Download 21st century runoff sensitivities of major global river basins

GEOPHYSICAL RESEARCH LETTERS, VOL. 39, L06403, doi:10.1029/2011GL050834, 2012
21st century runoff sensitivities of major global river basins
Qiuhong Tang1,2 and Dennis P. Lettenmaier2
Received 31 December 2011; revised 22 February 2012; accepted 24 February 2012; published 21 March 2012.
[1] River runoff is a key index of renewable water
resources which affect almost all human and natural
systems. Any substantial change in runoff will therefore
have serious social, environmental, and ecological
consequences. We estimate the runoff response to global
mean temperature change implied by the climate change
experiments generated for the Fourth Assessment Report
of the Intergovernmental Panel on Climate Change (IPCC
AR4). In contrast to previous studies, we estimate the
runoff sensitivity using global mean temperature change as
an index of anthropogenic climate changes in temperature
and precipitation, with the rationale that this removes the
dependence on emissions scenarios. Our results show that
the runoff sensitivity implied by the IPCC experiments is
relatively stable across emissions scenarios and global
mean temperature increments, but varies substantially
across models with the exception of the high-latitudes and
currently arid or semi-arid areas. The runoff sensitivities
are slightly higher at 0.5 C warming than for larger
amounts of warming. The estimated ratio of runoff change
to (local) precipitation change (runoff elasticity) ranges
from about one to three, and the runoff temperature
sensitivity (change in runoff per degree C of local
temperature increase) ranges from decreases of about 2 to
6% over most basins in North America and the middle
and high latitudes of Eurasia. Citation: Tang, Q., and D. P.
to cumulative global greenhouse gas emissions, and in turn
to global mean temperature change [Murphy et al., 2004;
Watterson and Whetton, 2011]. We therefore take an
approach that differs somewhat from past studies of water
resources susceptibility to climate change for specific future
times [Arnell, 2003; Milly et al., 2005; Nohara et al., 2006],
and instead use an approach similar to a recent National
Research Council Report [National Research Council
(NRC), 2010] and compute relative runoff change per
degree C of increase in global mean temperature [Chiew
et al., 2009]. By so doing, the dependence on emissions
scenarios is mostly decoupled, as the global mean temperature change is a good index of cumulative emissions and
does not depend on the emission pathway [Matthews et al.,
2009]. It should be noted that the global mean temperature
(denoted as GMT hereafter) is an index which links global
climate change in temperature, precipitation (both amount
and intensity), and other climatic variables and changes in
land surface hydrology, but is not necessarily indicative of
the causes of the changes [Held and Soden, 2006]. The climate change experiments generated for the Fourth Assessment Report (AR4) of the Intergovernmental Panel on
Climate Change (IPCC) are used in this analysis, and our
inferred runoff sensitivity estimates are therefore reflective
of the state of the art of the AR4 GCMs.
Lettenmaier (2012), 21st century runoff sensitivities of major
global river basins, Geophys. Res. Lett., 39, L06403, doi:10.1029/
2011GL050834.
2. Data and Methods
1. Introduction
[2] Water is a vital resource for human well-being [Oki
and Kanae, 2006] and the functioning of ecosystems
[Zhao and Running, 2010]. Decreasing freshwater discharge
to the oceans and increasing global aridity have been
reported since the 1970s, in association with (although we
emphasize, not necessarily caused by) increases in global
mean temperature [Dai et al., 2009; Cayan et al., 2010].
Understanding predictions for future changes in runoff for
large global river basins is central to assessing the impact
of climate change on water resources [Vörösmarty et al.,
2000a]. However, there is considerable uncertainty in predictions of future changes in runoff from general circulation
models (GCMs) [Allen and Ingram, 2002].
[3] Future changes in the major climatic drivers of runoff
(especially precipitation and temperature) are closely related
1
Institute of Geographic Sciences and Natural Resources Research,
Chinese Academy of Sciences, Beijing, China.
2
Department of Civil and Environmental Engineering, University of
Washington, Seattle, Washington, USA.
Copyright 2012 by the American Geophysical Union.
0094-8276/12/2011GL050834
[4] The largest 194 river basins globally (by drainage
area) were identified from the Simulated Topological Network (STN-30p) [Vörösmarty et al., 2000b] and summarized in Table S1 in the auxiliary material.1 The total area
of the river basins is about 95 106 km2, covering 72% of
the global land surface area (excluding the Antarctica and
Greenland), 60% of the global population [Center for
International Earth Science Information Network, 2011],
and 50% of global Gross Domestic Product (GDP) [Yetman
et al., 2010].
[5] We analyzed model outputs from the IPCC SRES B1,
A1B, and A2 emissions scenarios for the 23 GCMs which
performed most of the experiments for these scenarios. The
relative runoff change was computed from the difference
between the basin-averaged runoff for 1971–2000 and the
30-year average for the future periods for GMT increments
that we prescribed (see auxiliary material). We calculated the
multimodel-ensemble medians (MMs) of relative runoff
change per degree of GMT increase (i.e. runoff sensitivity)
from different subsets of the GCMs, emissions scenarios,
and GMT increments to show the effects of emissions scenarios and GMT increment on the sensitivities. We did not
attempt to select models from the pool of AR4 models
1
Auxiliary materials are available in the HTML. doi:10.1029/
2011GL050834.
