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Halldin, Sven
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Publications (10 of 53) Show all publications
Quesada Montano, B., Wetterhall, F., Westerberg, I. K., Hidalgo, H. G. & Halldin, S. (2019). Characterising droughts in Central America with uncertain hydro-meteorological data. Journal of Theoretical and Applied Climatology, 137(3-4), 2125-2138
Open this publication in new window or tab >>Characterising droughts in Central America with uncertain hydro-meteorological data
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2019 (English)In: Journal of Theoretical and Applied Climatology, ISSN 0177-798X, E-ISSN 1434-4483, Vol. 137, no 3-4, p. 2125-2138Article in journal (Refereed) Published
Abstract [en]

Central America is frequently affected by droughts that cause significant socio-economic and environmental problems. Drought characterisation, monitoring and forecasting are potentially useful to support water resource management. Drought indices are designed for these purposes, but their ability to characterise droughts depends on the characteristics of the regional climate and the quality of the available data. Local comprehensive and high-quality observational networks of meteorological and hydrological data are not available, which limits the choice of drought indices and makes it important to assess available datasets. This study evaluated which combinations of drought index and meteorological dataset were most suitable for characterising droughts in the region. We evaluated the standardised precipitation index (SPI), a modified version of the deciles index (DI), the standardised precipitation evapotranspiration index (SPEI) and the effective drought index (EDI). These were calculated using precipitation data from the Climate Hazards Group Infra-Red Precipitation with Station (CHIRPS), the CRN073 dataset, the Climate Research Unit (CRU), ECMWF Reanalysis (ERA-Interim) and a regional station dataset, and temperature from the CRU and ERA-Interim datasets. The gridded meteorological precipitation datasets were compared to assess how well they captured key features of the regional climate. The performance of all the drought indices calculated with all the meteorological datasets was then evaluated against a drought index calculated using river discharge data. Results showed that the selection of database was more important than the selection of drought index and that the best combinations were the EDI and DI calculated with CHIRPS and CRN073. Results also highlighted the importance of including indices like SPEI for drought assessment in Central America.

Keywords
droughts; scarce data; Central America; drought indices
National Category
Oceanography, Hydrology and Water Resources
Research subject
Hydrology; Meteorology
Identifiers
urn:nbn:se:uu:diva-330134 (URN)10.1007/s00704-018-2730-z (DOI)000477054700036 ()
Funder
Sida - Swedish International Development Cooperation Agency, 54100006EU, FP7, Seventh Framework Programme, 329762
Available from: 2017-09-26 Created: 2017-09-26 Last updated: 2019-09-09Bibliographically approved
Gebrehiwot, S. G., Di Baldassarre, G., Bishop, K., Halldin, S. & Breuer, L. (2019). Is observation uncertainty masking the signal of land use change impacts on hydrology?. Journal of Hydrology, 570, 393-400
Open this publication in new window or tab >>Is observation uncertainty masking the signal of land use change impacts on hydrology?
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2019 (English)In: Journal of Hydrology, ISSN 0022-1694, E-ISSN 1879-2707, Vol. 570, p. 393-400Article in journal (Refereed) Published
Abstract [en]

Analysis of hydrological impacts of land use change raises questions about whether, and how much, such impacts are misrepresented because of errors in river flow observations. In this paper, land use change impacts (represented by changes in watershed storage) and different ranges of discharge measurement error are compared to assess how errors in discharge measurement can potentially mask a land use change impact. Using a watershed from the Ethiopian highlands to exemplify this, we simulated five different levels of land use change impacts with five levels of watershed storage reductions (from 10% to 50% change) and the associated time series of runoff. Different levels of observation error were then introduced into these artificial time series. Comparison was made between every pair, i.e. a time series derived from a certain level of land use change (storage reduction) versus a time series corresponding to a given level of observation error, using a step-change t-test. Significant step-changes between pairs define the detectability of land use change impact. The analysis was made for the entire 30-year time series as well as for the most extreme annual weather conditions. The results showed that for the average year and wettest year, 75% or more error in observed discharge masks the maximum simulated land use change impact on hydrology. In dry years, a 50% error in discharge is enough to mask the same impact. Knowing (and improving) the level of data quality contributes to a better understanding of hydrological uncertainties and improves the precision in assessing land use change impacts. Both of these are essential elements in water resources development planning.

