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  • 1. Anastasiadis, Stavros
    et al.
    Boglis, Argiris
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Lekkas, Demetris F.
    Baltas, Evaggelos
    APPLICATION OF GIS BASED CLARK'S UNIT HYDROGRAPH AND TRANSFER FUNCTION MODEL TO DESCRIBE RUNOFF RESPONSE IN A SMALL CATCHMENT, CASE STUDY: LYKOREMMA RIVER, GREECE2013In: Fresenius Environmental Bulletin, ISSN 1018-4619, E-ISSN 1610-2304, Vol. 22, no 7B, p. 2152-2158Article in journal (Refereed)
    Abstract [en]

    The hydrologic community has recently focused substantial attention on ungauged or poorly gauged catchments, since hydrological prediction under these conditions is highly uncertain, but represents the majority of practical applications. Catchments in Greece are usually ungauged, due to resource constrains, whilst in gauged areas the period of record is often short for safe estimation of highly parameterised hydrological models. This paper is driven by the Prediction in Ungauged Basins initiative aiming to estimate catchment responses using readily available data, i.e. topographical, soil and land use information. The parsimonious rainfall-runoff model developed in a Geographical Information System (GIS) environment is based on the Clark's synthetic unit hydrograph technique to estimate the hydrological response. The method requires estimation of the time of concentration (based on the curve number), the storage attenuation coefficient and the time area histogram of the catchment. The models further compared with a data-based modelling approach using a Transfer Function and the simulated streamflow is analysed to investigate similarities as well as to better understand possible extensions of the resulting unit hydrograph. A case study using 10-minute observed data from the 15 km(2) Lykorema catchment, Attica, Greece, highlights the potential of the GIS-based model to predict, at least, the dynamic characteristics of the runoff response in ungauged or poorly gauged catchments.

  • 2.
    Andersson, Jafet
    et al.
    SMHI, Research Department, Hydrology.
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Gustafsson, David
    SMHI, Research Department, Hydrology.
    Donnelly, Chantal
    SMHI, Research Department, Hydrology.
    Arheimer, Berit
    SMHI, Research Department, Hydrology.
    Key factors for improving large-scale hydrological model performance2015In: European Water, ISSN 1792-085X, Vol. 49, p. 77-88Article in journal (Refereed)
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  • 3.
    Cantone, Carolina
    et al.
    SMHI, Samhällsberedskap.
    Ivars Grape, Helen
    SMHI, Samhällsberedskap.
    El Habash, Shadi
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    A co-generation success story: Improving drinking water management through hydro-climate services2023In: Climate Services, E-ISSN 2405-8807, Vol. 31, article id 100399Article in journal (Refereed)
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    A co-generation success story: Improving drinking water management through hydro-climate services
  • 4. Contreras, Eva
    et al.
    Herrero, Javier
    Crochemore, Louise
    SMHI, Research Department, Hydrology.
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Photiadou, Christiana
    SMHI, Research Department, Hydrology.
    Aguilar, Cristina
    Jose Polo, Maria
    Advances in the Definition of Needs and Specifications for a Climate Service Tool Aimed at Small Hydropower Plants' Operation and Management2020In: Energies, E-ISSN 1996-1073, Vol. 13, no 7, article id 1827Article in journal (Refereed)
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  • 5.
    Crochemore, Louise
    et al.
    SMHI, Research Department, Hydrology.
    Cantone, Carolina
    SMHI, Professional Services.
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Photiadou, Christiana
    SMHI, Research Department, Hydrology.
    How Does Seasonal Forecast Performance Influence Decision-Making?: Insights from a Serious Game2021In: Bulletin of The American Meteorological Society - (BAMS), ISSN 0003-0007, E-ISSN 1520-0477, Vol. 102, no 9, p. E1682-E1699Article in journal (Refereed)
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    How Does Seasonal Forecast Performance Influence Decision-Making?
  • 6.
    Crochemore, Louise
    et al.
    SMHI, Research Department, Hydrology.
    Ramos, M. -H
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Can Continental Models Convey Useful Seasonal Hydrologic Information at the Catchment Scale?2020In: Water resources research, ISSN 0043-1397, E-ISSN 1944-7973, Vol. 56, no 2, article id e2019WR025700Article in journal (Refereed)
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  • 7. Dasgupta, Antara
    et al.
    Arnal, Louise
    Emerton, Rebecca
    Harrigan, Shaun
    Matthews, Gwyneth
    Muhammad, Ameer
    O'Regan, Karen
    Perez-Ciria, Teresa
    Valdez, Emixi
    van Osnabrugge, Bart
    Werner, Micha
    Buontempo, Carlo
    Cloke, Hannah
    Pappenberger, Florian
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Prudhomme, Christel
    Ramos, Maria-Helena
    Salamon, Peter
    Connecting hydrological modelling and forecasting from global to local scales: Perspectives from an international joint virtual workshop2023In: Journal of Flood Risk Management, E-ISSN 1753-318XArticle in journal (Refereed)
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    Connecting hydrological modelling and forecasting from global to local scales: Perspectives from an international joint virtual workshop
  • 8. Du, Tien L. T.
    et al.
    Lee, Hyongki
    Bui, Duong D.
    Graham, Phil
    SMHI, Professional Services.
    Darby, Stephen D.
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Leyland, Julian
    Biswas, Nishan K.
    Choi, Gyewoon
    Batelaan, Okke
    Bui, Thao T. P.
    Do, Son K.
    Tran, Tinh, V
    Nguyen, Hoa Thi
    Hwang, Euiho
    Streamflow Prediction in Highly Regulated, Transboundary Watersheds Using Multi-Basin Modeling and Remote Sensing Imagery2022In: Water resources research, ISSN 0043-1397, E-ISSN 1944-7973, Vol. 58, no 3, article id e2021WR031191Article in journal (Refereed)
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    Streamflow Prediction in Highly Regulated, Transboundary Watersheds Using Multi-Basin Modeling and Remote Sensing Imagery
  • 9.
    Girons, Marc
    et al.
    SMHI, Core Services.
    Crochemore, Louise
    SMHI, Research Department, Hydrology.
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Benchmarking an operational hydrological model for providing seasonal forecasts in Sweden2021In: Hydrology and Earth System Sciences, ISSN 1027-5606, E-ISSN 1607-7938, Vol. 25, no 3, p. 1189-1209Article in journal (Refereed)
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    Benchmarking an operational hydrological model for providing seasonal forecasts in Sweden
  • 10. Giuliani, Matteo
    et al.
    Crochemore, Louise
    SMHI, Research Department, Hydrology.
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Castelletti, Andrea
    From skill to value: isolating the influence of end user behavior on seasonal forecast assessment2020In: Hydrology and Earth System Sciences, ISSN 1027-5606, E-ISSN 1607-7938, Vol. 24, no 12, p. 5891-5902Article in journal (Refereed)
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  • 11.
    Hundecha, Yeshewatesfa
    et al.
    SMHI, Research Department, Hydrology.
    Arheimer, Berit
    SMHI, Research Department, Hydrology.
    Berg, Peter
    SMHI, Research Department, Hydrology.
    Capell, Réne
    SMHI, Research Department, Hydrology.
    Musuuza, Jude
    SMHI, Research Department, Hydrology.
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Photiadou, Christiana
    SMHI, Research Department, Hydrology.
    Effect of model calibration strategy on climate projections of hydrological indicators at a continental scale2020In: Climatic Change, ISSN 0165-0009, E-ISSN 1573-1480Article in journal (Refereed)
    Abstract [en]

