Water/Data uncertainties limitations: Difference between revisions
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{{ComponentDataUncertaintyAndLimitationsTemplate | {{ComponentDataUncertaintyAndLimitationsTemplate | ||
|Status=On hold | |Status=On hold | ||
|Reference=Haddeland et al., 2011; Biemans et al., 2009; Biemans et al., 2011; Vörösmarty et al., 2000; Biemans, 2012; | |||
|Description===Data== | |||
The hydrological part of [[LPJml model|LPJmL]] uses external data on the river network ([[XXRef]]). | |||
==Uncertainty in water availability== | |||
Three water extraction sources are distinguished in the LPJmL model: rivers and natural lakes, man-made reservoirs, and groundwater. Simulations of water availability from all those sources suffer from uncertainty. | |||
A model intercomparison of global hydrological models shows that LPJmL simulations of monthly discharges are in agreement with estimates of other global hydrological models ([[Haddeland et al., 2011]]). However, a validation of simulated discharges with observations for 300 locations, globally, ([[Biemans et al., 2009]]) also showed that LPJmL overestimates the discharge from some basins in the tropics, but underestimates discharges from several arctic basins. The underestimations in the Arctic, to a large extent, may be explained by known errors in precipitation input data, but the overestimations in the tropics are caused by processes that are not described in LPJmL, such as evaporation losses from wetlands, tropical rivers and floodplains. | |||
Because uncertainties in precipitation input data propagate through to the calculation of river discharge, it is important to use multiple climate change scenarios for the assessment of future water availability. | |||
LPJmL includes a reservoir operation scheme that simulates the management of 7000 of the worlds’ largest reservoirs, as well as the withdrawal and distribution of irrigation water from those reservoirs. Biemans et al. ([[Biemans et al., 2011]]) quantified that reservoirs annually contribute around 500 km3 of irrigation water. As there are no other studies that quantify the contribution of reservoirs to irrigation, the uncertainty in this estimation is difficult to determine. | |||
Globally, groundwater contributes around a third to the water supply used for irrigation. Groundwater availability is not explicitly included in the model and global data on the amount of usable groundwater storage does not exist. As it is unknown how long various groundwater reservoirs could still be exploited, the uncertainty about the future availability of groundwater resources results in an uncertainty in the assessment of future water stress. | |||
==Uncertainty in water demand== | |||
Several studies already showed that the most important process leading to increased water stress is the increase in water demand rather than a changing climate ([[Vörösmarty et al., 2000]]; [[Biemans, 2012]]). Therefore, scenario assumptions on the expansion of irrigated areas and increases in water-use efficiency in all sectors influence the assessment of future water stressed areas. Although there is consensus about the fact that water demand will increase under a growing population, the extent of this increase largely depends on scenario assumptions on the size of irrigation areas and on efficiency improvements. | |||
Uncertainty regarding future water availability, water demand and water stress propagates through to other model components. Examples include crop yield simulations and future cropland allocations. | |||
A more extensive assessment of uncertainties with respect to the quantification of agricultural water availability and demand can be found in [[Biemans, 2012]]. | |||
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Revision as of 12:57, 10 December 2013
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