Climate prediction and agriculture: advances and challenges ; with 55 tables
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2007
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| Beschreibung: | XXVI, 306 S. Ill., graph. Darst., Kt. 235 mm x 155 mm |
| ISBN: | 9783540446491 3540446494 |
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Datensatz im Suchindex
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CONTENTS CLIMATE PREDICTION AND AGRICULTURE: SUMMARY AND THE WAY FORWARD
M. V.K. SIVAKUMAR . ]. HANSEN ., , 1 1.1 INTRODUCTION. . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . 1 1.2 PREDICTING CLIMATE
FLUCTUATIONS AND AGRICULTURAL IMPACTS 2 1.3 EFFECTIVENESS OF SEASONAL
FORECASTS AND CLIMATE RISK MANAGEMENT 3 1.4 ECONOMICS OF CLIMATE
FORECAST APPLICATIONS 5 1.5 ASSESSING ADOPTION AND BENEFIT , 6 1.6
BUILDING ON FARMERS' KNOWLEDGE 7 1.7 WAY FORWARD . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . 8 1.7.1 IMPROVE THE ACCURACY OF
PREDICTION MODELS 8 1.7.2 GENERATE QUANTITATIVE EVIDENCE OF THE
USEFULNESS OF FORECASTS 9 1.7.3 GIVE GREATER PRIORITY TO EXTENSION AND
COMMUNICATION . . . . . . . . 9 1.7.4 RESPOND TO USERS' NEEDS AND
INVOLVE THEM MORE ACTIVELY 9 1.7.5 LEARN FROM NON-ADOPTION SITUATIONS 10
1.7.6 CREATE BETTER INSTITUTIONAL AND POLICY ENVIRONMENT 10 1.7.7 DERIVE
ECONOMIC BENEFIT THROUGH APPLICATIONS TO TRADE AND STORAGE 11 1.8
CONCLUSIONS " 11 ACKNOWLEDGEMENTS 11 REFERENCES 11 2 CLIMATE
DOWNSCALING: ASSESSMENT OF THE ADDED VALUES USING REGIONAL CLIMATE
MODELS L. SUN . M. N. WARD 15 2.1 INTRODUCTION " 15 2.2 SMALLER SPATIAL
SCALES 16 2.3 PREDICTABILITYAT SMALLER SPATIAL AND TEMPORAL SCALES 19
2.4 DYNAMICAL DOWNSCALING FORECASTS 23 2.5 FUTURE DIRECTIONS 26 2.5.1
IMPROVED MODEL PHYSICS AND PARAMETERIZATIONS 26 2.5.2 LAND
INITIALIZATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . 27 2.5.3 NESTING STRATEGY 27
2.5-4 DOWNSCALING FORECASTS - LINKING PREDICTION AND APPLICATION 27
REFERENCES 27 XII CONTENTS 3 DEVELOPMENT OFA COMBINED CROP ANDCLIMATE
FORECASTING SYSTEM FORSEASONAL TO DECADAL PREDICTIONS T. WHEELER . A.
CHALLINOR . T. OSBORNE . ]. SLINGO . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . 31 3.1 RATIONALE. . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . 31 3.2 NUMERICAL CROP AND CLIMATE MODELS 31 3.3
COMBINING CROP AND CLIMATE MODELS 32 3.4 CONSIDERATION OF THE FORECAST
SKILLOF A COMBINED CROP-CLIMATE MODELING SYSTEM . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . 34 3.5 AN INTEGRATED APPROACH
TO CLIMATE-CROP MODELING . . . . . . . . . . . . . . . . . . . . . . .
. 35 3.6 CONCLUSIONS. . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
REFERENCES 39 4 DELIVERING CLIMATE FORECAST PRODUCTS TO FARMERS: EX POST
ASSESSMENT OF IMPACTS OFCLIMATE INFORMATION ON COM PRODUCTION SYSTEMS IN
ISABELA, PHILIPPINES F. P. LANSIGAN . W: L.DE LOSSANTOS . ]. HANSEN 41
4.1 INTRODUCTION 41 4.2 METHODS 42 4.2.1 DETERMINING
PLANTINGDATESRECOMMENDATION FOR CORN FARMERS IN ISABELA,PHILIPPINES 42
4.2.2 FIELD IMPLEMENTATION 42 4.2.3 DATA GATHERING 43 4.3 RESULTS. . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . 44 4.3.1 PARMERS-COOPERATORS'
BACKGROUND 44 4*3*2 CORNYIELDS 44 4.3.3 INCOME FROM CORN PRODUCTION 45
4.4
CONCLUSIONS.
46 ACKNOWLEDGEMENTS 47 REFERENCES 47 5 SEASONAL PREDICTIONS
ANDMONITORING FORSAHEL REGION G. MARACCHI . V. CAPECCHI . A. CRISCI . F.
PIANI 49 5*1 INTRODUCTION. . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 5*2
DATAAND METHODS 50 5*3 RESULTS. . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. 51 5*4 CONCLUSIONS. . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 REFERENCES
55 6 INSTITUTIONALIZING CLIMATE FORECAST APPLICATIONS FOR AGRICULTURE
A.R. SUBBIAH . R.SELVARAJU 57 6.1 INTRODUCTION. . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . 57 6.2 INSTITUTIONALPROC1IVITY AND EVOLUTION 57 6*3 ROLE OF
DEMONSTRATION STUDIESIN INSTITUTIONALIZATION 59 6*4 ENABLING LOCAL
INSTITUTIONS :::::::::::::::::::::: 59 6.5 CONC1USIONS
. 60
REFERENCES
. 61
CONTENTS XIII 7 CLIMATE APPLICATIONS AND AGRICULTURE: CGIAREFFORTS,
CAPACITIES AND PARTNER OPPORTUNITIES B. 1. SHAPIRO . M. WINSLOW . P. S.
'IRAORE . V.BALAJI . P. COOPER* K. P. C. RAO . S. WANI . S. KOALA 63 7.1
INTRODUCTION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
7.2 CGIARINTER-CENTER INITIATIVES . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . 63 7.3 GETTING A
GRIP ON VARIABILITY 64 7.4 IMPROVING ANALYTICAL TOOLS FOR MONITORING
DROUGHT AND DESERTIFICATION 64 7.5 PREDICTING SEASONAL RAINFALL 65 7.6
PREDICTING CLIMATE CHANGE AND HS CONSEQUENCES . . . . . . . . . . . . .
