Flood forecasting by reach
Ensemble weather forecasts drive hydrological and hydraulic models to give the probability of exceeding warning thresholds at each gauge, by lead time.
GCRI · Water Nexus
Forecasting turns observations into lead time: hours for flash floods, days for river floods, weeks to a season for drought. The value is in the lead time and the stated skill, not in a single number.
Forecasting and time-series analysis predict future values of variables from past observations and explanatory information. They support alerta temprana and planning across hazards, markets and health. In water, climate and hazards and infraestructura crítica, forecasts trigger early action and anticipatory finance before shocks materialise. Probabilistic forecasts allow decisions to account for uncertainty across connected sistemas. The canonical description is on STEM Commons.
Ensemble weather forecasts drive hydrological and hydraulic models to give the probability of exceeding warning thresholds at each gauge, by lead time.
Sub-seasonal and seasonal climate forecasts are combined with current storage and soil moisture to state the odds of deficit categories for the coming months.
Operators receive inflow distributions, not point forecasts, so release rules can be set against the risk of both spill and shortage.
Lluvia, aguas de inundación y humedad del suelo en la zona radicular sobre la cuenca del Nilo, de NASA GIBS. Cada capa lleva su propia fecha.
El mapa interactivo requiere JavaScript; la lista de capas y las fuentes figuran a continuación.
Capas 3
El agua ahora, para esta página
Teclado, con el mapa seleccionado
Mantenga pulsado Ctrl o ⌘ y desplace para ampliar
Último disponible
NASA GIBS / EOSDIS · ASTER GDEM (METI, NASA) · Blue Marble (NASA) · © colaboradores de OpenStreetMap (ODbL) · Natural Earth
Cargando las imágenes más recientes de la NASA.
Arrastre para desplazar. Ctrl o ⌘ y desplazamiento, pellizco o los botones para ampliar; pase el puntero para ver los valores; restablecer devuelve a la región.
El agua ahora, con encuadre en la cuenca del Nilo.Productos satelitales y de modelos tal como los publica la NASA, cada uno con su propia fecha. Son indicadores, no evaluaciones de ningún lugar.
Capas y fechas
Datasets and records used by forecasting and time-series analysis on this platform, with the role each plays and the label its values carry. Sources are listed in el registro de fuentes.
| Datos | Función | Etiqueta |
|---|---|---|
| Ensemble numerical weather prediction | Forcing | PRONÓSTICO |
| Seasonal climate forecasts | Outlook forcing | PRONÓSTICO |
| Real-time gauge telemetry | Asimilación de datos | OBSERVADO |
| Snow and soil-moisture state | Initial conditions | MODELADO |
La pantalla que utilizaría un equipo para seguir este método: sus mediciones, estados y decisiones. Los nombres son ejemplos y los valores son ilustrativos.
Water · Hydrological forecasting · Run R-0460
held-out period
| T+2 | 0.33 | 0.29 | 0.19 | Skilful |
| T+4 | 0.20 | 0.26 | 0.33 | Skilful |
| T+6 | 0.26 | 0.09 | 0.39 | Marginal |
| T+8 | 0.33 | 0.30 | 0.28 | Marginal |
Forecasts are evaluated out of sample with proper scoring rules and reliability diagrams. Rolling-origin evaluation tests performance over time.
| Verificación | Cómo se hace |
|---|---|
| Hindcast verification | Skill is measured on past forecasts against what happened, by lead time and threshold |
| Reliability diagrams | A forecast of thirty percent must come true about thirty percent of the time |
| Warning performance | Hits, misses and false alarms are reported for every threshold |
Structural breaks and regime changes undermine models trained on the past. Forecast skill typically declines rapidly with lead time.
Rain becomes runoff by the curve number method, drains each sub-catchment through a linear reservoir and travels down the main stem by Muskingum routing; play it to watch the flood wave move and flatten. Teaching model with stated illustrative values, not a prediction. The map on this page shows The Nile Basin; the model itself is not tied to a place.
