
Muhammad Zeeshan Hussain *
Department of Agronomy, MNS-University of Agriculture, Multan, Pakistan.
Muhammad Huzaifa Mahmood
Department of Agricultural, Forestry and Food Sciences, University of Turin, Largo Paolo Braccini, 2, 10095 Grugliasco, Italy.
Farwa
Punjab Agriculture Department, Pakistan.
Fatima Siddiqa
Institute of Soil and Environmental Science, University of Agriculture, Faisalabad, Pakistan.
Sajjad Ahmad
University of Agriculture, Faisalabad, Pakistan.
Anees ur Rehman
Department of Environmental Science, Karakorum International University, Pakistan.
Gill Ammara
School of Surveying and Land Information Engineering, Henan Polytechnic University, Jiaozuo 454003, China.
Abaid Ur Rehman Nasir
Faculty of Agriculture, Institute of Soil and Environmental Sciences, University of Agriculture Faisalabad, Pakistan.
*Author to whom correspondence should be addressed.
Abstract
For several years, crop models have been applied to describe and to estimate the magnitudes of weather and climate impacts on crop growth and production. This paper describes the AquaCrop model, constructed by the FAO, for the purpose of modelling and evaluation of crop production practices and climate change mitigation measures. AquaCrop is particularly useful for regions characterized with dry lands whereby soil water status plays a major role in yield potential, that is AquaCrop therefore embodies simple, accurate and stable performance. It has been then validated for global climate and management practices for simulation of crop phenology, biomass and yield, water balance and water use efficiency, and evapotranspiration. It has proved efficient in the application in crops like Maize, wheat, barley, tea, sorghum and pulse crops including groundnut and soya beans. Stress coefficients for water, fertilizing and temperature are used by AquaCrop for evaluating their impact on crop canopy growth and dry matter production, stomatal closure, flowering, pollination and harvest index. Three levels of calibration, those of canopy cover expansion, dry matter accruement and the relative amount of moisture in the root zone is also available to simulate growth conditions. Reliability of the developed model is assessed by different statistical measures such as Root Mean Square Error (RMSE), Nash-Sutcliffe efficiency, coefficient of determination (R²) and ratio (d). It plays the role of the decision support system in the context of climate change effects, water use efficiency, sowing dates, plant density and fertilizer practices under different climate conditions.
Keywords: AquaCrop, crop models, drought resistant cultivars, agricultural production