. . . . . . . . . . . . . 65 7.7 EFFECTS OF CLIMATE VARIABILITY ON
AGRICULTURE 65 7.7.1 EFFECTS ON CROPS 65 7.7.2 CROP-ENVIRONMENT
INTERACTIONS 66 7.7.3 EFFECTS ON PESTS 66 7.7.4 HOW CLIMATE VARIABILITY
AFFECTS PEOPLE 66 7.8 FARMER PERCEPTIONS OF DROUGHT 67 7.9 LIVESTOCK AND
DROUGHT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . 67 7.10 DROUGHT INSURANCE TO HELP LAND USERS MANAGE CLIMATIC
VARIABILITY. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . 67 7-11 INFORMATION
TECHNOLOGY FOR KNOWLEDGE-SHARING 68 7.12 CONCLUSIONS: FUTURE CLIMATE
APPLICATIONS IN CGIAR CENTERS AND PARTNERSHIP OPPORTUNITIES 68
REFERENCES 69 8 INSTITUTIONAL CAPACITY BUILDING IN DEVELOPING COUNTRIES
THROUGH REGIONAL CLIMATE OUTLOOK FORUMS (RCOFS) PROCESS K. A. KONNEH 71
8.1 INTRODUCTION 71 8.2 ORIGIN OF THE COFS 72 8.3 COF AND ASSOCIATED
INSTITUTIONAL SYNERGIES 72 8.4 CAPACITY BUILDING OF THE NATIONAL
METEOROLOGICAL AND HYDROLOGICAL SERVICES (NMHSS) 73 8.5 CAPACITY
BUILDING OF USERS OF CLIMATE INFORMATION 74 8.6 CAPACITY BUILDING OF
JOURNALIST INSTITUTIONS 74 8.7 IMPROVING REGIONAL AND NATIONAL
SCIENTIFIC AND CLIMATE RESEARCH CAPABILITY 75 8.8 INSTITUTIONAL
CHALLENGES . , . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . 75 8.9 TECHNICAL CHALLENGES
76 8.10 CONCLUSIONS AND RECOMMENDATIONS 76 REFERENCES 77 9 USE OF
ENSO-DRIVEN CLIMATIC INFORMATION FOR OPTIMUM IRRIGATION UNDER DROUGHT
CONDITIONS: PRELIMINARY ASSESSMENT BASED ON MODEL RESULTS FOR THE MAIPO
RIVER BASIN, CHILE F. T. MEZA 79 9.1 INTRODUCTION. . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . 79 XIV 9*2 9*3 9*4 CONTENTS CLIMATE
VARIABILITY AND AGRICULTURAL SYSTEMS 80 METHODOLOGICAL FRAMEWORK
. . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . 82 RESULTS AND DISCUSSION . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
ACKNOWLEDGEMENTS 87 REFERENCES 87 10 TOWARDSTHE DEVELOPMENTOF A SPATIAL
DECISIONSUPPORT SYSTEM (SDSS) FOR THE APPLICATION OF CLIMATE FORECASTS
IN URUGUAYAN RICE PRODUCTIONSECTOR A. ROEL . VV. E.BAETHGEN 89 10.1
INTRODUCTION 89 10.2 MATERIALS AND METHODS . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . 89 10.3 RESULTS
AND DISCUSSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . 90 10.3.1 ENSOEFFECTS
ON URUGUAYAN RIEE PRODUCTION 90 10.3.2 SPATIAL VARIABILITY 91 10.3.3
TEMPORAL VARIABILITY . . . . . . . . . . . . . . . . . . . .
. . . . . . . 94 10.3.4 SPATIOTEMPORAL VARIABILITY . . . . . . .
. . . . . . . . . . . . . . . . . . . 94 10.4 CONCLUSIONS 95
REFERENCES 97 11 ASSESSINGTHE USE OF SEASONAL-CLIMATE FORECASTS TO
SUPPORT FARMERS IN THE ANDEAN HIGHLANDS G. A. BAIGORRIA 99 11.1
INTRODUCTION. . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 11.2 DATA
AND METHODS 99 11.2.1 STUDY AREA . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . 99 11.2.2 FIELD SURVEY 100 11.2.3 SEA SURFACE TEMPERATURE DATA 101
11.2*4 SPATIAL AND TEMPORAL DOWNSCALING 101 11.2*5 GEOSPATIAL MODELING
102 11.3 RESULTS AND DISCUSSION . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . 103 11.3*1 FIELD
SURVEY 103 11.3*2 SPATIAL AND TEMPORAL DOWNSCALING 103 11.3.3 GEOSPATIAL
MODELING 105 11.4
CONCLUSIONS.
109 ACKNOWLEDGEMENTS 109 REFERENCES 109 12 APPLICATION OF SEASONAL
CLIMATEFORECASTS FOR SUSTAINABLE AGRICULTURAL PRODUCTION IN TELANGANA
SUBDIVISION OF ANDHRA PRADESH,INDIA K. K.SINGH . D. R. REDDY . S.
KAUSHIK . L. S. RATHORE . [. HANSEN . G. SREENIVAS 12.1 INTRODUCTION
. 12.2
METHODS . 12.2.1 DESCRIPTION OF KEY SITES
:::::::::::::::::::::::::::::::: 12.2.2 DATA
. 111 111
112 112 113 CONTENTS XV 12.2.3 GCM PREDICTOR SELECTION AND RAINFALL
HINDCASTS 113 12.2.4 STOCHASTIC DISAGGREGATION OF MONTHLY RAINFALL 114
12.2.5 CROP SIMULATION AND CERES MODELS 114 12.2.6 MANAGEMENT STRATEGIES
CONSIDERED 115 12.3 RESULTS AND DISCUSSION 118 12.3.1 RAINFALL AND CROP
YIELD ANALYSIS 118 12.3.2 HINDCAST OF RAINFALL 120 12.3.3 CROP YIELD
SIMULATION WITH ACTUAL AND HINDCAST RAINFALL 122 12.3.4 FARMERS
PERCEPTIONS 125 12.4 CONCLUSIONS 126 ACKNOWLEDGEMENTS 126 REFERENCES 127
13 LOCALIZED CLIMATE FORECASTING SYSTEM: SEASONAL CLIMATE AND WEATHER
PREDICTION FOR FARM-LEVEL DECISION-MAKING R. RENGALAKSHMI 129 13.1
INTRODUCTION 129 13.2 STUDY AREA 129 13.3 METHODOLOGY 130 13.4 RESULTS
AND DISCUSSION . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . 131 13.5 PRELIMINARY CONCLUSIONS
133 ACKNOWLEDGEMENTS 134 14 USE OF SEA SURFACETEMPERATURE FOR PREDICTING
OPTIMUM PLANTING WINDOW FOR POTATO AT PENGALENGAN, WEST JAVA, INDONESIA
R. BOER . I. WAHAB 135 14.1 INTRODUCTION 135 14.2
METHODOLOGY.
136 14.3 RESULTS AND DISCUSSION , 137 ACKNOWLEDGEMENTS 140 REFERENCES
140 15 CLIMATE FORECASTFOR BETTER WATER MANAGEMENT IN AGRICULTURE: A
CASE STUDY FOR SOUTHERN INDIA R. SELVARAJU . H. MEINKE . L- HANSEN 143
15.1 INTRODUCTION 143 15.2 DESCRIPTION OF THE STUDY AREA ., 143 15.3
FARM AND FARMERS CHARACTERISTICS 144 15.4 ENSO RESPONSE ANALYSIS 146
15.5 SPATIOTEMPORAL VARIABILITY IN WATER TABLE LEVELS 147 15.6 ENSO,
RAINFALL AND PET 147 15.7 CROP EVAPOTRANSPIRATION AND IRRIGATION
REQUIREMENT 148 15.7.1 MAIZE 148 15.7.2 CROPPING SYSTEMS 149 15.7.3 CROP
AREA DECISIONS BASED ON ENSO PHASES 150 15.8 CONCLUSIONS 154 XVI
CONTENTS ACKNOWLEDGEMENTS . REFERENCES . 155 155 16 LINKING CORN
PRODUCTION, CLIMATE INFORMATION AND FARM-LEVEL DECISION-MAKING: A CASE
STUDY IN ISABELA, PHILIPPINES W: L.DE LOSSANTOS . F. P. LANSIGAN .
