308 research outputs found

    A model-based constraint on CO<sub>2</sub> fertilisation

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    We derive a constraint on the strength of CO2 fertilisation of the terrestrial biosphere through a “top-down” approach, calibrating Earth system model parameters constrained by the post-industrial increase of atmospheric CO2 concentration. We derive a probabilistic prediction for the globally averaged strength of CO2 fertilisation in nature, for the period 1850 to 2000 AD, implicitly net of other limiting factors such as nutrient availability. The approach yields an estimate that is independent of CO2 enrichment experiments. To achieve this, an essential requirement was the incorpo- ration of a land use change (LUC) scheme into the GENIE Earth system model. Using output from a 671-member ensemble of transient GENIE simulations, we build an emulator of the change in atmospheric CO2 concentration change since the preindustrial period. We use this emulator to sample the 28-dimensional input parameter space. A Bayesian calibration of the emulator output suggests that the increase in gross primary productivity (GPP) in response to a doubling of CO2 from preindustrial values is very likely (90 % confidence) to exceed 20 %, with a most likely value of 40–60 %. It is important to note that we do not represent all of the possible contributing mechanisms to the terrestrial sink. The missing processes are subsumed into our calibration of CO2 fertilisation, which therefore represents the combined effect of CO2 fertilisation and additional missing processes. If the missing processes are a net sink then our estimate represents an upper bound. We derive calibrated estimates of carbon fluxes that are consistent with existing estimates. The present-day land–atmosphere flux (1990–2000) is estimated at −0.7 GTC yr−1 (likely, 66 % confidence, in the range 0.4 to −1.7 GTC yr−1). The present-day ocean–atmosphere flux (1990–2000) is estimated to be −2.3 GTC yr−1 (likely in the range −1.8 to −2.7 GTC yr−1). We estimate cumulative net land emissions over the post-industrial period (land use change emissions net of the CO2 fertilisation and climate sinks) to be 66 GTC, likely to lie in the range 0 to 128 GTC

    Effects of precipitation uncertainty on discharge calculations for main river basins

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    This study quantifies the uncertainty in discharge calculations caused by uncertainty in precipitation input for 294 river basins worldwide. Seven global gridded precipitation datasets are compared at river basin scale in terms of mean annual and seasonal precipitation. The representation of seasonality is similar in all datasets, but the uncertainty in mean annual precipitation is large, especially in mountainous, arctic, and small basins. The average precipitation uncertainty in a basin is 30%, but there are strong differences between basins. The effect of this precipitation uncertainty on mean annual and seasonal discharge was assessed using the uncalibrated dynamic global vegetation and hydrology model Lund-Potsdam-Jena managed land (LPJmL), yielding even larger uncertainties in discharge (average 90%). For 95 basins (out of 213 basins for which measurements were available) calibration of model parameters is problematic because the observed discharge falls within the uncertainty of the simulated discharge. A method is presented to account for precipitation uncertainty in discharge simulations

    Human alterations of the terrestrial water cycle through land management

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    This study quantifies current and potential future changes in transpiration, evaporation, interception loss and river discharge in response to land use change, irrigation and climate change, by performing several distinct simulations within the consistent hydrology and biosphere modeling framework LPJmL (Lund-Potsdam-Jena managed Land). We distinguished two irrigation simulations: a water limited one in which irrigation was restricted by local renewable water resources (ILIM), and a potential one in which no such limitation was assumed but withdrawals from deep groundwater or remote rivers allowed (IPOT). We found that the effect of historical land use change as compared to potential natural vegetation was pronounced, including a reduction in interception loss and transpiration by 25.9% and 10.6%, respectively, whereas river discharge increased by 6.6% (climate conditions of 1991–2000). Furthermore, we estimated that about 1170 km&lt;sup&gt;3&lt;/sup&gt;yr&lt;sup&gt;&amp;minus;1&lt;/sup&gt; of irrigation water could be withdrawn from local renewable water resources (in ILIM), which resulted in a reduction of river discharge by 1.5%. However, up to 1660 km&lt;sup&gt;3&lt;/sup&gt;yr&lt;sup&gt;&amp;minus;1&lt;/sup&gt; of water withdrawals were required in addition under the assumption that optimal growth of irrigated crops was sustained (IPOT), which resulted in a slight net increase in global river discharge by 2.0% due to return flows. Under the HadCM3 A2 climate and emission scenario, climate change alone will decrease total evapotranspiration by 1.5% and river discharge by 0.9% in 2046–2055 compared to 1991–2000 average due to changes in precipitation patterns, a decrease in global precipitation amount, and the net effect of CO&lt;sub&gt;2&lt;/sub&gt; fertilization. A doubling of agricultural land in 2046–2055 compared to 1991–2000 average as proposed by the IMAGE land use change scenario will result in a decrease in total evapotranspiration by 2.5% and in an increase in river discharge by 3.9%. That is, the effects of land use change in the future will be comparable in magnitude to the effects of climate change in this particular scenario. On present irrigated areas future water withdrawal will increase especially in regions where climate changes towards warmer and dryer conditions will be pronounced

