Esta simulación ofrece una forma práctica de predecir etapas de desarrollo del maíz y evaluar estrés de crecimiento usando datos meteorológicos horarios detallados. Usa datos de entrada precisos del modelo HRRR de NOAA, incluidos temperatura, radiación solar, velocidad del viento, humedad y humedad del suelo, para estimar el crecimiento del cultivo con métodos agrometeorológicos avanzados.
La simulación usa Photothermal Units (PTU), una métrica que combina temperaturas horarias por encima de una base, comúnmente 10 °C para maíz, con radiación solar en MJ/m² por hora. A diferencia de los Growing Degree Days (GDD) tradicionales, PTU incorpora condiciones térmicas y de radiación, dando una representación más realista del crecimiento del cultivo. El cálculo bruto de PTU se refina con factores de estrés para simular condiciones realistas durante la temporada.
El modelo se apoya en varios supuestos clave. Usa valores horarios de temperatura y radiación, ajustados con un factor empírico de 0.55 para alinear las predicciones con cronologías típicas de desarrollo de maíz observadas históricamente en Iowa. El estrés por humedad del suelo se calcula con un punto de marchitez (wilting point) de 0.15 y una capacidad de campo (field capacity) de 0.30, valores típicos para suelos agrícolas del Midwest. Las velocidades de viento medidas a 10 m se ajustan para aproximar condiciones a 2 m, mejorando el cálculo de evapotranspiración (ET₀).
ET₀ se calcula con la ecuación Penman-Monteith, produciendo estimaciones horarias de demanda de agua del cultivo, un dato clave para predecir estrés por sequía. Un coeficiente de cultivo (crop coefficient, Kc) constante de 1.05 representa la demanda típica de agua del maíz durante la temporada. El umbral de estrés de ET₀ se fija en 0.35 mm/hora para identificar períodos en los que la falta de agua podría limitar significativamente el crecimiento.
El estrés por frío se evalúa comparando temperaturas horarias contra umbrales definidos por el usuario, lo que ayuda a resaltar períodos en los que temperaturas bajas podrían afectar la salud y el desarrollo del cultivo. El estrés por radiación identifica de forma similar momentos con radiación solar insuficiente, algo crítico para entender limitaciones de crecimiento durante condiciones nubladas o cubiertas.
El panel permite interpretar estos resultados visualmente con gráficos claros. La temperatura aparece junto a umbrales importantes para ver rápidamente posibles eventos de estrés por frío. La humedad del suelo se compara contra el punto de marchitez y la capacidad de campo para señalar posibles condiciones de sequía. El gráfico de ET₀, acompañado por humedad, resalta períodos de estrés hídrico elevado.
Además, el panel visualiza PTU acumulado durante la temporada, permitiendo comparar directamente crecimiento potencial contra crecimiento real ajustado por estrés. Los valores finales de PTU ajustado corresponden a etapas establecidas del maíz, desde emergencia y panojamiento hasta grano lechoso, dentado y madurez, dando una lectura inmediata del progreso esperado del cultivo.
Esta simulación da a productores, agrónomos e investigadores una herramienta directa para predecir desarrollo de maíz. Ayuda a tomar decisiones de siembra, riego y cosecha al identificar temprano condiciones de estrés, contribuyendo a mejores rindes y a una gestión agrícola más informada.
Los gráficos de abajo muestran el ciclo completo desde la siembra el 1 de mayo hasta la madurez en los primeros días de septiembre. Haz zoom para apreciar mejor las correlaciones entre variables meteorológicas, factores de estrés y crecimiento.
