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Halldin, Sven
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Publications (10 of 46) Show all publications
Fuentes–Andino, D., Beven, K., Halldin, S., Xu, C.-Y., Reynolds, E. & Di Baldassarre, G. (2017). Reproducing an extreme flood with uncertain post-event information. Hydrology and Earth System Sciences Discussions, 21(7), 3597-3618.
Open this publication in new window or tab >>Reproducing an extreme flood with uncertain post-event information
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2017 (English)In: Hydrology and Earth System Sciences Discussions, ISSN 1812-2108, E-ISSN 1812-2116, Vol. 21, no 7, 3597-3618 p.Article in journal (Refereed) Published
Abstract [en]

Studies for the prevention and mitigation of floods require information on discharge and extent of inundation, commonly unavailable or uncertain, especially during extreme events. This study was initiated by the devastating flood in Tegucigalpa, the capital of Honduras, when Hurricane Mitch struck the city. In this study we hypothesized that it is possible to estimate, in a trustworthy way considering large data uncertainties, this extreme 1998 flood discharge and the extent of the inundations that followed from a combination of models and post-event measured data. Postevent data collected in 2000 and 2001 were used to estimate discharge peaks, times of peak, and high-water marks. These data were used in combination with rain data from two gauges to drive and constrain a combination of well-known modelling tools: TOPMODEL, Muskingum-Cunge-Todini routing, and the LISFLOOD-FP hydraulic model. Simulations were performed within the generalized likelihood uncertainty estimation (GLUE) uncertainty-analysis framework. The model combination predicted peak discharge, times of peaks, and more than 90% of the observed highwater marks within the uncertainty bounds of the evaluation data. This allowed an inundation likelihood map to be produced. Observed high-water marks could not be reproduced at a few locations on the floodplain. Identifications of these locations are useful to improve model set-up, model structure, or post-event data-estimation methods. Rainfall data were of central importance in simulating the times of peak and results would be improved by a better spatial assessment of rainfall, e. g. from radar data or a denser rain-gauge net-work. Our study demonstrated that it was possible, considering the uncertainty in the post-event data, to reasonably reproduce the extreme Mitch flood in Tegucigalpa in spite of no hydrometric gauging during the event. The method proposed here can be part of a Bayesian framework in which more events can be added into the analysis as they become available.

National Category
Oceanography, Hydrology and Water Resources
Identifiers
urn:nbn:se:uu:diva-317261 (URN)10.5194/hess-21-3597-2017 (DOI)000405652200001 ()
Funder
Sida - Swedish International Development Cooperation Agency, 54100006Swedish National Infrastructure for Computing (SNIC), p2011010
Available from: 2017-03-12 Created: 2017-03-12 Last updated: 2018-01-13Bibliographically approved
Reynolds, E., Halldin, S., Xu, C.-Y., Seibert, J. & Kauffeldt, A. (2017). Sub-daily runoff predictions using parameters calibrated on the basis of data with a daily temporal resolution. Journal of Hydrology, 550, 399-411.
Open this publication in new window or tab >>Sub-daily runoff predictions using parameters calibrated on the basis of data with a daily temporal resolution
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2017 (English)In: Journal of Hydrology, ISSN 0022-1694, E-ISSN 1879-2707, Vol. 550, 399-411 p.Article in journal (Refereed) Published
Abstract [en]