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TANG AND LETTENMAIER: 21ST CENTURY RUNOFF SENSITIVITIES
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Figure 1. Runoff sensitivities (percent per degree C GMT change) estimated from different subsets of models, emissions
scenarios and GMT increments. (a) Multimodel ensemble medians (MMs) for each of the three emissions scenarios (B2,
A1B, and A2) plotted against MMs across all emissions scenarios and GMT increments, and (b) MMs at each GMT increment plotted against MMs across all emissions scenarios and GMT increments. River basins are in the order of runoff
sensitivity (Table S1). The shaded area shows the inner quartile range of the ensemble values across all emissions scenarios
and GMT increments.
according to their performance, both because the superiority
of the multimodel ensemble method to any individual model
has been demonstrated in both global and regional studies
[Reichler and Kim, 2008; Pierce et al., 2009], and because
attempts to rank or weight AR4 models based on their performance have generally found that the results are highly
dependent on the evaluation criteria [Mote et al., 2011]. The
superiority of the MMs is largely caused by the cancellation
of offsetting errors in the individual global models [Pierce
et al., 2009]. The number of global basins with decreasing
runoff at the GMT increment, and associated global land
area, world population, and GDP, were also estimated. In
addition, we fit linear models [Anderson and Legendre,
1999] for each river basin using the 30-year average data
to analyze the runoff sensitivities to basin mean annual
precipitation change (b) and basin average temperature
change (a) (see auxiliary material).
3. Results
[6] Consistent with the rationale that the effects of cumulative emissions, rather than emissions pathways, are associated with the GMT rise [Allen et al., 2009], we found little
difference in the runoff sensitivities for different emissions
scenarios. Figure 1a shows the runoff sensitivity for each
river basin estimated using the multimodel-ensemble median
(MM) across all GMT increments for each emissions scenario (red, yellow, and blue lines) and MM across all emissions scenarios and GMT increments (black line). Estimates
for different emissions scenarios are generally similar to the
ensemble medians over the emissions scenarios. Figure 1b
shows the runoff sensitivity for each river basin estimated
as MM across all of the three emissions scenarios for each
GMT increment (colored lines) and the ensemble median
value across all emissions scenarios and GMT increments
(black line). The estimates are quite similar, with little difference aside from the values estimated from 0.5 C GMT
increase, which show slightly higher sensitivities than for
larger increases. The runoff sensitivities for large GMT
increases (over 1.0 C) are generally within the interquartile
range of the ensemble values across all emissions scenarios
and GMT increments.
[7] Most model runs agree as to the direction of changes in
runoff in the regions where the ensemble mean changes are
greatest. Figure 2 shows the runoff sensitivity estimated as
MM across all emissions scenarios and GMT increments
(same values as black lines in Figure 1), along with the
fraction of positive minus negative (FPN) estimates as in
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TANG AND LETTENMAIER: 21ST CENTURY RUNOFF SENSITIVITIES
Figure 2. Relative runoff change per degree warming. (a)
Multimodel-ensemble medians (MMs) across all emissions
scenarios and GMT increments for the 194 global river
basins. (b) FPN (fraction positive minus fraction negative)
for each river basin.
work by Milly et al. [2005] and NRC [2010]. FPN is calculated as the number of the ensemble members showing a
positive change minus the number showing a negative
change, divided by the total number of the ensemble members. Areas of prominent agreement are the high-latitudes
and currently arid or semi-arid areas. Runoff decreases are
projected in many temperate river basins outside Eurasia,
with the greatest decreases in areas that are currently arid or
semi-arid. Results show that projected drying of the southwestern United States extends east to the Gulf of Mexico
and south to the Caribbean Sea region. On the other hand,
the results show no obvious direction of runoff change in
the Amazon region, supporting neither a positive change
[Nohara et al., 2006] nor a negative change [Milly et al.,
2005] as suggested in previous studies (Figure 2a and
Table S1). In general, the number of river basins with
decreasing runoff, and subsequently effected global population and GDP, is expected to grow as GMT increases
(Figure S1). The portion of GDP increases much faster than
either the land area or population because expanding dry
areas are mostly in areas with high GDP such as the U.S.
Southwest and southern Europe.
[8] The runoff response along the trajectory of global
mean warming is approximately linear over most of the
global land area. Figure S2 (see auxiliary material) compares
the relative runoff change per degree of warming estimated
at 0.5 C increase in GMT with that estimated over all 5
GMT increments. Nonlinearities are most apparent in West
Africa, Central Australia, the U.S. South, and the southeastern part of continental Eurasia, with deviations from
linearity most apparent for small increments in GMT. The
nonlinearities, where most apparent, tend to stabilize for
larger increments in GMT (Figure S3). The apparent
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nonlinear responses of runoff to warming suggests that
current decadal trends (when GMT increase is less than
about 0.5 C) may not be representative of the long term
response.
