hydrology-pysheds

name	hydrology-pysheds
description	Use this Skill for DEM-based hydrological analysis: watershed delineation, flow direction/accumulation, stream networks, and runoff estimation with pysheds.
tags	["earth-science","hydrology","pysheds","dem","watershed"]
version	1.0.0
authors	[{"name":"Rosetta Skills Contributors","github":"@xjtulyc"}]
license	MIT
platforms	["claude-code","codex","gemini-cli","cursor"]
dependencies	{"python":["pysheds>=0.3","rasterio>=1.3","geopandas>=0.14","matplotlib>=3.7","numpy>=1.24","scipy>=1.11"]}
last_updated	2026-03-17
status	stable

Hydrological Analysis with pysheds

One-line summary: Derive watersheds, stream networks, and flow accumulation from Digital Elevation Models (DEMs) using pysheds, rasterio, and geopandas.

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When to Use This Skill

• When delineating watershed boundaries from a DEM for a pour point
• When extracting stream networks from topographic data
• When computing flow direction and accumulation grids
• When estimating runoff and drainage basin area
• When conditioning DEMs to remove pits and flat areas
• When analyzing upstream contributing area for flood modeling

Trigger keywords: watershed delineation, DEM, flow direction, flow accumulation, stream network, pysheds, hydrological analysis, basin area, pour point

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Background & Key Concepts

DEM Processing Pipeline

$$ \text{Raw DEM} \xrightarrow{\text{pit-fill}} \text{Conditioned DEM} \xrightarrow{\text{flow direction}} \text{D8 grid} \xrightarrow{\text{accumulation}} \text{Flow acc.} \xrightarrow{\text{threshold}} \text{Stream network} $$

D8 Flow Direction

Each cell flows to one of 8 neighbors based on steepest descent. Flow direction encoding: N=64, NE=128, E=1, SE=2, S=4, SW=8, W=16, NW=32.

Flow Accumulation

$A_{ij}$ = number of upstream cells draining through cell $(i,j)$. Cells with high accumulation are stream channels.

Watershed Delineation

Starting from a pour point (outlet), trace upstream through the flow direction grid to find all contributing cells.

SCS Curve Number Method

For runoff estimation:

$$ Q = \frac{(P - I_a)^2}{P - I_a + S}, \quad S = \frac{25400}{CN} - 254, \quad I_a = 0.2S $$

where $P$ is precipitation depth (mm), $CN$ is the SCS curve number.

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Environment Setup

Install Dependencies

pip install pysheds>=0.3 rasterio>=1.3 geopandas>=0.14 \
            matplotlib>=3.7 numpy>=1.24 scipy>=1.11

Download a Test DEM

# Download SRTM DEM tile (90m resolution) for a test region
# Using elevation package or manual download from USGS
pip install elevation
eio clip -o dem_test.tif --bounds -105.5 39.5 -104.5 40.5  # Colorado Front Range

Verify Installation

from pysheds.grid import Grid
 numpy  np
 matplotlib.pyplot  plt

()

dem_arr = np.random.rand(, ) * 
()