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Irrigation intensifies land use by increasing crop yield but also impacts water resources. It affects water and energy balances and consequently the microclimate in irrigated regions. Therefore, knowledge of the extent of irrigated land is important for hydrological and crop modelling, global change research, and assessments of resource use and management. Information on the historical evolution of irrigated lands is limited. The new global Historical Irrigation Dataset (HID) provides estimates of the temporal development of the area equipped for irrigation (AEI) between 1900 and 2005 at 5 arc-minute resolution. We collected subnational irrigation statistics from various sources and found that the global extent of AEI increased from 63 million ha (Mha) in 1900 to 112 Mha in 1950 and 306 Mha in 2005. We developed eight gridded versions of time series of AEI by combining subnational irrigation statistics with different data sets on the historical extent of cropland and pasture. Different rules were applied to maximize consistency of the gridded products to subnational irrigation statistics or to historical cropland and pasture data sets. The HID reflects very well the spatial patterns of irrigated land in the western United States as shown on historical maps. Mean aridity on irrigated land increased and river discharge decreased from 1900–1950 whereas aridity decreased from 1950–2005. The dataset and its documentation are made available in an open data repository at https://mygeohub.org/publications/8 (doi:10.13019/M2MW2G).
Global-scale assessments of freshwater fluxes and storages by hydrological models under historic climate conditions are subject to a variety of uncertainties. Using the global hydrological model WaterGAP 2.2, we investigated the sensitivity of simulated freshwater fluxes and water storage variations to five major sources of uncertainty: climate forcing, land cover input, model structure, consideration of human water use and calibration (or no calibration). In a modelling experiment, five variants of the standard version of WaterGAP 2.2 were generated that differed from the standard version only regarding the investigated source of uncertainty. Sensitivity was analyzed by comparing water fluxes and water storage variations computed by the variants to those of the standard version, considering both global averages and grid cell values for the time period 1971–2000. The basin-specific calibration approach for WaterGAP, which forces simulated mean annual river discharge to be equal to observed values at 1319 gauging stations (representing 54% of global land area except Antarctica and Greenland), has the highest effect on modelled water fluxes and leads to the best fit of modelled to observed monthly and seasonal river discharge. Alternative state-of-the-art climate forcings rank second regarding the impact on grid cell specific fluxes and water storage variations, and their impact is ubiquitous and stronger than that of alternative land cover inputs. The diverse model refinements during the last decade lead to an improved fit to observed discharge, and affect globally averaged fluxes and storage values (the latter mainly due to modelling of groundwater depletion) but only affect a relatively small number of grid cells. Considering human water use is important for the global water storage trend (in particular in the groundwater compartment) but impacts on water fluxes are rather local and only important where water use is high. The best fit to observed time series of monthly river discharge (Nash–Sutcliffe criterion) or discharge seasonality is obtained with the standard WaterGAP 2.2 model version which is calibrated and driven by a sequence of two time series of daily observation-based climate forcings, WFD/WFDEI. Discharge computed by a calibrated model version using monthly CRU 3.2 and GPCC v6 climate input reduced the fit to observed discharge for most stations. Taking into account the investigated uncertainties of climate and land cover data, we estimate that the global 1971–2000 discharge into oceans and inland sinks is between 40 000 and 42 000 km3 yr−1. The range is mainly due differences in precipitation data that affect discharge in uncalibrated river basins. Actual evapotranspiration, with approximately 70 000 km3 yr−1, is rather unaffected by climate and land cover in global sum but differs spatially. Human water use is calculated to reduce river discharge by approximately 1000 km3 yr−1. Thus, global renewable water resources are estimated to range between 41 000 and 43 000 km3 yr−1. The climate data sets WFD (available until 2001) and WFDEI (starting in 1979) were found to be inconsistent with respect to short wave radiation data, resulting in strongly different potential evapotranspiration. Global assessments of freshwater fluxes and storages would therefore benefit from the development of a global data set of consistent daily climate forcing from 1900 to current.
Water footprints have been proposed as sustainability indicators, relating the consumption of goods like food to the amount of water necessary for their production and the impacts of that water use in the source regions. We further developed the existing water footprint methodology, by globally resolving virtual water flows from production to consumption regions for major food crops at 5 arcmin spatial resolution. We distinguished domestic and international flows, and assessed local impacts of export production. Applying this method to three exemplary cities, Berlin, Delhi and Lagos, we find major differences in amounts, composition, and origin of green and blue virtual water imports, due to differences in diets, trade integration and crop water productivities in the source regions. While almost all of Delhi's and Lagos' virtual water imports are of domestic origin, Berlin on average imports from more than 4000 km distance, in particular soy (livestock feed), coffee and cocoa. While 42% of Delhi's virtual water imports are blue water based, the fractions for Berlin and Lagos are 2 and 0.5%, respectively, roughly equal to the water volumes abstracted in these two cities for domestic water use. Some of the external source regions of Berlin's virtual water imports appear to be critically water scarce and/or food insecure. However, for deriving recommendations on sustainable consumption and trade, further analysis of context-specific costs and benefits associated with export production will be required.
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.