Watershed Dynamics and Hydrological Extremes
Research Focus
In the WaterExtremes group we develop effective process-informed data-driven methods grounded in comprehensive perceptual representation of dominant hydrological dynamics and catchment organization to leverage the increasing sample sizes of hydrometeorological observations from small- to mesoscales. With these methods we uncover regularities in complex hydrological systems to understand better the emergence of extremes and provide more reliable predictions at large scales.
Opportunities
The following Master thesis/Internships are currently available in the group:
- Improving parameter regionalization of the distributed catchment model (contact: Dr. Zhenyu Wang)
- Drought and post-drought impacts on pollutant transport from catchments to streams (contact: Felipe Saavedra)
- Effect of extreme events on nutrient concentrations and ratios in the Elbe River catchment (contact: Felipe Saavedra)
We also looking to host Doctoral/Postdoctoral research stays supported by the HIDA network on various topics concerning explainable machine learning and deep learning (contact: Dr. Larisa Tarasova).
Felipe Saavedra
Doctoral researcher (PhD Cohort DYNAMO; TRACER Resarch School)
Topic: Effects of hydrological events on solute mobilization and delivery in German river catchments
Dr. Zhenyu Wang
Postdoctoral researcher
Topic: Event-type-based diagnostics of hydrological models and groundwater droughts
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Jiarui Yu
Visiting doctoral researcher
Topic: Damage footprint of different flood generation processes
Ying Zhang
Visiting doctoral researcher
Topic: Forecasting widespread floods using deep learning
Former group members
- Chahinaz Ziani, Master student "Development of topographically-enhanced catchment descriptors", now research assistant at TH Cologne, Germany
- Matteo Pesce, visiting PhD researcher from Polotecnico di Torino, Italy "Classification of river flood events in the North-East of Italy", now researcher at University of Padua, Italy
- Safae Aala, Master student "The effect of space-time dynamics of precipitation on timing and shape of streamflow events", now at GIZ Agadir, Morocco
Uncovering generation processes of complex hazards using data evidences supported by simulations
- changes in flood generation processes
- archetypes of drought propagation through catchment compartments
- spatial extremes
- impact of extremes on nutrient mobilization
Improving process foundation of conceptual, statistical, machine and deep learning models for more reliable predictions under global change
- event-type-based diagnostics of hydrological models
- explainable AI
- sparse neural networks for S2S forecasting
- physically-enhanced statistical approaches for estimating extremes
Developing methods to account for inherent spatial organization within hydrological catchments
PREDICTED
Propensity of rivers to extreme floods: climate-landscape controls and early detection
(DFG Research Project, grant 421396820, 2019-2022)
DYNAMO
Events as dynamic drivers of pollutant transport, turnover and export in catchments – from monitoring to models
Subproject 3: Effects of hydrological events on solute mobilization and delivery in German river catchments
(Helmholtz Centre for Environmental Research - UFZ PhD college, 2020-2023)
Inhalt:
Weiterführende Recherchen können Sie in unserem Publikationsverzeichnis durchführen.
2024 (4)
- Jiang, S., Tarasova, L., Yu, G., Zscheischler, J. (2024):
Compounding effects in flood drivers challenge estimates of extreme river floods
Sci. Adv. 10 (13), eadl4005 10.1126/sciadv.adl4005 - Saavedra, F., Musolff, A., von Freyberg, J., Merz, R., Knöller, K., Müller, C., Brunner, M., Tarasova, L. (2024):
Winter post-droughts amplify extreme nitrate concentrations in German rivers
Environ. Res. Lett. 19 (2), art. 024007 10.1088/1748-9326/ad19ed - Tarasova, L., Ahrens, B., Hoff, A., Lall, U. (2024):
The value of large-scale climatic indices for monthly forecasting severity of widespread flooding using dilated convolutional neural networks
Earth Future 12 (2), e2023EF003680 10.1029/2023ef003680 - Tarasova, L., Gnann, S., Yang, S., Hartmann, A., Wagener, T. (2024):
Catchment characterization: Current descriptors, knowledge gaps and future opportunities
Earth-Sci. Rev. 252 , art. 104739 10.1016/j.earscirev.2024.104739
2023 (11)
- Basso, S., Merz, R., Tarasova, L., Miniussi, A. (2023):
Extreme flooding controlled by stream network organization and flow regime
