ALBERT

Description: This study compares, spatially explicitly and at global scale, per capita water availability and water requirements for food production presently (1971–2000) and in the future given climate and population change (2070–99). A vegetation and hydrology model Lund–Potsdam–Jena managed Land (LPJmL) was used to calculate green and blue water availability per capita, water requirements to produce a balanced diet representing a benchmark for hunger alleviation [3000 kilocalories per capita per day (1 kilocalorie = 4184 joules), here assumed to consist of 80% vegetal food and 20% animal products], and a new water scarcity indicator that relates the two at country scale. A country was considered water-scarce if its water availability fell below the water requirement for the specified diet, which is presently the case especially in North and East Africa and in southwestern Asia. Under climate (derived from 17 general circulation models) and population change (A2 and B1 emissions and population scenarios), water availability per person will most probably diminish in many regions. At the same time the calorie-specific water requirements tend to decrease, due mainly to the positive effect of rising atmospheric CO2 concentration on crop water productivity—which, however, is very uncertain to be fully realized in most regions. As a net effect of climate, CO2, and population change, water scarcity will become aggravated in many countries, and a number of additional countries are at risk of losing their present capacity to produce a balanced diet for their inhabitants.

Description: During the past decades large-scale models have been developed to simulate global and continental terrestrial water cycles. It is an open question whether these models are suitable to capture hydrological drought, in terms of runoff, on a global scale. A multimodel ensemble analysis was carried out to evaluate if 10 such large-scale models agree on major drought events during the second half of the twentieth century. Time series of monthly precipitation, monthly total runoff from 10 global hydrological models, and their ensemble median have been used to identify drought. Temporal development of area in drought for various regions across the globe was investigated. Model spread was largest in regions with low runoff and smallest in regions with high runoff. In vast regions, correlation between runoff drought derived from the models and meteorological drought was found to be low. This indicated that models add information to the signal derived from precipitation and that runoff drought cannot directly be determined from precipitation data alone in global drought analyses with a constant aggregation period. However, duration and spatial extent of major drought events differed between models. Some models showed a fast runoff response to rainfall, which led to deviations from reported drought events in slowly responding hydrological systems. By using an ensemble of models, this fast runoff response was partly overcome and delay in drought propagating from meteorological drought to drought in runoff was included. Finally, an ensemble of models also allows for consideration of uncertainty associated with individual model structures.

Description: Climate change and its impacts already pose considerable challenges for societies that will further increase with global warming (IPCC, 2014a, b). Uncertainties of the climatic response to greenhouse gas emissions include the potential passing of large-scale tipping points (e.g. Lenton et al., 2008; Levermann et al., 2012; Schellnhuber, 2010) and changes in extreme meteorological events (Field et al., 2012) with complex impacts on societies (Hallegatte et al., 2013). Thus climate change mitigation is considered a necessary societal response for avoiding uncontrollable impacts (Conference of the Parties, 2010). On the other hand, large-scale climate change mitigation itself implies fundamental changes in, for example, the global energy system. The associated challenges come on top of others that derive from equally important ethical imperatives like the fulfilment of increasing food demand that may draw on the same resources. For example, ensuring food security for a growing population may require an expansion of cropland, thereby reducing natural carbon sinks or the area available for bio-energy production. So far, available studies addressing this problem have relied on individual impact models, ignoring uncertainty in crop model and biome model projections. Here, we propose a probabilistic decision framework that allows for an evaluation of agricultural management and mitigation options in a multi-impact-model setting. Based on simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP), we outline how cross-sectorally consistent multi-model impact simulations could be used to generate the information required for robust decision making. Using an illustrative future land use pattern, we discuss the trade-off between potential gains in crop production and associated losses in natural carbon sinks in the new multiple crop- and biome-model setting. In addition, crop and water model simulations are combined to explore irrigation increases as one possible measure of agricultural intensification that could limit the expansion of cropland required in response to climate change and growing food demand. This example shows that current impact model uncertainties pose an important challenge to long-term mitigation planning and must not be ignored in long-term strategic decision making.