Place, publisher, year, edition, pages
ELSEVIER SCIENCE BV, 2019
Keywords
Detectability, Discharge, Error range, Watershed storage, Upper-Didesa watershed
National Category
Oceanography, Hydrology and Water Resources
Identifiers
urn:nbn:se:uu:diva-380488 (URN)10.1016/j.jhydrol.2018.12.058 (DOI)000460709400031 ()
Available from: 2019-03-28 Created: 2019-03-28 Last updated: 2019-03-28Bibliographically approved
Quesada Montano, B., Westerberg, I. K., Fuentes–Andino, D., Hidalgo, H. G. & Halldin, S. (2018). Can climate variability information constrain a hydrological model for an ungauged Costa Rican catchment?. Hydrological Processes, 32(6), 830-846
Open this publication in new window or tab >>Can climate variability information constrain a hydrological model for an ungauged Costa Rican catchment?
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2018 (English)In: Hydrological Processes, ISSN 0885-6087, E-ISSN 1099-1085, Vol. 32, no 6, p. 830-846Article in journal (Refereed) Published
Abstract [en]

Long-term hydrological data are key to understanding catchment behaviour and for decision making within water management and planning. Given the lack of observed data in many regions worldwide, such as Central America, hydrological models are an alternative for reproducing historical streamflow series. Additional types of informationto locally observed dischargecan be used to constrain model parameter uncertainty for ungauged catchments. Given the strong influence that climatic large-scale processes exert on streamflow variability in the Central American region, we explored the use of climate variability knowledge as process constraints to constrain the simulated discharge uncertainty for a Costa Rican catchment, assumed to be ungauged. To reduce model uncertainty, we first rejected parameter relationships that disagreed with our understanding of the system. Then, based on this reduced parameter space, we applied the climate-based process constraints at long-term, inter-annual, and intra-annual timescales. In the first step, we reduced the initial number of parameters by 52%, and then, we further reduced the number of parameters by 3% with the climate constraints. Finally, we compared the climate-based constraints with a constraint based on global maps of low-flow statistics. This latter constraint proved to be more restrictive than those based on climate variability (further reducing the number of parameters by 66% compared with 3%). Even so, the climate-based constraints rejected inconsistent model simulations that were not rejected by the low-flow statistics constraint. When taken all together, the constraints produced constrained simulation uncertainty bands, and the median simulated discharge followed the observed time series to a similar level as an optimized model. All the constraints were found useful in constraining model uncertainty for anassumed to beungauged basin. This shows that our method is promising for modelling long-term flow data for ungauged catchments on the Pacific side of Central America and that similar methods can be developed for ungauged basins in other regions where climate variability exerts a strong control on streamflow variability.

Place, publisher, year, edition, pages
WILEY, 2018
Keywords
Central America, climate variability, hydrological model, process constraints, uncertainty, ungauged basins
National Category
Oceanography, Hydrology and Water Resources
Identifiers
urn:nbn:se:uu:diva-351432 (URN)10.1002/hyp.11460 (DOI)000427118400010 ()
Funder
Sida - Swedish International Development Cooperation Agency, 54100006Swedish Research Council Formas, 942-2015-321
Available from: 2018-06-01 Created: 2018-06-01 Last updated: 2018-06-01Bibliographically approved
Reynolds, J. E., Halldin, S., Seibert, J. & Xu, C.-Y. (2018). Definitions of climatological and discharge days: do they matter in hydrological modelling?. Hydrological Sciences Journal, 63(5), 836-844
Open this publication in new window or tab >>Definitions of climatological and discharge days: do they matter in hydrological modelling?
2018 (English)In: Hydrological Sciences Journal, ISSN 0262-6667, E-ISSN 2150-3435, Vol. 63, no 5, p. 836-844Article in journal (Refereed) Published
Abstract [en]

The performance of hydrological models is affected by uncertainty related to observed climatological and discharge data. Although the latter has been widely investigated, the effects on hydrological models from different starting times of the day have received little interest. In this study, observational data from one tropical basin were used to investigate the effects on a typical bucket-type hydrological model, the HBV, when the definitions of the climatological and discharge days are changed. An optimization procedure based on a genetic algorithm was used to assess the effects on model performance. Nash-Sutcliffe efficiencies varied considerably between day definitions, with the largest dependence on the climatological-day definition. The variation was likely caused by how storm water was assigned to one or two daily rainfall values depending on the definition of the climatological day. Hydrological models are unlikely to predict high flows accurately if rainfall intensities are reduced because of the day definition.

