| publications-771 |
PEER REVIEWED ARTICLE |
2015 |
Rene Orth , Maria Staudinger , Sonia I. Seneviratne , Jan Seibert , Massimiliano Zappa |
Does model performance improve with complexity? A case study with three hydrological models |
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10.1016/j.jhydrol.2015.01.044 |
Simulation & Modeling |
River Basins |
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No abstract available |
282769 |
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| publications-772 |
PEER REVIEWED ARTICLE |
2015 |
MarĂa Pedro-MonzonĂs , Javier Ferrer , Abel Solera , Teodoro Estrela , Javier Paredes-Arquiola |
Key issues for determining the exploitable water resources in a Mediterranean river basin |
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10.1016/j.scitotenv.2014.07.042 |
Simulation & Modeling |
Precipitation & Ecological Systems |
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No abstract available |
282769 |
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| publications-773 |
PEER REVIEWED ARTICLE |
2015 |
James H. Stagge , Lena M. Tallaksen , Lukas Gudmundsson , Anne F. Van Loon , Kerstin Stahl |
Candidate Distributions for Climatological Drought Indices (SPI and SPEI) |
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10.1002/joc.4267 |
IoT & Sensors |
Uncategorized |
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AbstractThe Standardized Precipitation Index (SPI), a wellâreviewed meteorological drought index recommended by the World Meteorological Organization (WMO), and its more recent climatic water balance variant, the Standardized PrecipitationâEvapotranspiration Index (SPEI), both rely on selection of a univariate probability distribution to normalize the index, allowing for comparisons across climates. Choice of an improper probability distribution may impart bias to the index values, exaggerating or minimizing drought severity. This study compares a suite of candidate probability distributions for use in SPI and SPEI normalization using the 0.5° Ă 0.5° gridded Watch Forcing Dataset (WFD) at the continental scale, focusing on Europe. Several modifications to the SPI and SPEI methodology are proposed, as well as an updated procedure for evaluating SPI/SPEI goodness of fit based on the ShapiroâWilk test. Candidate distributions for SPI organize into two groups based on their ability to model shortâterm accumulation (1â2 months) or longâterm accumulation (>3 months). The twoâparameter gamma distribution is recommended for general use when calculating SPI across all accumulation periods and regions within Europe, in agreement with previous studies. The generalized extreme value distribution is recommended when computing the SPEI, in disagreement with previous recommendations. |
282769 |
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| publications-774 |
PEER REVIEWED ARTICLE |
2012 |
K. Stahl , L. M. Tallaksen , J. Hannaford , H. A. J. van Lanen |
Filling the white space on maps of European runoff trends: estimates from a multi-model ensemble |
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10.5194/hess-16-2035-2012 |
IoT & Sensors |
Uncategorized |
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Abstract. An overall appraisal of runoff changes at the European scale has been hindered by "white space" on maps of observed trends due to a paucity of readily-available streamflow data. This study tested whether this white space can be filled using estimates of trends derived from model simulations of European runoff. The simulations stem from an ensemble of eight global hydrological models that were forced with the same climate input for the period 1963â2000. The derived trends were validated for 293 grid cells across the European domain with observation-based trend estimates. The ensemble mean overall provided the best representation of trends in the observations. Maps of trends in annual runoff based on the ensemble mean demonstrated a pronounced continental dipole pattern of positive trends in western and northern Europe and negative trends in southern and parts of eastern Europe, which has not previously been demonstrated and discussed in comparable detail. Overall, positive trends in annual streamflow appear to reflect the marked wetting trends of the winter months, whereas negative annual trends result primarily from a widespread decrease in streamflow in spring and summer months, consistent with a decrease in summer low flow in large parts of Europe. High flow appears to have increased in rain-dominated hydrological regimes, whereas an inconsistent or decreasing signal was found in snow-dominated regimes. The different models agreed on the predominant continental-scale pattern of trends, but in some areas disagreed on the magnitude and even the direction of trends, particularly in transition zones between regions with increasing and decreasing runoff trends, in complex terrain with a high spatial variability, and in snow-dominated regimes. Model estimates appeared most reliable in reproducing observed trends in annual runoff, winter runoff, and 7-day high flow. Modelled trends in runoff during the summer months, spring (for snow influenced regions) and autumn, and trends in summer low flow were more variable â both among models and in the spatial patterns of agreement between models and the observations. The use of models to display changes in these hydrological characteristics should therefore be viewed with caution due to higher uncertainty. |
282769 |
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| publications-775 |
PEER REVIEWED ARTICLE |
2012 |
M. H. J. van Huijgevoort , P. Hazenberg , H. A. J. van Lanen , R. Uijlenhoet |
A generic method for hydrological drought identification across different climate regions |
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10.5194/hess-16-2437-2012 |
AI & Machine Learning |
Uncategorized |
