remediation measures historical changes affecting ......…with contributions anna Åkesson, andrea...

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7/22/2016 1 Remediation measures of agricultural streams Anders Wörman The Royal Institute of Technology, Sweden …with contributions Anna Åkesson, Andrea BottacinBusolin, Jud Harvey, Andrea Marion, Lars Marklund, Ida Morén, Aaron Packman, Roberto Revelli, Luca Ridolfi, Susa Stonedahl, Joakim Riml. 1. Historical changes in agricultural streams 2. Design approach for remediation measures Nutrient sources The Baltic Sea Landbased remediation actions 1905 1917 1936 1968 1950s 1810s Historical changes affecting agricultural streams Drainage works State supported in 1800s Gradual, continuous and extensive Hydropower Most watersheds are affected by regulations Climate change Fluctuations Global warming 79 selected watersheds Anna Åkesson, PhD thesis, KTH. 2015. Åkesson et al, 2015, Online in Water Resources Research Centurylong pattern in daily discharge timeseries Only “sporadic” water quality data is available for the last 50 years Historical daily, discharge timeseries from 1800s Unregulated to moderately regulated Series 55 years (median 83 years). Total coverage 131,000 km 2 , 1/3 of Sweden. Year 1933.3 1933.4 1933.5 1933.6 1933.7 1933.8 1933.9 Precipitation (m 3 /s) 0 10 20 30 40 50 60 70 80 90 100 Year 1933.3 1933.4 1933.5 1933.6 1933.7 1933.8 1933.9 Discharge (m 3 /s) 10 20 30 40 50 60 70 80 90 100 Separating runoff processes and climate 2. Instantaneous unit hydrograph: Stream network Channel structure Distances Slope 1.Climate Wörman, et al., 2010. Hydrological Processes Riml and Wörman, 2015. Water Resources Research Qt P(t ) ET (t ) * P(t) and ET(t) 3.Discharge

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  • 7/22/2016

    1

    Remediation measures of agricultural streams

    Anders WörmanThe Royal Institute of Technology, Sweden

    …with contributions Anna Åkesson, Andrea Bottacin‐Busolin, Jud Harvey, Andrea Marion, Lars Marklund, Ida Morén, Aaron Packman, Roberto Revelli, Luca Ridolfi, Susa Stonedahl, Joakim Riml.

    1. Historical changes in agricultural streams2. Design approach for remediation measures

    Nutrient sources

    The Baltic Sea

    Land‐based remediation actions

    1905 1917 1936 1968

    1950s

    1810s

    Historical changes affecting agricultural streams

    Drainage works‐ State supported in 1800s‐ Gradual, continuous and 

    extensive

    Hydropower‐ Most watersheds are 

    affected by regulations

    Climate change‐ Fluctuations‐ Global warming

    79 selected watersheds

    Anna Åkesson, PhD thesis, KTH. 2015.Åkesson et al, 2015, Online in Water Resources Research

    Century‐long pattern in daily discharge time‐seriesOnly “sporadic” water quality data is available for the last 50 years

    Historical daily, discharge time‐series from 1800s

    Unregulated tomoderately regulated

    Series ≥ 55 years (median 83 years).

    Total coverage 131,000 km2 , 1/3 of Sweden.

    Year1933.3 1933.4 1933.5 1933.6 1933.7 1933.8 1933.9

    Pre

    cipi

    tatio

    n (m

    3 /s)

    0

    10

    20

    30

    40

    50

    60

    70

    80

    90

    100

    Year1933.3 1933.4 1933.5 1933.6 1933.7 1933.8 1933.9

    Dis

    char

    ge (m

    3 /s)

    10

    20

    30

    40

    50

    60

    70

    80

    90

    100

    Separating runoff processes and climate 

    2. Instantaneous unit hydrograph: ‐ Stream network‐ Channel structure‐ Distances‐ Slope

    1.Climate

    Wörman, et al., 2010. Hydrological ProcessesRiml and Wörman, 2015. Water Resources Research

    Q t P(t)ET (t) *

    P(t) and ET(t)

    3.Discharge

  • 7/22/2016

    2

    Year1933.3 1933.4 1933.5 1933.6 1933.7 1933.8 1933.9

    Pre

    cipi

    tatio

    n (m

    3 /s)

    0

    10

    20

    30

    40

    50

    60

    70

    80

    90

    100

    Year1933.3 1933.4 1933.5 1933.6 1933.7 1933.8 1933.9

    Dis

    char

    ge (m

    3 /s)

