# Northern Thailand Ping River Monitor

Live water levels, discharge, rainfall and machine-learning flood forecasts for the
Ping River basin around Chiang Mai. Collects hourly gauge data from public sources,
keeps the full history in PostgreSQL, and serves a bilingual dashboard, an open REST
API, and 6/12/24-hour flood-risk forecasts per gauge.

**Live: [water.buildfor.life](https://water.buildfor.life/)** · API reference at
[/docs](https://water.buildfor.life/docs) · built by [buildfor.life](https://buildfor.life)
after the [October 2024 flood](https://buildfor.life/blog/chiang-mai-flood-2024/) —
background in [Teaching a Model to See the Ping River Rise 13 Hours Early](https://buildfor.life/blog/ping-river-monitor/).

[![CI](https://git.b4l.co.th/B4L/Northern-Thailand-Ping-River-Monitor/actions/workflows/ci.yml/badge.svg)](https://git.b4l.co.th/B4L/Northern-Thailand-Ping-River-Monitor/actions)
[![Security](https://git.b4l.co.th/B4L/Northern-Thailand-Ping-River-Monitor/actions/workflows/security.yml/badge.svg)](https://git.b4l.co.th/B4L/Northern-Thailand-Ping-River-Monitor/actions)
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[![Python 3.11](https://img.shields.io/badge/Python-3.11-blue.svg)](https://python.org)
[![License: MIT](https://img.shields.io/badge/License-MIT-green.svg)](LICENSE)

## What it does

- **Collects** hourly water level and discharge from 16 Royal Irrigation Department
  (RID) telemetry gauges, Chiang Dao to the southern basin, since 2018-08; hourly
  rainfall and water level from 400+ ThaiWater/HII stations; Open-Meteo catchment
  rainfall (archive + 48 h forecast); daily Mae Ngat reservoir state. Every source and
  its quirks: [docs/DATA_SOURCES.md](docs/DATA_SOURCES.md).
- **Fills gaps.** The raw RID grid had readings for ~56 % of hours; a full-history
  re-fetch plus HII cross-fill brought it to ~93 %. `GET /api/stats` reports the
  current figure.
- **Forecasts.** Per gauge and horizon, a gradient-boosted model predicts the rise
  within 6/12/24 h and the probability of crossing the station's warning and danger
  levels. Trained on the monitor's own history plus catchment rain; evaluated
  rolling-origin, event by event. On the October 2024 record flood, trained only on
  data through August 2024, the first alert came **13 hours before** P.1 crossed
  3.70 m. Everything about the model, including what did not work:
  [docs/FLOOD_FORECASTING.md](docs/FLOOD_FORECASTING.md).
- **Shows it.** A Leaflet map with the river drawn as OSM geometry and styled by live
  discharge, rain gauges, the Chiang Mai inundation zones, per-station history, the
  forecast card, a replay of the 2024 flood, English/Thai, light/dark.
- **Notifies.** Public push alerts over a self-hosted [ntfy](https://ntfy.sh): one
  message when a gauge crosses its warning or danger level, one all-clear on the
  way down, an opt-in early-warning topic from the model, nothing in between.
  Subscribe from the free app, no account. Matrix room alerts for a team are
  also supported.

## Quick start

Python **3.11** (3.13 breaks the pinned `psycopg2-binary`), PostgreSQL for anything
beyond a quick look, [uv](https://docs.astral.sh/uv/).

```bash
git clone https://git.b4l.co.th/B4L/Northern-Thailand-Ping-River-Monitor.git
cd Northern-Thailand-Ping-River-Monitor
uv sync --python 3.11
cp .env.example .env            # DB_TYPE, POSTGRES_CONNECTION_STRING, optional MATRIX_*
uv run python run.py --web-api  # dashboard + API on http://localhost:8000
```

`DB_TYPE=sqlite` works for the dashboard and API; the forecasting path expects the
PostgreSQL history.

```bash
uv run python run.py --status          # collector status
uv run python run.py --test            # one collection cycle
uv run python run.py --fill-gaps 7     # re-fetch the last 7 days from RID
uv run python run.py --collect-hii     # one ThaiWater/HII collection cycle
uv run python run.py --alert-check     # evaluate thresholds, notify Matrix
uv run python scripts/train_flood_model.py --stations all   # retrain (~12 min)
make test                              # pytest, synthetic data, no network
make format                            # black + isort (the CI contract)
```

## API

Read-only, no key, JSON. Base URL `https://water.buildfor.life`; timestamps are
Asia/Bangkok wall-clock without an offset suffix.

