Niko Wanders

Human water consumption intensifies hydrological drought worldwide

Over the past 50 years, human water use has more than doubled and affected streamflow over various regions of the world. However, it remains unclear to what degree human water consumption intensifies hydrological drought (the occurrence of anomalously low streamflow). Here, we quantify over the period 1960‐2010 the impact of human water consumption on the intensity and frequency of hydrological drought worldwide. The results show that human water consumption substantially reduced local and downstream streamflow over Europe, North America and Asia, and subsequently intensified the magnitude of hydrological droughts by 10‐500%, occurring during nation- and continent-wide drought events. Also, human water consumption alone increased global drought frequency by 27 ( 6)%. The intensification of drought frequency is most severe over Asia (35 7%), but also substantial over North America (25 6%) and Europe (20 5%). Importantly, the severe drought conditions are driven primarily by human water consumption over many parts of these regions. Irrigation is responsible for the intensification of hydrological droughts over the western and central US, southern Europe and Asia, whereas the impact of industrial and households’ consumption on the intensification is considerably larger over the eastern US and western and central Europe. Our findings reveal that human water consumption is one of the more important mechanisms intensifying hydrological drought, and is likely to remain as a major factor affecting drought intensity and frequency in the coming decades.

The benefits of using remotely sensed soil moisture in parameter identification of large‐scale hydrological models

Large-scale hydrological models are nowadays mostly calibrated using observed discharge. As a result, a large part of the hydrological system, in particular the unsaturated zone, remains uncalibrated. Soil moisture observations from satellites have the potential to fill this gap. Here we evaluate the added value of remotely sensed soil moisture in calibration of large-scale hydrological models by addressing two research questions: (1) Which parameters of hydrological models can be identified by calibration with remotely sensed soil moisture? (2) Does calibration with remotely sensed soil moisture lead to an improved calibration of hydrological models compared to calibration based only on discharge observations, such that this leads to improved simulations of soil moisture content and discharge? A dual state and parameter Ensemble Kalman Filter is used to calibrate the hydrological model LISFLOOD for the Upper Danube. Calibration is done using discharge and remotely sensed soil moisture acquired by AMSR-E, SMOS, and ASCAT. Calibration with discharge data improves the estimation of groundwater and routing parameters. Calibration with only remotely sensed soil moisture results in an accurate identification of parameters related to land-surface processes. For the Upper Danube upstream area up to 40,000 km2, calibration on both discharge and soil moisture results in a reduction by 10–30% in the RMSE for discharge simulations, compared to calibration on discharge alone. The conclusion is that remotely sensed soil moisture holds potential for calibration of hydrological models, leading to a better simulation of soil moisture content throughout the catchment and a better simulation of discharge in upstream areas.

How climate seasonality modifies drought duration and deficit

Drought propagation through the terrestrial hydrological cycle is associated with a change in drought characteristics (duration and deficit), moving from precipitation via soil moisture to discharge. Here we investigate climate controls on drought propagation with a modeling experiment in 1271 virtual catchments that differ only in climate type. For these virtual catchments we studied the bivariate distribution of drought duration and standardized deficit for the variables precipitation, soil moisture, and discharge. We found that for meteorological drought (below-normal precipitation), the bivariate distributions of drought characteristics have a linear shape in all climates and are thus not affected by seasonality in climate. Despite the linear shape of meteorological drought, soil moisture drought (below-normal storage in the unsaturated zone) and hydrological drought (below-normal water availability in aquifers, lakes, and/or streams) show strongly nonlinear shapes in drought characteristics in climates with a pronounced seasonal cycle in precipitation and/or temperature. These seasonality effects on drought propagation are found in monsoonal, savannah, and Mediterranean climate zones. In these regions, both soil moisture and discharge show deviating shapes in drought characteristics. The effect of seasonality on drought propagation is even stronger in cold seasonal climates (i.e., at high latitudes and altitudes), where snow accumulation during winter prevents recovery from summer hydrological drought, and deficit increases strongly with duration. This has important implications for water resources management in seasonal climates, which cannot solely rely on meteorology-based indices as proxies for hydrological drought duration and deficit and need to include seasonal variation in both precipitation and temperature in hydrological drought forecasting.

