Evaluating the impact of weather forecasts on productivity and environmental footprint of irrigated maize production systems
Article
Article Title | Evaluating the impact of weather forecasts on productivity and environmental footprint of irrigated maize production systems |
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ERA Journal ID | 3551 |
Article Category | Article |
Authors | Collins, Brian, Lai, Yunru, Grewer, Uwe G, Attard, Steve, Sexton, Justin and Pembleton, Keith G. |
Journal Title | Science of the Total Environment |
Journal Citation | 954 |
Article Number | 176368 |
Number of Pages | 18 |
Year | 2024 |
Publisher | Elsevier |
Place of Publication | Netherlands |
ISSN | 0048-9697 |
1879-1026 | |
Digital Object Identifier (DOI) | https://doi.org/10.1016/j.scitotenv.2024.176368 |
Web Address (URL) | https://www.sciencedirect.com/science/article/pii/S0048969724065240 |
Abstract | Integrating weather forecasts into decision support systems empowers farmers to optimise irrigation schedules, thereby boosting crop yields and conserving water. However, inaccurate forecasts can jeopardise productivity and irrigation efficiency. This study combines a crop model with a stochastic pseudo-weather forecast algorithm to: (1) determine the reliability needed in a weather forecast algorithm for effective irrigation management; and (2) assess the impact of weather forecast reliability on the productivity and environmental footprint of various maize cropping systems across diverse climates. It employs the Next Generation of Agricultural Production Systems sIMulator (APSIM NextGen) to simulate maize growth at eleven locations representing diverse climates globally. Various planting schedules, soil types, irrigation systems, and nitrogen availability levels were considered to examine the effects of perfect and imperfect weather forecasts. The findings underscore the potential of integrating weather forecasts into irrigation management for enhanced productivity and sustainability. High-confidence forecasts and longer lead times increase yields (up to 11 %) and improve sustainability outcomes, particularly in wetter climates and for conditions with low nitrogen availability. Conversely, when the accuracy of forecasts is low, forecast-driven irrigation management may lead to yield reductions compared to a baseline system, especially in drier climates (up to 26 % reduction), necessitating tailored management strategies. Soil type and farmer's risk tolerance further influence the effectiveness of forecast-driven irrigation management, emphasising the need for context-specific approaches. By understanding and leveraging the interconnected impacts of weather forecasts on yield, water use efficiency, nitrogen loss, and greenhouse gas emissions, farmers can optimise productivity while minimising environmental impacts. |
Keywords | APSIM; Crop modelling; Environmental footprint; Irrigation management; Water use efficiency |
Article Publishing Charge (APC) Funding | School/Centre |
Contains Sensitive Content | Does not contain sensitive content |
ANZSRC Field of Research 2020 | 3004. Crop and pasture production |
4199. Other environmental sciences | |
3002. Agriculture, land and farm management | |
Byline Affiliations | Centre for Sustainable Agricultural Systems |
AgriTech Solutions, Australia | |
Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia | |
School of Agriculture and Environmental Science |
https://research.usq.edu.au/item/zq02x/evaluating-the-impact-of-weather-forecasts-on-productivity-and-environmental-footprint-of-irrigated-maize-production-systems
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