Concentration times in small and medium-sized basins (similar to 10-1000 km(2)) are commonly less than 24 h. Flood-forecasting models are thus required to provide simulations at high temporal resolutions (1 h-6 h), although time-series of input and runoff data with sufficient lengths are often only available at the daily temporal resolution, especially in developing countries. This has led to study the relationships of estimated parameter values at the temporal resolutions where they are needed from the temporal resolutions where they are available. This study presents a methodology to treat empirically model parameter dependencies on the temporal resolution of data in two small basins using a bucket-type hydrological model, HBV-light, and the generalised likelihood uncertainty estimation approach for selecting its parameters. To avoid artefacts due to the numerical resolution or numerical method of the differential equations within the model, the model was consistently run using modelling time steps of one-hour regardless of the temporal resolution of the rainfall-runoff data. The distribution of the parameters calibrated at several temporal resolutions in the two basins did not show model parameter dependencies on the temporal resolution of data and the direct transferability of calibrated parameter sets (e.g., daily) for runoff simulations at other temporal resolutions for which they were not calibrated (e.g., 3 h or 6 h) resulted in a moderate (if any) decrease in model performance, in terms of Nash-Sutcliffe and volume-error efficiencies. The results of this study indicate that if sub-daily forcing data can be secured, flood forecasting in basins with sub-daily concentration times may be possible with model-parameter values calibrated from long time series of daily data. Further studies using more models and basins are required to test the generality of these results.

Keyword
Rainfall-runoff modelling, Parameter transferability, Temporal resolution, Modelling time-step, Flood forecasting
National Category
Oceanography, Hydrology and Water Resources
Identifiers
urn:nbn:se:uu:diva-330029 (URN)10.1016/j.jhydrol.2017.05.012 (DOI)000404816000032 ()
Funder
Sida - Swedish International Development Cooperation Agency
Available from: 2017-09-29 Created: 2017-09-29 Last updated: 2018-01-13Bibliographically approved
Kauffeldt, A., Halldin, S., Pappenberger, F., Wetterhall, F., Xu, C.-Y. & Cloke, H. L. (2015). Imbalanced land surface water budgets in a numerical weather prediction system. Geophysical Research Letters, 42(11), 4411-4417.
Open this publication in new window or tab >>Imbalanced land surface water budgets in a numerical weather prediction system
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2015 (English)In: Geophysical Research Letters, ISSN 0094-8276, E-ISSN 1944-8007, Vol. 42, no 11, 4411-4417 p.Article in journal (Refereed) Published
Abstract [en]

There has been a significant increase in the skill and resolution of numerical weather prediction models (NWPs) in recent decades, extending the time scales of useful weather predictions. The land surface models (LSMs) of NWPs are often employed in hydrological applications, which raises the question of how hydrologically representative LSMs really are. In this paper, precipitation (P), evaporation (E), and runoff (R) from the European Centre for Medium-Range Weather Forecasts global models were evaluated against observational products. The forecasts differ substantially from observed data for key hydrological variables. In addition, imbalanced surface water budgets, mostly caused by data assimilation, were found on both global (P-E) and basin scales (P-E-R), with the latter being more important. Modeled surface fluxes should be used with care in hydrological applications, and further improvement in LSMs in terms of process descriptions, resolution, and estimation of uncertainties is needed to accurately describe the land surface water budgets.

Keyword
water budget, data assimilation, runoff, reanalysis, precipitation
National Category
Geophysics Geology
Identifiers
urn:nbn:se:uu:diva-260141 (URN)10.1002/2015GL064230 (DOI)000357511200021 ()
Available from: 2015-08-18 Created: 2015-08-17 Last updated: 2017-12-04Bibliographically approved
Halldin, S., Bynander, F. & van Groningen, E. (2015). Preface: Natural Disaster Science: A Nordic Approach to Integrated Research on Disaster Risk. Geografiska Annaler. Series A, Physical Geography, 97(1), 1-7.
Open this publication in new window or tab >>Preface: Natural Disaster Science: A Nordic Approach to Integrated Research on Disaster Risk
2015 (English)In: Geografiska Annaler. Series A, Physical Geography, ISSN 0435-3676, E-ISSN 1468-0459, Vol. 97, no 1, 1-7 p.Article in journal, Editorial material (Other academic) Published
Keyword
natural disasters, interdisciplinary, integrated research, risk, disaster risk reduction
National Category
Earth and Related Environmental Sciences
Identifiers
urn:nbn:se:uu:diva-251680 (URN)10.1111/geoa.12098 (DOI)000350500400001 ()
Available from: 2015-04-24 Created: 2015-04-23 Last updated: 2017-12-04Bibliographically approved
Westerberg, I. K., Gong, L., Beven, K. J., Seibert, J., Semedo, A., Xu, C.-Y. & Halldin, S. (2014). Regional water balance modelling using flow-duration curves with observational uncertainties. Hydrology and Earth System Sciences, 18(8), 2993-3013.
Open this publication in new window or tab >>Regional water balance modelling using flow-duration curves with observational uncertainties
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2014 (English)In: Hydrology and Earth System Sciences, ISSN 1027-5606, E-ISSN 1607-7938, Vol. 18, no 8, 2993-3013 p.Article in journal (Refereed) Published
Abstract [en]