A Preliminary Study toward Consistent Soil Moisture from AMSR2

AbstractA preliminary study toward consistent soil moisture products from the Advanced Microwave Scanning Radiometer 2 (AMSR2) is presented. Its predecessor, the Advanced Microwave Scanning Radiometer for Earth Observing System (AMSR-E), has provided Earth scientists with a consistent and continuous global soil moisture dataset. A major challenge remains to achieve synergy between these soil moisture datasets, which is hampered by the lack of an overlapping observation period of the sensors. Here, observations of the multifrequency microwave radiometer on board the Tropical Rainfall Measuring Mission (TRMM) satellite were used to improve consistency between AMSR-E and AMSR2. Several scenarios to achieve synergy between the AMSR-E and AMSR2 soil moisture products were evaluated. The novel soil moisture retrievals from C-band observations, a frequency band that is lacking on board the TRMM satellite, are also presented. A global comparison of soil moisture retrievals against ERA-Interim soil moisture demons...

Forecasting the Hydroclimatic Signature of the 2015/16 El Niño Event on the Western United States

AbstractDry conditions in 2013–16 in much of the western United States were responsible for severe drought and led to an exceptional fire season in the Pacific Northwest in 2015. Winter 2015/16 was forecasted to relieve drought in the southern portion of the region as a result of increased precipitation due to a very strong El Nino signal. A student forecasting challenge is summarized in which forecasts of winter hydroclimate across the western United States were made on 1 January 2016 for the winter hydroclimate using several dynamical and statistical forecast methods. They show that the precipitation forecasts had a large spread and none were skillful, while anomalously high observed temperatures were forecasted with a higher skill and precision. The poor forecast performance, particularly for precipitation, is traceable to high uncertainty in the North American Multi-Model Ensemble (NMME) forecast, which appears to be related to the inability of the models to predict an atmospheric blocking pattern ove...

Intensification of hydrological drought in California by human water management

We analyze the contribution of human water management to the intensification or mitigation of hydrological drought over California using the PCR-GLOBWB hydrological model at 0.5° resolution for the period 1979–2014. We demonstrate that including water management in the modeling framework results in more accurate discharge representation. During the severe 2014 drought, water management alleviated the drought deficit by ∼50% in Southern California through reservoir operation during low-flow periods. However, human water consumption (mostly irrigation) in the Central Valley increased drought duration and deficit by 50% and 50–100%, respectively. Return level analysis indicates that there is more than 50% chance that the probability of occurrence of an extreme 2014 magnitude drought event was at least doubled under the influence of human activities compared to natural variability. This impact is most significant over the San Joaquin Drainage basin with a 50% and 75% likelihood that the return period is more than 3.5 and 1.5 times larger, respectively, because of human activities.We analyze the contribution of human water management to the intensification and mitigation of hydrological drought over California using the PCR-GLOBWB hydrological model for the period 1979-2014. We demonstrate that considering water management results in more accurate discharge representation. During the severe 2014 drought, water management alleviated the drought deficit by ?50% in Southern California through reservoir operation during low flow periods. However, human water consumption (mostly irrigation) in the Central Valley increased drought duration and deficit by 50% and 50-100%, respectively. Return level analysis indicates that there is more than 50% chance that the probability of occurrence of an extreme 2014-magnitude drought event was at least doubled under the influence of human activities compared to natural variability. This impact is most significant over the San Joaquin Drainage basin with a 50% and 75% likelihood that the return period is more than 3.5 and 1.5 times larger, respectively, because of human activities.