    The effect of model calibration on the projection of climate change impact on hydrological indicators was assessed by employing variants of a pan-European hydrological model driven by forcing data from an ensemble of climate models. The hydrological model was calibrated using three approaches: calibration at the outlets of major river basins, regionalization through calibration of smaller scale catchments with unique catchment characteristics, and building a model ensemble by sampling model parameters from the regionalized model. The large-scale patterns of the change signals projected by all model variants were found to be similar for the different indicators. Catchment scale differences were observed between the projections of the model calibrated for the major river basins and the other two model variants. The distributions of the median change signals projected by the ensemble model were found to be similar to the distributions of the change signals projected by the regionalized model for all hydrological indicators. The study highlights that the spatial detail to which model calibration is performed can highly influence the catchment scale detail in the projection of climate change impact on hydrological indicators, with an absolute difference in the projections of the locally calibrated model and the model calibrated for the major river basins ranging between 0 and 55% for mean annual discharge, while it has little effect on the large-scale pattern of the projection.

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  • 12.
    Hundecha, Yeshewatesfa
    et al.
    SMHI, Research Department, Hydrology.
    Arheimer, Berit
    SMHI, Research Department, Hydrology.
    Donnelly, Chantal
    SMHI, Research Department, Hydrology.
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    A regional parameter estimation scheme for a pan-European multi-basin model.2016In: Journal of Hydrology, ISSN 0022-1694, E-ISSN 1879-2707, Vol. 6, p. 90-111Article in journal (Refereed)
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  • 13. Kiesel, Jens
    et al.
    Stanzel, Philipp
    Kling, Harald
    Fohrer, Nicola
    Jaehnig, Sonja C.
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Streamflow-based evaluation of climate model sub-selection methods2020In: Climatic Change, ISSN 0165-0009, E-ISSN 1573-1480Article in journal (Refereed)
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  • 14. Kiesel, Jens
    et al.
    Stanzel, Philipp
    Kling, Harald
    Fohrer, Nicola
    Jahnig, Sonja C.
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Streamflow-based evaluation of climate model sub-selection methods (vol 163, pg 1267, 2020)2021In: Climatic Change, ISSN 0165-0009, E-ISSN 1573-1480, Vol. 169, no 3-4, article id 25Article in journal (Refereed)
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    Correction to: Streamflow-based evaluation of climate model sub-selection methods
  • 15.
    Klehmet, Katharina
    et al.
    SMHI, Research Department, Hydrology.
    Berg, Peter
    SMHI, Research Department, Hydrology.
    Bozhinova, Denica
    SMHI, Research Department, Hydrology.
    Crochemore, Louise
    Yiheng, Du
    SMHI, Research Department, Hydrology.
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Photiadou, Christiana
    Yang, Wei
    SMHI, Research Department, Hydrology.
    Robustness of hydrometeorological extremes in surrogated seasonal forecasts2024In: International Journal of Climatology, ISSN 0899-8418, E-ISSN 1097-0088Article in journal (Refereed)
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    Robustness of hydrometeorological extremes in surrogated seasonal forecasts
  • 16. Krysanova, Valentina
    et al.
    Vetter, Tobias
    Eisner, Stephanie
    Huang, Shaochun
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Strauch, Michael
    Gelfan, Alexander
    Kumar, Rohini
    Aich, Valentin
    Arheimer, Berit
    SMHI, Research Department, Hydrology.
    Chamorro, Alejandro
    van Griensven, Ann
    Kundu, Dipangkar
    Lobanova, Anastasia
    Mishra, Vimal
    Plotner, Stefan
    Reinhardt, Julia
    Seidou, Ousmane
    Wang, Xiaoyan
    Wortmann, Michel
    Zeng, Xiaofan
    Hattermann, Fred F.
    Intercomparison of regional-scale hydrological models and climate change impacts projected for 12 large river basins worldwide-a synthesis2017In: Environmental Research Letters, E-ISSN 1748-9326, Vol. 12, no 10, article id 105002Article in journal (Refereed)
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  • 17. Lavers, David A.
    et al.
    Ramos, Maria-Helena
    Magnusson, Linus
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Klein, Bastian
    Prudhomme, Christel
    Arnal, Louise
    Crochemore, Louise
    SMHI, Research Department, Hydrology.
    Van Den Hurk, Bart
    Weerts, Albrecht H.
    Harrigan, Shaun
    Cloke, Hannah L.
    Richardson, David S.
    Pappenberger, Florian
    A Vision for Hydrological Prediction2020In: Atmosphere, E-ISSN 2073-4433, Vol. 11, no 3, article id 237Article in journal (Refereed)
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  • 18. Macian-Sorribes, Hector
    et al.
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Crochemore, Louise
    SMHI, Research Department, Hydrology.
    Pulido-Velazquez, Manuel
    Fuzzy Postprocessing to Advance the Quality of Continental Seasonal Hydrological Forecasts for River Basin Management2020In: Journal of Hydrometeorology, ISSN 1525-755X, E-ISSN 1525-7541, Vol. 21, no 10, p. 2375-2389Article in journal (Refereed)
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  • 19.
    Musuuza, Jude
    et al.
    SMHI, Research Department, Hydrology.
    Crochemore, Louise
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Evaluation of Earth Observations and In Situ Data Assimilation for Seasonal Hydrological Forecasting2023In: Water resources research, ISSN 0043-1397, E-ISSN 1944-7973, Vol. 59, no 4, article id e2022WR033655Article in journal (Refereed)
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    Evaluation of Earth Observations and In Situ Data Assimilation for Seasonal Hydrological Forecasting
  • 20.
    Musuuza, Jude
    et al.
    SMHI, Research Department, Hydrology.
    Gustafsson, David
    SMHI, Research Department, Hydrology.
    Pimentel, Rafael
    Crochemore, Louise
    SMHI, Research Department, Hydrology.
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Impact of Satellite and In Situ Data Assimilation on Hydrological Predictions2020In: Remote Sensing, E-ISSN 2072-4292, Vol. 12, no 5, article id 811Article in journal (Refereed)
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  • 21. Nijzink, R.C.
    et al.
    Almeida, S.
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Capell, Réne
    SMHI, Research Department, Hydrology.
    Gustafsson, David
    SMHI, Research Department, Hydrology.
    Arheimer, Berit
    SMHI, Research Department, Hydrology.
    Parajka, J.
    Freer, J.
    Han, D.
    Wagener, T.
    van Nooijen, R.R.P.
    Savenije, H.H.G.
    Hrachowitz, M.
    Constraining Conceptual Hydrological ModelsWith Multiple Information Sources2018In: Water resources research, ISSN 0043-1397, E-ISSN 1944-7973, Vol. 54, no 10, p. 8332-8362Article in journal (Refereed)
    Abstract [en]

    The calibration of hydrological models without streamflow observations is problematic, and the simultaneous, combined use of remotely sensed products for this purpose has not been exhaustively tested thus far. Our hypothesis is that the combined use of products can (1) reduce the parameter search space and (2) improve the representation of internal model dynamics and hydrological signatures. Five different conceptual hydrological models were applied to 27 catchments across Europe. A parameter selection process, similar to a likelihood weighting procedure, was applied for 1,023 possible combinations of 10 different data sources, ranging from using 1 to all 10 of these products. Distances between the two empirical distributions of model performance metrics with and without using a specific product were determined to assess the added value of a specific product. In a similar way, the performance of the models to reproduce 27 hydrological signatures was evaluated relative to the unconstrained model. Significant reductions in the parameter space were obtained when combinations included Advanced Microwave Scanning Radiometer ‐ Earth Observing System and Advanced Scatterometer soil moisture, Gravity Recovery and Climate Experiment total water storage anomalies, and, in snow‐dominated catchments, the Moderate Resolution Imaging Spectroradiometer snow cover products. The evaporation products of Land Surface Analysis ‐ Satellite Application Facility and MOD16 were less effective for deriving meaningful, well‐constrained posterior parameter distributions. The hydrological signature analysis indicated that most models profited from constraining with an increasing number of data sources. Concluding, constraining models with multiple data sources simultaneously was shown to be valuable for at least four of the five hydrological models to determine model parameters in absence of streamflow.

