“If the map does not match the terrain — trust the terrain!”
— Principle of field geoscience

This is how the effective catchment area of the Inhulets River looks within the study region.

The upstream part — above the Karachunivske Reservoir's dam, the outlet of the Saksahan derivative tunnel, and the confluence of the Stara Saksahan River — was excluded from the calculation.

Within the analyzed area, surface runoff is possible only from the highlighted zone.
The rest of the “catchment basin” is hydrologically inactive: runoff is intercepted by ponds, settling tanks, and other anthropogenic landforms.

🌍 The analysis was based on the Copernicus GLO-30 DEM, integrated with hydrological modeling and terrain processing in open-source GIS.

#Hydrology #Geochemistry #InhuletsRiver #GIS #SAGAGIS #QGIS #HydrologicalModeling #RemoteSensing #GeospatialAnalysis #EnvironmentalData #RStats #LandscapeGeochemistry #Copernicus

The resulting hydrological framework will serve as the base for next-phase modeling — extending to the entire surface-runoff system of the Kryvyi Rih Iron Ore Basin.

I’ll share more maps and data snapshots later.

Open-source workflow only: SAGA GIS + QGIS + R.

#Geospatial #hydrologicalmodeling #datadrivenresearch

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High-Resolution, Integrated Hydrological Modeling of Climate Change Impacts on a Semi-Arid Urban Watershed in Niamey, Niger

This study evaluates the impact of climate change on water resources in a large, semi-arid urban watershed located in the Niamey Republic of Niger, West Africa. The watershed was modeled using the fully integrated surface–subsurface HydroGeoSphere model at a high spatial resolution. Historical (1980–2005) and projected (2020–2050) climate scenarios, derived from the outputs of three regional climate models (RCMs) under the regional climate projection (RCP) 4.5 scenario, were statistically downscaled using the multiscale quantile mapping bias correction method. Results show that the bias correction method is optimum at daily and monthly scales, and increased RCM resolution does not improve the performance of the model. The three RCMs predicted increases of up to 1.6% in annual rainfall and of 1.58 °C for mean annual temperatures between the historical and projected periods. The durations of the minimum environmental flow (MEF) conditions, required to supply drinking and agricultural water, were found to be sensitive to changes in runoff resulting from climate change. MEF occurrences and durations are likely to be greater from 2020–2030, and then they will be reduced for the 2030–2050 statistical periods. All three RCMs consistently project a rise in groundwater table of more than 10 m in topographically high zones, where the groundwater table is deep, and an increase of 2 m in the shallow groundwater table.

MDPI