Description: Climate change is expected to alter the hydrological cycle resulting in large-scale impacts on water availability. However, future climate change impact assessments are highly uncertain. For the first time, multiple global climate (three) and hydrological models (eight) were used to systematically assess the hydrological response to climate change and project the future state of global water resources. This multi-model ensemble allows us to investigate how the hydrology models contribute to the uncertainty in projected hydrological changes compared to the climate models. Due to their systematic biases, GCM outputs cannot be used directly in hydrological impact studies, so a statistical bias correction has been applied. The results show a large spread in projected changes in water resources within the climate–hydrology modelling chain for some regions. They clearly demonstrate that climate models are not the only source of uncertainty for hydrological change, and that the spread resulting from the choice of the hydrology model is larger than the spread originating from the climate models over many areas. But there are also areas showing a robust change signal, such as at high latitudes and in some midlatitude regions, where the models agree on the sign of projected hydrological changes, indicative of higher confidence in this ensemble mean signal. In many catchments an increase of available water resources is expected but there are some severe decreases in Central and Southern Europe, the Middle East, the Mississippi River basin, southern Africa, southern China and south-eastern Australia.

Description: Climate change is expected to alter the hydrological cycle resulting in large-scale impacts on water availability. However, future climate change impact assessments are highly uncertain. For the first time, multiple global climate (three) and hydrological models (eight) were used to systematically assess the hydrological response to climate change and project the future state of global water resources. The results show a large spread in projected changes in water resources within the climate–hydrology modelling chain for some regions. They clearly demonstrate that climate models are not the only source of uncertainty for hydrological change. But there are also areas showing a robust change signal, such as at high latitudes and in some mid-latitude regions, where the models agree on the sign of projected hydrological changes, indicative of higher confidence. In many catchments an increase of available water resources is expected but there are some severe decreases in central and Southern Europe, the Middle East, the Mississippi river basin, Southern Africa, Southern China and south eastern Australia.

Description: In order to achieve climate change mitigation, long-term decisions are required that must be reconciled with other societal goals that draw on the same resources. For example, ensuring food security for a growing population may require an expansion of crop land, thereby reducing natural carbon sinks or the area available for bio-energy production. Here, we show that current impact-model uncertainties pose an important challenge to long-term mitigation planning and propose a new risk-assessment and decision framework that accounts for competing interests. Based on cross-sectorally consistent simulations generated within the Inter-Sectoral Impact Model Intercomparison Project (ISI-MIP) we discuss potential gains and limitations of additional irrigation and trade-offs of the expansion of agricultural land as two possible response measures to climate change and growing food demand. We describe an illustrative example in which the combination of both measures may close the supply demand gap while leading to a loss of approximately half of all natural carbon sinks. We highlight current limitations of available simulations and additional steps required for a comprehensive risk assessment.

Description: In the ongoing political debate on climate change, global mean temperature change (ΔTglob) has become the yardstick by which mitigation costs, impacts from unavoided climate change, and adaptation requirements are discussed. For a scientifically informed discourse along these lines, systematic assessments of climate change impacts as a function of ΔTglob are required. The current availability of climate change scenarios constrains this type of assessment to a narrow range of temperature change and/or a reduced ensemble of climate models. Here, a newly composed dataset of climate change scenarios is presented that addresses the specific requirements for global assessments of climate change impacts as a function of ΔTglob. A pattern-scaling approach is applied to extract generalised patterns of spatially explicit change in temperature, precipitation and cloudiness from 19 Atmosphere–Ocean General Circulation Models (AOGCMs). The patterns are combined with scenarios of global mean temperature increase obtained from the reduced-complexity climate model MAGICC6 to create climate scenarios covering warming levels from 1.5 to 5 degrees above pre-industrial levels around the year 2100. The patterns are shown to sufficiently maintain the original AOGCMs' climate change properties, even though they, necessarily, utilise a simplified relationships between ΔTglob and changes in local climate properties. The dataset (made available online upon final publication of this paper) facilitates systematic analyses of climate change impacts as it covers a wider and finer-spaced range of climate change scenarios than the original AOGCM simulations.

