Digital terrain modeling for hydrological analysis and territorial planning in eastern and southeastern regions of Kazakhstan

Abstract

The study presents a reproducible methodology for regional digital terrain modeling based on Sentinel-1 SLC radar imagery for Almaty, Zhetysu, Zhambyl, Abai, and East Kazakhstan regions. The objective was to generate a geoinformation terrain layer suitable for hydrological analysis, surface runoff interpretation, identification of flood-prone depressions, morphometric assessment, and territorial planning in areas with contrasting plains, piedmonts, intermontane basins, and mountainous landscapes. The workflow combines interferometric processing in SNAP with subsequent DEM post-processing and spatial analysis in ArcGIS. Sentinel-1 image pairs were selected using temporal interval, orbit identity, relative orbit consistency, baseline length, spatial overlap, and expected coherence. Processing included metadata verification, precise S-1 Back Geocoding, Enhanced Spectral Diversity correction, interferogram and coherence generation, Goldstein phase filtering, phase unwrapping in SNAPHU, geocoding, mosaicking, hydro-correction, and derivation of slope, aspect, hillshade, flow direction, and flow accumulation layers. The resulting DEM and its visual representations reveal clear altitudinal and morphostructural differentiation across the study area. Lowlands, piedmont belts, dissected mountain slopes, watershed divides, talwegs, and valley systems are distinguishable in both color elevation and hillshade outputs. The model provides a practical regional basis for watershed delineation, erosion-control planning, contour organization of agricultural landscapes, assessment of slope processes, and preparation of flood modeling scenarios. The analysis also demonstrates that Sentinel-1 InSAR products should be interpreted as regional analytical terrain models rather than centimeter-level elevation datasets. For local engineering design, flood hazard mapping at fine scale, or microrelief reconstruction, integration with LiDAR, UAV photogrammetry, or ground geodetic measurements remains necessary. This distinction is essential for selecting adequate datasets, defining acceptable accuracy, and avoiding methodological overstatement in applied hydrological and planning studies. The proposed workflow is therefore suitable for regional screening, comparative mapping, and preparation of subsequent detailed field verification in data-limited mountain and piedmont environments.