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  • 22. Nijzink, Remko
    et al.
    Hutton, Christopher
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Capell, Réne
    SMHI, Research Department, Hydrology.
    Arheimer, Berit
    SMHI, Research Department, Hydrology.
    Freer, Jim
    Han, Dawei
    Wagener, Thorsten
    McGuire, Kevin
    Savenije, Hubert
    Hrachowitz, Markus
    The evolution of root-zone moisture capacities after deforestation: a step towards hydrological predictions under change?2016In: Hydrology and Earth System Sciences, ISSN 1027-5606, E-ISSN 1607-7938, Vol. 20, no 12, p. 4775-4799Article in journal (Refereed)
    Abstract [en]

    The core component of many hydrological systems, the moisture storage capacity available to vegetation, is impossible to observe directly at the catchment scale and is typically treated as a calibration parameter or obtained from a priori available soil characteristics combined with estimates of rooting depth. Often this parameter is considered to remain constant in time. Using long-term data (30–40 years) from three experimental catchments that underwent significant land cover change, we tested the hypotheses that: (1) the root-zone storage capacity significantly changes after deforestation, (2) changes in the root-zone storage capacity can to a large extent explain post-treatment changes to the hydrological regimes and that (3) a time-dynamic formulation of the root-zone storage can improve the performance of a hydrological model.A recently introduced method to estimate catchment-scale root-zone storage capacities based on climate data (i.e. observed rainfall and an estimate of transpiration) was used to reproduce the temporal evolution of root-zone storage capacity under change. Briefly, the maximum deficit that arises from the difference between cumulative daily precipitation and transpiration can be considered as a proxy for root-zone storage capacity. This value was compared to the value obtained from four different conceptual hydrological models that were calibrated for consecutive 2-year windows.It was found that water-balance-derived root-zone storage capacities were similar to the values obtained from calibration of the hydrological models. A sharp decline in root-zone storage capacity was observed after deforestation, followed by a gradual recovery, for two of the three catchments. Trend analysis suggested hydrological recovery periods between 5 and 13 years after deforestation. In a proof-of-concept analysis, one of the hydrological models was adapted to allow dynamically changing root-zone storage capacities, following the observed changes due to deforestation. Although the overall performance of the modified model did not considerably change, in 51 % of all the evaluated hydrological signatures, considering all three catchments, improvements were observed when adding a time-variant representation of the root-zone storage to the model.In summary, it is shown that root-zone moisture storage capacities can be highly affected by deforestation and climatic influences and that a simple method exclusively based on climate data can not only provide robust, catchment-scale estimates of this critical parameter, but also reflect its time-dynamic behaviour after deforestation.

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  • 23.
    Olsson, Jonas
    et al.
    SMHI, Research Department, Hydrology.
    Pers, Charlotta
    SMHI, Research Department, Hydrology.
    Bengtsson, Lisa
    SMHI, Research Department, Meteorology.
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Berg, Peter
    Körnich, Heiner
    SMHI, Research Department, Meteorology.
    Distance-dependent depth-duration analysis in high-resolution hydro-meteorological ensemble forecasting: A case study in Malmo City, Sweden2017In: Environmental Modelling & Software, ISSN 1364-8152, E-ISSN 1873-6726, Vol. 93, p. 381-397Article in journal (Refereed)
  • 24. Papacharalampous, Georgia
    et al.
    Tyralis, Hristos
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Grimaldi, Salvatore
    Volpi, Elena
    Massive feature extraction for explaining and foretelling hydroclimatic time series forecastability at the global scale2022In: Geoscience Frontiers, ISSN 1674-9871, Vol. 13, no 3, article id 101349Article in journal (Refereed)
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    Massive feature extraction for explaining and foretelling hydroclimatic time series forecastability at the global scale
  • 25. Pechlivanidis, G. I.
    et al.
    Keramaris, E.
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Samaras, G. A.
    Shear stress estimation in the linear zone over impermeable and permeable beds in open channels2015In: Desalination and Water Treatment, ISSN 1944-3994, E-ISSN 1944-3986, Vol. 54, no 8, p. 2181-2189Article in journal (Refereed)
    Abstract [en]

    This paper investigates the shear stresses in the linear zone of open channel flows with permeable and impermeable bed. The permeable bed is simulated using a flexible vegetation of 2 cm thickness. Laboratory experiments were used for the calculation of the turbulent velocity profiles. The measurements were obtained using a two-dimensional (2D) particle image velocimetry (PIV). This optical method of fluid visualization is used to obtain instantaneous velocity measurements related properties in the fluids. The PIV method assumes that the particles of a fluid faithfully follow the flow dynamics; hence the motion of these seeding particles is used to calculate the dynamic characteristics of the flow. The measurements were conducted at a 12 x 10 cm(2) region located 4 m away from the channel's entrance, where the flow is considered fully developed. The uniformity of the flow was checked measuring the flow depth at two cross-sections (2 m distance between the two regions). The total discharge was estimated using a calibrated venture apparatus. Measurements of velocity were taken for the horizontal channel slope. Results showed that the type of bed can significantly influence the shear stress definition in the linear zone.