Decadal predictability of river discharge with climate oscillations over the 20th and early 21st century

Long-term hydrological forecasts are important to increase our resilience and preparedness to extreme hydrological events. The skill in these forecasts is still limited due to large uncertainties inherent in hydrological models and poor predictability of long-term meteorological conditions. Here we show that strong (lagged) correlations exist between four different major climate oscillation modes and modeled and observed discharge anomalies over a 100 year period. The strongest correlations are found between the El Nino-Southern Oscillation signal and river discharge anomalies all year round, while North Atlantic Oscillation and Antarctic Oscillation time series are strongly correlated with winter discharge anomalies. The correlation signal is significant for periods up to 5 years for some regions, indicating a high added value of this information for long-term hydrological forecasting. The results suggest that long-term hydrological forecasting could be significantly improved by including the climate oscillation signals and thus improve our preparedness for hydrological extremes in the near future.

Integrating remotely sensed surface water extent into continental scale hydrology

Highlights • First continent-scale assimilation of surface water extent into hydrological model.• Improvements in flood peaks timing and volume for 60% of validated gauges.• Daily surface water extent provide promising opportunities for ungauged regions.

Anthropogenic warming exacerbates European soil moisture droughts

Anthropogenic warming is anticipated to increase soil moisture drought in the future. However, projections are accompanied by large uncertainty due to varying estimates of future warming. Here, using an ensemble of hydrological and land-surface models, forced with bias-corrected downscaled general circulation model output, we estimate the impacts of 1–3 K global mean temperature increases on soil moisture droughts in Europe. Compared to the 1.5 K Paris target, an increase of 3 K—which represents current projected temperature change—is found to increase drought area by 40% (±24%), affecting up to 42% (±22%) more of the population. Furthermore, an event similar to the 2003 drought is shown to become twice as frequent; thus, due to their increased occurrence, events of this magnitude will no longer be classified as extreme. In the absence of effective mitigation, Europe will therefore face unprecedented increases in soil moisture drought, presenting new challenges for adaptation across the continent.Severe drought plagued Europe in 2003, amplifying heatwave conditions that killed more than 30,000 people. Assuming business as usual, such soil moisture deficits will become twice as frequent in the future and affect up to two-thirds of the European population.

Assessing Seasonal Climate Forecasts over Africa to Support Decision-Making : Bridging Science and Policy Implication for Managing Climate Extremes

Recent drought events like in the 2011 Horn of Africa and the ongoing drought in California have an enormous impact on nature and society. Reliable seasonal weather outlooks are critical for drought management and other applications like, crop modelling, flood forecasting and planning of reservoir operation, and would help reduce the potential economic damage from extremes as well as help optimize crop yields during more normal weather years from improved agricultural management. However, most seasonal forecasts are limited by low spatial and temporal model resolutions. The newly released North American Multi-Model Ensemble phase 2 (NMME-2), provides subseasonal forecast that increase the temporal resolution from monthly to daily, enabling subseasonal forecasting for end-user applications that rely on a daily temporal resolution. In this study we give an overview of the current status of the NMME subseasonal forecasts ensembles, their skill over the African continent and the forecast skill of the ensembles for applications related to agriculture and hydrology. We show that the NMME-2 subseasonal forecasts are significantly skilful for both precipitation and 2 m air temperature for large parts of Africa. The precipitation forecasts are skilful up to a lead time of two months, while temperature anomaly forecasts have a significant skill beyond the three months lead for most of Africa. Potential applications that would benefit from the new NMME-2 ensemble were studied in more detail for West Africa. We show that the models have a significant skill in forecasting the onset of the annual rain season in West Africa, and thereby the start of the growing season. Additionally, the models have a significant forecast skill to predict the onset and peak of the high flow season for most parts of West Africa. The low uncertainty in the forecasts compared to the observed anomalies indicates that local stakeholders will benefit from the high temporal resolution that the NMME-2 provides. Results encourage future research into the potential of the new subseasonal NMME-2 forecast ensemble to forecast more specific end-user applications and climate services, which require skilful high temporal resolution forecasts.