Robust and reliable water-resource mapping in ungauged basins requires estimation of the uncertainties in the hydrologic model, the regionalisation method, and the observational data. In this study we investigated the use of regionalised flow-duration curves (FDCs) for constraining model predictive uncertainty, while accounting for all these uncertainty sources. A water balance model was applied to 36 basins in Central America using regionally and globally available precipitation, climate and discharge data that were screened for inconsistencies. A rating-curve analysis for 35 Honduran discharge stations was used to estimate discharge uncertainty for the region, and the consistency of the model forcing and evaluation data was analysed using two different screening methods. FDCs with uncertainty bounds were calculated for each basin, accounting for both discharge uncertainty and, in many cases, uncertainty stemming from the use of short time series, potentially not representative for the modelling period. These uncertain FDCs were then used to regionalise a FDC for each basin, treating it as ungauged in a cross-evaluation, and this regionalised FDC was used to constrain the uncertainty in the model predictions for the basin. There was a clear relationship between the performance of the local model calibration and the degree of data set consistency - with many basins with inconsistent data lacking behavioural simulations (i.e. simulations within predefined limits around the observed FDC) and the basins with the highest data set consistency also having the highest simulation reliability. For the basins where the regionalisation of the FDCs worked best, the uncertainty bounds for the regionalised simulations were only slightly wider than those for a local model calibration. The predicted uncertainty was greater for basins where the result of the FDC regionalisation was more uncertain, but the regionalised simulations still had a high reliability compared to the locally calibrated simulations and often encompassed them. The regionalised FDCs were found to be useful on their own as a basic signature constraint; however, additional regionalised signatures could further constrain the uncertainty in the predictions and may increase the robustness to severe data inconsistencies, which are difficult to detect for ungauged basins.

National Category
Oceanography, Hydrology and Water Resources
Identifiers
urn:nbn:se:uu:diva-234221 (URN)10.5194/hess-18-2993-2014 (DOI)000341597600012 ()
Available from: 2014-10-15 Created: 2014-10-15 Last updated: 2018-01-11
Kauffeldt, A., Halldin, S., Rodhe, A., Xu, C.-Y. & Westerberg, I. K. (2013). Disinformative data in large-scale hydrological modelling. Hydrology and Earth System Sciences, 17(7), 2845-2857.
Open this publication in new window or tab >>Disinformative data in large-scale hydrological modelling
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2013 (English)In: Hydrology and Earth System Sciences, ISSN 1027-5606, E-ISSN 1607-7938, Vol. 17, no 7, 2845-2857 p.Article in journal (Refereed) Published
Abstract [en]

