Simulation of reservoir influences on annual and seasonal streamflow changes for the Lena, Yenisei, and Ob' rivers

Adam, J. C.; Haddeland, Ingjerd; Su, Fengge; Lettenmaier, Dennis P.

doi:10.1029/2007jd008525

Cited by 132 publications

(132 citation statements)

References 57 publications

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“…Local anthropogenic water-use changes, for instance the construction and use of dams, may also influence the runoff and complicate the assessment of precipitation-runoff relations (Shibuo et al 2007;Adam et al 2007;Rawlins et al 2009b;Shiklomanov and Lammers 2009), although the effect of dams on annual discharge in the Arctic is generally small over longer time periods . In the Churchill basin, however, large-scale diversions of water out of the basin have strongly influenced the river flow (Déry et al 2005), yielding a considerably greater decrease in runoff than in precipitation over the studied period.…”

Section: Discussionmentioning

confidence: 99%

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Relevance of Hydro-Climatic Change Projection and Monitoring for Assessment of Water Cycle Changes in the Arctic

Bring

Destouni

2010

AMBIO

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Rapid changes to the Arctic hydrological cycle challenge both our process understanding and our ability to find appropriate adaptation strategies. We have investigated the relevance and accuracy development of climate change projections for assessment of water cycle changes in major Arctic drainage basins. Results show relatively good agreement of climate model projections with observed temperature changes, but high model inaccuracy relative to available observation data for precipitation changes. Direct observations further show systematically larger (smaller) runoff than precipitation increases (decreases). This result is partly attributable to uncertainties and systematic bias in precipitation observations, but still indicates that some of the observed increase in Arctic river runoff is due to water storage changes, for example melting permafrost and/or groundwater storage changes, within the drainage basins. Such causes of runoff change affect sea level, in addition to ocean salinity, and inland water resources, ecosystems, and infrastructure. Process-based hydrological modeling and observations, which can resolve changes in evapotranspiration, and groundwater and permafrost storage at and below river basin scales, are needed in order to accurately interpret and translate climate-driven precipitation changes to changes in freshwater cycling and runoff. In contrast to this need, our results show that the density of Arctic runoff monitoring has become increasingly biased and less relevant by decreasing most and being lowest in river basins with the largest expected climatic changes.

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Section: Discussionmentioning

confidence: 99%

“…For all basins, only years with complete runoff data for all months of the year were included. We have not corrected for the influence of dams in our analysis, as their effect on annual discharge trends over longer time periods has been shown to be relatively insignificant Adam et al 2007;Shiklomanov and Lammers 2009). …”

Section: Methodsmentioning

confidence: 99%

Relevance of Hydro-Climatic Change Projection and Monitoring for Assessment of Water Cycle Changes in the Arctic

Bring

Destouni

2010

AMBIO

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“…4 and 5). In this study, however, only the impact on long-term averaged discharge was analyzed, while possible seasonal impacts, e.g., due to reservoir operation, were not considered (Adam et al, 2007;Döll et al, 2009).…”

Section: Discussionmentioning

confidence: 99%

Variations of global and continental water balance components as impacted by climate forcing uncertainty and human water use

Schmied

Adam

Eisner

et al. 2016

Hydrol. Earth Syst. Sci.

