Qiuhong Tang

Multimodel assessment of water scarcity under climate change

Water scarcity severely impairs food security and economic prosperity in many countries today. Expected future population changes will, in many countries as well as globally, increase the pressure on available water resources. On the supply side, renewable water resources will be affected by projected changes in precipitation patterns, temperature, and other climate variables. Here we use a large ensemble of global hydrological models (GHMs) forced by five global climate models and the latest greenhouse-gas concentration scenarios (Representative Concentration Pathways) to synthesize the current knowledge about climate change impacts on water resources. We show that climate change is likely to exacerbate regional and global water scarcity considerably. In particular, the ensemble average projects that a global warming of 2 °C above present (approximately 2.7 °C above preindustrial) will confront an additional approximate 15% of the global population with a severe decrease in water resources and will increase the number of people living under absolute water scarcity (<500 m3 per capita per year) by another 40% (according to some models, more than 100%) compared with the effect of population growth alone. For some indicators of moderate impacts, the steepest increase is seen between the present day and 2 °C, whereas indicators of very severe impacts increase unabated beyond 2 °C. At the same time, the study highlights large uncertainties associated with these estimates, with both global climate models and GHMs contributing to the spread. GHM uncertainty is particularly dominant in many regions affected by declining water resources, suggesting a high potential for improved water resource projections through hydrological model development.

Constraints and potentials of future irrigation water availability on agricultural production under climate change

Significance Freshwater availability is relevant to almost all socioeconomic and environmental impacts of climate and demographic change and their implications for sustainability. We compare ensembles of water supply and demand projections driven by ensemble output from five global climate models. Our results suggest reasons for concern. Direct climate impacts to maize, soybean, wheat, and rice involve losses of 400–2,600 Pcal (8–43% of present-day total). Freshwater limitations in some heavily irrigated regions could necessitate reversion of 20–60 Mha of cropland from irrigated to rainfed management, and a further loss of 600–2,900 Pcal. Freshwater abundance in other regions could help ameliorate these losses, but substantial investment in infrastructure would be required. We compare ensembles of water supply and demand projections from 10 global hydrological models and six global gridded crop models. These are produced as part of the Inter-Sectoral Impacts Model Intercomparison Project, with coordination from the Agricultural Model Intercomparison and Improvement Project, and driven by outputs of general circulation models run under representative concentration pathway 8.5 as part of the Fifth Coupled Model Intercomparison Project. Models project that direct climate impacts to maize, soybean, wheat, and rice involve losses of 400–1,400 Pcal (8–24% of present-day total) when CO2 fertilization effects are accounted for or 1,400–2,600 Pcal (24–43%) otherwise. Freshwater limitations in some irrigated regions (western United States; China; and West, South, and Central Asia) could necessitate the reversion of 20–60 Mha of cropland from irrigated to rainfed management by end-of-century, and a further loss of 600–2,900 Pcal of food production. In other regions (northern/eastern United States, parts of South America, much of Europe, and South East Asia) surplus water supply could in principle support a net increase in irrigation, although substantial investments in irrigation infrastructure would be required.

Cold winter extremes in northern continents linked to Arctic sea ice loss

The satellite record since 1979 shows downward trends in Arctic sea ice extent in all months, which are smallest in winter and largest in September. Previous studies have linked changes in winter atmospheric circulation, anomalously cold extremes and large snowfalls in mid-latitudes to rapid decline of Arctic sea ice in the preceding autumn. Using observational analyses, we show that the winter atmospheric circulation change and cold extremes are also associated with winter sea ice reduction through an apparently distinct mechanism from those related to autumn sea ice loss. Associated with winter sea ice reduction, a high-pressure anomaly prevails over the subarctic, which in part results from fewer cyclones owing to a weakened gradient in sea surface temperature and lower baroclinicity over sparse sea ice. The results suggest that the winter atmospheric circulation at high northern latitudes associated with Arctic sea ice loss, especially in the winter, favors the occurrence of cold winter extremes at middle latitudes of the northern continents.

Multisectoral climate impact hotspots in a warming world

The impacts of global climate change on different aspects of humanity’s diverse life-support systems are complex and often difficult to predict. To facilitate policy decisions on mitigation and adaptation strategies, it is necessary to understand, quantify, and synthesize these climate-change impacts, taking into account their uncertainties. Crucial to these decisions is an understanding of how impacts in different sectors overlap, as overlapping impacts increase exposure, lead to interactions of impacts, and are likely to raise adaptation pressure. As a first step we develop herein a framework to study coinciding impacts and identify regional exposure hotspots. This framework can then be used as a starting point for regional case studies on vulnerability and multifaceted adaptation strategies. We consider impacts related to water, agriculture, ecosystems, and malaria at different levels of global warming. Multisectoral overlap starts to be seen robustly at a mean global warming of 3 °C above the 1980–2010 mean, with 11% of the world population subject to severe impacts in at least two of the four impact sectors at 4 °C. Despite these general conclusions, we find that uncertainty arising from the impact models is considerable, and larger than that from the climate models. In a low probability-high impact worst-case assessment, almost the whole inhabited world is at risk for multisectoral pressures. Hence, there is a pressing need for an increased research effort to develop a more comprehensive understanding of impacts, as well as for the development of policy measures under existing uncertainty.

