Change in streamflow response in unregulated catchments in Sweden over the last century

Åkesson, Anna; Wörman, Anders; Riml, Joakim; Seibert, Jan

doi:10.1002/2015wr018116

Cited by 5 publications

(2 citation statements)

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“…As shown in Figure , there is a significant damping of the discharge power spectral densities from the upstream, smaller subwatersheds and the aggregated hydrograph response further downstream. This damping is partly due to the statistical smoothing that results from the different runoff travel times from various subwatersheds (geomorphological dispersion), but it is also due to runoff from different watersheds for which the runoff correlation is less than one, the hydrodynamic diffusion (wave diffusion) that occurs within the subwatersheds and, to some degree, along river channels [ Åkesson et al ., ; Zmijewski and Wörman , ]. The solid blue curve in Figure shows the standardized variance in the storage as an average of the 303 subwatersheds (506 hydropower stations) considering the watershed damping.…”

Section: Resultsmentioning

confidence: 99%

“…This translation of runoff to inflow is performed by expressing the reservoir inflow as a convolution between runoff, r i , and the catchment instantaneous unit hydrograph (IUH), ψ i , so that q i = r i *ψ i . Because the corresponding power spectral form can be expressed as S q,i = S r,i S ψ,i , we can represent the variance in the storage for constant demand D (scenario 1, section 2.1)

{S t d}^{2} (|, V_{T o t, i}) = \int_{T_{f} = T_{1}}^{T_{2}} (|, S_{r, i} (|, T_{f}) S_{ψ, i} (|, T_{f})) d T_{f},

where S ψ is the square of the modulus of the Fourier transform of the IUH, which is referred to as a “scaling function” for the watershed [ Riml and Wörman , ; Åkesson et al ., ], and i = 1, 2, … N . Furthermore, the relative RVD under constant demand D is obtained by combining equations , , and

R_{R V D, i} (|, T_{2}) = z_{p} \frac{\sqrt{{false\int}_{T_{f} = T_{1}}^{T_{2}} (S_{r, i} (T_{f}) S_{ψ, i} (T_{f})) d T_{f}}}{V_{D R V, i}},

where the second factor (the fraction) on the right‐hand side of equation is the standardized relative RVD, i.e., R S−RVD .…”

Section: Methodsmentioning

confidence: 99%

See 1 more Smart Citation

Spectral decomposition of regulatory thresholds for climate‐driven fluctuations in hydro‐ and wind power availability

Wörman

Bottacin‐Busolin

Zmijewski

et al. 2017

Water Resources Research

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Climate‐driven fluctuations in the runoff and potential energy of surface water are generally large in comparison to the capacity of hydropower regulation, particularly when hydropower is used to balance the electricity production from covarying renewable energy sources such as wind power. To define the bounds of reservoir storage capacity, we introduce a dedicated reservoir volume that aggregates the storage capacity of several reservoirs to handle runoff from specific watersheds. We show how the storage bounds can be related to a spectrum of the climate‐driven modes of variability in water availability and to the covariation between water and wind availability. A regional case study of the entire hydropower system in Sweden indicates that the longest regulation period possible to consider spans from a few days of individual subwatersheds up to several years, with an average limit of a couple of months. Watershed damping of the runoff substantially increases the longest considered regulation period and capacity. The high covariance found between the potential energy of the surface water and wind energy significantly reduces the longest considered regulation period when hydropower is used to balance the fluctuating wind power.

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Section: Resultsmentioning

confidence: 99%