Abteilung Systemanalyse, Integrated Assessment und Modellierung

Study region: Northeast China
Study focus: Northeast China is one of the largest agricultural regions in the world and a strategically
important granary for China. Information on hydrological extremes is crucially important
for water management. Yet, comprehensive studies on hydrological extremes, both extreme flood
and drought events, based on hydrological gauge comprehensive and large coverage observations
are still lacking in Northeast China. This study investigated observed hydrological extremes with
124 hydrological gauges in the region ranging from the 1950s to present for the first time.
New hydrological insights for the region: We find that flood extremes, mean discharge and standardized
discharge are decreasing in over 80% of the gauges, and no gauges show significantly
increasing flood extremes. The findings suggest that sustainable water management strategies
should be employed to meet increasing water demand for long-term development. In addition, we
find that flood peak discharge and flood volume are significantly correlated in all the gauges,
motivating flood risk studies considering multiple flood variables together. Further, we quantify
probability changes of severe and extreme hydrological droughts, and find that the probability of
drought events is decreasing in most of the gauges, suggesting that the number of drought events
is reducing.
Data availability: Discharge data are from the hydrology bureau, and can be found by contacting
Songliao River Water Resources Commission, Ministry of Water Resources, the People’s Republic
of China (http://www.mwr.gov.cn/english/).

The inclusion of environmental flow requirements (EFRs) in global water scarcity assessments is essential to obtain a reasonable representation of the water scarcity status. However, at a global scale, the quantification of EFRs is subject to large uncertainties resulting from various methods. So far, it is unclear to what extent the uncertainties in EFRs affect global water scarcity assessments. In this study, we examined the differences between EFR estimation methods and quantified their effects on spatially explicit water scarcity assessments, based on reconstructed global water withdrawal data and naturalized streamflow simulations. The global mean EFRs estimated by different methods ranged from 129 m³ s⁻¹ to 572 m³ s⁻¹. Consequently, with the fulfillment of the EFRs, the area under water scarcity ranged between 8% and 52% of the total global land area, and the affected population ranged between 28% and 60% of the total population. In India and Northern China, 44%–66% and 22%–58% of the country's land area, respectively, is affected by water scarcity; this percentage is higher than that found in other countries. The effects of different EFRs on water scarcity assessment are large in many regions, but relatively small in regions that experience intensive water use due to anthropological activities (such as Northern China and India). Through this study, we have put forth the need for the reconciliation of the estimates of EFRs to produce more reasonable and consistent water scarcity assessments.

In hydrological modeling, the identification of model mechanisms best suited for representing individual hydrological (physical) processes is of major scientific and operational interest. We present a statistical hypothesis-testing perspective on this model identification challenge and contribute a mechanism identification framework that combines: (i) Bayesian estimation of posterior probabilities of individual mechanisms from a given ensemble of model structures; (ii) a test statistic that defines a “dominant” mechanism as a mechanism more probable than all its alternatives given observed data; and (iii) a flexible modeling framework to generate model structures using combinations of available mechanisms. The uncertainty in the test statistic is approximated using bootstrap sampling from the model ensemble. Synthetic experiments (with varying error magnitude and multiple replicates) and real data experiments are conducted using the hydrological modeling system FUSE (7 processes and 2–4 mechanisms per process yielding 624 feasible model structures) and data from the Leizarán catchment in northern Spain. The mechanism identification method is reliable: it identifies the correct mechanism as dominant in all synthetic trials where an identification is made. As data/model errors increase, statistical power (identifiability) decreases, manifesting as trials where no mechanism is identified as dominant. The real data case study results are broadly consistent with the synthetic analysis, with dominant mechanisms identified for 4 of 7 processes. Insights on which processes are most/least identifiable are also reported. The mechanism identification method is expected to contribute to broader community efforts on improving model identification and process representation in hydrology.

Socioeconomic development has led to increased consumption of both blue and green water. Consequently, China is facing serious water scarcity issue. However, few studies have investigated interactions of blue and green water footprints, as well as driving forces underlying the changes in water footprints across provinces and sectors. To fill in this knowledge gap, we quantified the spatial-temporal dynamics of the blue and green water footprint (BWF and GWF, respectively), and analyzed the key factors that drive the provincial-level changes in BWF and GWF from 2002 to 2012. The analysis is facilitated by the approaches of multi-region input-output analysis and structural decomposition analysis, and we developed one decoupling index to quantify the water-economy relation and substitution between green and blue water. The results show that China's BWF averaged at 161 billion m³/yr, about one-third the size of the GWF. In addition, water scarce provinces in Northern China were moving towards decoupling between economic growth and blue water consumption, with GWF playing an increasingly important role. The changes in the WFs were mainly influenced by changes in affluence (final demand per capita), technological improvements (decreased direct water consumption intensity), and consumption pattern (composition of the final demand) rather than changes in the population and export. Technology improvement, consumption pattern shift and industrial structure adjustment contribute to WF reductions, thus help improve water security and sustainability in China. This study provides a new approach to analyze water-economy relations for water scarce countries.