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Abstract. The identification of hydrological drought at global scale has received considerable attention during the last decade. However, climate-induced variation in runoff across the world makes such analyses rather complicated. This especially holds for the drier regions of the world (both cold and warm), where, for a considerable period of time, zero runoff can be observed. In the current paper, we present a method that enables to identify drought at global scale across climate regimes in a consistent manner. The method combines the characteristics of the classical variable threshold level method that is best applicable in regions with non-zero runoff most of the time, and the consecutive dry days (period) method that is better suited for areas where zero runoff occurs. The newly presented method allows a drought in periods with runoff to continue in the following period without runoff. The method is demonstrated by identifying droughts from discharge observations of four rivers situated within different climate regimes, as well as from simulated runoff data at global scale obtained from an ensemble of five different land surface models. The identified drought events obtained by the new approach are compared to those resulting from application of the variable threshold level method or the consecutive dry period method separately. Results show that, in general, for drier regions, the threshold level method overestimates drought duration, because zero runoff periods are included in a drought, according to the definition used within this method. The consecutive dry period method underestimates drought occurrence, since it cannot identify droughts for periods with runoff. The developed method especially shows its relevance in transitional areas, because, in wetter regions, results are identical to the classical threshold level method. By combining both methods, the new method is able to identify single drought events that occur during positive and zero runoff periods, leading to a more realistic global drought characterization, especially within drier environments. |
282769 |
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| publications-776 |
PEER REVIEWED ARTICLE |
2013 |
M. H. J. van Huijgevoort , P. Hazenberg , H. A. J. van Lanen , A. J. Teuling , D. B. Clark , S. Folwell , S. N. Gosling , N. Hanasaki , J. Heinke , S. |
Global Multimodel Analysis of Drought in Runoff for the Second Half of the Twentieth Century |
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10.1175/jhm-d-12-0186.1 |
Uncategorized |
Uncategorized |
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Abstract During the past decades large-scale models have been developed to simulate global and continental terrestrial water cycles. It is an open question whether these models are suitable to capture hydrological drought, in terms of runoff, on a global scale. A multimodel ensemble analysis was carried out to evaluate if 10 such large-scale models agree on major drought events during the second half of the twentieth century. Time series of monthly precipitation, monthly total runoff from 10 global hydrological models, and their ensemble median have been used to identify drought. Temporal development of area in drought for various regions across the globe was investigated. Model spread was largest in regions with low runoff and smallest in regions with high runoff. In vast regions, correlation between runoff drought derived from the models and meteorological drought was found to be low. This indicated that models add information to the signal derived from precipitation and that runoff drought cannot directly be determined from precipitation data alone in global drought analyses with a constant aggregation period. However, duration and spatial extent of major drought events differed between models. Some models showed a fast runoff response to rainfall, which led to deviations from reported drought events in slowly responding hydrological systems. By using an ensemble of models, this fast runoff response was partly overcome and delay in drought propagating from meteorological drought to drought in runoff was included. Finally, an ensemble of models also allows for consideration of uncertainty associated with individual model structures. |
282769 |
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| publications-777 |
PEER REVIEWED ARTICLE |
2014 |
M.H.J. van Huijgevoort , H.A.J. van Lanen , A.J. Teuling , R. Uijlenhoet |
Identification of changes in hydrological drought characteristics from a multi-GCM driven ensemble constrained by observed discharge |
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10.1016/j.jhydrol.2014.02.060 |
Uncategorized |
Uncategorized |
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No abstract available |
282769 |
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| publications-778 |
PEER REVIEWED ARTICLE |
2013 |
H. A. J. Van Lanen , N. Wanders , L. M. Tallaksen , A. F. Van Loon |
Hydrological drought across the world: impact of climate and physical catchment structure |
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10.5194/hess-17-1715-2013 |
Uncategorized |
Uncategorized |
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Abstract. Large-scale hydrological drought studies have demonstrated spatial and temporal patterns in observed trends, and considerable difference exists among global hydrological models in their ability to reproduce these patterns. In this study a controlled modeling experiment has been set up to systematically explore the role of climate and physical catchment structure (soils and groundwater systems) to better understand underlying drought-generating mechanisms. Daily climate data (1958â2001) of 1495 grid cells across the world were selected that represent KöppenâGeiger major climate types. These data were fed into a conceptual hydrological model. Nine realizations of physical catchment structure were defined for each grid cell, i.e., three soils with different soil moisture supply capacity and three groundwater systems (quickly, intermediately and slowly responding). Hydrological drought characteristics (number, duration and standardized deficit volume) were identified from time series of daily discharge. Summary statistics showed that the equatorial and temperate climate types (A- and C-climates) had about twice as many drought events as the arid and polar types (B- and E-climates), and the durations of more extreme droughts were about half the length. Selected soils under permanent grassland were found to have a minor effect on hydrological drought characteristics, whereas groundwater systems had major impact. Groundwater systems strongly controlled the hydrological drought characteristics of all climate types, but particularly those of the wetter A-, C- and D-climates because of higher recharge. The median number of droughts for quickly responding groundwater systems was about three times higher than for slowly responding systems. Groundwater systems substantially affected the duration, particularly of the more extreme drought events. Bivariate probability distributions of drought duration and standardized deficit for combinations of KöppenâGeiger climate, soil and groundwater system showed that the responsiveness of the groundwater system is as important as climate for hydrological drought development. This urges for an improvement of subsurface modules in global hydrological models to be more useful for water resources assessments. A foreseen higher spatial resolution in large-scale models would enable a better hydrogeological parameterization and thus inclusion of lateral flow. |
