Abstract:The paper presents a method for the correction of low quality DEMs, based on aerial photographs, for use in 2D flood modeling. The proposed method was developed and tested on the example of the floodplain of the Warta River, which is the third biggest river in Poland. The correction of DEM is based on a series of a small number of measurements using GPS-RTK, which enable calculations of the global statistics like mean error (ME), root mean square error (RMSE) and standard deviation (SD). The impact of DEM accuracy was estimated by using a 2D numerical model. The calculated values of flow velocities, inundation area and volume of floodplain for each tested DEM were compared. The analyses indicate that, after the correction procedure, the predictions of corrected DEM based on poor quality data is in good quantitative and qualitative agreement with the referenced LIDAR DEM. The proposed method may be applied in the areas for which high resolution DEMs based on LIDAR data are not available.

The article describes how the Structure-from-Motion (SfM) method can be used to calculate the volume of anthropogenic microtopography. In the proposed workflow, data is obtained using mass-market devices such as a compact camera (Canon G9) and a smartphone (iPhone5). The volume is computed using free open source software (VisualSFMv0.5.23, CMPMVSv0.6.0., MeshLab) on a PCclass computer. The input data is acquired from video frames. To verify the method laboratory tests on the embankment of a known volume has been carried out. Models of the test embankment were built using two independent measurements made with those two devices. No significant differences were found between the models in a comparative analysis. The volumes of the models differed from the actual volume just by 0.7‰ and 2‰. After a successful laboratory verification, field measurements were carried out in the same way. While building the model from the data acquired with a smartphone, it was observed that a series of frames, approximately 14% of all the frames, was rejected. The missing frames caused the point cloud to be less dense in the place where they had been rejected. This affected the model’s volume differed from the volume acquired with a camera by 7%. In order to improve the homogeneity, the frame extraction frequency was increased in the place where frames have been previously missing. A uniform model was thereby obtained with point cloud density evenly distributed. There was a 1.5% difference between the embankment’s volume and the volume calculated from the camera-recorded video. The presented method permits the number of input frames to be increased and the model’s accuracy to be enhanced without making an additional measurement, which may not be possible in the case of temporary features.

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.

The paper presents the results of the effects of control drainage (CD) on the groundwater table and subsurface outflow in Central Poland. The hydrologic model DRAINMOD was used to simulate soil water balance with drain spacing of 7 and 14 m, different initial groundwater Table 40, 60 and 80 cm b.s.l., and dates at the beginning of control drainage of 1 March, 15 March, 1 April, and 15 April. The CD restricts flow at the drain outlet to maintain a water table during the growing season. Simulations were made for the periods from March to September for the years 2014, 2017, and 2018, which were average, wet, and dry, respectively. The simulations showed a significant influence of the initial groundwater tables and date blocking the outflow from the drainage network on the obtained results. In the conditions of central Poland, the use of CD is rational only when it is started between 1 and 15 March. In this case, the groundwater table can be increased from 10 to 33 cm (7 m spacing) and from 10 to 41 cm (14 m spacing) in relation to the conventional system (free drainage-FD). In the case of blocking the outflow on 1 March, the reduction is about 80% on average in the period from March to September. With a delay in blocking the outflow, the impact of CDs decreases and ranges from 8% to 50%. Studies have shown that the proper use of the drainage network infrastructure complies with the idea of sustainable development, as it allows efficient water management, by reduction of the outflow and, thus, nitrates from agricultural areas. Furthermore, CD solutions can contribute to mitigating the effects of climate change on agriculture by reducing drought and flood risk.Sustainability 2019, 11, 4201 2 of 18 water users to be affected by the consequences of climate change in different way [5]. Consequently, this will lead to exacerbated competition among water users and sectors [6].One of the main challenges for sustainable development is the adaptation of national economies to climate change. Most often, climate change adaptation projects in Poland are carried out in cities and areas subject to urban sprawl [7][8][9]. Agriculture is a key sector for food supply, and its functioning depends largely on access to water. It is, therefore, necessary to take various actions to protect this sector of national economies against climate change. The most frequently asked question is whether and to what extent it is possible to take action in the adaptation of agriculture to climate change while maintaining high environmental standards and accounting for the acceptance of society and economic balance.The greatest scope for the mitigation of the effects of climate change is in improving adaptive capacity and responding to changes in water demands [10]. Agricultural subsurface drainage, popularly known as tile drainage, is an essential water management practice in agricultural regions with seasonal high groundwater tables [11]. Around 193.9 × 10 6 ha of arable land, and permanent crops have been drained around the world. In 30 countries, th...

Pollution of river bottom sediments with heavy metals (HMs) has emerged as a main environmental issue related to intensive anthropopressure on the water environment. In this context, the risk of harmful effects of the HMs presence in the bottom sediments of the Warta River, the third longest river in Poland, has been assessed. The concentrations of Cr, Ni, Cu, Zn, Cd, and Pb in the river bottom sediments collected at 24 sample collection stations along the whole river length have been measured and analyzed. Moreover, in the GIS environment, a method predicting variation of HMs concentrations along the whole river length, not at particular sites, has been proposed. Analysis of the Warta River bottom sediment pollution with heavy metals in terms of the indices: the Geoaccumulation Index (Igeo), Enrichment Factor (EF), Pollution Load Index (PLI), and Metal Pollution Index (MPI), has proved that, in 2016, the pollution was heavier than in 2017. Assessment of the potential toxic effects of HMs accumulated in bottom sediments, made on the basis of Threshold Effect Concentration (TEC), Midpoint Effect Concentration (MEC), and Probable Effect Concentration (PEC) values, and the Toxic Risk Index (TRI), has shown that the ecological hazard in 2017 was much lower. Cluster analysis revealed two main groups of sample collection stations at which bottom sediments showed similar chemical properties. Changes in classification of particular sample collection stations into the two groups analyzed over a period of two subsequent years indicated that the main impact on the concentrations of HMs could have their point sources in urbanized areas and river fluvial process.