[:HANSEN 157 16.1 INTRODUCTION 157 16.2 METHODOLOGY 158 16.2.1 CASE
STUDY SITES 158 16.2.2 DATA COLLECTION 159 16*3 RESULTS AND DISCUSSION
159 16.3.1 THE IMPACT OF CLIMATE VARIABILITY ON CORN PRODUCTION 159
16.3.2 CLIMATE-RELATED INFORMATION CURRENTLY ACCESSIBLE IN ISABELA " 161
16.3.3 IMPACT OF SEASONAL CLIMATE FORECAST INFORMATION ON
DECISION-MAKING 161 16.3*4 FORECAST INFORMATION OF GREATEST VALUE TO
CORN PRODUCTION 162 16.3.5 EFFECTIVE MEDIUM FOR COMMUNICATING CLIMATE
FORECAST INFORMATION 162 16*4 SUMMARYAND CONCLUSIONS 163
ACKNOWLEDGEMENTS 164 REFERENCES 164 17 USEOF ENSO-BASED SEASONAL
RAINFALL FORECASTING FOR INFORMED CROPPING DECISIONS BY FARMERS IN THE
SATINDIA V. NAGESWARA RAO . P. SINGH . ]. HANSEN . T. GIRIDHARA KRISHNA
. S. K. KRISHNAMURTHY 165 17*1 INTRODUCTION 165 17*2 ADVANCES IN
SEASONAL CLIMATE FORECASTING 165 17*3 ADVANCES IN CROP MODE1ING 166 17*4
OVERALL OBJECTIVE 166 17*5 SPECIFIC OBJECTIVES 166 17*6 STUDY AREA 167
17*7 APPROACH 168 17*7*1 CLIMATE ANALYSES AND SEASONAL PREDICTION 168
17*7*2 CROP YIELDVARIABILITY IN RESPONSE TO ENSO PHASES 171 17*7*3
FARMERS'DECISION OPTIONS 174 17*7*4 SIMULATIONS OF CROPPING SYSTEMS 175
17*7*5 SIMULATION SCENARIOS OF BASELINE MANAGEMENT 177 17*7.6 VALUE OF
SEASONAL FORECASTING SKILL 177 17*8 RESULTS AND DISCUSSION 178 17*9
CONCLUSIONS 179 REFERENCES 179 18 APPLICATION OF CLIMATE PREDICTION FOR
RICE PRODUCTION IN THE MEKONG RIVER DELTA (VIETNAM) NGUYEN T. HIEN THUAN
. LUONG V. VIET . NGUYEN T. PHUONG . LE T. X. LAN . NGUYEN D. PHU . . .
. . . 181 18.1 INTRODUCTION 181 CONTENTS XVII 18.2 DATA AND METHODOLOGY
182 18.2.1 WEATHER DATA 183 18.2.2 CROP DATA 183 18.2.3 SOIL DATA . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . 183 18.3 RESULTS 183 18.3.1
RELATIONSHIP BETWEEN ENSO INDICES AND TEMPERATURE AND RAINFALL 183
18.3.2 FIELD SURVEYS 183 18.3.3 FORECAST INFORMATION FOR DISSEMINATION
TO FARMERS 185 18.3.4 CROP SIMULATION 185 18.4 CONCLUSIONS 186
ACKNOWLEDGEMENTS 187 REFERENCES 187 19 CLIMATE PREDICTION AND
AGRICULTURE: WHAT 15 DIFFERENT ABOUT SUDANO-SAHELIAN WEST AFRICA? P. C.
S. TRAORE . M. KOURESSY . M. VAKSMANN . R. TABO . I. MAIKANO . S. B.
TRAORE . P. COOPER . . . . . 189 19.1 INTRODUCTION 189 19.2 THE
CONTEXT: DISTINCTIVE CLIMATE VARIABILITY 189 19.2.1 A VARIETY OF
FORCINGS 189 19.2.2 THE PROBLEM: A NOTORIOUSLY UNPREDICTABLE GROWING
SEASON 191 19.2.3 WHAT ARE THE OPTIONS IN THE FACE OF CLIMATE
VARIABILITY? 193 19.3 FORECASTS FOR SMALLHOLDER FOOD SECURITY: WHICH WAY
FORWARD? 194 19.3.1 WHERE DO WE STAND NOW? 194 19.3.2 DEVELOP DYNAMIC
LAND SURFACE SCHEMES IN CLIMATE MODELS (LONG-TERM) 195 19.3.3 ADAPT CROP
MODELS (SHORT-TERM) 195 19.3.4 APPLY GIS AND CROP MODELS TO TARGET
BREEDING STRATEGIES (MEDIUM-TERM) 195 19.3.5 REVISIT EARLY CROP YIE1D
ASSESSMENT TECHNIQUES (MEDIUM-TERM) 198 19.4 CONCLUSIONS 198 REFERENCES
200 20 CAN ENSO HELP IN AGRICULTURAL DECISION-MAKING IN GHANA? S. G.
K.ADIKU . F. D.MAWUNYA . I. VV. IONES . M. YANGYOURU 205 20.1
INTRODUCTION 205 20.2 MATERIALS AND METHODS . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . 206 20.2.1 SITES 206
20.2.2 DATA SOURCES AND ANALYSIS . . . . . . 206 20.3 RESULTS AND
DISCUSSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . 207 20.3.1 RAINFALL ANALYSES 207
20.4 GENERAL DISCUSSION 210 20.5 CONCLUSIONS 210 ACKNOWLEDGEMENTS 211
REFERENCES 211 XVIII CONTENTS 21 APPLICATION OF SEASONAL CLIMATE
FORECA~TS TO PREDICT REGIONAL SCALE CROP YIELDS IN SOUTH AFNCA T. G.
LUMSDEN . R.E.SCHULZE 213 21.1 INTRODUETION 213 21.2 STUDY AREA AND
METHODOLOGY 214 21.2.1 CROP YIELD MODEL 214 21.2.2 STUDY AREA . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . 214 21.2.3 CLIMATE FOREEASTS AND
DOWNSEALING 214 21.2*4 CROP YIELD SIMULATIONS PERFORMED 216 21.2*5 CROP
MODEL INPUTS 218 21.3 RESULTS 219 21.4 DISEUSSION AND REEOMMENDATIONS .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
220 AEKNOWLEDGEMENTS 223 REFERENEES 223 22 CLIMATE INFORMATION FOR FOOD
SECURITY: RESPONDING TO USER'S CLIMATE INFORMATION NEEDS M. WAISWA . P.