Nat. Geosci. 16 (4), 339 - 343 10.1038/s41561-023-01155-w - Bieroza, M., Acharya, S., Benisch, J., ter Borg, R.N., Hallberg, L., Negri, C., Pruitt, A., Pucher, M., Saavedra, F., Staniszewska, K., van’t Veen, S.G.M., Vincent, A., Winter, C., Basu, N.B., Jarvie, H.P., Kirchner, J.W. (2023):
Advances in catchment science, hydrochemistry, and aquatic ecology enabled by high-frequency water quality measurements
Environ. Sci. Technol. 57 (12), 4701 - 4719 10.1021/acs.est.2c07798 - Miniussi, A., Basso, S. (2023):
Files and code for the paper "Unprecedented flooding foretold by stream network organization and flow regime" by S. Basso, R. Merz, L. Tarasova and A. Miniussi
HydroShare 10.4211/hs.a6bcc341413c4fb0b195b25ebe1bb3e6 - Miniussi, A., Merz, R., Kaule, L., Basso, S. (2023):
Identifying discontinuities of flood frequency curves
J. Hydrol. 617, Part B , art. 128989 10.1016/j.jhydrol.2022.128989 - Mushtaq, S., Miniussi, A., Merz, R., Tarasova, L., Marra, F., Basso, S. (2023):
Prediction of extraordinarily high floods emerging from heterogeneous flow generation processes
Geophys. Res. Lett. 50 (20), e2023GL105429 10.1029/2023GL105429 - Tarasova, L. (2023):
Widespread flood severity index time series for Germany [Data set]
Zenodo 10.5281/zenodo.7688006 - Tarasova, L., Lun, D., Merz, R., Blöschl, G., Basso, S., Bertola, M., Miniussi, A., Rakovec, O., Samaniego, L., Thober, S., Kumar, R. (2023):
Shifts in flood generation processes exacerbate regional flood anomalies in Europe
Commun. Earth Environ. 4 , art. 49 10.1038/s43247-023-00714-8 - Tarasova, L., Merz, R. (2023):
Großräumige Analyse von Abflussereignissen: Entstehungsprozesse und deren Effekt auf die räumliche und zeitliche Variabilität der Abflussdynamik – Large scale analysis of runoff events: generation processes and their effect on the spatio-temporal variability of runoff event dynamics
Hydrol. Wasserbewirtsch. 67 (5), 275 - 286 10.5675/HyWa_2023.5_4 - Wachholz, A., Dehaspe, J., Ebeling, P., Kumar, R., Musolff, A., Saavedra, F., Winter, C., Yang, S., Graeber, D. (2023):
Stoichiometry on the edge - humans induce strong imbalances of reactive C:N:P ratios in streams
Environ. Res. Lett. 18 (4), art. 044016 10.1088/1748-9326/acc3b1 - Wang, H.-J., Merz, R., Yang, S., Basso, S. (2023):
Inferring heavy tails of flood distributions through hydrograph recession analysis
Hydrol. Earth Syst. Sci. 27 (24), 4369 - 4384 10.5194/hess-27-4369-2023 - Wang, H.-J., Merz, R., Yang, S., Tarasova, L., Basso, S. (2023):
Emergence of heavy tails in streamflow distributions: the role of spatial rainfall variability
Adv. Water Resour. 171 , art. 104359 10.1016/j.advwatres.2022.104359
2022 (11)
- Basso, S., Bakken, T.H. (2022):
Editorial: Reconciling small hydropower and ecosystem services in river basins
Front. Environ. Sci. 10 , art. 874065 10.3389/fenvs.2022.874065 - Giani, G., Tarasova, L., Woods, R.A., Rico-Ramirez, M.A. (2022):
An objective time-series-analysis method for rainfall-runoff event identification
Water Resour. Res. 58 (2), e2021WR031283 10.1029/2021WR031283 - Merz, B., Basso, S., Fischer, S., Lun, D., Blöschl, G., Merz, R., Guse, B., Viglione, A., Vorogushyn, S., Macdonald, E., Wietzke, L., Schumann, A. (2022):
Understanding heavy tails of flood peak distributions
Water Resour. Res. 58 (6), e2021WR030506 10.1029/2021WR030506 - Merz, R., Miniussi, A., Basso, S., Petersen, K.-J., Tarasova, L. (2022):
More complex is not necessarily better in large-scale hydrological modelling: A model complexity experiment across the contiguous United States
Bull. Amer. Meteorol. Soc. 103 (8), E1947 - E1967 10.1175/BAMS-D-21-0284.1 - Mushtaq, S., Miniussi, A., Merz, R., Basso, S. (2022):
Reliable estimation of high floods: A method to select the most suitable ordinary distribution in the Metastatistical extreme value framework
Adv. Water Resour. 161 , art. 104127 10.1016/j.advwatres.2022.104127 - Peña-Guerrero, M.D., Umirbekov, A., Tarasova, L., Müller, D. (2022):
Comparing the performance of high-resolution global precipitation products across topographic and climatic gradients of Central Asia
Int. J. Climatol. 42 (11), 5554 - 5569 10.1002/joc.7548 - Saavedra, F.A., Musolff, A., von Freyberg, J., Merz, R., Basso, S., Tarasova, L. (2022):
Disentangling scatter in long-term concentration–discharge relationships: the role of event types
Hydrol. Earth Syst. Sci. 26 (23), 6227 - 6245 10.5194/hess-26-6227-2022 - Tarasova, L. (2022):
Code: flood generation processes and flood anomalies
Version: 1 Zenodo 10.5281/zenodo.6403860 - Tarasova, L. (2022):