  • 26.
    Pechlivanidis, Ilias
    et al.
    SMHI, Research Department, Hydrology.
    Arheimer, Berit
    SMHI, Research Department, Hydrology.
    Large-scale hydrological modelling by using modified PUB recommendations: the India-HYPE case2015In: Hydrology and Earth System Sciences, ISSN 1027-5606, E-ISSN 1607-7938, Vol. 19, no 11, p. 4559-4579Article in journal (Refereed)
    Abstract [en]

    The scientific initiative Prediction in Ungauged Basins (PUB) (2003-2012 by the IAHS) put considerable effort into improving the reliability of hydrological models to predict flow response in ungauged rivers. PUB's collective experience advanced hydrologic science and defined guidelines to make predictions in catchments without observed runoff data. At present, there is a raised interest in applying catchment models to large domains and large data samples in a multi-basin manner, to explore emerging spatial patterns or learn from comparative hydrology. However, such modelling involves additional sources of uncertainties caused by the inconsistency between input data sets, i.e. particularly regional and global databases. This may lead to inaccurate model parameterisation and erroneous process understanding. In order to bridge the gap between the best practices for flow predictions in single catchments and multi-basins at the large scale, we present a further developed and slightly modified version of the recommended best practices for PUB by Takeuchi et al. (2013). By using examples from a recent HYPE (Hydrological Predictions for the Environment) hydrological model set-up across 6000 subbasins for the Indian subcontinent, named India-HYPE v1.0, we explore the PUB recommendations, identify challenges and recommend ways to overcome them. We describe the work process related to (a) errors and inconsistencies in global databases, unknown human impacts, and poor data quality; (b) robust approaches to identify model parameters using a stepwise calibration approach, remote sensing data, expert knowledge, and catchment similarities; and (c) evaluation based on flow signatures and performance metrics, using both multiple criteria and multiple variables, and independent gauges for "blind tests". The results show that despite the strong physiographical gradient over the subcontinent, a single model can describe the spatial variability in dominant hydrological processes at the catchment scale. In addition, spatial model deficiencies are used to identify potential improvements of the model concept. Eventually, through simultaneous calibration using numerous gauges, the median Kling-Gupta efficiency for river flow increased from 0.14 to 0.64. We finally demonstrate the potential of multi-basin modelling for comparative hydrology using PUB, by grouping the 6000 subbasins based on similarities in flow signatures to gain insights into the spatial patterns of flow generating processes at the large scale.

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  • 27.
    Pechlivanidis, Ilias
    et al.
    SMHI, Research Department, Hydrology.
    Arheimer, Berit
    SMHI, Research Department, Hydrology.
    Donnelly, Chantal
    SMHI, Research Department, Hydrology.
    Hundecha, Yeshewatesfa
    SMHI, Research Department, Hydrology.
    Huang, S.
    Aich, V.
    Samaniego, L.
    Eisner, S.
    Shi, P.
    Analysis of hydrological extremes at different hydro-climatic regimes under present and future conditions2017In: Climatic Change, ISSN 0165-0009, E-ISSN 1573-1480, Vol. 141, no 3, p. 467-481Article in journal (Refereed)
  • 28.
    Pechlivanidis, Ilias
    et al.
    SMHI, Research Department, Hydrology.
    Arheimer, Berit
    SMHI, Research Department, Hydrology.
    Donnelly, Chantal
    SMHI, Research Department, Hydrology.
    Hundecha, Yeshewatesfa
    SMHI, Research Department, Hydrology.
    Huang, S.
    Aich, V.
    Samaniego, L.
    Eisner, S.
    Shi, P.
    Analysis of hydrological extremes at different hydro-climatic regimes under present and future conditions.2016In: Climatic Change, ISSN 0165-0009, E-ISSN 1573-1480Article in journal (Refereed)
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    fulltext
  • 29.
    Pechlivanidis, Ilias
    et al.
    SMHI, Research Department, Hydrology.
    Crochemore, Louise
    SMHI, Research Department, Hydrology.
    Rosberg, Jörgen
    SMHI, Research Department, Hydrology.
    Bosshard, Thomas
    SMHI, Research Department, Hydrology.
    What Are the Key Drivers Controlling the Quality of Seasonal Streamflow Forecasts?2020In: Water resources research, ISSN 0043-1397, E-ISSN 1944-7973, Vol. 56, no 6, article id e2019WR026987Article in journal (Refereed)
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    What are the key Drivers Controlling the Quality of Seasonal Streamflow Forecasts
  • 30.
    Pechlivanidis, Ilias
    et al.
    SMHI, Research Department, Hydrology.
    Gupta, H.
    Bosshard, Thomas
    SMHI, Research Department, Hydrology.
    An Information Theory Approach to Identifying a Representative Subset of Hydro-Climatic Simulations for Impact Modeling Studies2018In: Water resources research, ISSN 0043-1397, E-ISSN 1944-7973, Vol. 54, no 8, p. 5422-5435Article in journal (Refereed)
  • 31.
    Pechlivanidis, Ilias
    et al.
    SMHI, Research Department, Hydrology.
    Jackson, B.
    McMillan, H.
    Gupta, H.
    Use of an entropy-based metric in multiobjective calibration to improve model performance2014In: Water resources research, ISSN 0043-1397, E-ISSN 1944-7973, Vol. 50, no 10, p. 8066-8083Article in journal (Refereed)
    Abstract [en]

