Continuous hydrologic modelling for design simulation in small and ungauged basins: A step forward and some tests for its practical use

Abstract The design hydrograph estimation in small and ungauged basins represents one of the most common practices and, yet, a challenging open research topic for hydrologists. When discharge observations are not available, the practitioner is compelled to apply empirical approaches. The rational formula is slowly disappearing, while event-based approaches are more and more widespread. A step forward is represented by continuous models that have the potential to address the major drawbacks of event-based approaches. In this work we applied a continuous model specifically designed for ungauged basins (COSMO4SUB) and tested its use in conditions where typically the rational formula and the event-based approaches are applied. Results confirm that the continuous modelling is suitable for rapid and effective design simulations supporting flood hazard modelling and mapping studies.

[1]  Govindasamy Bala,et al.  Evaluation of a WRF dynamical downscaling simulation over California , 2008 .

[2]  Alaa El-Sadek Upscaling Field Scale Hydrology and Water Quality Modelling to Catchment Scale , 2003 .

[3]  Attilio Castellarin,et al.  Calibration of rainfall-runoff models in ungauged basins: A regional maximum likelihood approach , 2010 .

[4]  Christos Makropoulos,et al.  A rainfall disaggregation scheme for sub-hourly time scales: Coupling a Bartlett-Lewis based model with adjusting procedures , 2018 .

[5]  B. Merz,et al.  A continuous modelling approach for design flood estimation on sub-daily time scale , 2019, Hydrological Sciences Journal.

[6]  Andrea Petroselli,et al.  A continuous simulation model for design-hydrograph estimation in small and ungauged watersheds , 2012 .

[7]  J. Smithers,et al.  Review: Continuous simulation modelling for design flood estimation – a South African perspective and recommendations , 2018, Water SA.

[8]  Andrea Petroselli,et al.  Green‐Ampt Curve‐Number mixed procedure as an empirical tool for rainfall–runoff modelling in small and ungauged basins , 2013 .

[9]  B. Saghafian,et al.  Comparison of design peak flow estimation methods for ungauged basins in Iran , 2020, Hydrological Sciences Journal.

[10]  Andrea Petroselli,et al.  Design hydrograph estimation in small and ungauged watersheds: continuous simulation method versus event-based approach , 2012 .

[11]  U. Haberlandt,et al.  Short time step continuous rainfall modeling and simulation of extreme events , 2017 .

[12]  S. Yin,et al.  A frequency-domain nonstationary multi-site rainfall generator for use in hydrological impact assessment , 2020, Journal of Hydrology.

[13]  F. Nardi,et al.  Quantifying the relative impact of hydrological and hydraulic modelling parameterizations on uncertainty of inundation maps , 2020 .

[14]  U. Haberlandt,et al.  Hydrological model calibration for derived flood frequency analysis using stochastic rainfall and probability distributions of peak flows , 2014 .

[15]  F. Castelli,et al.  Investigating hydrogeomorphic floodplain mapping performance with varying DTM resolution and stream order , 2019, Hydrological Sciences Journal.

[16]  S. Sorooshian,et al.  A Review of Global Precipitation Data Sets: Data Sources, Estimation, and Intercomparisons , 2018 .

[17]  S. Grimaldi,et al.  A parsimonious geomorphological unit hydrograph for rainfall–runoff modelling in small ungauged basins , 2012 .

[18]  Y. Hundecha,et al.  Spatially coherent flood risk assessment based on long-term continuous simulation with a coupled model chain , 2015 .

[19]  Patrick Willems,et al.  Parsimonious rainfall-runoff model construction supported by time series processing and validation of hydrological extremes , 2010 .

[20]  Sérgio Freire,et al.  Unveiling 25 Years of Planetary Urbanization with Remote Sensing: Perspectives from the Global Human Settlement Layer , 2018, Remote. Sens..

[21]  Anne-Catherine Favre,et al.  Flood type specific construction of synthetic design hydrographs , 2017 .

[22]  D. Schertzer,et al.  Rain gauge networks’ limitations and the implications to hydrological modelling highlighted with a X-band radar , 2020 .

[23]  A. Petroselli,et al.  Flood mapping in small ungauged basins: a comparison of different approaches for two case studies in Slovakia , 2018, Hydrology Research.

[24]  S. Kanae,et al.  A high‐accuracy map of global terrain elevations , 2017 .

[25]  Vazken Andréassian,et al.  How crucial is it to account for the antecedent moisture conditions in flood forecasting? Comparison of event-based and continuous approaches on 178 catchments , 2009 .

[26]  B. L. McGlynn,et al.  A data acquisition framework for runoff prediction in ungauged basins , 2013 .

[27]  P. Claps,et al.  Global warming increases flood risk in mountainous areas , 2009 .

[28]  A. Petroselli,et al.  Design hydrograph estimation in small and fully ungauged basins: a preliminary assessment of the EBA4SUB framework , 2018 .

[29]  F. Nardi,et al.  GEV Parameter Estimation and Stationary vs. Non-Stationary Analysis of Extreme Rainfall in African Test Cities , 2018 .

[30]  Xuefeng Chu,et al.  Event and Continuous Hydrologic Modeling with HEC-HMS , 2009 .

[31]  F. Nardi,et al.  Hydrologic scaling for hydrogeomorphic floodplain mapping: Insights into human‐induced floodplain disconnectivity , 2018, River Research and Applications.

[32]  P. Willems,et al.  Trends and multidecadal oscillations in rainfall extremes, based on a more than 100‐year time series of 10 min rainfall intensities at Uccle, Belgium , 2008 .