Large-scale hydrological modelling has become an important tool for the study of global and regional water resources, climate impacts, and water-resources management. However, modelling efforts over large spatial domains are fraught with problems of data scarcity, uncertainties and inconsistencies between model forcing and evaluation data. Model-independent methods to screen and analyse data for such problems are needed. This study aimed at identifying data inconsistencies in global datasets using a pre-modelling analysis, inconsistencies that can be disinformative for subsequent modelling. The consistency between (i) basin areas for different hydrographic datasets, and (ii) between climate data (precipitation and potential evaporation) and discharge data, was examined in terms of how well basin areas were represented in the flow networks and the possibility of water-balance closure. It was found that (i) most basins could be well represented in both gridded basin delineations and polygon-based ones, but some basins exhibited large area discrepancies between flow-network datasets and archived basin areas, (ii) basins exhibiting too-high runoff coefficients were abundant in areas where precipitation data were likely affected by snow undercatch, and (iii) the occurrence of basins exhibiting losses exceeding the potential-evaporation limit was strongly dependent on the potential-evaporation data, both in terms of numbers and geographical distribution. Some inconsistencies may be resolved by considering subgrid variability in climate data, surface-dependent potential-evaporation estimates, etc., but further studies are needed to determine the reasons for the inconsistencies found. Our results emphasise the need for pre-modelling data analysis to identify dataset inconsistencies as an important first step in any large-scale study. Applying data-screening methods before modelling should also increase our chances to draw robust conclusions from subsequent model simulations.

National Category
Natural Sciences
Identifiers
urn:nbn:se:uu:diva-206677 (URN)10.5194/hess-17-2845-2013 (DOI)000322376000031 ()
Available from: 2013-09-03 Created: 2013-09-02 Last updated: 2017-12-06Bibliographically approved
Guerrero, J.-L., Westerberg, I., Halldin, S., Lundin, L.-C. & Xu, C.-Y. (2013). Exploring the hydrological robustness of model-parameter values with alpha shapes. Water resources research, 49(10), 6700-6715.
Open this publication in new window or tab >>Exploring the hydrological robustness of model-parameter values with alpha shapes
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2013 (English)In: Water resources research, ISSN 0043-1397, E-ISSN 1944-7973, Vol. 49, no 10, 6700-6715 p.Article in journal (Refereed) Published
Abstract [en]

Estimation of parameter values in hydrological models has gradually moved from subjective, trial-and-error methods into objective estimation methods. Translation of nature's complexity to bit operations is an uncertain process as a result of data errors, epistemic gaps, computational deficiencies, and other limitations, and relies on calibration to fit model output to observed data. The robustness of the calibrated parameter values to these types of uncertainties is therefore an important concern. In this study, we investigated how the hydrological robustness of the model-parameter values varied within the geometric structure of the behavioral (well-performing) parameter space with a depth function based on α shapes and an in-depth posterior performance analysis of the simulations in relation to the observed discharge uncertainty. The α shape depth is a nonconvex measure that may provide an accurate and tight delimitation of the geometric structure of the behavioral space for both unimodal and multimodal parameter-value distributions. WASMOD, a parsimonious rainfall-runoff model, was applied to six Honduran and one UK catchment, with differing data quality and hydrological characteristics. Model evaluation was done with two performance measures, the Nash-Sutcliffe efficiency and one based on flow-duration curves. Deep parameter vectors were in general found to be more hydrologically robust than shallow ones in the analyses we performed; model-performance values increased with depth, deviations to the observed data for the high-flow aspects of the hydrograph generally decreased with increasing depth, deep parameter vectors generally transferred in time with maintained high performance values, and the model had a low sensitivity to small changes in the parameter values. The tight delimitation of the behavioral space provided by the α shapes depth function showed a potential to improve the efficiency of calibration techniques that require further exploration. For computational reasons only a three-parameter model could be used, which limited the applicability of this depth measure and the conclusions drawn in this paper, especially concerning hydrological robustness at low flows.

Keyword
robustness, parameter estimation, alpha shape
National Category
Ocean and River Engineering
Identifiers
urn:nbn:se:uu:diva-190679 (URN)10.1002/wrcr.20533 (DOI)000327432500040 ()
Available from: 2013-01-08 Created: 2013-01-08 Last updated: 2017-12-06Bibliographically approved
Guerrero, J.-L., Westerberg, I. K., Halldin, S., Xu, C.-Y. & Lundin, L.-C. (2012). Temporal variability in stage-discharge relationships. Journal of Hydrology, 446, 90-102.
Open this publication in new window or tab >>Temporal variability in stage-discharge relationships
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2012 (English)In: Journal of Hydrology, ISSN 0022-1694, E-ISSN 1879-2707, Vol. 446, 90-102 p.Article in journal (Refereed) Published
Abstract [en]