    Parameter estimation for hydrological models is complicated for many reasons, one of which is the arbitrary emphasis placed, by most traditional measures of fit, on various magnitudes of the model residuals. Recent research has called for the development of robust diagnostic measures that provide insights into which model structural components and/or data may be inadequate. In this regard, the flow duration curve (FDC) represents the historical variability of flow and is considered to be an informative signature of catchment behavior. Here we investigate the potential of using the recently developed conditioned entropy difference metric (CED) in combination with the Kling-Gupta efficiency (KGE). The CED respects the static information contained in the flow frequency distribution (and hence the FDC), but does not explicitly characterize temporal dynamics. The KGE reweights the importance of various hydrograph components (correlation, bias, variability) in a way that has been demonstrated to provide better model calibrations than the commonly used Nash-Sutcliffe efficiency, while being explicitly time sensitive. We employ both measures within a multiobjective calibration framework and achieve better performance over the full range of flows than obtained by single-criteria approaches, or by the common multiobjective approach that uses log-transformed and untransformed data to balance fitting of low and high flow periods. The investigation highlights the potential of CED to complement KGE (and vice versa) during model identification. It is possible that some of the complementarity is due to CED representing more information from moments >2 than KGE or other common metrics. We therefore suggest that an interesting way forward would be to extend KGE to include higher moments, i.e., use different moments as multiple criteria. Key Points <list id="wrcr21161-list-0001" list-type="bulleted"> <list-item id="wrcr21161-li-0001">CED provides an appropriate quantitative measure of fit to the FDC <list-item id="wrcr21161-li-0002">Complements between CED and KGE extracted flow information <list-item id="wrcr21161-li-0003">CED-KGE achieves better performance than single or common multiobjectives <doi origin="wiley" registered="yes">10.1002/(ISSN)1944-7973</doi

  • 32.
    Pechlivanidis, Ilias
    et al.
    SMHI, Research Department, Hydrology.
    Jackson, Bethanna
    Mcmillan, Hilary
    Gupta, Hoshin V.
    Robust informational entropy-based descriptors of flow in catchment hydrology2016In: Hydrological Sciences Journal, ISSN 0262-6667, E-ISSN 2150-3435, Vol. 61, no 1, p. 1-18Article in journal (Refereed)
    Abstract [en]

    This paper explores the use of entropy-based measures in catchment hydrology, and provides an importance-weighted numerical descriptor of the flow-duration curve. Although entropy theory is being applied in a wide spectrum of areas (including environmental and water resources), artefacts arising from the discrete, under-sampled and uncertain nature of hydrological data are rarely acknowledged, and have not been adequately explored. Here, we examine challenges to extracting hydrologically meaningful entropy measures from a flow signal; the effect of binning resolution on calculation of entropy is investigated, along with artefacts caused by (1) emphasis of information theoretic measures towards flow ranges having more data (statistically dominant information), and (2) effects of discharge measurement truncation errors. We introduce an importance-weighted entropy-based measure to counter the tendency of common binning approaches to over-emphasise information contained in the low flows which dominate the record. The measure uses a novel binning method, and overcomes artefacts due to data resolution and under-sampling. Our analysis reveals a fundamental problem with the extraction of information at high flows, due to the lack of statistically significant samples in this range. By separating the flow-duration curve into segments, our approach constrains the computed entropy to better respect distributional properties over the data range. When used as an objective function for model calibration, this approach constrains high flow predictions, as well as the commonly used Nash-Sutcliffe efficiency, but provides much better predictions of low flow behaviour.

  • 33.
    Pechlivanidis, Ilias
    et al.
    SMHI, Research Department, Hydrology.
    McIntyre, N.
    Wheater, H. S.
    The significance of spatial variability of rainfall on simulated runoff: an evaluation based on the Upper Lee catchment, UK2017In: Hydrology Research, ISSN 1998-9563, E-ISSN 2224-7955, Vol. 48, no 4, p. 1118-1130Article in journal (Refereed)
  • 34.
    Pechlivanidis, Ilias
    et al.
    SMHI, Research Department, Hydrology.
    Olsson, Jonas
    SMHI, Research Department, Hydrology.
    Sharma, D.
    Bosshard, Thomas
    SMHI, Research Department, Hydrology.
    Sharma, K. C.
    ASSESSMENT OF THE CLIMATE CHANGE IMPACTS ON THE WATER RESOURCES OF THE LUNI REGION, INDIA2015In: GLOBAL NEST JOURNAL, ISSN 1790-7632, Vol. 17, no 1, p. 29-40Article in journal (Refereed)
    Abstract [en]

    Climate change is expected to have a strong impact on water resources at the local, regional and global scales. In this study, the impact of climate change on the hydro-climatology of the Luni region, India, is investigated by comparing statistics of current and projected future fluxes resulting from three representative concentration pathways (RCP2.6, RCP4.5, and RCP8.5). The use of different scenarios allows for the estimation of uncertainty of future impacts. The projections are based on the CORDEX-South Asia framework and are bias-corrected using the DBS method before being entered into the HYPE (HYdrological Predictions for the Environment) hydrological model to generate predictions of runoff, evapotranspiration, soil moisture deficit, and applied irrigation water to soil. Overall, the high uncertainty in the climate projections is propagated in the impact model, and as a result the spatiotemporal distribution of change is subject to the climate change scenario. In general, for all scenarios, results show a -20 to +20% change in the long-term average precipitation and evapotranspiration, whereas more pronounced impacts are expected for runoff (-40 to +40% change). Climate change can also affect other hydro-climatic components, however, at a lower impact. Finally, the flow dynamics in the Luni River are substantially affected in terms of shape and magnitude.

