Extremeness of recent drought events in Switzerland: dependence on variable and return period choice

Brunner, Manuela Irene; Liechti, Katharina; Zappa, Massimiliano

doi:10.5194/nhess-19-2311-2019

Cited by 47 publications

(52 citation statements)

References 41 publications

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“…Results of this study showed that the total days and maximum duration of SM drought stress was generally highest in 2018, making this event more severe than earlier (recent) benchmark events, such as 2003. The long nature of the drought of 2018 was also found in a recent study for Switzerland, the country directly south of our study region, in Brunner et al, (2019). We also found that the annual maximum duration and total time of SM drought stress never exceeded 6 months, and most of the root zones reached field capacity again each year before the start of the new growing season.…”

Section: Discussionsupporting

confidence: 90%

Controls on the development and persistence of soil moisture drought across Southwestern Germany

Tijdeman

Menzel

2020

Preprint

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Abstract. The drought of 2018 in Central and Northern Europe showed once more the large impact this natural hazard can have on the environment and society. Such droughts are often seen as slowly developing phenomena. However, root zone soil moisture deficits can rapidly develop during periods of lacking precipitation and meteorological conditions that favour high evapotranspiration rates. These periods of soil moisture drought stress can persist for as long as the meteorological drought conditions last, thereby negatively affecting vegetation and crop health. In this study, we aim to characterize past soil moisture drought stress events over the cropland of South-Western Germany as well as to relate the characteristics of these past events to different soil and climate properties. We first simulated daily soil moisture over the period 1989–2018 on a 1-km resolution grid using the physical based hydrological model TRAIN. We then derived various soil moisture drought stress characteristics; likelihood, development time and persistence, from the simulated time series of all agricultural grid cells (n ≈ 15 000). Logistic regression and correlation were then applied to relate the derived characteristics to the storage capacity of the root zone as well as to the climatological setting. Results reveal that the majority of the agricultural grid cells across the study region reached soil moisture drought stress during prominent drought years. The development time of these soil moisture drought stress events varied substantially, from as little as 10 days to up to 4 months. The persistence of soil moisture drought stress varied as well and was especially high for the drought of 2018. The dominant control on the likelihood and development time of soil moisture drought stress was found to be the storage capacity of the root zone, whereas the persistence was not strongly linearly related to any of the considered controls. Overall, results give insights in the large spatial and temporal variability of soil moisture drought stress characteristics and highlight the importance of considering differences in root zone soil storage for agricultural drought assessments.

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Section: Discussionsupporting

confidence: 90%

Controls on the development and persistence of soil moisture drought across Southwestern Germany

Tijdeman

Menzel

2020

Preprint

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“…The flood threshold is fixed at the 25th percentile of the annual maximum time series of each catchment separately to guarantee a balanced number of extracted events across catchments (Schlef et al, 2019). The drought threshold is fixed at the highest value of the annual minimum time series and the time series smoothed over a window of 30 years to limit the extraction of dependent events (Brunner et al, 2019d;Tallaksen and Hisdal, 1997).…”

Section: Regime Clustering and Classificationmentioning

confidence: 99%

Future streamflow regime changes in the United States: assessment using functional classification

Brunner

Melsen

Newman

et al. 2020

Hydrol. Earth Syst. Sci.

