Improved understanding of regional groundwater  drought development through time series modelling:  the 2018–2019 drought in the Netherlands

Brakkee, Esther; Huijgevoort, M.H.J. van; Bartholomeus, R.P.

doi:10.5194/hess-26-551-2022

Cited by 28 publications

(15 citation statements)

References 45 publications

(95 reference statements)

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“…Compared to these episodes, the drought of 2018 in the study area was generally more extreme in terms of the duration and severity of precipitation, soil moisture, and river flow deficits, which is in line with findings for northern Europe and Switzerland (respectively Bakke et al, 2020;Brunner et al, 2019). Our study further revealed a multi-year nature of the drought of 2018 that made the event more impactful, which is in line with drought impacts that were reported in the media for Germany over this prolonged period (De Brito et al, 2020) and findings for the groundwater drought in the Netherlands (Brakkee et al, 2022). Hydrological droughts for part of the catchments and wells persisted far into 2019.…”

Section: Typical Droughts and Their Hazard And Impact Characteristicssupporting

confidence: 91%

Different drought types and the spatial variability in their hazard, impact, and propagation characteristics

Tijdeman

Blauhut

Stoelzle

et al. 2022

Nat. Hazards Earth Syst. Sci.

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Abstract. Droughts often have a severe impact on the environment, society, and the economy. The variables and scales that are relevant to understand the impact of drought motivated this study, which compared hazard and propagation characteristics, as well as impacts, of major droughts between 1990 and 2019 in southwestern Germany. We bring together high-resolution datasets of air temperature, precipitation, soil moisture simulations, and streamflow and groundwater level observations, as well as text-based information on drought impacts. Various drought characteristics were derived from the hydrometeorological and drought impact time series and compared across variables and spatial scales. Results revealed different drought types sharing similar hazard and impact characteristics. The most severe drought type identified is an intense multi-seasonal drought type peaking in summer, i.e., the events in 2003, 2015, and 2018. This drought type appeared in all domains of the hydrological cycle and coincided with high air temperatures, causing a high number of and variability in drought impacts. The regional average drought signals of this drought type exhibit typical drought propagation characteristics such as a time lag between meteorological and hydrological drought, whereas propagation characteristics of local drought signals are variable in space. This spatial variability in drought hazard increased when droughts propagated through the hydrological cycle, causing distinct differences among variables, as well as regional average and local drought information. Accordingly, single variable or regional average drought information is not sufficient to fully explain the variety of drought impacts that occurred, supporting the conclusion that in regions as diverse as the case study presented here, large-scale drought monitoring needs to be complemented by local drought information to assess the multifaceted impact of drought.

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Section: Typical Droughts and Their Hazard And Impact Characteristicssupporting

confidence: 91%

Different drought types and the spatial variability in their hazard, impact, and propagation characteristics

Tijdeman

Blauhut

Stoelzle

et al. 2022

Nat. Hazards Earth Syst. Sci.

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“…During the validation period, the model overestimates the head in the summer months. These summers were particularly dry (e.g., Brakkee et al, 2022), and possibly stresses not included in the model (e.g., pumping for irrigation) could explain these deviations, but this has not been investigated here.…”

Section: Example Results At One Observation Wellmentioning

confidence: 98%

“…Dry summers and the growing demand for freshwater increases the pressure on limited groundwater resources. The groundwater table may drop significantly during and after dry summers (e.g., Brakkee et al, 2022) due to a set of stresses on the system including a decrease in precipitation, an increase in evaporation and transpiration, lower surface water levels, and higher groundwater use for both drinking water and irrigation (e.g., Van Loon et al, 2016). The effect of pumping wells on the head is one of the few stresses on the system that can be controlled.…”

Section: Introductionmentioning

confidence: 99%

Application of Time Series Analysis to Estimate Drawdown From Multiple Well Fields

Brakenhoff¹,

Vonk

Collenteur

et al. 2022

Front. Earth Sci.

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In 2018–2020, meteorological droughts over Northwestern Europe caused severe declines in groundwater heads with significant damage to groundwater-dependent ecosystems and agriculture. The response of the groundwater system to different hydrological stresses is valuable information for decision-makers. In this paper, a reproducible, data-driven approach using open-source software is proposed to quantify the effects of different hydrological stresses on heads. A scripted workflow was developed using the open-source Pastas software for time series modeling of heads. For each head time series, the best model structure and relevant hydrological stresses (rainfall, evaporation, river stages, and pumping at one or more well fields) were selected iteratively. A new method was applied to model multiple well fields with a single response function, where the response was scaled by the distances between the pumping and observation wells. Selection of the best model structure was performed through reliability checking based on four criteria. The time series model of each observation well represents an independent estimate of the contribution of different hydrological stresses to the head and is based exclusively on observed data. The approach was applied to estimate the drawdown caused by nearby well fields to 250 observed head time series measured at 122 locations in the eastern part of the Netherlands, a country where summer droughts can cause problems, even though the country is better known for problems with too much water. Reliable models were obtained for 126 head time series of which 78 contain one or more well fields as a contributing stress. The spatial variation of the modeled responses to pumping at the well fields show the expected decline with distance from the well field, even though all responses were modeled independently. An example application at one well field showed how the head response to pumping varies per aquifer. Time series analysis was used to determine the feasibility of reducing pumping rates to mitigate large drawdowns during droughts, which depends on the magnitude and response time of the groundwater system to changes in pumping. This is salient information for decision-makers. This article is part of the special issue “Rapid, Reproducible, and Robust Environmental Modeling for Decision Support: Worked Examples and Open-Source Software Tools”.

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“…The models developed in this study were primarily used to improve the understanding of the groundwater systems in Switzerland. In future studies, the models can be used for other purposes as well, for example for the hindcasting of heads to study long-term groundwater drought developments (e.g., Brakkee et al, 2022), or the short-term forecasting of heads (e.g., Mackay et al, 2014). Apart from practical applications, more work is required to further improve the application and robustness of the presented workflow, although high accuracy in the modeled groundwater dynamics was already obtained.…”

Section: Discussionmentioning

confidence: 99%

Analysis of nationwide groundwater monitoring networks using lumped-parameter models

Collenteur¹,

Moeck²,

Schirmer³

et al. 2023

Preprint

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Many countries maintain nationwide groundwater networks to monitor the status of their groundwater resources. For effective groundwater resource management, it is fundamental to understand the groundwater dynamics measured in the individual monitoring wells. Nationwide monitoring networks typically cover multiple aquifer systems with different degrees of environmental complexity. The analysis of the data of such networks thus requires flexible modeling approaches. In this study, we assessed the applicability and performance of lumped-parameter models using impulse response functions, as implemented in the Pastas software, to simulate hydraulic head data from the nationwide groundwater monitoring network in Switzerland. The selected 28 monitoring wells in the network are situated in unconsolidated, relatively shallow aquifers across Switzerland. Given the very diverse topography in the study area, snowmelt processes affect some aquifers, while groundwater-surface water interactions are important in the valleys. Different linear and nonlinear models were tested to take precipitation and potential evaporation into account, with a new model developed as part of this study to account for the effect of snow processes on recharge generation. After generally good fits in both the calibration and evaluation were achieved, the models were used to identify and quantify which stresses (e.g., precipitation, river stages) control the groundwater dynamics. The results show that precipitation and evaporation explain large parts of the measured dynamics, and about half of the monitoring wells in the network appear to be influenced by river stages. Explicitly accounting for snow processes in the recharge generating process is found to improve the simulation of the head dynamics across Switzerland, particularly for wells in high-altitude aquifers. This study demonstrates for the first time the applicability of lumped-parameter models using impulse response functions to model heads in Switzerland, and more generally, in climatic settings where snow processes are impacting the head dynamics.

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Improved understanding of regional groundwater drought development through time series modelling: the 2018–2019 drought in the Netherlands

Cited by 28 publications

References 45 publications

Different drought types and the spatial variability in their hazard, impact, and propagation characteristics

Different drought types and the spatial variability in their hazard, impact, and propagation characteristics

Application of Time Series Analysis to Estimate Drawdown From Multiple Well Fields

Analysis of nationwide groundwater monitoring networks using lumped-parameter models

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