Places of past conflicts and persistent objects that reflect such events often attract the attention of archaeological prospection which facilitates the construction of conflict narratives. Field prospection as a precise method for localization of aerial bombing craters (as an example of such persistent features) is a highly time- and resource-consuming task. Therefore, methods for automatic identification of such features are evolving. We present a comparison of three methods for possible automatic crater detection based on (a) extraterrestrial crater detection algorithms, (b) geomorphology-based edge extraction, and (c) image pattern recognition via a state-of-the-art convolutional neural network (CNN). All methods were preliminarily tested on a case study of eight Second World War (WWII) aerial bombing crater sites in NW Czechia via Airborne Laser Scanned LiDAR-derived digital terrain models with different spatial resolutions. We found that extraterrestrial crater detection algorithms and geomorphology-based edge extraction methods yield worse results given the standard indices of precision and recall. By comparison, the CNN method utilized for a particular task achieved satisfying results, predominantly with 0.5 m/px resolution (which is often available at the country level) of the input raster. Nevertheless, overall performance with this resolution varies significantly among the sites. Therefore, the quality and readability of the input data are crucial factors for the successful acquisition of precise ordinance location identification.

A wide variety of geographic information system tools and methods was used for pre-dam topography reconstruction and reservoir bottom surveying in two dam reservoirs in the Ohře River, Czech Republic. The pre-dam topography was reconstructed based on archival aerial imagery and old maps. The benefits and drawbacks of these methods were tested and explained with emphasis on the fact that not all processed archival data are suitable for pre-dam topography modeling. Bathymetric surveying of a reservoir bottom is presently routine, but in this study, we used a wide combination of bathymetric mapping methods (sonar, ground penetration radar, and sub-bottom profiler) and topographic survey tools (LiDAR and photogrammetry), bringing great benefits for bottom dynamic analysis and data cross-validation. The data that we gathered made it possible to evaluate the formation of the inflow deltas in the reservoirs studied and assess the sediment reworking during recent seasonal drawdowns. A typical inflow delta was formed in the deeper of the two studied reservoirs, while the summer 2019 drawdown caused the formation and incision of a temporary drawdown channel and erosive downstream transport of approximately 1/10 of the delta body thickness in approximately 1/10 of the delta transverse size. No inflow delta was formed in the shallower of the studied reservoirs, but unexpectedly extensive sediment reworking was observed in the inflow part of the reservoir. Both the studied reservoirs and the pre-dam river floodplain have accumulated historical contamination by risk elements such as As, Hg, Pb; thus, the enhanced erosion of existing sediment bodies expected in the future, owing to more frequent droughts and global climate change, will endanger the ecological quality of the water and solids outflowing from the reservoirs.