[33]  Fernando Nardi,et al.  Information-theoretic portfolio decision model for optimal flood management , 2019, Environ. Model. Softw..

[34]  David C. Garen,et al.  CURVE NUMBER HYDROLOGY IN WATER QUALITY MODELING: USES, ABUSES, AND FUTURE DIRECTIONS 1 , 2005 .

[35]  J. Seibert,et al.  Effective precipitation duration for runoff peaks based on catchment modelling , 2018 .

[36]  Andrea Petroselli,et al.  Flood mapping in ungauged basins using fully continuous hydrologic–hydraulic modeling , 2013 .

[37]  Kevin Sene,et al.  Flash Floods: Forecasting and Warning , 2012 .

[38]  Andrea Petroselli,et al.  Curve‐Number/Green–Ampt mixed procedure for streamflow predictions in ungauged basins: Parameter sensitivity analysis , 2013 .

[39]  W. Boughton,et al.  Continuous simulation for design flood estimation--a review , 2003, Environ. Model. Softw..

[40]  Lindell Ormsbee,et al.  RAINFALL DISAGGREGATION MODEL FOR CONTINUOUS HYDROLOGIC MODELING , 1989 .

[41]  P. E. O'connell,et al.  IAHS Decade on Predictions in Ungauged Basins (PUB), 2003–2012: Shaping an exciting future for the hydrological sciences , 2003 .

[42]  Maurizio Mazzoleni,et al.  A systematic comparison of statistical and hydrological methods for design flood estimation , 2019, Hydrology Research.

[43]  Sarka D. Blazkova,et al.  Continuous simulation for computing design hydrographs for water structures , 2017 .

[44]  Demetris Koutsoyiannis,et al.  Multivariate rainfall disaggregation at a fine timescale , 2003 .

[45]  Günter Blöschl,et al.  On the role of storm duration in the mapping of rainfall to flood return periods , 2008 .

[46]  T. Maurer,et al.  Coupling Poisson rectangular pulse and multiplicative microcanonical random cascade models to generate sub-daily precipitation timeseries , 2018, Journal of Hydrology.

[47]  M. Borga,et al.  Characterisation of selected extreme flash floods in Europe and implications for flood risk management , 2010 .

[48]  Minha Choi,et al.  Let-It-Rain: a web application for stochastic point rainfall generation at ungaged basins and its applicability in runoff and flood modeling , 2017, Stochastic Environmental Research and Risk Assessment.

[49]  N. Verhoest,et al.  A coupled stochastic rainfall–evapotranspiration model for hydrological impact analysis , 2017 .

[50]  Francesco Serinaldi,et al.  Synthetic Design Hydrographs Based on Distribution Functions with Finite Support , 2011 .

[51]  S. Grimaldi,et al.  Design discharge estimation in small and ungauged basins: EBA4SUB framework sensitivity analysis , 2020, Journal of Agricultural Engineering.

[52]  M. Hipsey,et al.  “Panta Rhei—Everything Flows”: Change in hydrology and society—The IAHS Scientific Decade 2013–2022 , 2013 .

[53]  José I. Barredo,et al.  Major flood disasters in Europe: 1950–2005 , 2007 .

[54]  Günter Blöschl,et al.  Runoff models and flood frequency statistics for design flood estimation in Austria – Do they tell a consistent story? , 2012 .

[55]  D. P. Guertin,et al.  A daily spatially explicit stochastic rainfall generator for a semi-arid climate , 2019, Journal of Hydrology.

[56]  Alexis Berne,et al.  Temporal and spatial resolution of rainfall measurements required for urban hydrology , 2004 .

[57]  Arthur C. Miller,et al.  ACCURACY AND PRECISION OF NRCS MODELS FOR SMALL WATERSHEDS 1 , 2001 .

[58]  Rob Lamb,et al.  Have applications of continuous rainfall–runoff simulation realized the vision for process-based flood frequency analysis? , 2016 .

[59]  A. Rinaldo,et al.  Fractal River Basins: Chance and Self-Organization , 1997 .

[60]  U. Haberlandt,et al.  Temporal rainfall disaggregation using a multiplicative cascade model for spatial application in urban hydrology , 2018 .

[61]  Keith Beven,et al.  Flood frequency estimation by continuous simulation for a catchment treated as ungauged (with uncertainty) , 2002 .

[62]  J. McDonnell,et al.  A decade of Predictions in Ungauged Basins (PUB)—a review , 2013 .

[63]  Luca Brocca,et al.  Design soil moisture estimation by comparing continuous and storm‐based rainfall‐runoff modeling , 2011 .

[64]  K. Breinl Driving a lumped hydrological model with precipitation output from weather generators of different complexity , 2016 .

[65]  V. Babovic,et al.  Three resampling approaches based on method of fragments for daily‐to‐subdaily precipitation disaggregation , 2018 .

[66]  Balaji Rajagopalan,et al.  BayGEN: A Bayesian Space‐Time Stochastic Weather Generator , 2019, Water Resources Research.

[67]  Simon Michael Papalexiou,et al.  Unified theory for stochastic modelling of hydroclimatic processes: Preserving marginal distributions, correlation structures, and intermittency , 2018 .

[68]  Sina Khatami,et al.  Improving Continuous Hydrologic Modeling of Data-Poor River Basins Using Hydrologic Engineering Center’s Hydrologic Modeling System: Case Study of Karkheh River Basin , 2017 .