Future Issues Related To Weather On Crop Modeling

For any application of a crop model weather data is an essential input and it continues to play a key role. So:

1 . There is an urgent need to develop standards for weather station equipment and sensors installation and maintenance.

2. It is also important that a uniform file format is defined for storage and distribution of weather data, so that they can easily be exchanged among agrometeorologists, crop modelers and others working in climate and weather aspects across the globe.

3. Easy access to weather data, preferably through the internet and the world wide web, will be critical for the application of crop models for yield forecasting and tactical decision making.

4. Previously one of the limitations of the current crop simulation models was that they can only simulate crop yield for a particular site. At this

Table 2. Results of sensitivity analysis for different climate change scenarios showing the simulated mean peanut seed yield (kg ha"1) at maturity and standard deviation (SD) for 25 years (1975-1999) of weather under irrigated and rainfed conditions at Hyderabad, India

Temperature increase (°C)

Irrigated

Rainfed

330 ppm C02

555 ppm C02

330 ppm C02

555 ppm C02

Yield

SD

Yield

SD

Yield

SD

Yield

SD

0.0

1570

112

2223

144

1431

219

2041

297

1.0

1526

120

2168

157

1369

234

1977

319

1.5

1484

119

2127

153

1322

224

1926

318

2.0

1451

130

2100

173

1294

236

1891

330

2.5

1436

132

2095

178

1274

240

1876

334

3.0

1437

134

2104

192

1260

251

1857

359

3.5

1450

139

2115

195

1187

354

1749

510

4.0

1210

551

1754

797

1060

480

1560

699

4.5

741

735

1077

1064

770

589

1148

869

5.0

377

621

555

916

530

560

662

818

Table 3. Results of sensitivity analysis for different climate change scenarios showing the simulated mean peanut seed yield (kg ha"1) at maturity and standard deviation (SD) for 25 years (1975-1999) of weather under rainfed conditions at Hyderabad, India with 20% increase or decrease in rainfall

Table 3. Results of sensitivity analysis for different climate change scenarios showing the simulated mean peanut seed yield (kg ha"1) at maturity and standard deviation (SD) for 25 years (1975-1999) of weather under rainfed conditions at Hyderabad, India with 20% increase or decrease in rainfall

Temperature increase (°C)

Rainfed (+20 % rainfall)

Rainfed (-20 % rainfall)

330 ppm C02

555 ppm C02

330 ppm C02

555 ppm C02

Yield

SD

Yield

SD

Yield

SD

Yield

SD

0.0

1494

106

2140

129

1430

219

1948

354

1.0

1437

95

2060

117

1298

294

1873

380

1.5

1400

88

2018

114

1254

283

1821

378

2.0

1368

82

1990

110

1222

295

1780

394

2.5

1356

82

1980

122

1195

295

1762

416

3.0

1367

93

2005

135

1177

315

1742

440

3.5

1385

106

2035

157

1095

394

1628

556

4.0

1346

301

1971

444

1015

452

1518

646

4.5

1238

475

1795

693

700

563

1048

830

5.0

1000

640

1213

1016

416

493

647

764

site weather (soil and management) data also must be available. It is a known fact that the weather data (and all these other details) are not available at all locations where crops are grown. To solve these problems the Geographical Information System (GIS) approach has opened up a whole field of crop modeling applications at spatial scale. From the field level for site-specific management to the regional level for productivity analysis and food security the role of GIS is going to be tremendous (Hoogenboom, 2000).

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