Cartography in Early Warning and Crisis Management

Remote sensing for disaster risk reduction

4504.1 - Morphometric Characteristics of River Basin as Factors Controlling Accuracy of Hydrologic Predictions

Tuesday, July 4
1:30 PM - 1:50 PM
Location: Virginia B

Recent technological development in hydroinformatics has simplified the process of obtaining information on hydrological hazards, and also accelerated data handling and processing. The main objective of the HydroProg system (project no. UMO-2011/01/D/ST10/04171, financed by National Science Centre, Poland) is to issue warnings against high flows on a basis of hydrograph predictions. The HydroProg system has been implemented to forecast water levels of rivers in the upper Nysa Klodzka (tributary of the Odra river) catchment in SW Poland. The system operates in real time and uses models that allow to calculate forecasts for every 15 minute ahead, with the maximum lead time of 3 hours. The simultaneous use of several models allows to determine the ensemble prognoses based on multimodelling. The system was described in paper Niedzielski et. al (2014).
The paper focuses on the detection and analysis of statistically significant correlation between the errors of water level forecasts and the morphometric characteristics of river basin where HydroProg system works. The system calculates prognoses for 11 gauges using two data-based models and their multimodel ensemble. Four statistics are used to quantify prediction errors and prediction performance of the models. Each catchment with its outlet at a specific gauge is characterised by morphometric characteristics which have been calculated based on DEM. They are: minimum elevation, maximum elevation, mean elevation, catchment area, and flow length. Additionally, Terrain Ruggedness Index (TRI) and Topographic Wetness Index (TWI) were calculated according to Hengl and Reuter (2008) describtion.
Time range was established as the entire meteorological year divided into individual seasons according to dates: 08/09/2013 – 07/12/2013 (autumn), 08/12/2013 – 08/03/2014 (winter), 09/03/2014 – 07/06/2014 (spring) and 08/06/2014 – 07/09/2014 (summer).
To analyse the correlation between prediction error/performance and morphometric parameters, samples have been composed from data from different gauges. Each season was analysed separately. Due to small sample problem, the bootstrap method has been used to compute the values of the correlation coefficient. Practical recommendations on the use of certain forecasts in the specific characteristics of catchment have been formulated.

Małgorzata Wieczorek

Adiunkt
University of Wrocław

Małgorzata Wieczorek is a teacher and researcher working in Department of Geoinformatics and Cartography at the University of Wrocław, Poland since 2009. She is the deputy head for Academic Education in Institute of Geography and Regional Development at the University of Wrocław. Her research interests focus on Geographic Information Systems, morphometry, map projection and data mining. She leads cartographic workshops for children both at the Children's University and during regional festival of science.

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Mariusz Szymanowski

University of Wrocław

Mariusz Szymanowski works as a professor at the University of Wroclaw, Poland. He serves as Head of Institute of Geography and Regional Development. His research interests focus on spatial analysis and Geographic Information Systems. He is also an expert in climate modelling, climate change and urban climate.

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Bartłomiej Miziński

University of Wroclaw

Bartłomiej Miziński works as research assistant at the University of Wroclaw, Poland. He holds MSc in Mathemathics and Bsc in Computer Science. His work focuses mainly on developing computer systems used in geosciences.

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Tomasz Niedzielski

University of Wroclaw

Tomasz Niedzielski works as a professor at the University of Wroclaw, Poland. He serves as head of Department of Geoinformatics and Cartography. His research interests focus on hydroinformatics, particularly on modelling and forecasting in hydrology. He is also an expert in applications of unmanned aerial vehicles in geosciences.

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Judith Maryna Storie

Dr
Geographic Risk Management (GRM)

Dr Storie is skilled in spatial and non-spatial analytical assessment of geographical data related to disaster risks. She applies Geoinformatics in disaster risk reduction in particular. As a multi-disciplinary expert that is able to conceptualise real-world challenges, she designs programmes to investigate and analyse the challenges that the intersection between hazards and vulnerabilities pose. She serves among others as specialist advisor on various South African Disaster Risk Advisory Forums. She is a Climate Change Adaptation specialist and Carbon Footprint Analyst. Her work focusses on Risk Management with a strong Geoinformatics focus, and human settlement vulnerability to disaster risks.

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