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    fulltext
  • 35.
    Pimentel, Rafael
    et al.
    SMHI, Research Department, Hydrology.
    Arheimer, Berit
    SMHI, Research Department, Hydrology.
    Crochemore, Louise
    SMHI, Research Department, Hydrology.
    Andersson, Jafet
    SMHI, Research Department, Hydrology.
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Gustafsson, David
    SMHI, Research Department, Hydrology.
    Which Potential Evapotranspiration Formula to Use in Hydrological Modeling World-Wide?2023In: Water resources research, ISSN 0043-1397, E-ISSN 1944-7973, Vol. 59, no 5, article id e2022WR033447Article in journal (Refereed)
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    Which Potential Evapotranspiration Formula to Use in Hydrological Modeling World-Wide
  • 36. Samaniego, L.
    et al.
    Kumar, R.
    Breuer, L.
    Chamorro, A.
    Floerke, M.
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Schaefer, D.
    Shah, H.
    Vetter, T.
    Wortmann, M.
    Zeng, X.
    Propagation of forcing and model uncertainties on to hydrological drought characteristics in a multi-model century-long experiment in large river basins2017In: Climatic Change, ISSN 0165-0009, E-ISSN 1573-1480, Vol. 141, no 3, p. 435-449Article in journal (Refereed)
  • 37. Sebok, Eva
    et al.
    Henriksen, Hans Jorgen
    Pasten-Zapata, Ernesto
    Berg, Peter
    SMHI, Research Department, Hydrology.
    Thirel, Guillaume
    Lemoine, Anthony
    Lira-Loarca, Andrea
    Photiadou, Christiana
    SMHI, Research Department, Hydrology.
    Pimentel, Rafael
    Royer-Gaspard, Paul
    Kjellström, Erik
    SMHI, Research Department, Climate research - Rossby Centre.
    Christensen, Jens Hesselbjerg
    Vidal, Jean Philippe
    Lucas-Picher, Philippe
    Donat, Markus G.
    Besio, Giovanni
    Jose Polo, Maria
    Stisen, Simon
    Caballero, Yvan
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Troldborg, Lars
    Refsgaard, Jens Christian
    Use of expert elicitation to assign weights to climate and hydrological models in climate impact studies2022In: Hydrology and Earth System Sciences, ISSN 1027-5606, E-ISSN 1607-7938, Vol. 26, no 21, p. 5605-5625Article in journal (Refereed)
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    Use of expert elicitation to assign weights to climate and hydrological models in climate impact studies
  • 38. Shyrokaya, Anastasiya
    et al.
    Messori, Gabriele
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Pappenberger, Florian
    Cloke, Hannah L.
    Di Baldassarre, Giuliano
    Significant relationships between drought indicators and impacts for the 2018-2019 drought in Germany2024In: Environmental Research Letters, E-ISSN 1748-9326, Vol. 19, no 1, article id 014037Article in journal (Refereed)
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    fulltext
  • 39. Shyrokaya, Anastasiya
    et al.
    Pappenberger, Florian
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Messori, Gabriele
    Khatami, Sina
    Mazzoleni, Maurizio
    Di Baldassarre, Giuliano
    Advances and gaps in the science and practice of impact-based forecasting of droughts2023In: WIREs Water, E-ISSN 2049-1948Article in journal (Refereed)
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    Advances and gaps in the science and practice of impact-based forecasting of droughts
  • 40. Urkmans, Ruud T. W. L. H.
    et al.
    Urk, Bart Van den H.
    Chmeits, Maurice S.
    Etterhall, Fredrik W.
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Seasonal Streamflow Forecasting for Fresh Water Reservoir Management in the Netherlands: An Assessment of Multiple Prediction Systems2023In: Journal of Hydrometeorology, ISSN 1525-755X, E-ISSN 1525-7541, Vol. 24, no 7, p. 1275-1290Article in journal (Refereed)
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    Seasonal Streamflow Forecasting for Fresh Water Reservoir Management in the Netherlands: An Assessment of Multiple Prediction Systems
  • 41. Varlas, George
    et al.
    Papadaki, Christina
    Stefanidis, Konstantinos
    Mentzafou, Angeliki
