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An FAO model comparison: Python Agroecological Zoning (PyAEZ) and AquaCrop to assess climate change impacts on crop yields in Nepal.

Authors :
Alvar-Beltrán, Jorge
Soldan, Riccardo
Vanuytrecht, Eline
Heureux, Ana
Shrestha, Nirman
Manzanas, Rodrigo
Prasad Pant, Krishna
Franceschini, Gianluca
Source :
Environmental Development; Sep2023, Vol. 47, pN.PAG-N.PAG, 1p
Publication Year :
2023

Abstract

To identify the most effective agricultural transformation and adaptation measures, the Food and Agriculture Organization (FAO) calls for action to produce robust crop suitability assessments. We developed a novel approach to assess the inputs and outputs of two FAO tools (AEZ and AquaCrop). We use Nepal as a case study, a country offering a myriad of ecoclimatic conditions for multiple crops. Our work provides further evidence of climate change impacts on rice, maize and wheat yields along the different agroclimatic zones of Nepal, equally under rainfed and irrigated conditions for future climate scenarios. The findings of bias-adjusted regional climate models (RCMs) shows increasing temperatures and precipitation; whereas the outputs of agroecological/crop models show effective adaptation of C3 crops to a CO2 enriched environment. In sum, this supports the climate-crop modelling user community, extension workers and government agencies with guidance's to overcome uncertainties associated with the application of these tools. • Increasing temperatures and precipitation is projected along the Koshi River Basin. • Effective adaptation of C3 crops to a CO 2 enriched environment. • PyAEZ is best suited to support various applications in agricultural development planning, scenarios studies of climate change impacts, while AquaCrop is better suited as a field level planning model to assist management decisions in both irrigated and rainfed agriculture. [ABSTRACT FROM AUTHOR]

Details

Language :
English
ISSN :
22114645
Volume :
47
Database :
Supplemental Index
Journal :
Environmental Development
Publication Type :
Academic Journal
Accession number :
170043999
Full Text :
https://doi.org/10.1016/j.envdev.2023.100882