River Network Map Generator for Research Maps

What is a river network map generator, and why researchers need one

A river network map generator takes a study region and draws its hydrography — main-stem rivers, tributaries, canals and derived streams — as line work you can style and label. The point is not decoration: catchment context explains where samples sit relative to flow, where pollutants travel, and how a watershed drains. Reviewers of hydrology, ecology and environmental papers expect that context, and hand-tracing it in a desktop GIS is slow and hard to reproduce.

AcadGIS treats rivers as a layer you add to a finished map. Scaling line width by stream order (Strahler-style ranking, where small headwaters are order 1 and the trunk river is highest) makes the drainage hierarchy legible at a glance — the Ganges reads heavier than a field ditch. Pair that with a clean study area map and you have a figure that stands on its own in a thesis or grant.

Make a river network map in Python

Load a boundary, plot it, then overlay the rivers. The by_order=True flag scales line width by stream order automatically, so trunk rivers stand out without any manual styling:

import acadgis as agis
bd = agis.load_boundaries("Bangladesh", level="district")
ax = agis.plot(bd, title="Bangladesh river network")
agis.add_rivers(ax, source="osm", by_order=True)
agis.add_cities(ax, bd)
agis.save("rivers.png", dpi=300)

Choosing a data source: Natural Earth, OpenStreetMap or a DEM

AcadGIS reads three kinds of hydrography, and the right one depends on scale:

• Natural Earth (source="ne") — generalised, global, clean at country and continental scale. Best for context and locator figures.
• OpenStreetMap (source="osm") — dense waterways plus canals and irrigation channels, ideal for deltas, floodplains and small catchments where Natural Earth is too coarse.
• DEM-derived streams — extracted from the Copernicus GLO-30 elevation model, giving a hydrologically consistent drainage network even where mapped rivers are sparse or ungauged.

These combine well: use OSM for the mapped canals near your sites, and DEM streams to fill in ungauged headwaters. For the elevation backdrop behind the streams, see the terrain map generator.

Composing rivers with terrain, cities and field sites

Because add_rivers draws onto an existing axis, you control the stacking order: basemap or terrain at the back, administrative boundaries next, then rivers, then cities and points on top. This lets one figure do the work of several — regional context, drainage and sample locations in a single panel.

A common ecology or water-quality layout puts DEM-shaded relief underneath, OSM rivers over it by stream order, and labelled monitoring stations on top. That pairs naturally with the sampling site map generator when you need to show exactly where measurements were taken along a channel.

Examples and use cases

Researchers reach for a river network map in situations like these:

• Hydrology and water quality — show a catchment's drainage with gauging or sampling stations along the channels.
• Ecology and fisheries — map species-survey reaches against tributary structure and stream order.
• Delta and floodplain studies — use dense OSM canals and distributaries where Natural Earth is too generalised.
• Regional overviews — Japan prefectures with their major rivers and cities for a country-scale figure, as shown below.

Tips for clean, publication-ready river figures

A few practices keep river maps readable at print size:

• Keep by_order=True so trunk rivers dominate and headwaters recede — flat-width networks look like noise at figure scale.
• Prefer Natural Earth at country scale and OpenStreetMap when you zoom into a district or floodplain, so line density matches the extent.
• Render at dpi=300 with agis.save() for journal figures; the academic theme keeps type and line weights consistent.
• Clip rivers to your region with load_boundaries so channels don't trail off the map edge.

Frequently asked questions