curl -X POST 'https://gribstream.com/api/v2/hrrr/timeseries' \
-H "Content-Type: application/json" \
-H "Authorization: Bearer [API_TOKEN]" \
-d '{
"fromTime": "2024-05-01T00:00:00Z",
"untilTime": "2024-05-05T00:00:00Z",
"minHorizon": 0,
"maxHorizon": 48,
"coordinates": [
{
"name": "Iowa",
"lat": 42.0347,
"lon": -93.6200
}
],
"variables": [
{ "name": "TMP", "level": "2 m above ground", "info": "", "alias": "temperature" },
{ "name": "SOILW", "level": "0.3-0.3 m below ground", "info": "", "alias": "soil_moisture" },
{ "name": "WIND", "level": "10 m above ground", "info": "", "alias": "wind" },
{ "name": "RH", "level": "2 m above ground", "info": "", "alias": "humidity" },
{ "name": "DSWRF", "level": "surface", "info": "", "alias": "dsw_radiation" },
{ "name": "ULWRF", "level": "surface", "info": "", "alias": "ulw_radiation" },
{ "name": "GFLUX", "level": "surface", "info": "", "alias": "ground_heat_flux" }
],
"expressions": [
{ "expression": "120", "alias": "emergence_threshold"},
{ "expression": "1300", "alias": "tasseling_threshold"},
{ "expression": "1500", "alias": "silking_threshold"},
{ "expression": "1800", "alias": "blister_threshold"},
{ "expression": "2100", "alias": "milk_threshold"},
{ "expression": "2400", "alias": "dough_threshold"},
{ "expression": "2700", "alias": "dent_threshold"},
{ "expression": "2900", "alias": "maturity_threshold"},
{ "expression": "wind * 0.748", "alias": "wind"},
{ "expression": "dsw_radiation * 0.0036", "alias": "dsw_radiation"},
{ "expression": "ulw_radiation * 0.0036", "alias": "ulw_radiation"},
{ "expression": "temperature - 273.15", "alias": "temperature"},
{ "expression": "humidity / 100", "alias": "humidity"},
{ "expression": "10", "alias": "base_temperature"},
{ "expression": "0", "alias": "cold_stress_threshold"},
{ "expression": "5", "alias": "cold_stress_recovery_temperature"},
{ "expression": "0.15", "alias": "wilting_point"},
{ "expression": "0.3", "alias": "field_capacity"},
{ "expression": "0.35", "alias": "max_et0_threshold"},
{ "expression": "0.25", "alias": "useful_radiation_cutoff"},
{ "expression": "ground_heat_flux * 0.0036", "alias": "ground_heat_flux"},
{ "expression": "0.066", "alias": "gamma"},
{ "expression": "dsw_radiation * 0.77 - ulw_radiation", "alias": "net_radiation"},
{ "expression": "0.6108 * 2.718281828 ^ (17.27 * temperature / (temperature + 237.3))", "alias": "es"},
{ "expression": "es * (1 - humidity)", "alias": "vpd"},
{ "expression": "(4098 * (0.6108 * 2.718281828 ^ (17.27 * temperature / (temperature + 237.3)))) / ((temperature + 237.3) ^ 2)", "alias": "delta"},
{ "expression": "(0.6108 * 2.718281828 ^ (17.27 * temperature / (temperature + 237.3))) * humidity", "alias": "ea"},
{ "expression": "max((0.408 * delta * (net_radiation - ground_heat_flux) + gamma * (37 * wind * vpd / (temperature + 273))) / (delta + gamma * (1 + 0.34 * wind)), 0)", "alias": "et0"},
{ "expression": "max(0, min(1, 1 - 1.05 * et0 / max_et0_threshold))", "alias": "et0_stress"},
{ "expression": "(max((temperature - base_temperature), 0) * dsw_radiation) * 0.55", "alias": "PTU" },
