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Droughts that exceed the magnitudes of historical variation ranges could occur increasingly frequently under future climate conditions. However, the time of the emergence of unprecedented drought conditions under climate change has rarely been examined. Here, using multimodel hydrological simulations, we investigate the changes in the frequency of hydrological drought (defined as abnormally low river discharge) under high and low greenhouse gas concentration scenarios and existing water resource management measures and estimate the timing of the first emergence of unprecedented regional drought conditions. When investigating 59 subcontinental-scale regions, the times are detected for 11 and 18 regions under low and high greenhouse gas concentration scenarios, respectively. Three regions (Southwestern South America, Mediterranean Europe, and Northern Africa) exhibit particularly robust and early timings under the high-emission scenario. These three regions are likely to confront unprecedented conditions within the next 30 years with a high likelihood regardless of the emission scenarios. Additionally, the results obtained herein demonstrate the benefits of the lower-emission pathway in reducing the likelihood of emergence. The Paris Agreement goals are shown to be effective in reducing the likelihood to the unlikely level in most regions. However, appropriate and prior adaptation measures are considered indispensable when facing unprecedented drought conditions. The results of this study underscore the importance of improving drought preparedness within the considered time horizons.

Better quantification of continental water storage variations is expected to improve our understanding of water flows, including evapotranspiration, runoff and river discharge as well as human water abstractions. For the first time, total water storage (TWS) on the land area of the globe as computed by the global water model WaterGAP (Water Global Assessment and Prognosis) was compared to both gravity recovery and climate experiment (GRACE) and global positioning system (GPS) observations. The GRACE satellites sense the effect of TWS on the dynamic gravity field of the Earth. GPS reference points are displaced due to crustal deformation caused by time-varying TWS. Unfortunately, the worldwide coverage of the GPS tracking network is irregular, while GRACE provides global coverage albeit with low spatial resolution. Detrended TWS time series were analyzed by determining scaling factors for mean annual amplitude (f GRACE) and time series of monthly TWS (f GPS). Both GRACE and GPS indicate that WaterGAP underestimates seasonal variations of TWS on most of the land area of the globe. In addition, seasonal maximum TWS occurs 1 month earlier according to WaterGAP than according to GRACE on most land areas. While WaterGAP TWS is sensitive to the applied climate input data, none of the two data sets result in a clearly better fit to the observations. Due to the low number of GPS sites, GPS observations are less useful for validating global hydrological models than GRACE observations, but they serve to support the validity of GRACE TWS as observational target for hydrological modeling. For unknown reasons, WaterGAP appears to fit better to GPS than to GRACE. Both GPS and GRACE data, however, are rather uncertain due to a number of reasons, in particular in dry regions. It is not possible to benefit from either GPS or GRACE observations to monitor and quantify human water abstractions if only detrended (seasonal) TWS variations are considered. Regarding GRACE, this is mainly caused by the attenuation of the TWS differences between water abstraction variants due to the filtering required for GRACE TWS. Regarding GPS, station density is too low. Only if water abstractions lead to long-term changes in TWS by depletion or restoration of water storage in groundwater or large surface water bodies, GRACE may be used to support the quantification of human water abstractions.

In the version of this Article originally published, in the section ‘Defining endorheic regions’ in Methods, the sentence starting “These watersheds were aggregated…” contained the phrase “(~100,000 thousand km2)”; this should have read (~100,000 km2) and has now been amended.

DC-Remissions-Eichkurven fur definierte Konzentrationsbereiche lassen sich mittels der Gleichung: ln S=a · Fb (bzw. ln S=a · Hb) weitgehend linearisieren. Dabei bedeuten F = Peakflachen, H = Peakhohen und S = passende Skalenteile fur die Substanzmenge. Im Rahmen des DC-Methodenfehlers werden gute Ubereinstimmungen zwischen Rechner-Geraden und Mesdaten erhalten, wie an 10 Beispielen von Arzneistoffen gezeigt wird. Fur enge Eichbereiche genugt meist schon eine Kurvenanpassung mit einer Potenzfunktion ohne Logarithmierung der S-Werte. Eine Arbeitstechnik, die zu guten Ergebnissen fuhrt, wird beschrieben.

Ca. 0,8 mVal Nitril in 50 ml Tetrahydrofuran werden mit 10 ml 0,5 M LiAlH4-Losung 15 min gekocht. Der Uberschus an Reagens wird vorsichtig mit 10 ml 10 N wasriger Natronlauge zersetzt, die wasrige Phase mit Aerosil 200 verdickt, die organische Phase mit dem entstandenen Amin zu 0,1 N Salzsaure dekantiert und mit 0,1 N Natronlauge potentiometrisch titriert. Von den untersuchten 18 Nitrilen ergaben 13 Resultate zwischen 96 und 100%.