[9] Figure 3 shows the runoff sensitivities to local mean
precipitation change and local temperature change among
the 194 global river basins. The inferred elasticities of runoff
with respect to mean annual precipitation (fractional change
in runoff per fractional change in local precipitation) generally range from 1.0 to 3.0 (Figure 3a and Table S1), i.e., a
10% change in mean annual precipitation results in a 10
to 30% change in mean annual runoff. This range is generally consistent with regional studies of precipitation elasticity from observations [Sankarasubramanian et al., 2001;
Chiew, 2006]. The lower runoff elasticities (<1.8) are in
mid latitudes of the Northern Hemisphere including North
Africa and basins with cold climates. The higher runoff
elasticities (>2.2) are in mid latitudes of the Southern
Hemisphere, Australia, equatorial Africa, eastern North
America, and eastern Asia.
[10] The estimated runoff sensitivity to local temperature
change (i.e., per degree C of local warming) is negative for
most river basins (Figure 3b and Table S1), and typically
ranges from 2 to 6 percent per degree of local warming,
with the largest sensitivities in absolute value in eastern
North America, southern Europe, and eastern Asia. The
estimated runoff sensitivity to local temperature change is
positive in a few river basins in Australia, northwest Africa,
and southern Asia. It should be noted that local air temperature increases have several potentially competing implications for runoff. First, higher temperatures are usually
associated with increased evaporation which implies
decreased runoff. Second, higher temperatures in most
models lead to increased frequency of extreme precipitation.
Figure 3. Runoff elasticities with respect to (a) basin mean
annual precipitation change and (b) temperature sensitivities
(percent per degree change in basin mean temperature) for
the 194 global river basins.
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Increased precipitation intensities generally imply increased
runoff [Wainwright and Parsons, 2002]. The relative magnitudes of these effects, however, vary among basins.
Figure 3 suggests that evaporation responses are the dominant effect in most river basins. The positive runoff sensitivities in Australia, northwest Africa, and southern Asia
suggest that increased extreme precipitation frequency may
offset the evaporation response in those water limited areas.
4. Summary and Conclusions
[11] Our results show that projected runoff sensitivities to
anthropogenic climate change are relatively stable across
emissions scenarios and GMT increments up to 2.5 C. The
runoff response, which includes runoff change in response to
changes in temperature, precipitation, and other climatic
variables, generally appears to be approximately linear with
respect to GMT change over most of the global land area.
However, the changes are relatively nonlinear in West
Africa, central Australia, the U.S. South, and the southeastern part of Eurasia when the GMT increment is small. In the
areas showing large nonlinearity, the sensitivity in runoff
per degree of GMT increase tends to be highest for small
GMT increments and to stabilize to smaller values when the
GMT increment is 1.0 C or larger.
[12] The estimated runoff sensitivity to mean annual precipitation change generally ranges from one to three. The
estimated runoff sensitivity to local temperature change is
negative over most river basins, with the exception of North
Africa, much of Australia, and other mostly arid areas. Over
most basins in North America, and the middle and high
latitudes of Eurasia, runoff sensitivities to local temperature
change range from 2 to 6% per degree of local temperature increase.
[13] The fact that runoff sensitivities are mostly approximately linear with respect to GMT rise (independent of the
emissions scenario) provides a compelling argument to view
inter-model differences in the context of increments of GMT
rise, rather than time slices, as has been done more commonly in the past. Furthermore, the fact that nonlinearities,
where apparent, tend to be highest for small GMT increments suggests that the effects of anthropogenic climate
change should not be extrapolated from recent hydrologic
trends. Nonetheless, it is important to emphasize that temperature changes (global or local) must be viewed as an
index to, rather than a causative factor of, runoff change.
What this work does show is that runoff changes in the IPCC
AR4 experiments track the predicted GMT changes in a
somewhat coherent manner, which is, aside from slight differences at the lowest GMT changes, linear, and which does
not depend on the emissions pathway.
[14] Acknowledgments. The genesis of some of the ideas reported in
this paper, notably exploring the relationship of runoff change per unit of
GMT change, came about when D. P. Lettenmaier served as a member of
the NRC Committee on Stabilization Targets for Atmospheric Greenhouse
Gas Concentrations [NRC, 2010], and the authors acknowledge the role that
those discussions had in development of the paper, especially conversations
with I. M. Held. The authors also appreciate the comments of P. C. D. Milly
on an earlier version of the paper. We thank J. Vano for her comments and
two anonymous reviewers for thoughtful comments and recommendations.
Financial support for this study came from the National Natural Science
Foundation of China (grant 41171031), National Basic Research Program
of China (grants 2012CB955403 and 2010CB950100), Strategic Priority
Research Program (grants XDA05080101) and Hundred Talents Program
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of the Chinese Academy of Sciences, and U.S. Department of Energy grant
DE-FG02-08ER64589 to the University of Washington.
[15] The Editor would like to thank two anonymous reviewers for their
assistance with this paper.
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D. P. Lettenmaier, Department of Civil and Environmental Engineering,
University of Washington, Seattle, WA 98195, USA.
Q. Tang, Institute of Geographic Sciences and Natural Resources
Research, Chinese Academy of Sciences, Beijing 100101, China.
([email protected])
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