    10

    20

    30

    40

    50

    60

    70

    80

    90

    100

    Separating runoff processes and climate 

    2. Instantaneous unit hydrograph: ‐ Stream network‐ Channel structure‐ Distances‐ Slope

    Time [days]100 101 102 103

    Spe

    ctra

    l den

    sity

    10-1

    100

    101

    102

    103

    Precipitation

    Spectrum

    , Sp(T)

    Period, T (days)

    Time [days]100 101 102 103

    Spe

    ctra

    l den

    sity

    10-1

    100

    101

    102

    103

    Precipitation

    River discharge

    Spectrum

    , SQ(T)

    Period, T (days)

    Gap closing with period

    1.Climate

    SP(T) = a Tb

    Steepness depends on runoff processes

    Wörman, et al., 2010. Hydrological ProcessesRiml and Wörman, 2015. Water Resources Research

    SQ S PET S Runoff scaling function

    P(t) and ET(t)

    3.Discharge

    Year1933.3 1933.4 1933.5 1933.6 1933.7 1933.8 1933.9

    Pre

    cipi

    tatio

    n (m

    3 /s)

    0

    10

    20

    30

    40

    50

    60

    70

    80

    90

    100

    Year1933.3 1933.4 1933.5 1933.6 1933.7 1933.8 1933.9

    Dis

    char

    ge (m

    3 /s)

    10

    20

    30

    40

    50

    60

    70

    80

    90

    100

    Separating runoff processes and climate 

    2. Instantaneous unit hydrograph: ‐ Stream network‐ Channel structure‐ Distances‐ Slope

    Time [days]100 101 102 103

    Spe

    ctra

    l den

    sity

    10-1

    100

    101

    102

    103

    Precipitation

    Spectrum

    , Sp(T)

    Period, T (days)

    Time [days]100 101 102 103

    Spe

    ctra

    l den

    sity

    10-1

    100

    101

    102

    103

    Precipitation

    River discharge

    Spectrum

    , SQ(T)

    Period, T (days)

    Period (days)

    Scaling functio

    n, 

    Gap closing with period

    Time frame in which runoff processes are important

    1.Climate

    Time frame in which climate fluctuations are important

    SP(T) = a Tb

    Steepness depends on runoff processes

    Wörman, et al., 2010. Hydrological ProcessesRiml and Wörman, 2015. Water Resources Research

    P(t) and ET(t)

    3.Discharge

    Year1900 1920 1940 1960 1980 2000-1

    0

    1

    2

    3

    4

    5Assmebro Catchment

    bP

    bQ

    1st pol. fit

    Period [days]100 101 102

    SQ

    [m6 ]

    10-2

    100

    102

    Decadal average of SQ Assmebro

    1933-19421943-19521953-19621963-19721973-19821983-19921993-20022003-2013

    Power spectrum for May – Oct period of each year

    Non‐changing watershed

    Fitted lineSQ(T) = a Tb

    Spectral den

    sity, S

    Q(T)

    Slop

    e, b         

    Period (days)

    Year Year1900 1920 1940 1960 1980 2000-1

    0

    1

    2

    3

    4

    5Nissafors Catchment

    bPbQ1st pol. fit

    Period [days]100 101 102

    SQ

    [m6 ]

    10-2

    100

    102

    Decadal average of SQ Nissafors

    1933-19421943-19521953-19621963-19721973-19821983-19921993-20022003-2013

    Changing watershed

    Period (days)

    Year

    Spectral den

    sity, S

    Q(T)

    Slop

    e, b         

    Discharge

    Precipitation

    Two similarcatchments.

    But different discharge statistics!

    Spectral discharge change with landscape changes

    Drainage works in agricultural land Changes in discharge spectrum slope

    1767        Today

    Hydropower regulation

    Wörman, Lindström, Åkesson, Riml, 2010. Hydrological Processes

    Simulated response using • Hydrodynamical routing• Map studies Gradual changes in discharge 

    time‐series can be explained by • Stream network topology• Channel morphology 

  • 7/22/2016

    3

    General trend for increasing discharge powerspectrum slope in the May – Oct period

    • More rapid flow changes and increased risk for floods (further downstream)

    • Similar pattern for the scaling function : change of the landscape dominates over climate change on time scales 

  • 7/22/2016

    4

    Calculating hyporheic exchange from measued static head distribution

    0.00E+00

    2.00E‐04

    4.00E‐04

    6.00E‐04

    8.00E‐04

    1.00E‐03

    1.20E‐03

    1.40E‐03

    0 1000 2000 3000 4000 5000 6000

    Hydraulic con

    ductivity

     (m/s)  