| Endpoint | Returns |
| --- | --- |
| `GET /stations` | The 16 RID gauges: code, Thai/English names, coordinates |
| `GET /measurements/latest?limit=N` | Newest reading per station |
| `GET /measurements/history/{code}?hours=N` | Hourly history; or `?start=YYYY-MM-DD&end=YYYY-MM-DD`; `limit` ≤ 100000 |
| `GET /forecast` | Current flood-risk forecast, every station × horizon, with thresholds and P.1 inundation-stage probabilities |
| `GET /api/forecast/history/{code}?hours=N&horizon=24` | Forecasts as issued, for auditing lead time after the fact |
| `GET /api/hii/rainfall/latest`, `/api/hii/waterlevel/latest` | Latest ThaiWater/HII gauge readings |
| `GET /api/hii/rainfall/catchment?days=N` | HII gauge catchment-mean rain next to the Open-Meteo series the model uses |
| `GET /api/forecast/skill?station_code=P.1` | Issued forecasts vs what happened, per deployed model version |
| `GET /api/notifications` | ntfy server and topic names for the subscribe panel |
| `GET /api/stats` | Row counts per source, date range, coverage |
| `GET /health` | DB / upstream / memory checks |

Interactive reference with schemas: [water.buildfor.life/docs](https://water.buildfor.life/docs).
Responses are cached briefly server-side; poll no faster than once a minute — the data
changes hourly.

## Deployment

Production is a systemd unit on a small VPS behind Cloudflare, updated by `git pull`.
`scripts/install.sh` (run as root from a checkout) creates the `water-monitor` user,
deploys to `/opt/thailand-water-monitor`, runs `uv sync` into `.venv`, installs
`water-monitor.service` and the monthly `water-monitor-retrain.timer`.

```bash
sudo bash scripts/install.sh
sudo systemctl start water-monitor.service
systemctl list-timers water-monitor-retrain.timer
```

The retrain timer runs `scripts/retrain.sh`, which trains into `models/.staging`,
refuses to promote anything that is not a rain-enabled (`hgb-v3+`) set covering the
expected stations, and renames the bundles into place. Details and the operations
runbook: [docs/FLOOD_FORECASTING.md](docs/FLOOD_FORECASTING.md) sections 6–8.

## Repository layout

```
src/                 collector, API (web_api.py), dashboard (static/dashboard.html)
src/ml/              features, training, evaluation harness, prediction, rain/dam/HII loaders
scripts/             train_flood_model.py, retrain.sh, evaluate_variants.py, install.sh, dev_proxy.py
tests/               pytest suite (synthetic data; no DB or network)
docs/                FLOOD_FORECASTING.md, DATA_SOURCES.md, deployment and station guides
models/              trained bundles + metrics.json (gitignored) and evaluation results (tracked)
.gitea/workflows/    ci (format/lint/tests), security (pip-audit/bandit), docs (link + OpenAPI checks)
```

## Documentation

- [docs/FLOOD_FORECASTING.md](docs/FLOOD_FORECASTING.md) — the model: data, features, evaluation, measured performance, negatives, deployment, retraining
- [docs/DATA_SOURCES.md](docs/DATA_SOURCES.md) — every ingested and candidate source, endpoints, quirks
- [docs/STATION_MANAGEMENT_GUIDE.md](docs/STATION_MANAGEMENT_GUIDE.md) — adding/editing gauges
- [docs/DATABASE_DEPLOYMENT_GUIDE.md](docs/DATABASE_DEPLOYMENT_GUIDE.md), [POSTGRESQL_SETUP.md](POSTGRESQL_SETUP.md) — database setup
- [docs/NOTIFICATIONS.md](docs/NOTIFICATIONS.md) — public push alerts: topics, semantics, ntfy deployment
- [docs/MATRIX_QUICK_START.md](docs/MATRIX_QUICK_START.md) — Matrix room alerts for a team
- [docs/GAP_FILLING_GUIDE.md](docs/GAP_FILLING_GUIDE.md) — data integrity tooling
- [docs/references/NOTABLE_DOCUMENTS.md](docs/references/NOTABLE_DOCUMENTS.md) — official Thai government resources
- Public overview: [buildfor.life/docs/tooling/ping-river-monitor](https://buildfor.life/docs/tooling/ping-river-monitor/)

Other database backends (VictoriaMetrics, InfluxDB, MySQL, SQLite) and the Grafana
dashboards under `grafana/` are supported by the adapters but not what production
runs; see [docs/VICTORIAMETRICS_SETUP.md](docs/VICTORIAMETRICS_SETUP.md) if you want them.

## Contributing

`make format` before committing (black 88 columns, isort black profile — the CI gate),
`make test` must stay green, tests use synthetic data only. See
[CONTRIBUTING.md](CONTRIBUTING.md). Issues and merge requests on
[git.b4l.co.th](https://git.b4l.co.th/B4L/Northern-Thailand-Ping-River-Monitor).

## Data sources and thanks

Royal Irrigation Department (RID) gauge telemetry; Hydro-Informatics Institute (HII) /
ThaiWater open API; Open-Meteo; OpenStreetMap contributors for the river geometry;
Chiang Mai Municipality for the inundation map the P.1 stages are keyed to. All
instruments are theirs; we aggregate, store, fill gaps and forecast.

## License

MIT — see [LICENSE](LICENSE).