MULAMBA . P. ISABIRYE 225 22.1 INTRODUCTION 225 22.2 METHODOLOGY . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . 225 22.2.1 SURVEY SITES "
226 22.2.2 FIELD SURVEYS 226 22.2*3 WEATHER STATION DATA 227 22*3
RESULTS 229 22*3*1 CHARAETERISTICS OF SURVEY AREAS " 229 22*3*2 CROP AND
LIVESTOEK PRODUETION SYSTEMS 229 22*3*3 RAINFALL SEASONS IN THE SURVEY
AREAS 230 22*3*4 PRODUCTION PROBLEMS 230 22*3*5 INDIGENOUS RAINFALL
INDICATORS 232 22*4 SUMMARY FINDINGS FOR WAKISO SURVEY 238 22*5
STATISTICAL VALIDATION OF FARMERS' KNOWLEDGE '" 238 22*5*1 ONSET DATES
OF IST WET SEASON 238 22*5*2 CORRE1ATION OF RAINFALL ONSET DATES WITH
MAXIMUM TEMPERATURES 239 22.6 REGRESSION MODELS DERIVED FROM THE
RELATIONSHIPS 241 22.6.1 MASINDI DISTRICT 241 22.6.2 WAKISO DISTRICT 241
22.6.3 IINJA DISTRICT " 243 22.6*4 TORORO DISTRICT 244 22*7 DISEUSSION
244 22*7*1 WEATHER AND CLIMATE KNOWLEDGE SYSTEMS 244 22*7.2 OUTPUTS FROM
KNOWLEDGE-SHARING 245 22.7*3 FARMERS'USE OF LOEAL FORECASTS 245 22.8
CONCLUSIONS 246 CONTENTS XIX REFERENCES 246 APPENDIX 247 23 IMPROVING
APPLICATIONS IN AGRICULTURE OF ENSO-BASED SEASONAL RAINFALL FORECASTS
CONSIDERING ATLANTIC OCEAN SURFACE TEMPERATURES G. O. MAGRIN . M. 1.
TRAVASSO . W: E.BAETHGEN . R. T. BOCA 249 23.1 INTRODUCTION 249 23.2
METHODS 250 23.3 RESULTS 250 23.4 CONCLUSIONS 256 REFERENCES 256 24
AGRIDEMA:AN EU-FUNDED EFFORT TO PROMOTE THE USE OF CLIMATE AND CROP
SIMULATION MODELS IN AGRICULTURAL DECISION-MAKING A. UTSET . ].
EITZINGER . V. AZEXANDROV 259 24.1 INTRODUCTION 259 24.2 AGRIDEMA
DESCRIPTION 260 24.3 AGRIDEMA CURRENT STATUS 263 REFERENCES 263 25
WEB-BASED SYSTEM TO TRUE-FORECAST DISEASE EPIDEMICS - CASE STUDY FOR
FUSARIUM HEAD BLIGHT OFWHEAT ]. M. C. FERNANDES . E. M. DEZ PONTE . W:
PAVAN . G. R. CUNHA 265 25.1 INTRODUCTION 265 25.2 MATERIAL AND METHODS
266 25.3 RESULTS AND DISCUSSION 267 ACKNOWLEDGEMENTS 270 REFERENCES 270
26 CLIMATE-BASED AGRICULTURAL RISK MANAGEMENT TOOLS FOR FLORIDA, GEORGIA
AND ALABAMA, USA G. HOOGENBOOM . C. VV: FRAISSE ], VV: IONES' K. T.
INGRAM . I. O'BRIEN . I. G. BELLOW . D.ZIERDEN' D.E.STOOKSBURY . ]. O.
PAZ . A. GARCIA Y GARCIA . 1. C. GUERRA . D.LETSON N. E. BREUER-
V.E.CABRERA .1. U. HATEH* C. RONEOZI 273 26.1 INTRODUCTION 273 26.2
METHODOLOGY 274 26.3 INFORMATION DISSEMINATION 275 26.4 EVALUATION AND
IMPACT ASSESSMENT 278 ACKNOWLEDGEMENTS 278 27 CLIMATE PREDICTION AND
AGRICULTURE: LESSONS LEARNED AND FUTURE CHALLENGES FROM AN AGRICULTURAL
DEVELOPMENT PERSPECTIVE ]. R. ANDERSON 279 27.1 INTRODUCTION 279 27.2
NEED FOR THE ASSESSMENT OF THE VALUE OF CLIMATE FORECASTS 279 XX
CONTENTS 27.3 CLIMATE PREDICTIONS AND RISK MANAGEMENT 281 27.4 CLIMATE
POLIEY AND CLIMATE PREDICTIONS 282 REFERENEES 282 28 CONCLUSIONS AND
RECOMMENDATIONS M. V. K.SIVAKUMAR . ]. HANSEN . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . 285 28.1
CONCLUSIONS 285 28.2 RECOMMENDATIONS 285 28.2.1 SEIENEE 285 28.2.2
CAPACITY BUILDING, NETWORK DEVELOPMENT AND INSTITUTIONAL PARTNERSHIP 287
28.2*3 OTHER RECOMMENDATIONS 288 SUBJECT INDEX 289 |
| adam_txt |
CONTENTS CLIMATE PREDICTION AND AGRICULTURE: SUMMARY AND THE WAY FORWARD
M. V.K. SIVAKUMAR . ]. HANSEN ., , 1 1.1 INTRODUCTION. . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . 1 1.2 PREDICTING CLIMATE
FLUCTUATIONS AND AGRICULTURAL IMPACTS 2 1.3 EFFECTIVENESS OF SEASONAL
FORECASTS AND CLIMATE RISK MANAGEMENT 3 1.4 ECONOMICS OF CLIMATE
FORECAST APPLICATIONS 5 1.5 ASSESSING ADOPTION AND BENEFIT , 6 1.6
BUILDING ON FARMERS' KNOWLEDGE 7 1.7 WAY FORWARD . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . 8 1.7.1 IMPROVE THE ACCURACY OF
PREDICTION MODELS 8 1.7.2 GENERATE QUANTITATIVE EVIDENCE OF THE
USEFULNESS OF FORECASTS 9 1.7.3 GIVE GREATER PRIORITY TO EXTENSION AND
COMMUNICATION . . . . . . . . 9 1.7.4 RESPOND TO USERS' NEEDS AND
INVOLVE THEM MORE ACTIVELY 9 1.7.5 LEARN FROM NON-ADOPTION SITUATIONS 10
1.7.6 CREATE BETTER INSTITUTIONAL AND POLICY ENVIRONMENT 10 1.7.7 DERIVE
ECONOMIC BENEFIT THROUGH APPLICATIONS TO TRADE AND STORAGE 11 1.8
CONCLUSIONS " 11 ACKNOWLEDGEMENTS 11 REFERENCES 11 2 CLIMATE
DOWNSCALING: ASSESSMENT OF THE ADDED VALUES USING REGIONAL CLIMATE
MODELS L. SUN . M. N. WARD 15 2.1 INTRODUCTION " 15 2.2 SMALLER SPATIAL
SCALES 16 2.3 PREDICTABILITYAT SMALLER SPATIAL AND TEMPORAL SCALES 19
2.4 DYNAMICAL DOWNSCALING FORECASTS 23 2.5 FUTURE DIRECTIONS 26 2.5.1
IMPROVED MODEL PHYSICS AND PARAMETERIZATIONS 26 2.5.2 LAND
INITIALIZATION . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . 27 2.5.3 NESTING STRATEGY 27
2.5-4 DOWNSCALING FORECASTS - LINKING PREDICTION AND APPLICATION 27
REFERENCES 27 XII CONTENTS 3 DEVELOPMENT OFA COMBINED CROP ANDCLIMATE
FORECASTING SYSTEM FORSEASONAL TO DECADAL PREDICTIONS T. WHEELER . A.