Controles
Lecturas
| Hour | Outlet (m³/s) | Unrouted (m³/s) | Upper reach (m³/s) |
|---|---|---|---|
| 2.4 | 0.0 | 678.9 | 0.0 |
| 12.0 | 308.3 | 1,151.4 | 181.8 |
| 21.6 | 452.4 | 35.1 | 73.7 |
| 31.2 | 363.3 | 1.1 | 11.1 |
| 40.8 | 198.8 | 0.0 | 1.5 |
| 50.4 | 79.3 | 0.0 | 0.2 |
| 60.0 | 25.4 | 0.0 | 0.0 |
| 69.6 | 6.9 | 0.0 | 0.0 |
| 79.2 | 1.7 | 0.0 | 0.0 |
| 88.8 | 0.4 | 0.0 | 0.0 |
| 98.4 | 0.1 | 0.0 | 0.0 |
| 108.0 | 0.0 | 0.0 | 0.0 |
| 117.6 | 0.0 | 0.0 | 0.0 |
| 127.2 | 0.0 | 0.0 | 0.0 |
| 136.8 | 0.0 | 0.0 | 0.0 |
The model runs on the teaching values set by the controls. To calibrate it for a place, read it against these admitted layers and series, which this page’s map can draw:
En los seis pilares, bajo la dirección de Nexus Consortium
Assembled from the Nexus Standards area profile Normas de riesgo hídrico: the hazards it names, the sistemas and sectors that carry the loss, the controls that dampen it and the data that observe it. Choose the components, pick an initiating hazard and step through the cascade. The Map view places the run on an example geography with open data. Every coupling weight is a stated assumption you can change. A teaching model, not a forecast, an assessment or a certification. To model a place of your own choosing, open the full Constructor de sistemas.
Amenazas
Sistemas y acoplamientos
Controles
NS-0 Constitución y principiosNS-1 La UNI y el catálogo de artefactos (gramática v0.2: segmentos de dominio, sector, región y entorno)NS-3 UNI de registros de riesgo (gramática, tabla de correspondencia heredada, autoridad de asignación)NS-3b Perfil de metadatos de conjuntos de datos y productos (STAC, DCAT, PROV-O)NS-9 UNI contextuales (despliegues, instancias, instancias de programa)NS-10 Políticas y cláusulas (obligaciones legibles por máquina: definición, carácter vinculante, evaluación y cumplimiento)NS-11 Verificación y seguimiento (evidencia, atestaciones, observación de la conformidad de confianza cero)NRS-U28 Universo platform profile: Water NexusNRS-H61 Familia de amenazas: fallo en cascada (NHS-1 sys.cascade)NRS-K42 Perfil del paquete de dominio: cuencas transfronterizas (DOMAIN-042)NRS-N1 Riesgo hídrico y resilienciaNRS-N7 Acoplamiento del nexo agua-energía-alimentación-salud-biodiversidad-infraestructuraNRS-H62 Familia de amenazas: eventos compuestos y multiamenaza (NHS-1 sys.compound)Observación
Geografía de ejemplo
Clima y amenazas stewards forecasting and time-series analysis for the Consortium and reviews how it is applied across platforms.
The sectors hydrological forecasting touches and how strongly they depend on each other: what a study has to observe and model together.
Firma
El agua y sus socios
El agua aporta riego a la alimentación (0,8), agua de refrigeración e hidroelectricidad a la energía (0,6) y caudales ecológicos a la biodiversidad (0,6).
W · E · I · F · H · B
El modelo, sus supuestos, sus datos y su incertidumbre, en la forma en que un científico o un ingeniero los comprobaría. Las estructuras siguen métodos publicados. Los valores representados son ilustrativos, no hallazgos.
The couplings between the systems in hydrological forecasting: signs of influence, a reinforcing and a balancing loop, and cross-links where stress jumps.
serie Reports is the Consortium’s quarterly publication. What you know about this subject can become evidence, a case or a correction in the next edition, credited to you and published under CC BY 4.0 where it is your own work.
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