A new framework to quantify maize production risk from chilling injury in Northeast China

Agricultural production frequently suffers from meteorological risks. Timely and accurately estimating yield losses will greatly improve disaster risk management, especially for a useful tool to transfer risks—agricultural insurance. The weather index insurance products have increasingly become prom...

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Main Authors: Ziyue Li, Zhao Zhang, Jing Zhang, Yuchuan Luo, Liangliang Zhang
Format: Article
Language:English
Published: Elsevier 2021-01-01
Series:Climate Risk Management
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2212096321000280
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author Ziyue Li
Zhao Zhang
Jing Zhang
Yuchuan Luo
Liangliang Zhang
author_facet Ziyue Li
Zhao Zhang
Jing Zhang
Yuchuan Luo
Liangliang Zhang
author_sort Ziyue Li
collection DOAJ
description Agricultural production frequently suffers from meteorological risks. Timely and accurately estimating yield losses will greatly improve disaster risk management, especially for a useful tool to transfer risks—agricultural insurance. The weather index insurance products have increasingly become promising alternatives to traditional ones. However, the current single-index insurances, mainly based on a statistical model with a lower explanation ability and at an aggregate scale (e.g. county, province), are lack of mechanistic processes and having huge basis risk. Here, we proposed a new framework to quantify maize production risk by running the well calibrated CERES-Maize driven by various chilling scenarios. We first analyzed the chilling risk across Northeast China, then developed a composite chilling index (CCI) and CCI-based vulnerability curves to derive the corresponding yield losses. Finally, the specific pure premium rates were calculated respectively at 16 sites across the studied areas. The results showed that composite-index insurance (RMSE¯ ≤ 721 kg/ha) outperformed (R2 improved by 35%) every single index (RMSE¯ ≈ 1140 kg/ha) in quantifying yield loss. We believe our proposed framework will benefit insurer companies rapidly estimating yield losses and designing more promising products, and potentially apply into other regions for other crops and hazards to transfer climate risk in the future.
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spelling doaj.art-7dd9a65de7b2481e9f1a276193be419e2022-12-21T18:48:14ZengElsevierClimate Risk Management2212-09632021-01-0132100299A new framework to quantify maize production risk from chilling injury in Northeast ChinaZiyue Li0Zhao Zhang1Jing Zhang2Yuchuan Luo3Liangliang Zhang4State Key Laboratory of Earth Surface Processes and Resource Ecology/MoE Key Laboratory of Environmental Change and Natural Hazards, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, ChinaCorresponding author at: Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China.; State Key Laboratory of Earth Surface Processes and Resource Ecology/MoE Key Laboratory of Environmental Change and Natural Hazards, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, ChinaState Key Laboratory of Earth Surface Processes and Resource Ecology/MoE Key Laboratory of Environmental Change and Natural Hazards, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, ChinaState Key Laboratory of Earth Surface Processes and Resource Ecology/MoE Key Laboratory of Environmental Change and Natural Hazards, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, ChinaState Key Laboratory of Earth Surface Processes and Resource Ecology/MoE Key Laboratory of Environmental Change and Natural Hazards, Faculty of Geographical Science, Beijing Normal University, Beijing 100875, ChinaAgricultural production frequently suffers from meteorological risks. Timely and accurately estimating yield losses will greatly improve disaster risk management, especially for a useful tool to transfer risks—agricultural insurance. The weather index insurance products have increasingly become promising alternatives to traditional ones. However, the current single-index insurances, mainly based on a statistical model with a lower explanation ability and at an aggregate scale (e.g. county, province), are lack of mechanistic processes and having huge basis risk. Here, we proposed a new framework to quantify maize production risk by running the well calibrated CERES-Maize driven by various chilling scenarios. We first analyzed the chilling risk across Northeast China, then developed a composite chilling index (CCI) and CCI-based vulnerability curves to derive the corresponding yield losses. Finally, the specific pure premium rates were calculated respectively at 16 sites across the studied areas. The results showed that composite-index insurance (RMSE¯ ≤ 721 kg/ha) outperformed (R2 improved by 35%) every single index (RMSE¯ ≈ 1140 kg/ha) in quantifying yield loss. We believe our proposed framework will benefit insurer companies rapidly estimating yield losses and designing more promising products, and potentially apply into other regions for other crops and hazards to transfer climate risk in the future.http://www.sciencedirect.com/science/article/pii/S2212096321000280Maize production riskComposite index insuranceChilling injuryCrop modelHazard scenarios-driven
spellingShingle Ziyue Li
Zhao Zhang
Jing Zhang
Yuchuan Luo
Liangliang Zhang
A new framework to quantify maize production risk from chilling injury in Northeast China
Climate Risk Management
Maize production risk
Composite index insurance
Chilling injury
Crop model
Hazard scenarios-driven
title A new framework to quantify maize production risk from chilling injury in Northeast China
title_full A new framework to quantify maize production risk from chilling injury in Northeast China
title_fullStr A new framework to quantify maize production risk from chilling injury in Northeast China
title_full_unstemmed A new framework to quantify maize production risk from chilling injury in Northeast China
title_short A new framework to quantify maize production risk from chilling injury in Northeast China
title_sort new framework to quantify maize production risk from chilling injury in northeast china
topic Maize production risk
Composite index insurance
Chilling injury
Crop model
Hazard scenarios-driven
url http://www.sciencedirect.com/science/article/pii/S2212096321000280
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