CHALLINOR . T. OSBORNE . ]. SLINGO . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . 31 3.1 RATIONALE. . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . 31 3.2 NUMERICAL CROP AND CLIMATE MODELS 31 3.3
COMBINING CROP AND CLIMATE MODELS 32 3.4 CONSIDERATION OF THE FORECAST
SKILLOF A COMBINED CROP-CLIMATE MODELING SYSTEM . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . 34 3.5 AN INTEGRATED APPROACH
TO CLIMATE-CROP MODELING . . . . . . . . . . . . . . . . . . . . . . .
. 35 3.6 CONCLUSIONS. . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . 39
REFERENCES 39 4 DELIVERING CLIMATE FORECAST PRODUCTS TO FARMERS: EX POST
ASSESSMENT OF IMPACTS OFCLIMATE INFORMATION ON COM PRODUCTION SYSTEMS IN
ISABELA, PHILIPPINES F. P. LANSIGAN . W: L.DE LOSSANTOS . ]. HANSEN 41
4.1 INTRODUCTION 41 4.2 METHODS 42 4.2.1 DETERMINING
PLANTINGDATESRECOMMENDATION FOR CORN FARMERS IN ISABELA,PHILIPPINES 42
4.2.2 FIELD IMPLEMENTATION 42 4.2.3 DATA GATHERING 43 4.3 RESULTS. . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . 44 4.3.1 PARMERS-COOPERATORS'
BACKGROUND 44 4*3*2 CORNYIELDS 44 4.3.3 INCOME FROM CORN PRODUCTION 45
4.4
CONCLUSIONS.
46 ACKNOWLEDGEMENTS 47 REFERENCES 47 5 SEASONAL PREDICTIONS
ANDMONITORING FORSAHEL REGION G. MARACCHI . V. CAPECCHI . A. CRISCI . F.
PIANI 49 5*1 INTRODUCTION. . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 49 5*2
DATAAND METHODS 50 5*3 RESULTS. . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. 51 5*4 CONCLUSIONS. . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . 53 REFERENCES
55 6 INSTITUTIONALIZING CLIMATE FORECAST APPLICATIONS FOR AGRICULTURE
A.R. SUBBIAH . R.SELVARAJU 57 6.1 INTRODUCTION. . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . 57 6.2 INSTITUTIONALPROC1IVITY AND EVOLUTION 57 6*3 ROLE OF
DEMONSTRATION STUDIESIN INSTITUTIONALIZATION 59 6*4 ENABLING LOCAL
INSTITUTIONS :::::::::::::::::::::: 59 6.5 CONC1USIONS
. 60
REFERENCES
. 61
CONTENTS XIII 7 CLIMATE APPLICATIONS AND AGRICULTURE: CGIAREFFORTS,
CAPACITIES AND PARTNER OPPORTUNITIES B. 1. SHAPIRO . M. WINSLOW . P. S.
'IRAORE . V.BALAJI . P. COOPER* K. P. C. RAO . S. WANI . S. KOALA 63 7.1
INTRODUCTION. . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 63
7.2 CGIARINTER-CENTER INITIATIVES . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . 63 7.3 GETTING A
GRIP ON VARIABILITY 64 7.4 IMPROVING ANALYTICAL TOOLS FOR MONITORING
DROUGHT AND DESERTIFICATION 64 7.5 PREDICTING SEASONAL RAINFALL 65 7.6
PREDICTING CLIMATE CHANGE AND HS CONSEQUENCES . . . . . . . . . . . . .
. . . . . . . . . . . . . 65 7.7 EFFECTS OF CLIMATE VARIABILITY ON
AGRICULTURE 65 7.7.1 EFFECTS ON CROPS 65 7.7.2 CROP-ENVIRONMENT
INTERACTIONS 66 7.7.3 EFFECTS ON PESTS 66 7.7.4 HOW CLIMATE VARIABILITY
AFFECTS PEOPLE 66 7.8 FARMER PERCEPTIONS OF DROUGHT 67 7.9 LIVESTOCK AND
DROUGHT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . 67 7.10 DROUGHT INSURANCE TO HELP LAND USERS MANAGE CLIMATIC
VARIABILITY. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . 67 7-11 INFORMATION
TECHNOLOGY FOR KNOWLEDGE-SHARING 68 7.12 CONCLUSIONS: FUTURE CLIMATE
APPLICATIONS IN CGIAR CENTERS AND PARTNERSHIP OPPORTUNITIES 68
REFERENCES 69 8 INSTITUTIONAL CAPACITY BUILDING IN DEVELOPING COUNTRIES
THROUGH REGIONAL CLIMATE OUTLOOK FORUMS (RCOFS) PROCESS K. A. KONNEH 71
8.1 INTRODUCTION 71 8.2 ORIGIN OF THE COFS 72 8.3 COF AND ASSOCIATED
INSTITUTIONAL SYNERGIES 72 8.4 CAPACITY BUILDING OF THE NATIONAL
METEOROLOGICAL AND HYDROLOGICAL SERVICES (NMHSS) 73 8.5 CAPACITY
BUILDING OF USERS OF CLIMATE INFORMATION 74 8.6 CAPACITY BUILDING OF
JOURNALIST INSTITUTIONS 74 8.7 IMPROVING REGIONAL AND NATIONAL
SCIENTIFIC AND CLIMATE RESEARCH CAPABILITY 75 8.8 INSTITUTIONAL
CHALLENGES . , . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . 75 8.9 TECHNICAL CHALLENGES
76 8.10 CONCLUSIONS AND RECOMMENDATIONS 76 REFERENCES 77 9 USE OF
ENSO-DRIVEN CLIMATIC INFORMATION FOR OPTIMUM IRRIGATION UNDER DROUGHT
CONDITIONS: PRELIMINARY ASSESSMENT BASED ON MODEL RESULTS FOR THE MAIPO
RIVER BASIN, CHILE F. T. MEZA 79 9.1 INTRODUCTION. . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . 79 XIV 9*2 9*3 9*4 CONTENTS CLIMATE
VARIABILITY AND AGRICULTURAL SYSTEMS 80 METHODOLOGICAL FRAMEWORK
. . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . 82 RESULTS AND DISCUSSION . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 85
ACKNOWLEDGEMENTS 87 REFERENCES 87 10 TOWARDSTHE DEVELOPMENTOF A SPATIAL
DECISIONSUPPORT SYSTEM (SDSS) FOR THE APPLICATION OF CLIMATE FORECASTS
IN URUGUAYAN RICE PRODUCTIONSECTOR A. ROEL . VV. E.BAETHGEN 89 10.1
INTRODUCTION 89 10.2 MATERIALS AND METHODS . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . 89 10.3 RESULTS
AND DISCUSSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . 90 10.3.1 ENSOEFFECTS
ON URUGUAYAN RIEE PRODUCTION 90 10.3.2 SPATIAL VARIABILITY 91 10.3.3
TEMPORAL VARIABILITY . . . . . . . . . . . . . . . . . . . .
. . . . . . . 94 10.3.4 SPATIOTEMPORAL VARIABILITY . . . . . . .
