Tomasz Berezowski

Hydrological modelling of the Vistula and Odra river basins using SWAT

ABSTRACT This paper presents a large-scale application of the SWAT model for water balance and natural streamflow simulation in the entire basins of the Vistula and the Odra, covering most of the territory of Poland. A tailored calibration approach was designed to achieve satisfactory goodness-of-fit across a range of catchment sizes. Model calibration and evaluation driven by high-resolution climate data showed overall good behaviour for 80 benchmark catchments divided into eight clusters, and spatial evaluation for 30 gauges showed that the designed regionalization scheme performed well (median KGE of 0.76). Basin-averaged estimates of blue and green water flow and green water storage estimated using the calibrated model were 185, 517 and 206 mm, respectively. This study provides a basis for future work, such as assessing climate change impacts on hydrology, assessing flow alterations, and water quality simulation. The model output is publicly available through an online research data archive (doi:10.4121/uuid:b8ab4f5f-f692-4c93-a910-2947aea28f42). EDITOR A. Castellarin ASSOCIATE EDITOR G. Thirel

Preliminary validation of a method for simulating hyperspectral bands from multispectral images

This paper presents a validation of a recently developed method for simulating new spectral bands from multispectral images. We use the method to simulate CHRIS/PROBA bands from a Landsat ETM+ image. Next we validate the simulated bands by RMSE, band-band scatter plots and visual comparison with original CHRIS bands acquired 4 days before the ETM+ image. Finally, we calculate NDVI from the original and simulated CHRIS bands and from the ETM+ bands. Result show that the simulated CHRIS NDVI in the dominant vegetation types in the study area is more correlated to the original CHRIS NDVI, than ETM+ NDVI. For not dominant vegetation types, not included into the simulation process, the correlation is lower for simulated CHRIS NDVI than for ETM+ NDVI.

Towards rainfall interception capacity estimation using ALS LiDAR data

In this study we develop a spatial model for interception capacity of vegetation based on LiDAR data. The study is conducted in the natural wetland river valley dominated meadows, reeds and small bushes. The multiple regression model was chosen to relate the field measurements of interception capacity and LiDAR statistics at 2m grid. The optimal model was chosen by stepwise selection and further manual variables selection resulting in the r2 of 0.52 and the residual standard error of 0.27 mm. The model preserved the vegetation pattern spatially and showed reasonable estimates for both vegetation covered and not covered by field sampling. The model was, however, affected by LiDAR measurements corrupted by river inundation. The results show good perspective for using LiDAR data for interception capacity estimation.