Regional Hydrology: Coupling Experiments, Ground Monitoring, Remote Sensing and Citizen Science

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "New Sensors, New Technologies and Machine Learning in Water Sciences".

Deadline for manuscript submissions: closed (30 September 2021) | Viewed by 3238

Special Issue Editors


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Guest Editor
Institute of Hydraulic Engineering and Water Resources, Vienna University of Technology, A-1040 Vienna, Austria
Interests: hydrological modeling; prediction in ungauged sites; climate change; snow hydrology; regional water balance modeling; experimental research
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Guest Editor
Department of Land and Water Resources, Slovak University of Technology in Bratislava, Bratislava, Radlinskeho 11, 81005 Bratislava, Slovakia
Interests: regionalisation; comparative hydrology; land-use change impact; hydrological extremes

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Guest Editor
Institute of Geomatics and Civil Engineering, University of Sopron, 9400 Sopron, Hungary
Interests: forest hydrology; evapotranspiration; groundwater; field measurements

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Guest Editor
Institute of Hydraulic Engineering and Water Resources Management, Vienna Univ. of Technology, Karlsplatz 13/222, Vienna 1040, Austria
Interests: flood estimation; prediction in ungauged basins; experimental research, engineering hydrology; spatial patterns in regional hydrology

Special Issue Information

Dear Colleagues,

Increasing the availability of data and their assimilation into hydrological models based on the latest developments in radar meteorology, geophysics, experiments on hillslopes and tracer studies in catchments gives hydrologists an opportunity to critically examine process representations in hydrological catchment models and to evaluate and compare different models of the same type (e.g., distributed) or different types of models (e.g., distributed vs lumped, process-based vs conceptual) on a plot, hillslope and regional basis. Increased data availability supported by new measurement and sensing technologies calls for knowledge-based assimilation of these data into local and regional hydrology and catchment modelling. Coupling field experiments, remote sensing, network data and citizen science with process-oriented modelling helps to explore and respect the complexity and multiscale nature of the interactions among drivers and runoff generation in the area in comparative and regime studies at the regional scale.

This Special Issue is looking for studies focusing on and examining the following topics:

  • New supportive evidence from field experiments leading to better process understanding at the regional scale;
  • Coupling data from remote sensing, radar meteorology, plot- and hillslope-scale experiments, tracer studies, citizen science, etc. with catchment models;
  • Discovering regional patterns in hydrological processes and regimes on various temporal and spatial scales utilizing the new increased data availability;
  • Confrontation of the adequacy of process representations in hydrological catchment models with knowledge gained from new types of data;
  • Better process representations in hydrologic models in diverse environments and implications for more reliable predictions in gauged and ungauged basins, and the evaluation of the appropriateness of models for particular practical problems under changes in hydrological regimes of anthropogenic origin, including climate and land-use change impacts.

Prof. Dr. Juraj Parajka
Prof. Dr. Jan Szolgay
Prof. Dr. Zoltan Gribovszki
Prof. Dr. Günter Blöschl
Guest Editors

Manuscript Submission Information

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Keywords

  • regional hydrology
  • experimental hydrology
  • comparative hydrology
  • catchment modelling
  • spatial patterns
  • remote sensing
  • citizen science

Published Papers (1 paper)

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Research

18 pages, 2612 KiB  
Article
Impact of Climate and Geology on Event Runoff Characteristics at the Regional Scale
by Xiaofei Chen, Juraj Parajka, Borbála Széles, Peter Valent, Alberto Viglione and Günter Blöschl
Water 2020, 12(12), 3457; https://doi.org/10.3390/w12123457 - 09 Dec 2020
Cited by 7 | Viewed by 2527
Abstract
The dynamics of flood event characteristics, such as the runoff coefficient and the recession time constant, differ in time and space, due to differences in climate, geology, and runoff generation mechanisms. This study examines the variability of event runoff characteristics and relates them [...] Read more.
The dynamics of flood event characteristics, such as the runoff coefficient and the recession time constant, differ in time and space, due to differences in climate, geology, and runoff generation mechanisms. This study examines the variability of event runoff characteristics and relates them to climatic and hydro-geological characteristics available at the regional scale. The main focus is to examine the role of rainfall patterns (i.e., event precipitation volume, precipitation intensity, and antecedent precipitation) and runoff regime (i.e., initial flow before runoff event and event duration) characteristics on the seasonal dynamics of runoff response. The analysis is performed in four small Austrian catchments representing different hydro-geological settings obtained by field mapping. The results are based on an analysis of 982 runoff events identified from hourly measurements of streamflow and precipitation in the period 2002 to 2013. The results show that larger event runoff coefficients and flow peaks are estimated in catchments with high mean annual precipitation than in drier catchments. In contrast to some previous studies, the results show only poor relation between antecedent precipitation (as an index of catchment wetness) and event runoff response. The initial flow is found to be the main factor influencing the magnitude of runoff coefficient and event peaks in all analyzed catchments and geological settings. The recession time constant tends to be inversely related to the maximum event precipitation intensity, with an exception for one catchment (Wimitzbach), which is characterized by the largest proportion of deep interflow contribution to runoff. The analysis of the runoff response by different event types indicates that runoff coefficients and recession time constants are the largest for snowmelt runoff events. Full article
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