177

106

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Abstract. When assessing global water resources with hydrological models, it is essential to know about methodological uncertainties. The values of simulated water balance components may vary due to different spatial and temporal aggregations, reference periods, and applied climate forcings, as well as due to the consideration of human water use, or the lack thereof. We analyzed these variations over the period 1901–2010 by forcing the global hydrological model WaterGAP 2.2 (ISIMIP2a) with five state-of-the-art climate data sets, including a homogenized version of the concatenated WFD/WFDEI data set. Absolute values and temporal variations of global water balance components are strongly affected by the uncertainty in the climate forcing, and no temporal trends of the global water balance components are detected for the four homogeneous climate forcings considered (except for human water abstractions). The calibration of WaterGAP against observed long-term average river discharge Q significantly reduces the impact of climate forcing uncertainty on estimated Q and renewable water resources. For the homogeneous forcings, Q of the calibrated and non-calibrated regions of the globe varies by 1.6 and 18.5 %, respectively, for 1971–2000. On the continental scale, most differences for long-term average precipitation P and Q estimates occur in Africa and, due to snow undercatch of rain gauges, also in the data-rich continents Europe and North America. Variations of Q at the grid-cell scale are large, except in a few grid cells upstream and downstream of calibration stations, with an average variation of 37 and 74 % among the four homogeneous forcings in calibrated and non-calibrated regions, respectively. Considering only the forcings GSWP3 and WFDEI_hom, i.e., excluding the forcing without undercatch correction (PGFv2.1) and the one with a much lower shortwave downward radiation SWD than the others (WFD), Q variations are reduced to 16 and 31 % in calibrated and non-calibrated regions, respectively. These simulation results support the need for extended Q measurements and data sharing for better constraining global water balance assessments. Over the 20th century, the human footprint on natural water resources has become larger. For 11–18% of the global land area, the change of Q between 1941–1970 and 1971–2000 was driven more strongly by change of human water use including dam construction than by change in precipitation, while this was true for only 9–13 % of the land area from 1911–1940 to 1941–1970.

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“…The VIC model has been widely used at global scale in many previous studies and has been demonstrated to capture the hydrology of different regimes well (Nijssen et al, 1997(Nijssen et al, , 2001aMaurer et al, 2002;Adam et al, 2007). The VIC model has also been used to successfully simulate and reconstruct hydrologic extremes such as drought and floods globally Sheffield and Wood, 2008a,b;Voisin et al, 2011;Wang et al, 2011).…”

Section: The Variable Infiltration Capacity (Vic) Modelmentioning

confidence: 99%

On the sources of global land surface hydrologic predictability

Shukla

Sheffield

Wood

et al. 2013

Hydrol. Earth Syst. Sci.

105

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Abstract. Global seasonal hydrologic prediction is crucial to mitigating the impacts of droughts and floods, especially in the developing world. Hydrologic predictability at seasonal lead times (i.e., 1-6 months) comes from knowledge of initial hydrologic conditions (IHCs) and seasonal climate forecast skill (FS). In this study we quantify the contributions of two primary components of IHCs -soil moisture and snow water content -and FS (of precipitation and temperature) to seasonal hydrologic predictability globally on a relative basis throughout the year. We do so by conducting two modelbased experiments using the variable infiltration capacity (VIC) macroscale hydrology model, one based on ensemble streamflow prediction (ESP) and another based on Reverse-ESP (Rev-ESP), both for a 47 yr re-forecast period . We compare cumulative runoff (CR), soil moisture (SM) and snow water equivalent (SWE) forecasts from each experiment with a VIC model-based reference data set (generated using observed atmospheric forcings) and estimate the ratio of root mean square error (RMSE) of both experiments for each forecast initialization date and lead time, to determine the relative contribution of IHCs and FS to the seasonal hydrologic predictability. We find that in general, the contributions of IHCs to seasonal hydrologic predictability is highest in the arid and snow-dominated climate (high latitude) regions of the Northern Hemisphere during forecast periods starting on 1 January and 1 October. In mid-latitude regions, such as the Western US, the influence of IHCs is greatest during the forecast period starting on 1 April. In the arid and warm temperate dry winter regions of the Southern Hemisphere, the IHCs dominate during forecast periods starting on 1 April and 1 July. In equatorial humid and monsoonal climate regions, the contribution of FS is generally higher than IHCs through most of the year.Based on our findings, we argue that despite the limited FS (mainly for precipitation) better estimates of the IHCs could lead to improvement in the current level of seasonal hydrologic forecast skill over many regions of the globe at least during some parts of the year.

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Simulation of reservoir influences on annual and seasonal streamflow changes for the Lena, Yenisei, and Ob' rivers

Cited by 132 publications

References 57 publications

Relevance of Hydro-Climatic Change Projection and Monitoring for Assessment of Water Cycle Changes in the Arctic

Relevance of Hydro-Climatic Change Projection and Monitoring for Assessment of Water Cycle Changes in the Arctic

Variations of global and continental water balance components as impacted by climate forcing uncertainty and human water use

On the sources of global land surface hydrologic predictability

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