Sivakumar / Hansen / Meinke Climate Prediction and Agriculture

Advances and Challenges
1. Auflage 2007
ISBN: 978-3-540-44650-7
Verlag: Springer Berlin Heidelberg
Format: PDF
Kopierschutz: 1 - PDF Watermark

E-Book, Englisch, 319 Seiten

Based on an International Workshop held in Geneva in 2005, this book reviews the advances made so far in seasonal climate predictions and their applications for management and decision-making in agriculture. It also identifies the challenges to be addressed in the next 5 to 10 years to further enhance operational applications of climate predictions in agriculture, especially in developing countries.

Autoren/Hrsg.

Meinke, Holger

Sivakumar, Mannava Vk

Hansen, James

Inhaltsverzeichnis

1;Foreword;5
2;Preface;8
3;Contents;10
4;Contributors;20
5;Climate Prediction and Agriculture: Summary and the Way Forward;26
5.1;Introduction;26
5.2;Predicting Climate Fluctuations and Agricultural Impacts;27
5.3;Effectiveness of Seasonal Forecasts and Climate Risk Management;28
5.4;Economics of Climate Forecast Applications;30
5.5;Assessing Adoption and Benefit;31
5.6;Building on Farmers’ Knowledge;32
5.7;Way Forward;33
5.8;Conclusions;36
5.9;Acknowledgements;36
5.10;References;36
6;Climate Downscaling: Assessment of the Added Values Using Regional Climate Models;39
6.1;Introduction;39
6.2;Smaller Spatial Scales;40
6.3;Predictability at Smaller Spatial and Temporal Scales;43
6.4;Dynamical Downscaling Forecasts;47
6.5;Future Directions;50
6.6;References;51
7;Development of a Combined Crop and Climate Forecasting System for Seasonal to Decadal Predictions;54
7.1;Rationale;54
7.2;Numerical Crop and Climate Models;54
7.3;Combining Crop and Climate Models;55
7.4;Consideration of the Forecast Skill of a Combined Crop- Climate Modeling System;57
7.5;An Integrated Approach to Climate-Crop Modeling;58
7.6;Conclusions;62
7.7;References;62
8;Delivering Climate Forecast Products to Farmers: Ex Post Assessment of Impacts of Climate Information on Corn Production Systems in Isabela, Philippines;64
8.1;Introduction;64
8.2;Methods;65
8.3;Results;67
8.4;Conclusions;69
8.5;Acknowledgements;70
8.6;References;70
9;Seasonal Predictions and Monitoring for Sahel Region;72
9.1;Introduction;72
9.2;Data and Methods;73
9.3;Results;74
9.4;Conclusions;76
9.5;References;78
10;Institutionalizing Climate Forecast Applications for Agriculture;80
10.1;Introduction;80
10.2;Institutional Proclivity and Evolution;80
10.3;Role of Demonstration Studies in Institutionalization;82
10.4;Enabling Local Institutions;82
10.5;Conclusions;83
10.6;References;84
11;Climate Applications and Agriculture: CGIAR Efforts, Capacities and Partner Opportunities;85
11.1;Introduction;85
11.2;CGIAR Inter-Center Initiatives;85
11.3;Getting a Grip on Variability;86
11.4;Improving Analytical Tools for Monitoring Drought and Desertification;86
11.5;Predicting Seasonal Rainfall;87
11.6;Predicting Climate Change and Its Consequences;87
11.7;Effects of Climate Variability on Agriculture;87
11.8;Farmer Perceptions of Drought;89
11.9;Livestock and Drought;89
11.10;Drought Insurance to Help Land Users Manage Climatic Variability;89
11.11;Information Technology for Knowledge-Sharing;90
11.12;Conclusions: Future Climate Applications in CGIAR Centers and Partnership Opportunities;90
11.13;References;91
12;Institutional Capacity Building in Developing Countries through Regional Climate Outlook Forums (RCOFs) Process;93
12.1;Introduction;93
12.2;Origin of the COFs;94
12.3;COF and Associated Institutional Synergies;94
12.4;Capacity Building of the National Meteorological and Hydrological Services (NMHSs);95
12.5;Capacity Building of Users of Climate Information;96
12.6;Capacity Building of Journalist Institutions;96
12.7;Improving Regional and National Scientific and Climate Research Capability;97
12.8;Institutional Challenges;97
12.9;Technical Challenges;98
12.10;Conclusions and Recommendations;98
12.11;References;99
13;Use of ENSO-Driven Climatic Information for Optimum Irrigation under Drought Conditions: Preliminary Assessment Based on Model Results for the Maipo River Basin, Chile;100
13.1;Introduction;100
13.2;Climate Variability and Agricultural Systems;101
13.3;Methodological Framework;103
13.4;Results and Discussion;106
13.5;Acknowledgements;108
13.6;References;108
14;Towards the Development of a Spatial Decision Support System ( SDSS) for the Application of Climate Forecasts in Uruguayan Rice Production Sector;110
14.1;Introduction;110
14.2;Materials and Methods;110
14.3;Results and Discussion;111
14.4;Conclusions;116
14.5;References;118
15;Assessing the Use of Seasonal Climate Forecasts to Support Farmers in the Andean Highlands;119
15.1;Introduction;119
15.2;Data and Methods;119
15.3;Results and Discussion;123