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Papadopoulos, Anastasios
    Dimitriou, Elias
    Increasing Trends in Discharge Maxima of a Mediterranean River during Early Autumn2023In: Water, E-ISSN 2073-4441, Vol. 15, no 6, article id 1022Article in journal (Refereed)
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    Increasing Trends in Discharge Maxima of a Mediterranean River during Early Autumn
  • 42. Vetter, Tobias
    et al.
    Reinhardt, Julia
    Floerke, Martina
    van Griensven, Ann
    Hattermann, Fred
    Huang, Shaochun
    Koch, Hagen
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Ploetner, Stefan
    Seidou, Ousmane
    Su, Buda
    Vervoort, R. Willem
    Krysanova, Valentina
    Evaluation of sources of uncertainty in projected hydrological changes under climate change in 12 large-scale river basins2017In: Climatic Change, ISSN 0165-0009, E-ISSN 1573-1480, Vol. 141, no 3, p. 419-433Article in journal (Refereed)
  • 43. White, Christopher J.
    et al.
    Domeisen, Daniela I., V
    Acharya, Nachiketa
    Adefisan, Elijah A.
    Anderson, Michael L.
    Aura, Stella
    Balogun, Ahmed A.
    Bertram, Douglas
    Bluhm, Sonia
    Brayshaw, David J.
    Browell, Jethro
    Bueler, Dominik
    Charlton-Perez, Andrew
    Chourio, Xandre
    Christel, Isadora
    Coelho, Caio A. S.
    DeFlorio, Michael J.
    Delle Monache, Luca
    Di Giuseppe, Francesca
    Garcia-Solorzano, Ana Maria
    Gibson, Peter B.
    Goddard, Lisa
    Romero, Carmen Gonzalez
    Graham, Richard J.
    Graham, Robert M.
    Grams, Christian M.
    Halford, Alan
    Huang, W. T. Katty
    Jensen, Kjeld
    Kilavi, Mary
    Lawal, Kamoru A.
    Lee, Robert W.
    MacLeod, David
    Manrique-Sunen, Andrea
    Martins, Eduardo S. P. R.
    Maxwell, Carolyn J.
    Merryfield, William J.
    Munoz, Angel G.
    Olaniyan, Eniola
    Otieno, George
    Oyedepo, John A.
    Palma, Lluis
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Pons, Diego
    Ralph, F. Martin
    Reis, Dirceu S.
    Remenyi, Tomas A.
    Risbey, James S.
    Robertson, Donald J. C.
    Robertson, Andrew W.
    Smith, Stefan
    Soret, Albert
    Sun, Ting
    Todd, Martin C.
    Tozer, Carly R.
    Vasconcelos, Francisco C., Jr.
    Vigo, Ilaria
    Waliser, Duane E.
    Wetterhall, Fredrik
    Wilson, Robert G.
    Advances in the Application and Utility of Subseasonal-to-Seasonal Predictions2022In: Bulletin of The American Meteorological Society - (BAMS), ISSN 0003-0007, E-ISSN 1520-0477, Vol. 103, no 6, p. E1448-E1472Article in journal (Refereed)
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    Advances in the Application and Utility of Subseasonal-to-Seasonal Predictions
  • 44. Worman, Anders
    et al.
    Uvo, Cintia Bertacchi
    Brandimarte, Luigia
    Busse, Stefan
    Crochemore, Louise
    SMHI, Research Department, Hydrology.
    Hao, Shuang
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Girons, Marc
    SMHI, Core Services.
    Riml, Joakim
    Virtual energy storage gain resulting from the spatio-temporal coordination of hydropower over Europe2020In: Applied Energy, ISSN 0306-2619, E-ISSN 1872-9118, Vol. 272, article id UNSP 115249Article in journal (Refereed)
  • 45.
    Yiheng, Du
    et al.
    SMHI, Research Department, Hydrology.
    Clemenzi, Ilaria
    SMHI, Research Department, Hydrology.
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Hydrological regimes explain the seasonal predictability of streamflow extremes2023In: Environmental Research Letters, E-ISSN 1748-9326, Vol. 18, no 9, article id 094060Article in journal (Refereed)
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    Hydrological regimes explain the seasonal predictability of streamflow extremes
  • 46. Ziogas, Alexandros I.
    et al.
    Pechlivanidis, Ilias
    SMHI, Research Department, Hydrology.
    Romas, Evangelos D.
    Tzimas, Apostolos M.
    Climate service derived indicators to assess the impact of climate change on local river assimilative capacity2021In: Climate Services, E-ISSN 2405-8807, Vol. 23, article id 100250Article in journal (Refereed)
    Abstract [en]

