Risk assessment in decision-making on rainfed cotton

被引:0
|
作者
Crétenet, M
Mohtar, RH
Moussa, AA
机构
[1] Cirad, Unite Rech Syst Cotonniers Petit Paysannat, F-34398 Montpellier 5, France
[2] Purdue Univ, Dept Agr & Biol Engn, W Lafayette, IN 47906 USA
[3] Irad, Ctr Maroua, Maroua, Cameroon
来源
CAHIERS AGRICULTURES | 2006年 / 15卷 / 01期
关键词
cotton; Burkina; pluviometry; cultivation; simulation models; fertilizers; crop protection; risk assessment; economic threshold;
D O I
暂无
中图分类号
S [农业科学];
学科分类号
09 ;
摘要
A probability-based methodology to assess the effect of year-to-year climatic variability, soil and management input on crop response is demonstrated using the COTONS (R) - SIMBAD system. The methodology allows for the quantification of the risk associated with these input variability using a systematic and bias-free approach. It also allows the user to identify relevant crop state variables that can be used for short-term better decision making related to crop management. Because of the high cost and time involved in evaluating management practices, these modeling approaches can be effective tools for better decision making. Due to the significance in their results, the authors recommend this risk-based approach as a way to address decision making under site and climatic uncertainties. The COTONS (R) - SIMBAD system is demonstrated as an important research tool for pushing back the limits of classical adaptative research programs. It provides an original tool to analyse the cotton crop response variability which could not have been assessed with classical enquiries or experimental designs. Under rainfed conditions, the climate remains the main determinant of variability in crop response Under a reference crop management sequence. This uncertainty in crop response is simulated by the model and analysed in terms of risk according to yield targets and crop management sequences. The intermediate crop state variables simulated by the model are used for day-to-day decision rules. This pilot research is an important step before evaluating these decision rules under field conditions. These decisions help reduce the risk of underyield a target value and have an economic cost associated which was also presented with these risks.
引用
收藏
页码:109 / 115
页数:7
相关论文
共 50 条
  • [31] A Decision-Making System for Cotton Irrigation Based on Reinforcement Learning Strategy
    Chen, Yi
    Yu, Zhuo
    Han, Zhenxiang
    Sun, Weihong
    He, Liang
    AGRONOMY-BASEL, 2024, 14 (01):
  • [32] OPERATIONAL RISK MANAGEMENT - A NEW PARADIGM FOR DECISION-MAKING
    BEROGGI, GEG
    WALLACE, WA
    IEEE TRANSACTIONS ON SYSTEMS MAN AND CYBERNETICS, 1994, 24 (10): : 1450 - 1457
  • [33] Between Professional Norms and Professionalism: Risk Assessment and Decision-Making of Arab Social Workers Regarding Children at Risk
    Nouman, Hani
    Enosh, Guy
    Jarjoura, Amal
    RESEARCH ON SOCIAL WORK PRACTICE, 2019, 29 (05) : 572 - 583
  • [34] The application of BP neural network in risk assessment of real estate investment decision-making stage
    Liu, Shuru
    You, Zeng
    Chang, Xiaojun
    PROCEEDINGS OF 2007 INTERNATIONAL CONFERENCE ON CONSTRUCTION & REAL ESTATE MANAGEMENT, VOLS 1 AND 2, 2007, : 695 - 698
  • [35] Multi-Criteria Decision-Making Model to Support Landfill Prioritization: Methane Risk Assessment
    Marceta, Una
    Vujic, Bogdana
    Srdjevic, Zorica
    Mihajlovic, Visnja
    Radosav, Dragica
    POLISH JOURNAL OF ENVIRONMENTAL STUDIES, 2021, 30 (02): : 1297 - 1306
  • [36] Risk assessment based collision avoidance decision-making for autonomous vehicles in multi-scenarios
    Li, Guofa
    Yang, Yifan
    Zhang, Tingru
    Qu, Xingda
    Cao, Dongpu
    Cheng, Bo
    Li, Keqiang
    TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2021, 122
  • [37] Cost Overrun Risk Assessment for Healthcare Projects: A Modified Fuzzy Group Decision-Making Approach
    Islam, Muhammad Saiful
    Salem, Mohamed
    Tantawy, Mohamed
    Salah, Mohamed
    JOURNAL OF CONSTRUCTION ENGINEERING AND MANAGEMENT, 2024, 150 (12)
  • [38] Rule-Guidance Reinforcement Learning for Lane Change Decision-making: A Risk Assessment Approach
    Xiong, Lu
    Li, Zhuoren
    Zhong, Danyang
    Xu, Puhang
    Tang, Chen
    CHINESE JOURNAL OF MECHANICAL ENGINEERING, 2025, 38 (01)
  • [39] Decision-Making Tool for Groundwater Level Spatial Distribution and Risk Assessment Using Geostatistics in R
    Varouchakis, Emmanouil A.
    Theodoridou, Panagiota G.
    Karatzas, George P.
    JOURNAL OF HAZARDOUS TOXIC AND RADIOACTIVE WASTE, 2020, 24 (01)
  • [40] A spatio-temporal population model to support risk assessment and damage analysis for decision-making
    Ahola, Terhi
    Virrantaus, Kirsi
    Krisp, Jukka Matthias
    Hunter, Gary J.
    INTERNATIONAL JOURNAL OF GEOGRAPHICAL INFORMATION SCIENCE, 2007, 21 (08) : 935 - 953