AutoCAD Civil 3D as an aiding tool in hydrological calculation

Violent changes in water regime require quicker and quicker information relating to flood threats. Polish monitoring system is insufficient, in particular in the case of small and average drainage areas. This creates the necessity of searching for different ways of acquiring data. This article presents the method of interpolation of topographical and geodesy information on a section of water-course, basing on the data from maps or from the measurements in the terrain. The software used for data processing as well as sections creating was the AutoCAD Civil 3D. The achieved data were used to calculate return periods using the “rainfall formula” method

Mountain Streambed Roughness and Flood Extent Estimation from Imagery Using the Segment Anything Model (SAM)

Machine learning models facilitate the search for non-linear relationships when modeling hydrological processes, but they are equally effective for automation at the data preparation stage. The tasks for which automation was analyzed consisted of estimating changes in the roughness coefficient of a mountain streambed and the extent of floods from images. The Segment Anything Model (SAM) developed in 2023 by Meta was used for this purpose. Images from many years from the Wielka Puszcza mountain stream located in the Polish Carpathians were used as the only input data. The model was not additionally trained for the described tasks. The SAM can be run in several modes, but the two most appropriate were used in this study. The first one is available in the form of a web application, while the second one is available in the form of a Jupyter notebook run in the Google Colab environment. Both methods do not require specialized knowledge and can be used by virtually any hydrologist. In the roughness estimation task, the average Intersection over Union (IoU) ranges from 0.55 for grass to 0.82 for shrubs/trees. Ultimately, it was possible to estimate the roughness coefficient of the mountain streambed between 0.027 and 0.059 based solely on image data. In the task of estimation of the flood extent, when selecting appropriate images, one can expect IoU at the level of at least 0.94, which seems to be an excellent result considering that the SAM is a general-purpose segmentation model. It can therefore be concluded that the SAM can be a useful tool for a hydrologist

A Novel Method of Design Flood Hydrographs Estimation for Flood Hazard Mapping

Flood hazard mapping requires knowledge of peak flow as well as flood wave volume and shape, usually represented as a design flood hydrograph (DFH). Statistical approaches for DFH development include nonparametric and parametric methods. The former are developed from long-term flow observations and are thus related to the physio-hydro-climatological catchment properties, but not applicable for ungauged catchments. The alternative parametric DFH can be estimated for any river cross-section, but its links with catchment characteristics are limited. The goal of this study was to introduce a novel hybrid approach for DFH estimation, where the parametric DFH is estimated from the selected properties of the nonparametric DFH (hydrograph width at the levels of 50% and 75% of the peak flow and skewness coefficient) that can be related to the catchment characteristics. The model that offers effective parameter estimation and best correspondence to the reference observation-based hydrograph was selected from among Gamma distribution, Strupczewski and Baptista candidates. The method was validated for 34 catchments of the upper Vistula River and Middle Odra water regions (Poland) based on data from the 1964–2010 period. The Baptista method was found to provide the best model for hybrid DFH construction according to the applied quality measures

Flow descriptors for parametric hydrographs accounting for afforestation of the catchment

Parametric flow hydrographs are used for design and management purposes in such fields as water management and aquatic engineering. They describe a theoretical hydrograph based on such parameters as maximum flow, time to peak, and surge duration. They are used to forecast flood risk and to evaluate the impact of land use on the run-off hydrograph. In Western Europe for many years methods have been used in which parametric hydrographs are determined based on physical catchment descriptors (PCDs), which are divided into three groups describing the physical features of a catchment. These descriptors are used to derive formulae enabling the determination of parametric flow hydrographs for any computational crosssection. In this work, such formulae are derived for the catchment of the Raba River, using the principles of design hydrology applied in Western European countries. The parametric hydrograph is described using Baptista’s gamma density function. The input hydrograph was a nonparametric flow hydrograph determined by Archer’s method. For nine gauging stations located in the Raba catchment, physical catchment descriptors were obtained for two 30-year periods: 1961-1990 and 1983-2012. Based on the nonparametric flow hydrograph and the PCDs, two groups of formulae were derived to describe the parametric hydrograph. Analysis of agreement between the computed parametric flow hydrographs and the input hydrograph indicated a high quality of fit. It should be noted that the formulae and analysis presented here refer only to the Raba catchment. However, the results confirm the possibility of applying these methods to the determination of parametric flow hydrographs for any river cross-section