15.4;Conclusions;129
15.5;Acknowledgements;129
15.6;References;129
16;Application of Seasonal Climate Forecasts for Sustainable Agricultural Production in Telangana Subdivision of Andhra Pradesh, India;131
16.1;Introduction;131
16.2;Methods;132
16.3;Results and Discussion;138
16.4;Conclusions;146
16.5;Acknowledgements;146
16.6;References;147
17;Localized Climate Forecasting System: Seasonal Climate and Weather Prediction for Farm- Level Decision- Making;148
17.1;Introduction;148
17.2;Study Area;148
17.3;Methodology;149
17.4;Results and Discussion;150
17.5;Preliminary Conclusions;152
17.6;Acknowledgements;153
18;Use of Sea Surface Temperature for Predicting Optimum Planting Window for Potato at Pengalengan, West Java, Indonesia;154
18.1;Introduction;154
18.2;Methodology;155
18.3;Results and Discussion;156
18.4;Acknowledgements;159
18.5;References;159
19;Climate Forecast for Better Water Management in Agriculture: A Case Study for Southern India;161
19.1;Introduction;161
19.2;Description of the Study Area;161
19.3;Farm and Farmers Characteristics;162
19.4;ENSO Response Analysis;164
19.5;Spatiotemporal Variability in Water Table Levels;165
19.6;ENSO, Rainfall and PET;165
19.7;Crop Evapotranspiration and Irrigation Requirement;166
19.8;Conclusions;171
19.9;Acknowledgements;173
19.10;References;173
20;Linking Corn Production, Climate Information and Farm- Level Decision- Making: A Case Study in Isabela, Philippines;174
20.1;Introduction;174
20.2;Methodology;175
20.3;Results and Discussion;176
20.4;Summary and Conclusions;180
20.5;Acknowledgements;181
20.6;References;181
21;Use of ENSO-Based Seasonal Rainfall Forecasting for Informed Cropping Decisions by Farmers in the SAT India;182
21.1;Introduction;182
21.2;Advances in Seasonal Climate Forecasting;182
21.3;Advances in Crop Modeling;183
21.4;Overall Objective;183
21.5;Specific Objectives;183
21.6;Study Area;184
21.7;Approach;185
21.8;Results and Discussion;195
21.9;Conclusions;196
21.10;References;196
22;Application of Climate Prediction for Rice Production in the Mekong River Delta ( Vietnam);198
22.1;Introduction;198
22.2;Data and Methodology;199
22.3;Results;200
22.4;Conclusions;203
22.5;Acknowledgements;204
22.6;References;204
23;Climate Prediction and Agriculture: What Is Different about Sudano- Sahelian West Africa?;205
23.1;Introduction;205
23.2;The Context: Distinctive Climate Variability;205
23.3;Forecasts for Smallholder Food Security: Which Way Forward?;210
23.4;Conclusions;214
23.5;References;216
24;Can ENSO Help in Agricultural Decision- Making in Ghana?;220
24.1;Introduction;220
24.2;Materials and Methods;221
24.3;Results and Discussion;222
24.4;General Discussion;225
24.5;Conclusions;225
24.6;Acknowledgements;226
24.7;References;226
25;Application of Seasonal Climate Forecasts to Predict Regional Scale Crop Yields in South Africa;228
25.1;Introduction;228
25.2;Study Area and Methodology;229
25.3;Results;234
25.4;Discussion and Recommendations;235
25.5;Acknowledgements;238
25.6;References;238
26;Climate Information for Food Security: Responding to User’s Climate Information Needs;240
26.1;Introduction;240
26.2;Methodology;240
26.3;Results;244
26.4;Summary Findings for Wakiso Survey;253
26.5;Statistical Validation of Farmers’ Knowledge;253
26.6;Regression Models Derived from the Relationships;256
26.7;Discussion;259
26.8;Conclusions;261
26.9;References;261
26.10;Appendix;262
27;Improving Applications in Agriculture of ENSO- Based Seasonal Rainfall Forecasts Considering Atlantic Ocean Surface Temperatures;264
27.1;Introduction;264
27.2;Methods;265
27.3;Results;265
27.4;Conclusions;271
27.5;References;271
28;AGRIDEMA: An EU-Funded Effort to Promote the Use of Climate and Crop Simulation Models in Agricultural Decision- Making;273
28.1;Introduction;273
28.2;AGRIDEMA Description;274
28.3;AGRIDEMA Current Status;277
28.4;References;277
29;Web-Based System to True-Forecast Disease Epidemics – Case Study for Fusarium Head Blight of Wheat;279
29.1;Introduction;279
29.2;Material and Methods;280
29.3;Results and Discussion;281
29.4;Acknowledgements;284
29.5;References;284
30;Climate-Based Agricultural Risk Management Tools for Florida, Georgia and Alabama, USA;286
30.1;Introduction;286
30.2;Methodology;287
30.3;Information Dissemination;288
30.4;Evaluation and Impact Assessment;291
30.5;Acknowledgements;291
31;Climate Prediction and Agriculture: Lessons Learned and Future Challenges from an Agricultural Development Perspective;292
31.1;Introduction;292
31.2;Need for the Assessment of the Value of Climate Forecasts;292
31.3;Climate Predictions and Risk Management;294
31.4;Climate Policy and Climate Predictions;295
31.5;References;295
32;Conclusions and Recommendations;297
32.1;Conclusions;297
32.2;Recommendations;297
33;Index;301