Although discharge estimations are central for water management and hydropower, there are few studies on the variability and uncertainty of their basis; deriving discharge from stage heights through the use of a rating curve that depends on riverbed geometry. A large fraction of the world's river-discharge stations are presumably located in alluvial channels where riverbed characteristics may change over time because of erosion and sedimentation. This study was conducted to analyse and quantify the dynamic relationship between stage and discharge and to determine to what degree currently used methods are able to account for such variability. The study was carried out for six hydrometric stations in the upper Choluteca River basin, Honduras, where a set of unusually frequent stage-discharge data are available. The temporal variability and the uncertainty of the rating curve and its parameters were analysed through a Monte Carlo (MC) analysis on a moving window of data using the Generalised Likelihood Uncertainty Estimation (GLUE) methodology. Acceptable ranges for the values of the rating-curve parameters were determined from riverbed surveys at the six stations, and the sampling space was constrained according to those ranges, using three-dimensional alpha shapes. Temporal variability was analysed in three ways: (i) with annually updated rating curves (simulating Honduran practices), (ii) a rating curve for each time window, and (iii) a smoothed, continuous dynamic rating curve derived from the MC analysis. The temporal variability of the rating parameters translated into a high rating-curve variability. The variability could turn out as increasing or decreasing trends and/or cyclic behaviour. There was a tendency at all stations to a seasonal variability. The discharge at a given stage could vary by a factor of two or more. The quotient in discharge volumes estimated from dynamic and static rating curves varied between 0.5 and 1.5. The difference between discharge volumes derived from static and dynamic curves was largest for sub-daily ratings but stayed large also for monthly and yearly totals. The relative uncertainty was largest for low flows but it was considerable also for intermediate and large flows. The standard procedure of adjusting rating curves when calculated and observed discharge differ by more than 5% would have required continuously updated rating curves at the studied locations. We believe that these findings can be applicable to many other discharge stations around the globe.

Keyword
Rating curve, Discharge, Uncertainty, Temporal variability, Alluvial river
National Category
Oceanography, Hydrology and Water Resources
Identifiers
urn:nbn:se:uu:diva-177587 (URN)10.1016/j.jhydrol.2012.04.031 (DOI)000305365300009 ()
Available from: 2012-07-16 Created: 2012-07-16 Last updated: 2018-01-12Bibliographically approved
Westerberg, I., Guerrero, J.-L., Younger, P. M., Beven, K., Seibert, J., Halldin, S., . . . Xu, C.-Y. -. (2011). Calibration of hydrological models using flow-duration curves. Hydrology and Earth System Sciences, 15(7), 2205-2227.
Open this publication in new window or tab >>Calibration of hydrological models using flow-duration curves
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2011 (English)In: Hydrology and Earth System Sciences, ISSN 1027-5606, E-ISSN 1607-7938, Vol. 15, no 7, 2205-2227 p.Article in journal (Refereed) Published
Abstract [en]

The degree of belief we have in predictions from hydrologic models will normally depend on how well they can reproduce observations. Calibrations with traditional performance measures, such as the Nash-Sutcliffe model efficiency, are challenged by problems including: (1) uncertain discharge data, (2) variable sensitivity of different performance measures to different flow magnitudes, (3) influence of unknown input/output errors and (4) inability to evaluate model performance when observation time periods for discharge and model input data do not overlap. This paper explores a calibration method using flow-duration curves (FDCs) to address these problems. The method focuses on reproducing the observed discharge frequency distribution rather than the exact hydrograph. It consists of applying limits of acceptability for selected evaluation points (EPs) on the observed uncertain FDC in the extended GLUE approach. Two ways of selecting the EPs were tested - based on equal intervals of discharge and of volume of water. The method was tested and compared to a calibration using the traditional model efficiency for the daily four-parameter WAS-MOD model in the Paso La Ceiba catchment in Honduras and for Dynamic TOPMODEL evaluated at an hourly time scale for the Brue catchment in Great Britain. The volume method of selecting EPs gave the best results in both catchments with better calibrated slow flow, recession and evaporation than the other criteria. Observed and simulated time series of uncertain discharges agreed better for this method both in calibration and prediction in both catchments. An advantage with the method is that the rejection criterion is based on an estimation of the uncertainty in discharge data and that the EPs of the FDC can be chosen to reflect the aims of the modelling application, e. g. using more/less EPs at high/low flows. While the method appears less sensitive to epistemic input/output errors than previous use of limits of acceptability applied directly to the time series of discharge, it still requires a reasonable representation of the distribution of inputs. Additional constraints might therefore be required in catchments subject to snow and where peak-flow timing at sub-daily time scales is of high importance. The results suggest that the calibration method can be useful when observation time periods for discharge and model input data do not overlap. The method could also be suitable for calibration to regional FDCs while taking uncertainties in the hydrological model and data into account.