    Advances and visions in large-scale hydrological modelling: findings from the 11th Workshop on Large-Scale Hydrological Modelling

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    Large-scale hydrological modelling has become increasingly wide-spread during the last decade. An annual workshop series on large-scale hydrological modelling has provided, since 1997, a forum to the German-speaking community for discussing recent developments and achievements in this research area. In this paper we present the findings from the 2007 workshop which focused on advances and visions in large-scale hydrological modelling. We identify the state of the art, difficulties and research perspectives with respect to the themes "sensitivity of model results", "integrated modelling" and "coupling of processes in hydrosphere, atmosphere and biosphere". Some achievements in large-scale hydrological modelling during the last ten years are presented together with a selection of remaining challenges for the future

    Effects of precipitation uncertainty on discharge calculations for main river basins

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    This study quantifies the uncertainty in discharge calculations caused by uncertainty in precipitation input for 294 river basins worldwide. Seven global gridded precipitation datasets are compared at river basin scale in terms of mean annual and seasonal precipitation. The representation of seasonality is similar in all datasets, but the uncertainty in mean annual precipitation is large, especially in mountainous, arctic, and small basins. The average precipitation uncertainty in a basin is 30%, but there are strong differences between basins. The effect of this precipitation uncertainty on mean annual and seasonal discharge was assessed using the uncalibrated dynamic global vegetation and hydrology model Lund-Potsdam-Jena managed land (LPJmL), yielding even larger uncertainties in discharge (average 90%). For 95 basins (out of 213 basins for which measurements were available) calibration of model parameters is problematic because the observed discharge falls within the uncertainty of the simulated discharge. A method is presented to account for precipitation uncertainty in discharge simulations

    Reconciling irrigated food production with environmental flows for Sustainable Development Goals implementation

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    Safeguarding river ecosystems is a precondition for attaining the UN Sustainable Development Goals (SDGs) related to water and the environment, while rigid implementation of such policies may hamper achievement of food security. River ecosystems provide life-supporting functions that depend on maintaining environmental flow requirements (EFRs). Here we establish gridded process-based estimates of EFRs and their violation through human water withdrawals. Results indicate that 41% of current global irrigation water use (997 km3 per year) occurs at the expense of EFRs. If these volumes were to be reallocated to the ecosystems, half of globally irrigated cropland would face production losses of ≥10%, with losses of ∼20–30% of total country production especially in Central and South Asia. However, we explicitly show that improvement of irrigation practices can widely compensate for such losses on a sustainable basis. Integration with rainwater management can even achieve a 10% global net gain. Such management interventions are highlighted to act as a pivotal target in supporting the implementation of the ambitious and seemingly conflicting SDG agenda

    A model-based constraint on CO2 fertilisation

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    We derive a constraint on the strength of CO2 fertilisation of the terrestrial biosphere through a "top-down" approach, calibrating Earth system model parameters constrained by the post-industrial increase of atmospheric CO2 concentration. We derive a probabilistic prediction for the globally averaged strength of CO2 fertilisation in nature, for the period 1850 to 2000 AD, implicitly net of other limiting factors such as nutrient availability. The approach yields an estimate that is independent of CO2 enrichment experiments. To achieve this, an essential requirement was the incorporation of a land use change (LUC) scheme into the GENIE Earth system model. Using output from a 671-member ensemble of transient GENIE simulations, we build an emulator of the change in atmospheric CO2 concentration change since the preindustrial period. We use this emulator to sample the 28-dimensional input parameter space. A Bayesian calibration of the emulator output suggests that the increase in gross primary productivity (GPP) in response to a doubling of CO2 from preindustrial values is very likely (90% confidence) to exceed 20%, with a most likely value of 40–60%. It is important to note that we do not represent all of the possible contributing mechanisms to the terrestrial sink. The missing processes are subsumed into our calibration of CO2 fertilisation, which therefore represents the combined effect of CO2 fertilisation and additional missing processes. If the missing processes are a net sink then our estimate represents an upper bound. We derive calibrated estimates of carbon fluxes that are consistent with existing estimates. The present-day land–atmosphere flux (1990–2000) is estimated at −0.7 GTC yr−1 (likely, 66% confidence, in the range 0.4 to −1.7 GTC yr−1). The present-day ocean–atmosphere flux (1990–2000) is estimated to be −2.3 GTC yr−1 (likely in the range −1.8 to −2.7 GTC yr−1). We estimate cumulative net land emissions over the post-industrial period (land use change emissions net of the CO2 fertilisation and climate sinks) to be 66 GTC, likely to lie in the range 0 to 128 GTC
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