. . . . . . . . . . . . . . . . . . . 94 10.4 CONCLUSIONS 95
REFERENCES 97 11 ASSESSINGTHE USE OF SEASONAL-CLIMATE FORECASTS TO
SUPPORT FARMERS IN THE ANDEAN HIGHLANDS G. A. BAIGORRIA 99 11.1
INTRODUCTION. . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . 99 11.2 DATA
AND METHODS 99 11.2.1 STUDY AREA . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . 99 11.2.2 FIELD SURVEY 100 11.2.3 SEA SURFACE TEMPERATURE DATA 101
11.2*4 SPATIAL AND TEMPORAL DOWNSCALING 101 11.2*5 GEOSPATIAL MODELING
102 11.3 RESULTS AND DISCUSSION . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . 103 11.3*1 FIELD
SURVEY 103 11.3*2 SPATIAL AND TEMPORAL DOWNSCALING 103 11.3.3 GEOSPATIAL
MODELING 105 11.4
CONCLUSIONS.
109 ACKNOWLEDGEMENTS 109 REFERENCES 109 12 APPLICATION OF SEASONAL
CLIMATEFORECASTS FOR SUSTAINABLE AGRICULTURAL PRODUCTION IN TELANGANA
SUBDIVISION OF ANDHRA PRADESH,INDIA K. K.SINGH . D. R. REDDY . S.
KAUSHIK . L. S. RATHORE . [. HANSEN . G. SREENIVAS 12.1 INTRODUCTION
. 12.2
METHODS . 12.2.1 DESCRIPTION OF KEY SITES
:::::::::::::::::::::::::::::::: 12.2.2 DATA
. 111 111
112 112 113 CONTENTS XV 12.2.3 GCM PREDICTOR SELECTION AND RAINFALL
HINDCASTS 113 12.2.4 STOCHASTIC DISAGGREGATION OF MONTHLY RAINFALL 114
12.2.5 CROP SIMULATION AND CERES MODELS 114 12.2.6 MANAGEMENT STRATEGIES
CONSIDERED 115 12.3 RESULTS AND DISCUSSION 118 12.3.1 RAINFALL AND CROP
YIELD ANALYSIS 118 12.3.2 HINDCAST OF RAINFALL 120 12.3.3 CROP YIELD
SIMULATION WITH ACTUAL AND HINDCAST RAINFALL 122 12.3.4 FARMERS
PERCEPTIONS 125 12.4 CONCLUSIONS 126 ACKNOWLEDGEMENTS 126 REFERENCES 127
13 LOCALIZED CLIMATE FORECASTING SYSTEM: SEASONAL CLIMATE AND WEATHER
PREDICTION FOR FARM-LEVEL DECISION-MAKING R. RENGALAKSHMI 129 13.1
INTRODUCTION 129 13.2 STUDY AREA 129 13.3 METHODOLOGY 130 13.4 RESULTS
AND DISCUSSION . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . 131 13.5 PRELIMINARY CONCLUSIONS
133 ACKNOWLEDGEMENTS 134 14 USE OF SEA SURFACETEMPERATURE FOR PREDICTING
OPTIMUM PLANTING WINDOW FOR POTATO AT PENGALENGAN, WEST JAVA, INDONESIA
R. BOER . I. WAHAB 135 14.1 INTRODUCTION 135 14.2
METHODOLOGY.
136 14.3 RESULTS AND DISCUSSION , 137 ACKNOWLEDGEMENTS 140 REFERENCES
140 15 CLIMATE FORECASTFOR BETTER WATER MANAGEMENT IN AGRICULTURE: A
CASE STUDY FOR SOUTHERN INDIA R. SELVARAJU . H. MEINKE . L- HANSEN 143
15.1 INTRODUCTION 143 15.2 DESCRIPTION OF THE STUDY AREA ., 143 15.3
FARM AND FARMERS CHARACTERISTICS 144 15.4 ENSO RESPONSE ANALYSIS 146
15.5 SPATIOTEMPORAL VARIABILITY IN WATER TABLE LEVELS 147 15.6 ENSO,
RAINFALL AND PET 147 15.7 CROP EVAPOTRANSPIRATION AND IRRIGATION
REQUIREMENT 148 15.7.1 MAIZE 148 15.7.2 CROPPING SYSTEMS 149 15.7.3 CROP
AREA DECISIONS BASED ON ENSO PHASES 150 15.8 CONCLUSIONS 154 XVI
CONTENTS ACKNOWLEDGEMENTS . REFERENCES . 155 155 16 LINKING CORN
PRODUCTION, CLIMATE INFORMATION AND FARM-LEVEL DECISION-MAKING: A CASE
STUDY IN ISABELA, PHILIPPINES W: L.DE LOSSANTOS . F. P. LANSIGAN .
[:HANSEN 157 16.1 INTRODUCTION 157 16.2 METHODOLOGY 158 16.2.1 CASE
STUDY SITES 158 16.2.2 DATA COLLECTION 159 16*3 RESULTS AND DISCUSSION
159 16.3.1 THE IMPACT OF CLIMATE VARIABILITY ON CORN PRODUCTION 159
16.3.2 CLIMATE-RELATED INFORMATION CURRENTLY ACCESSIBLE IN ISABELA " 161
16.3.3 IMPACT OF SEASONAL CLIMATE FORECAST INFORMATION ON
DECISION-MAKING 161 16.3*4 FORECAST INFORMATION OF GREATEST VALUE TO
CORN PRODUCTION 162 16.3.5 EFFECTIVE MEDIUM FOR COMMUNICATING CLIMATE
FORECAST INFORMATION 162 16*4 SUMMARYAND CONCLUSIONS 163
ACKNOWLEDGEMENTS 164 REFERENCES 164 17 USEOF ENSO-BASED SEASONAL
RAINFALL FORECASTING FOR INFORMED CROPPING DECISIONS BY FARMERS IN THE
SATINDIA V. NAGESWARA RAO . P. SINGH . ]. HANSEN . T. GIRIDHARA KRISHNA
. S. K. KRISHNAMURTHY 165 17*1 INTRODUCTION 165 17*2 ADVANCES IN
SEASONAL CLIMATE FORECASTING 165 17*3 ADVANCES IN CROP MODE1ING 166 17*4
OVERALL OBJECTIVE 166 17*5 SPECIFIC OBJECTIVES 166 17*6 STUDY AREA 167
17*7 APPROACH 168 17*7*1 CLIMATE ANALYSES AND SEASONAL PREDICTION 168
17*7*2 CROP YIELDVARIABILITY IN RESPONSE TO ENSO PHASES 171 17*7*3
FARMERS'DECISION OPTIONS 174 17*7*4 SIMULATIONS OF CROPPING SYSTEMS 175
17*7*5 SIMULATION SCENARIOS OF BASELINE MANAGEMENT 177 17*7.6 VALUE OF
SEASONAL FORECASTING SKILL 177 17*8 RESULTS AND DISCUSSION 178 17*9
CONCLUSIONS 179 REFERENCES 179 18 APPLICATION OF CLIMATE PREDICTION FOR
RICE PRODUCTION IN THE MEKONG RIVER DELTA (VIETNAM) NGUYEN T. HIEN THUAN
. LUONG V. VIET . NGUYEN T. PHUONG . LE T. X. LAN . NGUYEN D. PHU . . .