National Category
Natural Sciences
Identifiers
urn:nbn:se:uu:diva-158117 (URN)10.5194/hess-15-2205-2011 (DOI)000293268200011 ()
Available from: 2011-08-31 Created: 2011-08-31 Last updated: 2017-12-08Bibliographically approved
Gong, L., Halldin, S. & Xu, C.-Y. (2011). Large-scale runoff generation: parsimonious parameterisation using high-resolution topography. Hydrology and Earth System Sciences, 15(8), 2481-2494.
Open this publication in new window or tab >>Large-scale runoff generation: parsimonious parameterisation using high-resolution topography
2011 (English)In: Hydrology and Earth System Sciences, ISSN 1027-5606, E-ISSN 1607-7938, Vol. 15, no 8, 2481-2494 p.Article in journal (Refereed) Published
Abstract [en]

World water resources have primarily been analysed by global-scale hydrological models in the last decades. Runoff generation in many of these models are based on process formulations developed at catchments scales. The division between slow runoff (baseflow) and fast runoff is primarily governed by slope and spatial distribution of effective water storage capacity, both acting at very small scales. Many hydrological models, e. g. VIC, account for the spatial storage variability in terms of statistical distributions; such models are generally proven to perform well. The statistical approaches, however, use the same runoff-generation parameters everywhere in a basin. The TOPMODEL concept, on the other hand, links the effective maximum storage capacity with real-world topography. Recent availability of global high-quality, high-resolution topographic data makes TOPMODEL attractive as a basis for a physically-based runoff-generation algorithm at large scales, even if its assumptions are not valid in flat terrain or for deep groundwater systems. We present a new runoff-generation algorithm for large-scale hydrology based on TOPMODEL concepts intended to overcome these problems. The TRG (topography-derived runoff generation) algorithm relaxes the TOPMODEL equilibrium assumption so baseflow generation is not tied to topography. TRG only uses the topographic index to distribute average storage to each topographic index class. The maximum storage capacity is proportional to the range of topographic index and is scaled by one parameter. The distribution of storage capacity within large-scale grid cells is obtained numerically through topographic analysis. The new topography-derived distribution function is then inserted into a runoff-generation framework similar VIC's. Different basin parts are parameterised by different storage capacities, and different shapes of the storage-distribution curves depend on their topographic characteristics. The TRG algorithm is driven by the HydroSHEDS dataset with a resolution of 3 '' (around 90 m at the equator). The TRG algorithm was validated against the VIC algorithm in a common model framework in 3 river basins in different climates. The TRG algorithm performed equally well or marginally better than the VIC algorithm with one less parameter to be calibrated. The TRG algorithm also lacked equifinality problems and offered a realistic spatial pattern for runoff generation and evaporation.

National Category
Earth and Related Environmental Sciences
Identifiers
urn:nbn:se:uu:diva-159079 (URN)10.5194/hess-15-2481-2011 (DOI)000294458200005 ()
Available from: 2011-09-21 Created: 2011-09-21 Last updated: 2017-12-08Bibliographically approved
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