    Longitudinal distance along stream (m) 

    Depth = 3 cm Depth = 7 cm

    Type 1Type 2  Type 3Type 2Type 3

    Head variation

    Hydraulic conductivity

    Tullstorps Brook, Sweden

    PG i 2S (i )i4 ∆ i

    1 exp 2 2 / i 1 exp 2 2 / i

    W 2 PG i

    i1

    N

    K

    Decomposition of hyporheic fluxes on wavelengths

    Manuscript in prep.See also Wörman et al., Geophysical Research letters (2006, 2007)

    Wavelength,  (m) 

    Gradient S

    pectrum, P

    G

    Exchange velocity, W (m/s)

    1D gradient spectrum, PG (‐), along stream

    = wavelengthS() = Power spectral density of hydraulic headK = Hydraulic conductivity = depth to impermeable surface (or decay parameter)

    Hydrostatic vs. hydrodynamic drivers in Tullstops Brook

    Longest wavelength considered (m) 

    Static head driver

    Dynamic head driver

    Hydrostatic and hydrodynamic drivers can be created in remediation actions

    Partitioning of head gradient on drivinga) stream flow, andb) hyporheic flow Riffle‐and‐pool sequence

    Balance between preventing floods and purifying stream water

    no remediation measure

    increased meandering

    length=77 mT=4904 sCV(T)=63.1

    length=520 mT=855 sCV(T)=19.7

    Comparison with results from tracer tests using Rhodamine WT

    Tracer injection

    Breakthrough curves

    sediment trap/pond

  • 7/22/2016

    5

    “Acceptable” agreement between predicted and observed values of hyporheic exchange

    Verification of bio‐chemical treatment effect remains

    Planning Injection liquid

    Pumping

    Radioisotopes Injection container

    Aliquot from injection liquidWaste team

    Simultaneous Tracer Test: 3H2O, 15NO3 and 32PO4Not yet evaluated

    Conclusions

    Gradual increased risk for floods and rapid flow changes during 20th century‐ Gradual smaller proportion of head gradients used for purifying stream water‐ Lesser nutrient retention and decay?

    Hydrological changes can be noted in agricultural areas due to drainage works‐ Discharge statistics from mid 1800s ‐ (Limited) map studies and routing analyses

    Design approach for estimating hyporheic exchange and treatment effect‐ Static head drivers tend to dominate hyporheic flows‐ Optimization of total head fall for driving the stream and hyporheic flows

    Åkesson, A., Peakflow response of stream network, PhD thesis report TRITA‐HYD 2015:2, The Royal Institute of Technology, Stockholm, Sweden. 

    Åkesson, A., Wörman, A., Riml., J., Seibert, J., 2015. “Change in streamflow response in unregulated catchments in Sweden over the last century”, Online Water Resources Research

    Åkesson, A. , Wörman, A., Bottacin‐Busolin, A., 2015. Hydraulic response in flooded stream networks. Water Resources Research, 50, pp. 213‐240, doi: 10.1002/2014WR016279

    Boano, F., Harvey, J.W., Marion, A., Packman, A.I., Revelli, R., Ridolfi., L., Wörman, A., 2014. “Hyporheic flow and transport processes: Mechanisms, models, and biogeochemical implications”, Reviews of Geophysics. Volume 52, Issue 4, pages 603–679, December 2014, doi: 10.1002/ 2012RG000417

    Morén, I., Riml, J., Wörman, A., 2016. “Design of remediation actions in streams for retention and degradation of nutrients in the hyporheic zone”, Manuscript.

    Riml., J., Wörman, A., 2015. “Spatio‐temporal decomposition of solute dispersion in watersheds”, Water Resources Research, DOI: 10.1002/2014WR016385.

    Wörman, A., Packman, A.I., Marklund, L., Harvey, J.W., Stone, S., 2006. “Exact three‐dimensional spectral solution to surface‐groundwater interactions with arbitrary surface topography”, Geophys. Res. Lett., 33, L07402, doi:10.1029/2006GL025747.

    Wörman, A., A. I. Packman, L. Marklund, J. W. Harvey, and S. H. Stone, 2007. ”Fractal topography and subsurface water flows from fluvial bedforms to the continental shield”, Geophys. Res. Lett.: 34, L07402, doi:10.1029/2007GL029426.

    Wörman, A., Lindström, G., Riml., J., Åkesson, A., 2010. “Drifting runoff periodicity during the 20th century due to changing surface water volume”, Hydrological Processes 2010, 24(26), 3772 – 3784, DOI: 10.1002/hyp.7810

    This presentation is based on the following publications: