The German drought monitor

Zink, Matthias; Samaniego, Luis; Kumar, Rohini; Thober, Stephan; Mai, Juliane; Schäfer, David; Marx, Andréas

doi:10.1088/1748-9326/11/7/074002

Cited by 162 publications

(131 citation statements)

References 29 publications

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“…The total loss of the 2003 severe drought event was estimated to be EUR 8.7 billion in central and southern Europe (EC, 2007). More recently, the 2015 drought event (Laaha et al, 2017;Van Lanen et al, 2016;Zink et al, 2016) in central Europe also caused significant socio-economic and environmental problems. Economic losses due to droughts almost doubled between the 1976-1990 and 1991-2006 periods to approximately EUR 6.2 billion per year.…”

mentioning

confidence: 99%

Climate change alters low flows in Europe under global warming of 1.5, 2, and 3 °C

Marx

Kumar

Thober

et al. 2018

Hydrol. Earth Syst. Sci.

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178

136

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Abstract. There is growing evidence that climate change will alter water availability in Europe. Here, we investigate how hydrological low flows are affected under different levels of future global warming (i.e. 1.5, 2, and 3 K with respect to the pre-industrial period) in rivers with a contributing area of more than 1000 km 2 . The analysis is based on a multi-model ensemble of 45 hydrological simulations based on three representative concentration pathways (RCP2.6, RCP6.0, RCP8.5), five Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs: GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, NorESM1-M) and three state-of-theart hydrological models (HMs: mHM, Noah-MP, and PCR-GLOBWB). High-resolution model results are available at a spatial resolution of 5 km across the pan-European domain at a daily temporal resolution. Low river flow is described as the percentile of daily streamflow that is exceeded 90 % of the time. It is determined separately for each GCM/HM combination and warming scenario. The results show that the low-flow change signal amplifies with increasing warming levels. Low flows decrease in the Mediterranean region, while they increase in the Alpine and Northern regions. In the Mediterranean, the level of warming amplifies the signal from −12 % under 1.5 K, compared to the baseline period 1971-2000, to −35 % under global warming of 3 K, largely due to the projected decreases in annual precipitation. In contrast, the signal is amplified from +22 (1.5 K) to +45 % (3 K) in the Alpine region due to changes in snow accumulation. The changes in low flows are significant for regions with relatively large change signals and under higher levels of warming. However, it is not possible to distinguish climate-induced differences in low flows between 1.5 and 2 K warming because of (1) the large inter-annual variability which prevents distinguishing statistical estimates of periodaveraged changes for a given GCM/HM combination, and (2) the uncertainty in the multi-model ensemble expressed by the signal-to-noise ratio. The contribution by the GCMs to the uncertainty in the model results is generally higher than the one by the HMs. However, the uncertainty due to HMs cannot be neglected. In the Alpine, Northern, and Mediterranean regions, the uncertainty contribution by the HMs is partly higher than those by the GCMs due to different representations of processes such as snow, soil moisture and evapotranspiration. Based on the analysis results, it is recommended (1) to use multiple HMs in climate impact studies and (2) to embrace uncertainty information on the multimodel ensemble as well as its single members in the adaptation process.

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confidence: 99%

Climate change alters low flows in Europe under global warming of 1.5, 2, and 3 °C

Marx

Kumar

Thober

et al. 2018

Hydrol. Earth Syst. Sci.

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178

136

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“…Figure 13 displays the seasonality of groundwater heads over the whole catchment by means of calculating the long-term mean groundwater heads in spring, (the scale in this study), the MPR method shows a moderate improvement in groundwater recharge representation. Note that MPR has been successfully applied at a larger scale over Europe (Thober et al, 2015; 25 Kumar et al, 2013;Zink et al, 2016;Rakovec et al, 2016). The effectiveness of MPR to characterize groundwater dynamics at larger scales (e.g., 10 4 -10 6 km 2 ) even global scales is still unknown and needs to be explored.…”

Section: Model Evaluation Using Discharge and Groundwater Headsmentioning

confidence: 99%

Improved representation of groundwater at a regional scale – coupling of mesocale Hydrologic Model (mHM) with OpeneGeoSys (OGS)

Jing¹,

Heße²,

Wang³

et al. 2017

Preprint

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Abstract. Most of the current large scale hydrological models do not contain a physically-based groundwater flow component. The main difficulties in large-scale groundwater modeling include the efficient representation of unsaturated zone flow, the characterization of dynamic groundwater-surface water interaction and the numerical stability while preserving complex physical processes and high resolution. To address these problems, we propose a highly-scalable coupled hydrologic and groundwater model (mHM#OGS) based on the integration of two open-source modeling codes: the mesoscale hydrologic 5 Model (mHM) and the finite element simulator OpenGeoSys (OGS). mHM#OGS is coupled using a boundary condition-based coupling scheme that dynamically links the surface and subsurface parts. Nested time stepping allows smaller time steps for typically faster surface runoff routing in mHM and larger time steps for slower subsurface flow in OGS. mHM#OGS features the coupling interface which can transfer the groundwater recharge and river baseflow rate between mHM and OpenGeoSys.Verification of the coupled model was conducted using the time-series of observed streamflow and groundwater levels. More-10 over, we force the transient model using groundwater recharge in two scenarios: (1) spatially variable recharge based on the mHM simulations, and (2) spatially homogeneous groundwater recharge. The modeling result in first scenario has a slightly higher correlation with groundwater head time-series, which further validates the plausibility of spatial groundwater recharge distribution calculated by mHM in the mesocale. The statistical analysis of model predictions shows a promising prediction ability of the model. The offline coupling method implemented here can reproduce reasonable groundwater head time series 15 while keep a desired level of detail in the subsurface model structure with little surplus in computational cost. Our exemplary calculations show that the coupled model mHM#OGS can be a valuable tool to assess the effects of variability in land surface heterogeneity, meteorological, topographical forces and geological zonation on the groundwater flow dynamics. 1Geosci. Model Dev. Discuss., https://doi

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“…The monthly SMI values are categorized into seven classes which follow the notion of the US drought monitor and the German Drought Monitor (Zink et al, 2016). This stepwise approach allows to measure nonlinear effects of soil moisture.…”

Section: Soil Moisture Anomalies and Meteorologymentioning

confidence: 99%

“…These processing steps are also applied to the meteorological variables (P, T, E). The soil moisture fractions of each administrative district is then transformed into a percentile index (SMI) using the kernel density estimator explained above Thober et al, 2015;Zink et al, 2016). An index reduces the probability of measurement errors and the estimated coefficients in the regression models are supposed to be less prone to attenuation bias (Fisher et al, 2012;Auffhammer and Schlenker, 2014;5 Hsiang, 2016).…”

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confidence: 99%

“…The observation, that the SMI represents additional information to the meteorology is also pronounced by the fact that the pairwise correlations including SMI are lower compared to any other combination of the exogenous variables (Table 2). Further, dry anomalies in the late part of the season may indicate a long lasting water shortage condition, as soil moisture drought lasts over several month or potentially even years 20 (Sheffield and Wood, 2011;Samaniego et al, 2013;Zink et al, 2016).…”

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confidence: 99%

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The Effect of Soil Moisture Anomalies on Maize Yield in Germany

Peichl¹,

Thober²,

Meyer³

et al. 2017

Preprint

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Abstract. Crop models routinely use meteorological variations to estimate crop yield. Soil moisture, however, is the primary source of water for plant growth. The aim of this study is to investigate the intra-seasonal predictability of soil moisture to estimate silage maize yield in Germany. It is also evaluated how approaches considering soil moisture perform compared to those using only meteorological variables. Silage maize is one of the most widely cultivated crops in Germany because it is used as a main biomass supplier for energy production in the course of the German Energy Transition. Reduced form fixed 5 effect panel models are employed to investigate the relationships in this study. These models are estimated for each month of the growing season to gain insights into the time varying effects of soil moisture and meteorological variables. Temperature, precipitation, and potential evapotranspiration are used as meteorological variables. Soil moisture is transformed into anomalies which provide a measure for the inter-annual variation within each month. The main result of this study is that soil moisture anomalies have predictive skills which vary in magnitude and direction depending on the month. For instance, dry soil moisture 10 anomalies in August and September reduce silage maize yield more than 10 % other factors being equal. On the contrary, dry anomalies in May increase crop yield up to 7 % because absolute soil water content is higher in May compared to August due to its seasonality. With respect to the meteorological terms, models using both temperature and precipitation have higher predictabilities than models using only one meteorological variable. Also, models employing only temperature exhibit elevated effects.

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The German drought monitor

Cited by 162 publications

References 29 publications

Climate change alters low flows in Europe under global warming of 1.5, 2, and 3 °C

Climate change alters low flows in Europe under global warming of 1.5, 2, and 3 °C

Improved representation of groundwater at a regional scale – coupling of mesocale Hydrologic Model (mHM) with OpeneGeoSys (OGS)

The Effect of Soil Moisture Anomalies on Maize Yield in Germany

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The German drought monitor

Cited by 162 publications

References 29 publications

Climate change alters low flows in Europe under global warming of 1.5, 2, and 3 °C

Climate change alters low flows in Europe under global warming of 1.5, 2, and 3 °C

Improved representation of groundwater at a regional scale – coupling of mesocale Hydrologic Model (mHM) with OpeneGeoSys (OGS)

The Effect of Soil Moisture Anomalies on Maize Yield in Germany

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Climate change alters low flows in Europe under global warming of 1.5, 2, and 3 °C

Climate change alters low flows in Europe under global warming of 1.5, 2, and 3 °C