    Continental climate services provide information on essential climate variables and indicators, which can further be used to address challenges at the local scale. Climate impact indicators are the core data for evaluating the change of the assimilative capacity of the river systems under future projection scenarios. Here, the indicators from the Copernicus pan-European climate service are used to develop and showcase a water management information service for the Asopos River, Greece. River flow indicators are incorporated in the estimation of emission limit values which serve as environmental pressure indicators, for the reference and two future periods (early-and mid-century). Assimilative capacity is evaluated for six heavy metals, namely Cr, Cd, Cu, Pb, Ni and Zn. Socioeconomic indicators are also utilized to incorporate changes of economic activities in the assessment. Results from the large ensemble of 209 scenarios, consisting of different global circulation, regional climatic and impact model combinations as well as industrial activity evolution, indicate that a decrease (up to 33% of 209 scenarios) of assimilative capacity is more probable than an increase (up to 18% of the scenarios) in a future climate. Local industrial activity evolution also has an effect on the uncertainty of the results for the early century period. We conclude that although climate impact indicators are free of the need for laborious processing, they cannot cover all requirements for local analyses. Consequently information from continental climate services and local data should be used for climate change impact investigations.

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    Climate service derived indicators to assess the impact of climate change on local river assimilative capacity
1 - 46 of 46
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