Place, publisher, year, edition, pages
Taylor & Francis, 2018
Keywords
climatological day, discharge day, rainfall-runoff model, daily resolution, regionalization, floods
National Category
Oceanography, Hydrology and Water Resources
Identifiers
urn:nbn:se:uu:diva-353191 (URN)10.1080/02626667.2018.1451646 (DOI)000430212100010 ()
Available from: 2018-06-12 Created: 2018-06-12 Last updated: 2018-12-05Bibliographically approved
Reynolds, E., Halldin, S., Seibert, J., Xu, C.-Y. & Grabs, T. J. (2018). Robustness of Flood-Model Calibration using Single and Multiple Events. Hydrological Sciences Journal
Open this publication in new window or tab >>Robustness of Flood-Model Calibration using Single and Multiple Events
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2018 (English)In: Hydrological Sciences Journal, ISSN 0262-6667, E-ISSN 2150-3435Article in journal (Refereed) Submitted
National Category
Earth and Related Environmental Sciences
Identifiers
urn:nbn:se:uu:diva-368457 (URN)
Funder
Sida - Swedish International Development Cooperation Agency
Available from: 2018-12-04 Created: 2018-12-04 Last updated: 2018-12-05
Fuentes-Andino, D., Beven, K., Kauffeldt, A., Xu, C.-Y., Halldin, S. & Di Baldassarre, G. (2017). Event and model dependent rainfall adjustments to improve discharge predictions. Hydrological Sciences Journal, 62(2), 232-245
Open this publication in new window or tab >>Event and model dependent rainfall adjustments to improve discharge predictions
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2017 (English)In: Hydrological Sciences Journal, ISSN 0262-6667, E-ISSN 2150-3435, Vol. 62, no 2, p. 232-245Article in journal (Refereed) Published
Abstract [en]

Most conceptual rainfall–runoff models use as input spatially averaged rainfall fields which are typically associated with significant errors that affect the model outcome. In this study, it was hypothesised that a simple spatially and temporally averaged event-dependent rainfall multiplier can account for errors in the rainfall input. The potentials and limitations of this lumped multiplier approach were explored by evaluating the effects of multipliers on the accuracy and precision of the predictive distributions. Parameter sets found to be behavioural across a range of different flood events were assumed to be a good representation of the catchment dynamics and were used to identify rainfall multipliers for each of the individual events. An effect of the parameter sets on identified multipliers was found; however, it was small compared to the differences between events. Accounting for event-dependent multipliers improved the reliability of the predictions. At the cost of a small decrease in precision, the distribution of identified multipliers for past events can be used to account for possible rainfall errors when predicting future events. By using behavioural parameter sets to identify rainfall multipliers, the method offers a simple and computationally efficient way to address rainfall errors in hydrological modelling.

Keywords
rainfall multiplier, rainfall input error, reliability of the predictions, precision of predictions, Topmodel, floods
National Category
Earth and Related Environmental Sciences
Research subject
Earth Science with specialization in Environmental Analysis
Identifiers
urn:nbn:se:uu:diva-291537 (URN)10.1080/02626667.2016.1183775 (DOI)000392602000006 ()
Funder
Sida - Swedish International Development Cooperation Agency, 54100006Swedish National Infrastructure for Computing (SNIC), p2011010
Available from: 2016-05-03 Created: 2016-05-03 Last updated: 2018-09-03Bibliographically approved
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, p. 3597-3618Article 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, p. 399-411Article 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.

Keywords
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: 2018-12-05
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, p. 4411-4417Article 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.

Keywords
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, p. 1-7Article in journal, Editorial material (Other academic) Published
Keywords
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
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