282769 |
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| publications-779 |
PEER REVIEWED ARTICLE |
2012 |
A. F. Van Loon , H. A. J. Van Lanen |
A process-based typology of hydrological drought |
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10.5194/hess-16-1915-2012 |
Uncategorized |
Uncategorized |
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Abstract. Hydrological drought events have very different causes and effects. Classifying these events into distinct types can be useful for both science and management. We propose a hydrological drought typology that is based on governing drought propagation processes derived from catchment-scale drought analysis. In this typology six hydrological drought types are distinguished, i.e. (i) classical rainfall deficit drought, (ii) rain-to-snow-season drought, (iii) wet-to-dry-season drought, (iv) cold snow season drought, (v) warm snow season drought, and (vi) composite drought. The processes underlying these drought types are the result of the interplay of temperature and precipitation at catchment scale in different seasons. As a test case, about 125 groundwater droughts and 210 discharge droughts in five contrasting headwater catchments in Europe have been classified. The most common drought type in all catchments was the classical rainfall deficit drought (almost 50% of all events), but in the selected catchments these were mostly minor events. If only the five most severe drought events of each catchment are considered, a shift towards more rain-to-snow-season droughts, warm snow season droughts, and composite droughts was found. The occurrence of hydrological drought types is determined by climate and catchment characteristics. The drought typology is transferable to other catchments, including outside Europe, because it is generic and based upon processes that occur around the world. A general framework is proposed to identify drought type occurrence in relation to climate and catchment characteristics. |
282769 |
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| publications-780 |
PEER REVIEWED ARTICLE |
2012 |
A. F. Van Loon , M. H. J. Van Huijgevoort , H. A. J. Van Lanen |
Evaluation of drought propagation in an ensemble mean of large-scale hydrological models |
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10.5194/hess-16-4057-2012 |
Uncategorized |
Uncategorized |
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Abstract. Hydrological drought is increasingly studied using large-scale models. It is, however, not sure whether large-scale models reproduce the development of hydrological drought correctly. The pressing question is how well do large-scale models simulate the propagation from meteorological to hydrological drought? To answer this question, we evaluated the simulation of drought propagation in an ensemble mean of ten large-scale models, both land-surface models and global hydrological models, that participated in the model intercomparison project of WATCH (WaterMIP). For a selection of case study areas, we studied drought characteristics (number of droughts, duration, severity), drought propagation features (pooling, attenuation, lag, lengthening), and hydrological drought typology (classical rainfall deficit drought, rain-to-snow-season drought, wet-to-dry-season drought, cold snow season drought, warm snow season drought, composite drought). Drought characteristics simulated by large-scale models clearly reflected drought propagation; i.e. drought events became fewer and longer when moving through the hydrological cycle. However, more differentiation was expected between fast and slowly responding systems, with slowly responding systems having fewer and longer droughts in runoff than fast responding systems. This was not found using large-scale models. Drought propagation features were poorly reproduced by the large-scale models, because runoff reacted immediately to precipitation, in all case study areas. This fast reaction to precipitation, even in cold climates in winter and in semi-arid climates in summer, also greatly influenced the hydrological drought typology as identified by the large-scale models. In general, the large-scale models had the correct representation of drought types, but the percentages of occurrence had some important mismatches, e.g. an overestimation of classical rainfall deficit droughts, and an underestimation of wet-to-dry-season droughts and snow-related droughts. Furthermore, almost no composite droughts were simulated for slowly responding areas, while many multi-year drought events were expected in these systems. We conclude that most drought propagation processes are reasonably well reproduced by the ensemble mean of large-scale models in contrasting catchments in Europe. Challenges, however, remain in catchments with cold and semi-arid climates and catchments with large storage in aquifers or lakes. This leads to a high uncertainty in hydrological drought simulation at large scales. Improvement of drought simulation in large-scale models should focus on a better representation of hydrological processes that are important for drought development, such as evapotranspiration, snow accumulation and melt, and especially storage. Besides the more explicit inclusion of storage in large-scale models, also parametrisation of storage processes requires attention, for example through a global-scale dataset on aquifer characteristics, improved large-scale datasets on other land characteristics (e.g. soils, land cover), and calibration/evaluation of the models against observations of storage (e.g. in snow, groundwater). |
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