. . . 181 18.1 INTRODUCTION 181 CONTENTS XVII 18.2 DATA AND METHODOLOGY
182 18.2.1 WEATHER DATA 183 18.2.2 CROP DATA 183 18.2.3 SOIL DATA . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . 183 18.3 RESULTS 183 18.3.1
RELATIONSHIP BETWEEN ENSO INDICES AND TEMPERATURE AND RAINFALL 183
18.3.2 FIELD SURVEYS 183 18.3.3 FORECAST INFORMATION FOR DISSEMINATION
TO FARMERS 185 18.3.4 CROP SIMULATION 185 18.4 CONCLUSIONS 186
ACKNOWLEDGEMENTS 187 REFERENCES 187 19 CLIMATE PREDICTION AND
AGRICULTURE: WHAT 15 DIFFERENT ABOUT SUDANO-SAHELIAN WEST AFRICA? P. C.
S. TRAORE . M. KOURESSY . M. VAKSMANN . R. TABO . I. MAIKANO . S. B.
TRAORE . P. COOPER . . . . . 189 19.1 INTRODUCTION 189 19.2 THE
CONTEXT: DISTINCTIVE CLIMATE VARIABILITY 189 19.2.1 A VARIETY OF
FORCINGS 189 19.2.2 THE PROBLEM: A NOTORIOUSLY UNPREDICTABLE GROWING
SEASON 191 19.2.3 WHAT ARE THE OPTIONS IN THE FACE OF CLIMATE
VARIABILITY? 193 19.3 FORECASTS FOR SMALLHOLDER FOOD SECURITY: WHICH WAY
FORWARD? 194 19.3.1 WHERE DO WE STAND NOW? 194 19.3.2 DEVELOP DYNAMIC
LAND SURFACE SCHEMES IN CLIMATE MODELS (LONG-TERM) 195 19.3.3 ADAPT CROP
MODELS (SHORT-TERM) 195 19.3.4 APPLY GIS AND CROP MODELS TO TARGET
BREEDING STRATEGIES (MEDIUM-TERM) 195 19.3.5 REVISIT EARLY CROP YIE1D
ASSESSMENT TECHNIQUES (MEDIUM-TERM) 198 19.4 CONCLUSIONS 198 REFERENCES
200 20 CAN ENSO HELP IN AGRICULTURAL DECISION-MAKING IN GHANA? S. G.
K.ADIKU . F. D.MAWUNYA . I. VV. IONES . M. YANGYOURU 205 20.1
INTRODUCTION 205 20.2 MATERIALS AND METHODS . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . 206 20.2.1 SITES 206
20.2.2 DATA SOURCES AND ANALYSIS . . . . . . 206 20.3 RESULTS AND
DISCUSSION . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . 207 20.3.1 RAINFALL ANALYSES 207
20.4 GENERAL DISCUSSION 210 20.5 CONCLUSIONS 210 ACKNOWLEDGEMENTS 211
REFERENCES 211 XVIII CONTENTS 21 APPLICATION OF SEASONAL CLIMATE
FORECA~TS TO PREDICT REGIONAL SCALE CROP YIELDS IN SOUTH AFNCA T. G.
LUMSDEN . R.E.SCHULZE 213 21.1 INTRODUETION 213 21.2 STUDY AREA AND
METHODOLOGY 214 21.2.1 CROP YIELD MODEL 214 21.2.2 STUDY AREA . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . 214 21.2.3 CLIMATE FOREEASTS AND
DOWNSEALING 214 21.2*4 CROP YIELD SIMULATIONS PERFORMED 216 21.2*5 CROP
MODEL INPUTS 218 21.3 RESULTS 219 21.4 DISEUSSION AND REEOMMENDATIONS .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
220 AEKNOWLEDGEMENTS 223 REFERENEES 223 22 CLIMATE INFORMATION FOR FOOD
SECURITY: RESPONDING TO USER'S CLIMATE INFORMATION NEEDS M. WAISWA . P.
MULAMBA . P. ISABIRYE 225 22.1 INTRODUCTION 225 22.2 METHODOLOGY . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . 225 22.2.1 SURVEY SITES "
226 22.2.2 FIELD SURVEYS 226 22.2*3 WEATHER STATION DATA 227 22*3
RESULTS 229 22*3*1 CHARAETERISTICS OF SURVEY AREAS " 229 22*3*2 CROP AND
LIVESTOEK PRODUETION SYSTEMS 229 22*3*3 RAINFALL SEASONS IN THE SURVEY
AREAS 230 22*3*4 PRODUCTION PROBLEMS 230 22*3*5 INDIGENOUS RAINFALL
INDICATORS 232 22*4 SUMMARY FINDINGS FOR WAKISO SURVEY 238 22*5
STATISTICAL VALIDATION OF FARMERS' KNOWLEDGE '" 238 22*5*1 ONSET DATES
OF IST WET SEASON 238 22*5*2 CORRE1ATION OF RAINFALL ONSET DATES WITH
MAXIMUM TEMPERATURES 239 22.6 REGRESSION MODELS DERIVED FROM THE
RELATIONSHIPS 241 22.6.1 MASINDI DISTRICT 241 22.6.2 WAKISO DISTRICT 241
22.6.3 IINJA DISTRICT " 243 22.6*4 TORORO DISTRICT 244 22*7 DISEUSSION
244 22*7*1 WEATHER AND CLIMATE KNOWLEDGE SYSTEMS 244 22*7.2 OUTPUTS FROM
KNOWLEDGE-SHARING 245 22.7*3 FARMERS'USE OF LOEAL FORECASTS 245 22.8
CONCLUSIONS 246 CONTENTS XIX REFERENCES 246 APPENDIX 247 23 IMPROVING
APPLICATIONS IN AGRICULTURE OF ENSO-BASED SEASONAL RAINFALL FORECASTS
CONSIDERING ATLANTIC OCEAN SURFACE TEMPERATURES G. O. MAGRIN . M. 1.
TRAVASSO . W: E.BAETHGEN . R. T. BOCA 249 23.1 INTRODUCTION 249 23.2
METHODS 250 23.3 RESULTS 250 23.4 CONCLUSIONS 256 REFERENCES 256 24
AGRIDEMA:AN EU-FUNDED EFFORT TO PROMOTE THE USE OF CLIMATE AND CROP
SIMULATION MODELS IN AGRICULTURAL DECISION-MAKING A. UTSET . ].
EITZINGER . V. AZEXANDROV 259 24.1 INTRODUCTION 259 24.2 AGRIDEMA
DESCRIPTION 260 24.3 AGRIDEMA CURRENT STATUS 263 REFERENCES 263 25
WEB-BASED SYSTEM TO TRUE-FORECAST DISEASE EPIDEMICS - CASE STUDY FOR
FUSARIUM HEAD BLIGHT OFWHEAT ]. M. C. FERNANDES . E. M. DEZ PONTE . W:
PAVAN . G. R. CUNHA 265 25.1 INTRODUCTION 265 25.2 MATERIAL AND METHODS
266 25.3 RESULTS AND DISCUSSION 267 ACKNOWLEDGEMENTS 270 REFERENCES 270
26 CLIMATE-BASED AGRICULTURAL RISK MANAGEMENT TOOLS FOR FLORIDA, GEORGIA
AND ALABAMA, USA G. HOOGENBOOM . C. VV: FRAISSE ], VV: IONES' K. T.