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Abstract. Streamflow regimes are changing and expected to further change under the influence of climate change, with potential impacts on flow variability and the seasonality of extremes. However, not all types of regimes are going to change in the same way. Climate change impact assessments can therefore benefit from identifying classes of catchments with similar streamflow regimes. Traditional catchment classification approaches have focused on specific meteorological and/or streamflow indices, usually neglecting the temporal information stored in the data. The aim of this study is 2-fold: (1) develop a catchment classification scheme that enables incorporation of such temporal information and (2) use the scheme to evaluate changes in future flow regimes. We use the developed classification scheme, which relies on a functional data representation, to cluster a large set of catchments in the conterminous United States (CONUS) according to their mean annual hydrographs. We identify five regime classes that summarize the behavior of catchments in the CONUS: (1) intermittent regime, (2) weak winter regime, (3) strong winter regime, (4) New Year's regime, and (5) melt regime. Our results show that these spatially contiguous classes are not only similar in terms of their regimes, but also their flood and drought behavior as well as their physiographical and meteorological characteristics. We therefore deem the functional regime classes valuable for a number of applications going beyond change assessments, including model validation studies or predictions of streamflow characteristics in ungauged basins. To assess future regime changes, we use simulated discharge time series obtained from the Variable Infiltration Capacity hydrologic model driven with meteorological time series generated by five general circulation models. A comparison of the future regime classes derived from these simulations with current classes shows that robust regime changes are expected only for currently melt-influenced regions in the Rocky Mountains. These changes in mountainous, upstream regions may require adaption of water management strategies to ensure sufficient water supply in dependent downstream regions. Highlights. Functional data clustering enables formation of clusters of catchments with similar hydrological regimes and a similar drought and flood behavior. We identify five streamflow regime clusters: (1) intermittent regime, (2) weak winter regime, (3) strong winter regime, (4) New Year's regime, and (5) melt regime. Future regime changes are most pronounced for currently melt-dominated regimes in the Rocky Mountains. Functional regime clusters have widespread utility for predictions in ungauged basins and hydroclimate analyses.

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“…The flood threshold is fixed at the 25th percentile of the annual maxima time series of each catchment separately to guarantee a balanced number of extracted events across catchments (Schlef et al, 2019). The drought threshold is fixed at the highest value of the annual minimum time series and the time series smoothed over a window of 30 years to limit the extraction of dependent events (Brunner et al, 2019d;Tallaksen and Hisdal, 1997).…”

Section: Regime Clustering and Classificationmentioning

confidence: 99%

Future streamflow regime changes in the United States: assessment using functional classification

Brunner¹,

Melsen²,

Newman³

et al. 2020

Preprint

Self Cite

View full text Add to dashboard Cite

Abstract. Streamflow regimes are changing and expected to further change under the influence of climate change with potential impacts on flow variability and the seasonality of extremes. However, not all types of regimes are going to change in the same way. Climate change impact assessments can therefore benefit from identifying classes of catchments with similar streamflow regimes. Traditional catchment classification approaches have focused on specific meteorological and/or streamflow indices usually neglecting the temporal information stored in the data. The aim of this study is two-fold: (1) develop a catchment classification scheme that allows for the incorporation of such temporal information and (2) use the scheme to evaluate changes in future flow regimes. We use the developed classification scheme, which relies on a functional data representation, to cluster a large set of catchments in the conterminous United States (CONUS) according to their mean annual hydrographs. We identify five regime classes that summarize the behavior of catchments in the CONUS: (1) Intermittent regime, (2) weak winter regime, (3) strong winter regime, (4) New Year's regime, and (5) melt regime. Our results show that these spatially contiguous classes are not only similar in terms of their regimes, but also their flood and drought behavior, as well as their physiographical and meteorological characteristics. We therefore deem the functional regime classes valuable for a number of applications going beyond change assessments including model validation studies or the prediction of streamflow characteristics in ungauged basins. To assess future regime changes, we use simulated discharge time series obtained from the Variable Infiltration Capacity hydrologic model driven with meteorological time series generated by five general circulation models. A comparison of the future regime classes derived from these simulations with current classes shows that robust regime changes are expected only for currently melt-influenced regions in the Rocky Mountains. These changes in mountainous, upstream regions may require the adaptation of water management strategies to ensure sufficient water supply in dependent downstream regions.

show abstract

Extremeness of recent drought events in Switzerland: dependence on variable and return period choice

Cited by 47 publications

References 41 publications

Controls on the development and persistence of soil moisture drought across Southwestern Germany

Controls on the development and persistence of soil moisture drought across Southwestern Germany

Future streamflow regime changes in the United States: assessment using functional classification

Future streamflow regime changes in the United States: assessment using functional classification

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