Advances in the understanding of hydrology over the last century have been driven by the evolving needs of society and technological opportunities: new ideas are generated by hydrologists as they address society's demands with the technologies of their time. This paper specifically discusses the evolution of concepts related to flood runoff generation through different mechanisms: excess infiltration, excess saturation, subsurface flow, and more recently, the emphasis on hydrological connectivity. In particular, it highlights the ideas regarding the transition from moderate flood events to extreme ones. The evolution of concepts for quantifying flood peaks through extreme value statistics is briefly summarized. Finally, the talk outlines the evolution of approaches to combine statistics with hydrological processes, starting from the theory of derived distributions and including flood frequency hydrology and regional process hydrology, in order to complete regional statistical hydrology. It also evaluates the main driving factors, depending on the characteristics of climate and catchments. It is argued that the growing societal expectations for safety and the clear human influence on the hydrological cycle now more than ever require a process-based approach to the estimation of extreme floods.

How to cite: Blöschl, G.: Evolution in the Understanding of the Characteristics of Extreme Hydrological Events, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-2223, https://doi.org/10.5194/egusphere-egu25-2223, 2025.

In 2025, Czech hydrology celebrates several significant anniversaries. In 1775, the uninterrupted temperature series in the Klementinum Observatory in Prague began, in 1825 daily observations of water levels in Prague began, and in 1875 the hydrological service in Prague was established (Elleder, 2019). As far as 1775 is concerned, this is more about meteorological observations, but even here we find references to floods and droughts in the observation diaries, and the earliest records of rainfall and snow heights. Here, we focus on the first decade of observations (1775– 1785), when the extreme flood of February 1784 occurred. In 1781, the first water gauge in Prague was established by the Klementinum Observatory when it was incorporated into the Societas Meteorologica Palatina (SMP). However, these were only occasional observations of water levels. The floods of 1782, 1783 and 1784 were partially documented with the help of this water gauge. For the time of the flood (February 1784) we have incomplete records only for the beginning and end of the flood. The course of the water levels is still known relatively accurately in Prague, Beroun, Dresden and then Magdeburg.  The hydrograph of this extreme flood in Prague was reconstructed from indirect evidence of water levels (Elleder, 2010). The rate of water rise was enormous, up to 30 cm per hour. Using the Aqualog system, standardly used for hydrological forecasting, we have now attempted a hydrological re-simulation of this flood in the context of the entire Vltava basin in front of Prague. This means the scenarios generated only from measurements of temperature, air pressure and partly precipitation in Prague, or in relatively near stations Regensburg, Budapest, Zagan, Erfurt and Mannheim. Problems arose in obtaining rain and snowfall data due to uncertainties regarding the recording of precipitation in Prague. To better understand how precipitation is recorded, we attempted to consider measurements at other SMP observatory sites.   We documented the conditions of the severe winter that preceded the flood, including the likely ice thickness, water value of the snow, and partial rainfall. Using re-simulations with the Aqualogic modelling system, we obtained an approximate agreement of the water level courses in Beroun and Prague in terms of time, culmination and flood volume. The steep rise in levels could not be explained.  The flood in its entire European context is gradually being included in the Maps of Extreme Floods - MEF (Elleder and Šírová, 2023). We started with a reanalysis of the 1784 flood by showing reconstructions of major European floods, where documentary data are collected in advance in the MEF 2020 application. To date it is the most significant winter flood in Prague.

References:

Elleder, L., (2010) Reconstruction of the 1784 flood hydrograph for the Vltava River in Prague, Czech Republic. Global and Planetary Change 70, 117–124.

Elleder, L. 2019. A. R. Harlacher and his Role in founding of Czech Hydrological Service in Prague in 1875, https://meetingorganizer.copernicus.org/EGU2019/EGU2019-7860.pdf.

Elleder, L. Šírová, J. (2023) MEF application- the extreme floods are already in maps!

        https://meetingorganizer.copernicus.org/EGU23/EGU23-3160.html.

How to cite: Elleder, L., Krejčí, J., Šírová, J., and Stehlikova, H.: The oldest instrumental hydrological and meteorological records in Prague as a basis for the resimulation of the flood of February 1784, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-3625, https://doi.org/10.5194/egusphere-egu25-3625, 2025.

The well-known Muskingum-Cunge method and the variable parameter Muskingum-Cunge-Todini method (Todini 2007) have been developed by matching the diffusion coefficient of the numerical analogue of the kinematic wave equation with that of the physical diffusive wave equation governing the one dimensional flood wave propagation in channels. It is shown in this study that an alternative variable parameter Muskingum method can be directly derived from the diffusive wave equation without resorting to the matched diffusivity approach as followed in the above mentioned two methods. A comparative evaluation of the routing performances of this method with those of very two similar methods, known as the variable parameter Muskingum-Cunge-Todini (MCT) method as proposed by Todini (2007), and another Variable Parameter McCarthy-Muskingum (VPMM) method proposed by Perumal and Price (2013) is made in the study. For the purpose of comparative evaluation, all these three methods use the same set of benchmark solutions obtained by routing a given inflow hydrograph in twenty five trapezoidal channels each having the same bed width and the side slope, but each of them characterized by unique combinations of bed slopes and Manning’s roughness coefficients. Standard evaluation measures as available in the literature were used in assessing the capabilities of each of the three methods in reproducing the benchmark solutions obtained by routing the given hypothetical inflow hydrograph by the HEC-RAS model for a reach length of 100 km in each of these channels. All the three methods show equal performances in reproducing the benchmark solutions with NSE≳0.99, when the inflow hydrograph is characterized by the water surface gradient +(1/S₀)∂y/∂x≤0.5. But for the routing cases characterized by +(1/S₀)∂y/∂x>0.5, the MCT method fails to route the inflow hydrograph, while the other two methods yield results with diminished performance levels (NSE<0.99), though the proposed method performs better than the VPMM method for these cases.