{ "expression": "dsw_radiation >= useful_radiation_cutoff ? 1 : dsw_radiation / useful_radiation_cutoff", "alias": "radiation_stress"},
{ "expression": "min(max(0, (temperature - cold_stress_threshold) / (cold_stress_recovery_temperature - cold_stress_threshold)), 1)", "alias": "cold_stress"},
{ "expression": "min(max(0, (soil_moisture - wilting_point)/(field_capacity - wilting_point)), 1)", "alias": "water_stress" },
{ "expression": "PTU * water_stress * cold_stress * radiation_stress * et0_stress", "alias": "PTU_adjusted" }
]
}'Resultado:
forecasted_at,forecasted_time,lat,lon,name,PTU,PTU_adjusted,base_temperature,blister_threshold,cold_stress,cold_stress_recovery_temperature,cold_stress_threshold,delta,dent_threshold,dough_threshold,dsw_radiation,ea,emergence_threshold,es,et0,et0_stress,field_capacity,gamma,ground_heat_flux,humidity,maturity_threshold,max_et0_threshold,milk_threshold,net_radiation,radiation_stress,silking_threshold,soil_moisture,tasseling_threshold,temperature,ulw_radiation,useful_radiation_cutoff,vpd,water_stress,wilting_point,wind
2024-05-01T02:00:00Z,2024-05-01T02:00:00Z,42.0347,-93.6200,Iowa,0.0000,0.0000,10,1800,1,5,0,0.1177,2700,2400,0.0000,1.5558,120,1.8455,0,1,0.3000,0.0660,0.1440,0.8430,2900,0.3500,2100,-1.3260,0.0000,1500,0.2490,1300,16.2332,1.3260,0.2500,0.2898,0.6600,0.1500,1.9666
2024-05-01T03:00:00Z,2024-05-01T03:00:00Z,42.0347,-93.6200,Iowa,0.0000,0.0000,10,1800,1,5,0,0.1138,2700,2400,0.0000,1.5708,120,1.7769,0,1,0.3000,0.0660,0.0360,0.8840,2900,0.3500,2100,-1.3156,0.0000,1500,0.2490,1300,15.6400,1.3156,0.2500,0.2061,0.6600,0.1500,2.9006
2024-05-01T00:00:00Z,2024-05-01T00:00:00Z,42.0347,-93.6200,Iowa,0.0641,0.0026,10,1800,1,5,0,0.1265,2700,2400,0.0155,1.5834,120,2.0043,0,1,0.3000,0.0660,0.0720,0.7900,2900,0.3500,2100,-1.3388,0.0619,1500,0.2500,1300,17.5343,1.3508,0.2500,0.4209,0.6667,0.1500,1.6368
2024-05-01T04:00:00Z,2024-05-01T04:00:00Z,42.0347,-93.6200,Iowa,0.0000,0.0000,10,1800,1,5,0,0.1130,2700,2400,0.0000,1.6018,120,1.7622,0,1,0.3000,0.0660,0.2160,0.9090,2900,0.3500,2100,-1.3189,0.0000,1500,0.2490,1300,15.5103,1.3189,0.2500,0.1604,0.6600,0.1500,4.0706
2024-05-01T06:00:00Z,2024-05-01T06:00:00Z,42.0347,-93.6200,Iowa,0.0000,0.0000,10,1800,1,5,0,0.1031,2700,2400,0.0000,1.3385,120,1.5878,0,1,0.3000,0.0660,0.2880,0.8430,2900,0.3500,2100,-1.2832,0.0000,1500,0.2480,1300,13.8959,1.2832,0.2500,0.2493,0.6533,0.1500,4.6756
2024-05-01T07:00:00Z,2024-05-01T07:00:00Z,42.0347,-93.6200,Iowa,0.0000,0.0000,10,1800,1,5,0,0.0965,2700,2400,0.0000,1.1602,120,1.4724,0,1,0.3000,0.0660,0.3240,0.7880,2900,0.3500,2100,-1.2630,0.0000,1500,0.2480,1300,12.7389,1.2630,0.2500,0.3121,0.6533,0.1500,4.0216
2024-05-01T09:00:00Z,2024-05-01T09:00:00Z,42.0347,-93.6200,Iowa,0.0000,0.0000,10,1800,1,5,0,0.0839,2700,2400,0.0000,1.0344,120,1.2554,0,1,0.3000,0.0660,0.2520,0.8240,2900,0.3500,2100,-1.2218,0.0000,1500,0.2480,1300,10.3302,1.2218,0.2500,0.2210,0.6533,0.1500,2.1057
2024-05-01T05:00:00Z,2024-05-01T05:00:00Z,42.0347,-93.6200,Iowa,0.0000,0.0000,10,1800,1,5,0,0.1050,2700,2400,0.0000,1.4488,120,1.6205,0,1,0.3000,0.0660,0.2520,0.8940,2900,0.3500,2100,-1.2927,0.0000,1500,0.2490,1300,14.2103,1.2927,0.2500,0.1718,0.6600,0.1500,3.7411
...