Integrating seasonal climate forecasts with Robusta coffee model across the agricultural landscapes of Vietnam

Byrareddy, Vivekananda Mittahalli (2020) Integrating seasonal climate forecasts with Robusta coffee model across the agricultural landscapes of Vietnam. [Thesis (PhD/Research)]

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Abstract

Seasonal climate variations, extreme climatic events, particularly drought, and management practices such as fertiliser application and irrigation are among the factors affecting substantially Robusta coffee (Coffea canephora) production. In Vietnam, which is the world's largest Robusta coffee-producing country, the enhanced climate variability in recent decades significantly affected coffee production. Improved seasonal climate forecasts (SCF) integrated to Robusta coffee models are critical to reducing climate risk and capitalising on the opportunities. However, the methods to harness such integrated forecasting systems at the required temporal and spatial scales remain very much unknown or underutilised in Vietnam.

This Ph.D. project research aimed at addressing this vital question by developing an integrated SCF-Robusta coffee production model for yield forecasting, capable of simulating reliably Robusta coffee growth and predict yield under different environmental conditions and management practices at the regional scale. Specifically, we aimed to (1) characterise the fertiliser and irrigation management practices across the study area (the Central Highlands region of Vietnam) and develop empirical relationships between yields, fertiliser and irrigation; (2) assess drought impacts on coffee yield and profit, and the effectiveness of the mitigation strategies; (3) investigate the improvement of the simplified biophysical Robusta coffee model, the USQ-Robusta coffee model, through the integration of fertiliser and irrigation components; and (4) test the capability of integrating SCF and the modified version of the USQ-Robusta coffee model to forecast probabilistic coffee yields at sufficient lead times.

Farms data including management practices and coffee yield were collected randomly across the four major Vietnamese Robusta coffee-producing provinces (Dak Lak, Dak Nong, Gia Lai and Lam Dong) from 558 farmers over ten years (2008–2017). Climate data were retrieved from the US National Aeronautics and Space Administration’s Prediction Of Worlwide Energy Resources website. SCF derived from five selected prediction systems were sourced from the Climate Change Service website and from the University of Southern Queensland-Centre for Applied Climate Sciences (USQ-CACS)’s seasonal climate forecasting system.

Four types of chemical (urea, blended NPK, superphosphate and potassium chloride) and two types of natural (organic compost and lime) fertilisers were used routinely across the study provinces. The overuse of chemical fertilisers (double the recommended rates of N:P:K at 192:88:261 kg ha-1) did not result in higher yields in the majority of cases. The analysis of irrigation practices showed that, with adequate management practices, substantial water savings can be achieved: up to 26% reduction annually from the current levels (909 - 1818 L plant-1). With irrigation being typical in coffee farming, the majority of surveyed farmers adopted mulching in drought years and were best rewarded compared to their counterparts who did not (10% increase in gross margins on average). Our study also revealed that while drought reduced Robusta coffee yield by 6.5% on average, its impacts on gross margins were noticeable, with a 22% decline on average from levels achieved in average-rainfall-condition years. Improving the impacts of water stress on yield throughout the growth season in the USQ-Robusta coffee model resulted in better model performance. The existing water stress component was modified based on crop water requirements derived from the CROPWAT model. Prediction errors were reduced: up to 21% decrease of RMSE. Further, the probabilistic yield forecasting using SCF for May to November 2019 showed satisfactory results generally, with the median yield variance ranging from 0.26 to 0.29 t ha-1.

Improved management of fertiliser and irrigation, and crop diversification are options to enhance the profitability of coffee farming systems. This research knowledge could serve as a decision support tool for farmers and the coffee industry in business planning and climate risk management.


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Item Type: Thesis (PhD/Research)
Item Status: Live Archive
Additional Information: Doctor of Philosophy (PhD) thesis.
Faculty/School / Institute/Centre: Current - Institute for Life Sciences and the Environment - Centre for Applied Climate Sciences (1 Aug 2018 -)
Faculty/School / Institute/Centre: Current - Institute for Life Sciences and the Environment - Centre for Applied Climate Sciences (1 Aug 2018 -)
Supervisors: Stone, Roger; Mushtaq, Shahbaz; Kouadio, Louis
Date Deposited: 19 Oct 2020 06:49
Last Modified: 14 Jul 2021 22:05
Uncontrolled Keywords: Robusta coffee, seasonal climate forecasts, biophysical model, irrigation, fertiliser, drought adaptation strategy
Fields of Research (2008): 04 Earth Sciences > 0401 Atmospheric Sciences > 040104 Climate Change Processes
07 Agricultural and Veterinary Sciences > 0701 Agriculture, Land and Farm Management > 070108 Sustainable Agricultural Development
07 Agricultural and Veterinary Sciences > 0701 Agriculture, Land and Farm Management > 070105 Agricultural Systems Analysis and Modelling
07 Agricultural and Veterinary Sciences > 0703 Crop and Pasture Production > 070302 Agronomy
07 Agricultural and Veterinary Sciences > 0799 Other Agricultural and Veterinary Sciences > 079901 Agricultural Hydrology (Drainage, Flooding, Irrigation, Quality, etc.)
07 Agricultural and Veterinary Sciences > 0799 Other Agricultural and Veterinary Sciences > 079902 Fertilisers and Agrochemicals (incl. Application)
Fields of Research (2020): 37 EARTH SCIENCES > 3702 Climate change science > 370201 Climate change processes
30 AGRICULTURAL, VETERINARY AND FOOD SCIENCES > 3002 Agriculture, land and farm management > 300210 Sustainable agricultural development
30 AGRICULTURAL, VETERINARY AND FOOD SCIENCES > 3002 Agriculture, land and farm management > 300207 Agricultural systems analysis and modelling
30 AGRICULTURAL, VETERINARY AND FOOD SCIENCES > 3004 Crop and pasture production > 300403 Agronomy
30 AGRICULTURAL, VETERINARY AND FOOD SCIENCES > 3002 Agriculture, land and farm management > 300201 Agricultural hydrology
30 AGRICULTURAL, VETERINARY AND FOOD SCIENCES > 3004 Crop and pasture production > 300499 Crop and pasture production not elsewhere classified
Identification Number or DOI: doi:10.26192/k1v4-0907
URI: http://eprints.usq.edu.au/id/eprint/39933

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