Evo Usgs Flood Detection

evo-usgs-flood-detection

Overview

End-to-end pipeline for detecting flooding at USGS streamgages. Reads station IDs from a file, fetches daily streamflow values and historical statistics via dataretrieval.nwis, computes flood-day counts by comparing observed daily mean streamflow against the 90th percentile historical threshold for each calendar day, and writes filtered results to CSV.

Key Concepts

Flood Definition

A flood day is defined as a day where the observed daily mean streamflow (00060_Mean) exceeds the 90th percentile (p90_va) of historical daily mean streamflow for that same calendar day (month + day).

Data Sources

• Daily Values: nwis.get_dv(sites, parameterCd='00060', start, end) → returns (DataFrame, metadata) tuple
• Historical Stats: nwis.get_stats(sites, statReportType='daily', parameterCd='00060') → returns (DataFrame, metadata) tuple with columns month_nu, day_nu, p90_va

Station ID Handling

USGS station IDs have leading zeros (e.g., 04193500). Always read as strings, never as integers.

Functions

load_stations(filepath: str) -> List[str]

Reads station IDs from a flat text file (one per line) or CSV with station_id header. Preserves leading zeros.

get_station_flood_thresholds(site_id: str) -> pd.DataFrame

Fetches 90th percentile historical daily streamflow thresholds. Returns DataFrame with month_nu, day_nu, p90_va.

detect_floods_for_site(site_id: str, start_date: str, end_date: str) -> int

Fetches daily values, merges with thresholds on month/day, counts days where observed > p90. Returns integer count.

run_flood_detection_pipeline(stations_file, out_file, start, end) -> pd.DataFrame

Orchestrates the full pipeline. Processes all stations, filters to those with >=1 flood day, writes CSV.

Usage

pythonCopy code
import sys
sys.path.insert(0, '/app/environment/skills/evo-usgs-flood-detection/scripts')
from utils import load_stations, detect_floods_for_site, run_flood_detection_pipeline

# Run full pipeline
results = run_flood_detection_pipeline(
    stations_file='/root/data/michigan_stations.txt',
    out_file='/root/output/flood_results.csv',
    start='2025-04-01',
    end='2025-04-07'
)

Output Format

CSV with two columns:

• station_id: 8-digit USGS station ID (string with leading zeros)
• flood_days: Number of days with flooding (positive integer, max 7 for a 7-day window)

Only stations with at least 1 flood day are included.

Dependencies

• dataretrieval 1.0.10
• pandas 2.2.3
• Python 3.x