The Influence of Precipitation Variability and Partial Irrigation within Grid Cells on a Hydrological Simulation

Abstract The effects of natural and anthropogenic heterogeneity on a hydrological simulation are evaluated using a distributed biosphere hydrological model (DBHM) system. The DBHM embeds a biosphere model into a distributed hydrological scheme, representing both topography and vegetation in a mesoscale hydrological simulation, and the model system includes an irrigation scheme. The authors investigated the effects of two kinds of variability, precipitation variability and the variability of irrigation redistributing runoff, representing natural and anthropogenic heterogeneity, respectively, on hydrological processes. Runoff was underestimated if rainfall was placed spatially uniformly over large grid cells. Accounting for precipitation heterogeneity improved the runoff simulation. However, the negative runoff contribution, namely, the situation that mean annual precipitation is less than evapotranspiration, cannot be simulated by only considering the natural heterogeneity. This constructive model shortcom...

Modeling the Effects of Groundwater-Fed Irrigation on Terrestrial Hydrology over the Conterminous United States

Human alteration of the land surface hydrologic cycle is substantial. Recent studies suggest that local water management practices including groundwater pumping and irrigation could significantly alter the quantity and distribution of water in the terrestrial system, with potential impacts on weather and climate through land‐ atmosphere feedbacks. In this study, the authors incorporated a groundwater withdrawal scheme into the Community Land Model, version 4 (CLM4). To simulate the impact of irrigation realistically, they calibrated the CLM4 simulated irrigation amount against observations from agriculture censuses at the county scale over the conterminous United States. The water used for irrigation was then removed from the surface runoff and groundwater aquifer according to a ratio determined from the county-level agricultural census data. On the basis of the simulations, the impact of groundwater withdrawals for irrigation on land surface and subsurface fluxes were investigated. The results suggest that the impacts of irrigation on latent heat flux and potential recharge when water is withdrawn from surface water alone or from both surface and groundwater are comparable and local to the irrigation areas. However, when water is withdrawn from groundwater for irrigation, greater effects on the subsurface water balance are found, leading to significant depletion of groundwater storage in regions with low recharge rate and high groundwater exploitation rate. The results underscore the importance of local hydrologic feedbacks in governing hydrologic response to anthropogenic change in CLM4 and the need to more realistically simulate the two-way interactions among surface water, groundwater, and atmosphere to better understand the impacts of groundwater pumping on irrigation efficiency and climate.

Remote sensing: hydrology:

Satellite remote sensing is a viable source of observations of land surface hydrologic fluxes and state variables, particularly in regions where in situ networks are sparse. Over the last 10 years, the study of land surface hydrology using remote sensing techniques has advanced greatly with the launch of NASA’s Earth Observing System (EOS) and other research satellite platforms, and with the development of more sophisticated retrieval algorithms. Most of the constituent variables in the land surface water balance (eg, precipitation, evapotranspiration, snow and ice, soil moisture, and terrestrial water storage variations) are now observable at varying spatial and temporal resolutions and accuracy via remote sensing. We evaluate the current status of estimates of each of these variables, as well as river discharge, the direct estimation of which is not yet possible. Although most of the constituent variables are observable by remote sensing, attempts to close the surface water budget from remote sensing alone have generally been unsuccessful, suggesting that current generation sensors and platforms are not yet able to provide hydrologically consistent observations of the land surface water budget at any spatial scale.

Estimating the water budget of major US river basins via remote sensing

Nine satellite-based products, each of which provides information about land surface water budget terms, are used to estimate seasonal and annual variations in the water budget of the major river basins of the conterminous USA from 2003 to 2006. The remotely sensed terms are compared with gridded gauge precipitation, and estimates of evapotranspiration (E) and total water storage (TWS) derived from the Variable Infiltration Capacity (VIC) macroscale hydrology model. Among the remote sensing estimates, precipitation has the largest uncertainties. In general, apparent errors for E and TWS show substantial spatial variations, but the consistencies among these remote sensing products are greater than among precipitation products, possibly due in part to similarities in methodology, especially for TWS. Inferred run-off (as a residual of remote sensing estimates of precipitation, E, and TWS) is generally overestimated, due both to excessive precipitation and underestimation of combined E and terrestrial water storage change (TWSC) from remote sensing.

Hydrological Cycles Change in the Yellow River Basin during the Last Half of the Twentieth Century

Abstract A distributed biosphere hydrological (DBH) model system was used to explore the internal relations among the climate system, human society, and the hydrological system in the Yellow River basin, and to interpret possible mechanisms for observed changes in Yellow River streamflow from 1960 to 2000. Several scenarios were evaluated to elucidate the hydrological response to climate system, land cover, and irrigation. The results show that climate change is the dominant cause of annual streamflow changes in the upper and middle reaches, but human activities dominate annual streamflow changes in the lower reaches of the Yellow River basin. The annual river discharge at the mouth is affected by climate change and by human activities in nearly equal proportion. The linear component of climate change contributes to the observed annual streamflow decrease, but changes in the climate temporal pattern have a larger impact on annual river discharge than does the linear component of climate change. Low flow i...

21st century runoff sensitivities of major global river basins

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 degrees 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. Lettenmaier (2012), 21st century runoff sensitivities of major global river basins, Geophys. Res. Lett., 39, L06403, doi: 10.1029/2011GL050834.