INGRAM . I. O'BRIEN . I. G. BELLOW . D.ZIERDEN' D.E.STOOKSBURY . ]. O.
PAZ . A. GARCIA Y GARCIA . 1. C. GUERRA . D.LETSON N. E. BREUER-
V.E.CABRERA .1. U. HATEH* C. RONEOZI 273 26.1 INTRODUCTION 273 26.2
METHODOLOGY 274 26.3 INFORMATION DISSEMINATION 275 26.4 EVALUATION AND
IMPACT ASSESSMENT 278 ACKNOWLEDGEMENTS 278 27 CLIMATE PREDICTION AND
AGRICULTURE: LESSONS LEARNED AND FUTURE CHALLENGES FROM AN AGRICULTURAL
DEVELOPMENT PERSPECTIVE ]. R. ANDERSON 279 27.1 INTRODUCTION 279 27.2
NEED FOR THE ASSESSMENT OF THE VALUE OF CLIMATE FORECASTS 279 XX
CONTENTS 27.3 CLIMATE PREDICTIONS AND RISK MANAGEMENT 281 27.4 CLIMATE
POLIEY AND CLIMATE PREDICTIONS 282 REFERENEES 282 28 CONCLUSIONS AND
RECOMMENDATIONS M. V. K.SIVAKUMAR . ]. HANSEN . . . . . . . . . . . . .
. . . . . . . . . . . . . . . . . . . . . . . . . . . . 285 28.1
CONCLUSIONS 285 28.2 RECOMMENDATIONS 285 28.2.1 SEIENEE 285 28.2.2
CAPACITY BUILDING, NETWORK DEVELOPMENT AND INSTITUTIONAL PARTNERSHIP 287
28.2*3 OTHER RECOMMENDATIONS 288 SUBJECT INDEX 289 |
| any_adam_object | 1 |
| any_adam_object_boolean | 1 |
| author2 | Sivakumar, Manava V. K. |
| author2_role | edt |
| author2_variant | m v k s mvk mvks |
| author_facet | Sivakumar, Manava V. K. |
| building | Verbundindex |
| bvnumber | BV022450067 |
| classification_rvk | RB 10438 RB 10447 RB 10663 |
| classification_tum | GEO 780f LAN 090f |
| ctrlnum | (OCoLC)612878349 (DE-599)BVBBV022450067 |
| dewey-full | 630.2515 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 630 - Agriculture and related technologies |
| dewey-raw | 630.2515 |
| dewey-search | 630.2515 |
| dewey-sort | 3630.2515 |
| dewey-tens | 630 - Agriculture and related technologies |
| discipline | Geowissenschaften Physik Geologie / Paläontologie Agrarwissenschaft Agrar-/Forst-/Ernährungs-/Haushaltswissenschaft / Gartenbau Geographie |
| discipline_str_mv | Geowissenschaften Geologie / Paläontologie Physik Agrarwissenschaft Agrar-/Forst-/Ernährungs-/Haushaltswissenschaft / Gartenbau Geographie |
| format | Book |
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| id | DE-604.BV022450067 |
| illustrated | Illustrated |
| index_date | 2024-07-02T17:36:04Z |
| indexdate | 2024-07-20T09:17:20Z |
| institution | BVB |
| isbn | 9783540446491 3540446494 |
| language | English |
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| physical | XXVI, 306 S. Ill., graph. Darst., Kt. 235 mm x 155 mm |
| publishDate | 2007 |
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| spelling | Climate prediction and agriculture advances and challenges ; with 55 tables Manava V. K. Sivakumar ... (ed.) Berlin [u.a.] Springer 2007 XXVI, 306 S. Ill., graph. Darst., Kt. 235 mm x 155 mm txt rdacontent n rdamedia nc rdacarrier Klimaänderung (DE-588)4164199-1 gnd rswk-swf Grünlandwirtschaft (DE-588)4022303-6 gnd rswk-swf Landwirtschaft (DE-588)4034402-2 gnd rswk-swf Wettervorhersage (DE-588)4079256-0 gnd rswk-swf Agrarmeteorologie (DE-588)4141642-9 gnd rswk-swf (DE-588)4143413-4 Aufsatzsammlung gnd-content (DE-588)1071861417 Konferenzschrift 2005 Genf gnd-content Landwirtschaft (DE-588)4034402-2 s Klimaänderung (DE-588)4164199-1 s Wettervorhersage (DE-588)4079256-0 s DE-604 Agrarmeteorologie (DE-588)4141642-9 s Grünlandwirtschaft (DE-588)4022303-6 s 1\p DE-604 b DE-604 Sivakumar, Manava V. K. edt text/html http://deposit.dnb.de/cgi-bin/dokserv?id=2844147&prov=M&dok_var=1&dok_ext=htm Inhaltstext OEBV Datenaustausch application/pdf http://bvbr.bib-bvb.de:8991/F?func=service&doc_library=BVB01&local_base=BVB01&doc_number=015657953&sequence=000001&line_number=0001&func_code=DB_RECORDS&service_type=MEDIA Inhaltsverzeichnis 1\p cgwrk 20201028 DE-101 https://d-nb.info/provenance/plan#cgwrk |
| spellingShingle | Climate prediction and agriculture advances and challenges ; with 55 tables Klimaänderung (DE-588)4164199-1 gnd Grünlandwirtschaft (DE-588)4022303-6 gnd Landwirtschaft (DE-588)4034402-2 gnd Wettervorhersage (DE-588)4079256-0 gnd Agrarmeteorologie (DE-588)4141642-9 gnd |
| subject_GND | (DE-588)4164199-1 (DE-588)4022303-6 (DE-588)4034402-2 (DE-588)4079256-0 (DE-588)4141642-9 (DE-588)4143413-4 (DE-588)1071861417 |
| title | Climate prediction and agriculture advances and challenges ; with 55 tables |
| title_auth | Climate prediction and agriculture advances and challenges ; with 55 tables |
| title_exact_search | Climate prediction and agriculture advances and challenges ; with 55 tables |
| title_exact_search_txtP | Climate prediction and agriculture advances and challenges ; with 55 tables |
| title_full | Climate prediction and agriculture advances and challenges ; with 55 tables Manava V. K. Sivakumar ... (ed.) |
| title_fullStr | Climate prediction and agriculture advances and challenges ; with 55 tables Manava V. K. Sivakumar ... (ed.) |
| title_full_unstemmed | Climate prediction and agriculture advances and challenges ; with 55 tables Manava V. K. Sivakumar ... (ed.) |
| title_short | Climate prediction and agriculture |
| title_sort | climate prediction and agriculture advances and challenges with 55 tables |
| title_sub | advances and challenges ; with 55 tables |
| topic | Klimaänderung (DE-588)4164199-1 gnd Grünlandwirtschaft (DE-588)4022303-6 gnd Landwirtschaft (DE-588)4034402-2 gnd Wettervorhersage (DE-588)4079256-0 gnd Agrarmeteorologie (DE-588)4141642-9 gnd |
| topic_facet | Klimaänderung Grünlandwirtschaft Landwirtschaft Wettervorhersage Agrarmeteorologie Aufsatzsammlung Konferenzschrift 2005 Genf |
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