Description: We present protocols and input data for Phase 1 of the Global Gridded Crop Model Intercomparison, a project of the Agricultural Model Intercomparison and Improvement Project (AgMIP). The project includes global simulations of yields, phenologies, and many land-surface fluxes using 12–15 modeling groups for many crops, climate forcing data sets, and scenarios over the historical period from 1948 to 2012. The primary outcomes of the project include (1) a detailed comparison of the major differences and similarities among global models commonly used for large-scale climate impact assessment, (2) an evaluation of model and ensemble hindcasting skill, (3) quantification of key uncertainties from climate input data, model choice, and other sources, and (4) a multi-model analysis of the agricultural impacts of large-scale climate extremes from the historical record.

Description: Interannual climatic and hydrologic variability has been substantial during the past decades in many regions. While climate variability and its impacts on precipitation and soil moisture have been studied intensively, less is known on subsequent implications for global food production. In this paper we quantify effects of hydroclimatic variability on global "green" and "blue" water availability and demand in global agriculture, and thus complement former studies that have focused merely on long-term averages. Moreover, we assess some options to overcome chronic or sporadic water scarcity. The analysis is based on historical climate forcing data sets over the period 1977–2006, while demography, diet composition and land use are fixed to reference conditions (year 2000). In doing so, we isolate the effect of interannual hydroclimatic variability from other factors that drive food production. We analyse the potential of food production units (FPUs) to produce a reference diet for their inhabitants (3000 kcal cap−1 day−1, with 80% vegetal food and 20% animal products). We applied the LPJmL vegetation and hydrology model to calculate the variation in green-blue water availability and the water requirements to produce that very diet. An FPU was considered water scarce if its water availability was not sufficient to produce the diet (i.e. assuming food self-sufficiency to estimate dependency on trade from elsewhere). We found that 24% of the world's population lives in chronically water-scarce FPUs (i.e. water is scarce every year), while an additional 19% live under occasional water scarcity (water is scarce in some years). Among these 2.6 billion people altogether, 55% would have to rely on international trade to reach the reference diet, while for 24% domestic trade would be enough. For the remaining 21% of the population exposed to some degree of water scarcity, local food storage and/or intermittent trade would be enough to secure the reference diet over the occasional dry years.

Description: Global agricultural production is heavily sustained by irrigation, but irrigation system efficiencies are often surprisingly low. However, our knowledge of irrigation efficiencies is mostly confined to rough indicative estimates for countries or regions that do not account for spatio-temporal heterogeneity due to climate and other biophysical dependencies. To allow for refined estimates of global agricultural water use, and of water saving and water productivity potentials constrained by biophysical processes and also non-trivial downstream effects, we incorporated a dynamic representation of the three major irrigation systems (surface, sprinkler, and drip) into a process-based bio- and agrosphere model, LPJmL. Based on this enhanced model we provide a gridded worldmap of dynamically retrieved irrigation efficiencies reflecting differences in system types, crop types, climatic and hydrologic conditions, and overall crop management. We find pronounced regional patterns in beneficial irrigation efficiency (a refined irrigation efficiency indicator accounting for crop-productive water consumption only), due to differences in these features, with lowest values (〈 30%) in South Asia and Sub-Saharan Africa and highest values (〉 60%) in Europe and North America. We arrive at an estimate of global irrigation water withdrawal of 2396 km3 (2004–2009 average); irrigation water consumption is calculated to be 1212 km3, of which 511 km3 are non-beneficially consumed, i.e. lost through evaporation, interception, and conveyance. Replacing surface systems by sprinkler or drip systems could, on average across the world's river basins, reduce the non-beneficial consumption at river basin level by 54 and 76%, respectively, while maintaining the current level of crop yields. Accordingly, crop water productivity would increase by 9 and 15%, respectively, and by much more in specific regions such as in the Indus basin. This study significantly advances the global quantification of irrigation systems while providing a framework for assessing potential future transitions in these systems. Here presented opportunities associated with irrigation improvements are significant and suggest that they should be considered an important means on the way to sustainable food security.