Processed data: flood generation processes and flood anomalies [Data set]
Zenodo 10.5281/zenodo.6403851 - Winter, C., Tarasova, L., Lutz, S.R., Musolff, A., Kumar, R., Fleckenstein, J.H. (2022):
Explaining the variability in high-frequency nitrate export patterns using long-term hydrological event classification
Water Resour. Res. 58 (1), e2021WR030938 10.1029/2021WR030938 - Yang, S., Büttner, O., Kumar, R., Basso, S., Borchardt, D. (2022):
An analytical framework for determining the ecological risks of wastewater discharges in river networks under climate change
Earth Future 10 (10), e2021EF002601 10.1029/2021EF002601
2021 (3)
- Basso, S., Botter, G., Merz, R., Miniussi, A. (2021):
PHEV! The PHysically-based Extreme Value distribution of river flows
Environ. Res. Lett. 16 (12), art. 124065 10.1088/1748-9326/ac3d59 - Basso, S., Ghazanchaei, Z., Tarasova, L. (2021):
Characterizing hydrograph recessions from satellite-derived soil moisture
Sci. Total Environ. 756 , art. 143469 10.1016/j.scitotenv.2020.143469 - Miniussi, A., Marra, F. (2021):
Estimation of extreme daily precipitation return levels at-site and in ungauged locations using the simplified MEV approach
J. Hydrol. 603, Part B , art. 126946 10.1016/j.jhydrol.2021.126946
2020 (8)
- Basso, S., Lazzaro, G., Bovo, M., Soulsby, C., Botter, G. (2020):
Water-energy-ecosystem nexus in small run-of-river hydropower: Optimal design and policy
Appl. Energy 280 , art. 115936 10.1016/j.apenergy.2020.115936 - Merz, R., Tarasova, L., Basso, S. (2020):
The flood cooking book: ingredients and regional flavors of floods across Germany
Environ. Res. Lett. 15 (11), art. 114024 10.1088/1748-9326/abb9dd - Merz, R., Tarasova, L., Basso, S. (2020):
Parameter's controls of distributed catchment models—How much information is in conventional catchment descriptors?
Water Resour. Res. 56 (2), e2019WR026008 10.1029/2019WR026008 - Miniussi, A., Marani, M. (2020):
Estimation of daily rainfall extremes through the Metastatistical Extreme Value Distribution: uncertainty minimization and implications for trend detection
Water Resour. Res. 56 (7), e2019WR026535 10.1029/2019WR026535 - Miniussi, A., Marani, M., Villarini, G. (2020):
Metastatistical Extreme Value Distribution applied to floods across the continental United States
Adv. Water Resour. 136 , art. 103498 10.1016/j.advwatres.2019.103498 - Miniussi, A., Villarini, G., Marani, M. (2020):
Analyses through the Metastatistical Extreme Value distribution identify contributions of Tropical Cyclones to rainfall extremes in the Eastern US
Geophys. Res. Lett. 47 (7), e2020GL087238 10.1029/2020GL087238 - Tarasova, L., Basso, S., Merz, R. (2020):
Transformation of generation processes from small runoff events to large floods
Geophys. Res. Lett. 47 (22), e2020GL090547 10.1029/2020GL090547 - Tarasova, L., Basso, S., Wendi, D., Viglione, A., Kumar, R., Merz, R. (2020):
A process‐based framework to characterize and classify runoff events – the event typology of Germany
Water Resour. Res. 56 (5), e2019WR026951 10.1029/2019WR026951
2019 (1)
- Tarasova, L., Merz, R., Kiss, A., Basso, S., Blöschl, G., Merz, B., Viglione, A., Plötner, S., Guse, B., Schumann, A., Fischer, S., Ahrens, B., Anwar, F., Bárdossy, A., Bühler, P., Haberlandt, U., Kreibich, H., Krug, A., Lun, D., Müller‐Thomy, H., Pidoto, R., Primo, C., Seidel, J., Vorogushyn, S., Wietzke, L. (2019):
Causative classification of river flood events
Wiley Interdiscip. Rev.-Water 6 (4), e1353 10.1002/wat2.1353
2018 (3)
- Müller, C., Musolff, A., Strachauer, U., Brauns, M., Tarasova, L., Merz, R., Knöller, K. (2018):
Tomography of anthropogenic nitrate contribution along a mesoscale river
Sci. Total Environ. 615 , 773 - 783 10.1016/j.scitotenv.2017.09.297 - Tarasova, L., Basso, S., Poncelet, C., Merz, R. (2018):
Exploring controls on rainfall‐runoff events: 2. Regional patterns and spatial controls of event characteristics in Germany
Water Resour. Res. 54 (10), 7688 - 7710 10.1029/2018WR022588 - Tarasova, L., Basso, S., Zink, M., Merz, R. (2018):
Exploring controls on rainfall‐runoff events: 1. Time series‐based event separation and temporal dynamics of event runoff response in Germany
Water Resour. Res. 54 (10), 7711 - 7732 10.1029/2018WR022587
2016 (1)
- Tarasova, L., Knoche, M., Dietrich, J., Merz, R. (2016):
Effects of input discretization, model complexity, and calibration strategy on model performance in a data-scarce glacierized catchment in Central Asia
Water Resour. Res. 52 (6), 4674 - 4699 10.1002/2015WR018551