LIVE METEOROLOGY — Open-Meteo forecast is live. River gauges, satellite observations and official warnings are not connected; risk scores remain indicative decision support.
An 81-location indicative flood-risk view using live Open-Meteo precipitation forecasts. River-gauge, satellite and official-warning feeds are not connected.
Study label: Madisuk Crypto User-defined project label; not a verified geographic location.
An illustrative view of 81 provincial capital locations. These are not sensor sites or verified flood observations. Click a province to inspect a scenario; values change automatically but do not reflect real conditions.
Simulated national risk index—calculating…
Simulated alerts—across all provinces
Illustrative sensor count—no real sensors connected
Open-Meteo live precipitation—mm · Eastern Black Sea
Simulated regional risk map
LowModerateHighSevere
81 approximate provincial capital coordinates (WGS-84); these are not gauge locations or administrative centroids. Hover and click to explore the simulation →
Region inspector
simulated
Select a region—
—
0demo risk
Simulated river level—
Simulated flood stage—
Simulated discharge—
Simulated rainfall (6h)—
Simulated soil saturation—
Illustrative return-period label—
Illustrative population exposure—
Illustrative confidence—
Simulated trend—
Simulated river level — 24 steps vs. scenario threshold
Simulated event feed
demo
Illustrative 72-hour rainfall scenario
National
— mm simulated total— simulated peak (mm/h)
Scientific analysis layer
Live rainfall depth–duration–frequency explorer
The table uses the selected location’s live Open‑Meteo forecast window to calculate rolling rainfall depths and intensity. Return-period multipliers are an indicative screening proxy, not an official Turkish IDF curve or a design storm.
Intensity–duration–frequency (indicative)
waiting for live feed
Select a province to calculate from its live forecast.
Duration & return period
—
Duration
Live max
2 yr
10 yr
50 yr
Intensity
Live data bekleniyor…
◉
Taşkın taraması bekleniyor
Yağış ve debi verisi geldiğinde süre bazlı uyarı burada gösterilir.
Yöntem: Saatlik yağıştan hareketli toplamlar (1–24 saat), maksimum ortalama şiddet ve canlı GloFAS debi oranı hesaplanır. 2/10/50 yıllık sütunlar, kalibrasyon gerektiren ön tarama katsayılarıdır. Resmî proje hesabında MGM/DSİ istasyon serileri, bölgesel frekans analizi, dağılım seçimi ve güven aralıkları kullanılmalıdır.
Experimental AI forecast layer
Two-model precipitation outlook
Holt linear trend and Ridge autoregression AR(6) learn from the recent hourly Open‑Meteo window. Four horizons are compared and model disagreement is reported as uncertainty.
AI risk map · selected province
—
Schematic forecast surface around the selected city. It is not a satellite raster or an official inundation map.
Forecast horizons
waiting
Canlı model sonucu bekleniyor…
Model report
Holt and Ridge AR results will be compared here.
Model doğrulaması: Son 14 günlük model penceresi eğitim için kullanılır. Tahminler yakın dönem desenlerini uzatır; ekstrem yağışı güvenilir biçimde tahmin ettiği varsayılmaz. Operasyonel karar için MGM/ECMWF tahminleri, DSİ debileri, radar ve bağımsız olay doğrulaması gerekir.
Operator guide
How to use FloodVision AI
A five-step walkthrough for emergency managers, municipal teams and analysts. No prior training required.
01
Open the console
Click “Open the demo console” at the top of the page. The illustrative national view loads automatically. It is not a public flood-monitoring service.
02
Read the national status
The four cards at the top show the national risk index, number of active alerts, how many sensors are reporting, and the current peak rainfall. A rising risk index or a jump in active alerts is your first signal to look closer.
03
Inspect a region
On the simulated regional risk map, each node represents a provincial capital location, not a monitoring station. Colours and inspector figures are fictional scenario values. Click a node to explore the interface; do not use these figures for decisions.
04
Explore simulated events & rainfall
The simulated event feed generates fictional examples, newest at the top. The 72-hour rainfall chart is an illustrative scenario, not a forecast; do not use it for safety decisions.
05
Use official warnings for decisions
High and Severe colours here are generated by the simulation and are not real warnings. Never brief responders, issue public warnings or make evacuation decisions from this page. Follow official meteorological and emergency-management authorities instead.
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Reading the risk levels
Low, Moderate, High and Severe are only four colours for fictional scenario scores. They do not describe current conditions or official alert levels.
This is a demonstration build. All sensor readings, alerts and forecasts shown are simulated for illustration and do not represent real conditions.
Data & methodology
Proposed future data and methodology
The four-source pipeline below is a design proposal, not implemented in this demonstration. This build does not ingest observations, run a hydrological model or issue genuine alerts.
1
Ingest
Proposed: poll verified sources and normalise them to a common time base.
→
2
Fuse
Proposed: match observations to stations, basins and provinces; check data quality.
→
3
Model
Proposed: calibrate and validate a rainfall-runoff and routing model.
→
4
Score & alert
Proposed: validate any risk index and alert thresholds against independent events.
⛆ Weather & rainfall
Observed and forecast precipitation, temperature and wind that drive the rainfall input to the model.
Type — gridded forecast + station observations
Update — every 10 minutes (obs), hourly (forecast)
Analogue source — a national meteorology service (e.g. MGM) & global models (ECMWF / GFS)
≈ River & gauge sensors
Water level, flow velocity and discharge measured at river stations along each basin.
Type — in-situ telemetry (level + flow)
Update — every 1–5 minutes
Analogue source — state hydraulic / water authority gauge network (e.g. DSİ)
⌖ Satellite radar (SAR)
Synthetic-aperture radar maps standing water through cloud, day or night, to confirm flooding on the ground.
Type — C-band SAR backscatter imagery
Update — per satellite overpass (≈ 1–3 days)
Analogue source — Copernicus Sentinel-1 open data
▦ Soil & terrain
Soil-moisture, land cover and a digital elevation model determine how much rain runs off versus soaks in.
Type — soil-moisture probes + DEM raster
Update — hourly (moisture), static (terrain)
Analogue source — soil-moisture satellites + national elevation data
Conceptual risk index — not used by this demo
The equation below is a proposed design only. The page's displayed scores are generated from random regional baselines and drift, not from these four measured factors:
The simulated score is bucketed into Low (0–24), Moderate (25–49), High (50–74) and Severe (75–100). The displayed confidence is illustrative, not based on sensor coverage or model validation.
Demonstration note. This build does not connect to live feeds. All values are generated locally in your browser by app.js using an unseeded random simulation — province baselines are weighted by region (Black Sea & Southeastern Anatolia run higher) and then drift over time on a 3-second tick. No network requests are made and no data leaves your device. To make it operational, each source above would be wired to a verified real API or sensor stream in the ingest layer.
Capabilities
What powers the platform
◎
Proposed sensor fusion
A future operational system would need verified gauge, rainfall and soil-moisture feeds. None are connected in this demo.
⌖
Proposed satellite radar
A future system could use validated synthetic-aperture radar imagery. No radar imagery is used in this demo.
⤴
Proposed forecast models
No weather ensemble or calibrated hydrological model runs in this demo. A future model would need independent validation.
⚑
Proposed automated alerts
Current events are fictional interface examples and are not sent to municipalities, AFAD or the public.
▦
81-province coverage
Every province in Türkiye, from the Eastern Black Sea to the Mediterranean basins, in a single console.
↻
Always labelled as a demo
Values visibly change, but only because of a local random simulation; no fresh external data is received.