How to cite: Perumal, M. and Chintalacheruvu, M. R.: Direct derivation of an alternative variable parameter McCarthy-Muskingum method from the diffusive wave equation, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-7775, https://doi.org/10.5194/egusphere-egu25-7775, 2025.

Creating forecast systems that add value across spatial scales and time horizons is crucial for a variety of fields, from meteorology and climate science to business and public policy. The priorities for developing such systems may vary depending on the specific domain and objectives. Over the past 20 years, the international community of practice known as the Hydrological Ensemble Prediction Experiment (HEPEX) has been seeking to advance the science and practice of hydrological ensemble prediction and its use in impact- and risk-based decision-making. HEPEX is a volunteer-based community, active since 2004, with over 600 members (hepex.org.au/). It has been promoting knowledge utilizing cutting-edge techniques and data to innovate hydrological forecasting methods, products and systems, and improve services for users in the water-related sectors. Here, we present an overview of the history of HEPEX and reflect on the key priorities recently proposed by the community for (co-) creating hydrological forecast systems that add value across spatial scales and time horizons. We highlight that hydrological forecasts have advanced through rigorous data management that incorporates diverse, high-quality data sources and the application of cutting-edge AI/ML techniques to improve predictive accuracy. HEPEX has played a critical role in enhancing the reliability of water management globally by standardizing ensemble forecasting and fostering a broader framework for forecast evaluation. This complements HEPEX's broader initiative to bridge the gap between research-to-operations practice, making forecasting solutions both practical and accessible. Finally, we highlight how efforts supporting the United Nations Early Warnings for All initiative can contribute to the development of robust early warning systems through extensive global training and the sharing of technology. The integration of advanced science, user-centric methods and global collaboration can provide a solid framework for improving the prediction and management of hydrological extremes, aligning forecasting systems with the dynamic needs of water resource management in a changing climate.

How to cite: Pechlivanidis, I., Ramos, M.-H., and Wood, A. and the team: The 20-year history of HEPEX - Enhancing hydrological forecasting through strategic innovations, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-8059, https://doi.org/10.5194/egusphere-egu25-8059, 2025.

In the 21^st century, numerical models are a widespread tool for understanding, visualizing, and simulating hydrological processes, from alpine streams to tropical deltas. A large variety of different models is widely available and offers extensive possibilities for customization to researchers and decision-makers alike. While many challenges remain - such as proper parameterization or data-sparsity in many regions of the globe that renders calibration and validation difficult - numerical models now have a large community of users and the computational infrastructure needed to run them is readily available to most users. 

None of this was the case when the Mekong Delta Model was developed in the early 1960s. Numerical models were in their infancy and few institutions had access to computers. The Mekong Delta Model was a pioneering effort, funded by UNESCO. Its aim was to simulate the impact and assess the viability of a dam across the Tonle Sap river in Cambodia, proposed as part of the plan of the UN’s Economic Commission for Asia and the Far East (ECAFE) to support economic development in Southeast Asia. It was the first computational model built to represent a deltaic area and served not only as a proof of concept, but also as a basis on which many key figures in the numerical modelling community later developed their own work. 

This study seeks to trace the genesis of this groundbreaking model and to explore its impact on the development of computational approaches in hydrology from the 1960s onwards. It is based on an extensive bibliographical survey, archival research in the Archives d’Outre Mer in Aix-en-Provence and the UNESCO archives in Paris, and an in-person interview with a member of the original team at SOGREAH (Société Grenobloise d'Études et d'Applications Hydrauliques), which built the model. The results outline the story of the model, from the contentious tender process in which it prevailed against more established alternative approaches, over the often dangerous data gathering and harmonization stage (set against the background of the Vietnam War), to the influence it had on the community of modellers in places such as the Danish Hydraulic Institute and the University of Colorado. 

How to cite: Orieschnig, C. A.: The Mekong Delta Model: Pioneering Numerical Approaches and Lasting Impacts on Computational Hydrology , EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-10501, https://doi.org/10.5194/egusphere-egu25-10501, 2025.

A key challenge in hydrological modeling is representing the relationship between catchment wetness and hydrograph response. The concept of variable source area has been a significant influence in this area, proposing that a source area, which is dynamically shaped by catchment wetness, controls the amount of precipitation contributing to hydrograph peaks during rainfall events. This study explores two foundational theories of variable source area that have guided the development of hydrological models. The first, the Interacting Storage Elements theory, serves as the basis for models such as Xinanjiang, PDM, Arno, and VIC. The second, the Topographic Index theory, underpins the Topmodel approach. Although these theories differ in their conceptual models, they share a common goal of analyzing local hydrological processes which, through specific assumptions, lead to a functional relationship between average storage and source area at the catchment scale, providing clarity on the role of catchment properties in shaping this relationship. This study critically reviews and compares these theories, examining their application in early hydrological models, and highlights underlying similarities that may have been overlooked due to differences in presentation, notation, and numerical implementation. Additionally, the study investigates why these theories remain effective despite differences between theoretical assumptions and actual catchment behavior.

How to cite: Fenicia, F., Prieto, C., and Kavetski, D.: A historical perspective of variable source area theories in hydrological modeling, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-11535, https://doi.org/10.5194/egusphere-egu25-11535, 2025.

How to cite: Cenzon, A., Durighetto, N., and Botter, G.: The relationship between mean hillslope length and drainage density: from the Horton equation to dynamic river networks, EGU General Assembly 2025, Vienna, Austria, 27 Apr–2 May 2025, EGU25-16864, https://doi.org/10.5194/egusphere-egu25-16864, 2025.