Estimation of Polder Retention Capacity Based on ASTER, SRTM and LIDAR DEMs: The Case of Majdany Polder (West Poland)

Abstract

This study compares four digital elevation models (DEMs), based on various data sources, to define polder retention capacities. Two commercial and two publically available, free of charge data sources were used. Commercial sources are DEMs based on aerial images and LIDAR (Light Detection and Ranging) data. Free data source DEMs generated are based on: SRTM (Shuttle Radar Topography Mission) and ASTER GDEM (ASTER Global Digital Elevation Model). In addition, the impact of the spatial resolution of the numerical terrain model on the calculated polder volume was evaluated. A DEM based on LIDAR data was used as the reference model and was supplemented with our own geodetic GPS (Global Positioning System) measurements. In flood modeling and management, including retention of river valleys and polders, it is necessary to properly estimate their capacity and the relation between capacity and water level. The study showed the impact of quantitative and qualitative data sources in determining the retention capacity of a polder.

Possibilities of Using Low Quality Digital Elevation Models of Floodplains in Hydraulic Numerical Models

“…As shown in the earlier study [10], the ASTER and STRM models cannot be applied for hydraulic modelling.…”

“…Therefore, the commonly-used DEMs are based on aerial photographs and globally available datasets like SRTM (Shuttle Radar Topography Mission) and ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) [10][11][12].…”

“…Another approach is to use the global and local spatial autocorrelation indices, namely Moran's I and the Getis-Ord G indices. Walczak et al (2016) [10] and Gichamo et al [13] have proposed methods to correct freely-available, satellite-based DEMs. In the propositions of both authors, the vertical error correction is based on the determination of the average error calculated using field measurements.…”

“…In the propositions of both authors, the vertical error correction is based on the determination of the average error calculated using field measurements. Walczak et al [10] compared four DEMs based on various data sources (SRTM, ASTER GDEM, LIDAR and aerial photographs) to calculate polder retention capacity. The authors concluded that the accuracy of ASTER or SRTM DEMs is generally insufficient for flood modeling, especially for modelling polders' capacity as flood-protection systems.…”

“…The accuracy is most often estimated using global statistics like mean error (ME), root mean square error (RMSE) and standard deviation (SD) [10,13]. These statistics are used when the errors have normal distributions.…”