Managing the impactof fine sediment onriver ecosystems

Iwan Jones, Adrian Collins, JohnMurphy, David Sear, Pam Naden

Erosion and Deposition are Natural Processes

Human Activities Influence Load andRetention

Impact of Fine Sediment inRiver

Light reductionBed alteration

Altered hydrodynamicsOxygen depletion

ScouringBurial

Impact of Fine Sediment lossfrom Field

ErosionLoss of Fertility

Mechanical Difficulties

Need a better way to assess andmanage

Fine Sediment

Sources of fine sedimentNational-scale sediment sourceapportionment for England & Wales Relative

contribution ofagriculture toannual sedimentload

>50%<50%

Zhang, Collins et al. (2014) Env. Sci. Pol. 42:16-32

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WQ0128 Extending the evidencebase on the ecological impacts offine sediment and developing a

framework for targeting mitigationof agricultural sediment losses

Project structure

Impact of Fine Sediment

Assess Extent of ProblemIntrinsic Sediment Yields

Policy Options

The concept

Yield estimated from lake deposits

Psychic 2004 and Targets

Foster, I.D.L., Collins, A.L.,Naden, P.S., Sear, D.A. &Jones J.I. (2011) Journal ofPalaeolimnology 45, 287-306.

Impact of Fine Sediment

Review impacts on:Fish

InvertebratesMacrophytes

Diatoms

Impact of Fine Sediment inRiver

Light reductionBed alteration

Altered hydrodynamicsOxygen depletion

ScouringBurial

Impacts via

Suspended Sediment

Deposited Sediment

Habitat

Predators

Food

Lithophilous (gravel spawning) Fish

Kemp et al. (2011) Hydrological Processes

Sediment, Agricultural Calendar and FishReproduction

Survival of Atlantic salmon embryos in relation to% fine sediment

% S

urvi

val t

o ha

tch

Kemp et al. (2011) Hydrological Processes

Review Papers

Reviews of Biological Impacts– Key Findings

1. Catchment dependency2. Reach dependency3. Sediment dependency4. Taxon dependency5. Life-stage dependency

• Existing evidence base for impacts of fine sediment islargely correlative

• Failure to elucidate the critical process linkagesbetween sediment stress and key environmentalparameters/characteristics

Reviews of Biological Impacts– Key Findings

Improved Ecological Evidence

Fish response to sediment stress– Role of Sediment Oxygen Demand– New approaches to source apportionment– Manipulative experiments

Fish Experiments

C

C

CC

CC

CC

123510

12 3 510• Lethal and Sub-lethal Effects

• Identified the Critical Role of Organic Fraction

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Brown Trout

Atlantic Salmon

Bank Agriculture Road STW0

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Brown Trout

Atlantic Salmon

a

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cc d

ee e

Mor

talit

yM

orta

lity

a)

b) A

B

BCC

Sediment mass added (g wet weight)

Both load andsource important

Sear et al. (submitted)

• Extended field evidence andcalibration datasets for SedimentIntrusion and Dissolved Oxygen(SIDO)-UK spawning habitat model

• Applied new approaches to sourceapportionment – tracing sources oforganic matter

• Developed better understanding ofrole of Sediment Oxygen Demand

Source fingerprinting pasture topsoils cultivated topsoils damaged road verges channel

banks/subsurfacesources

STWs / pointsources

Artificial redd sediment sampling

Sediment fingerprinting

Sediment fingerprinting

Sediment fingerprinting

Sediment fingerprinting

• pasture topsoils– 29±1%

• cultivated topsoils– 3±1%

• damaged road verges– 33±1%

• channel banks / subsurfacesources– 31±1%

• STWs / point sources– 4±1%

Source fingerprinting farm yard manures

and slurries damaged road verges instream decaying

vegetation point sources (STWs /

septic tanks)

Organics analysis• shredded material:

– TC / TN– NIR– bulk isotopes 13C, 15N

• humic substances:– fluorescence– SUVA254– TOC

Sediment Oxygen Demand

Used SIDO-UK to develop abetter understanding of roleof Sediment OxygenDemand

Both agricultural and non-agricultural sediment has thepotential to impact aquaticecology.

More organic sedimentderived from pointsources and damaged roadverges resulted in morepronounced detrimentaleffects.

Sear et al. (2014) Hydrological Processes 28: 86-103

Improved Ecological Evidence

Invertebrate response to sediment stress– Correlative field survey– Manipulative experiments

Calibration dataset• 230 sites sampled for macroinvertebrates & deposited

fine sediment

• across a gradient of modelled sediment pressure

• across a gradient of stream types

• free from STW and urban area inputs

• upstream of lakes & reservoirs

• predominantly agricultural catchments

Objectives

• Establish relationship between macroinvertebratecommunity and fine sediment pressure at an appropriatemanagement scale

• Develop a diagnostic biotic index

• Independently test new index

Macroinvertebrate sampling

At each site:– macroinvertebrate sample (RIVPACS protocol)o record physical features of siteo acquire map-based data

Fine sediment samplingAt each site:

o remobilisation stilling wellsample surface drape and embedded fine sediment

from erosional and depositional areas

Processed in the lab for: mass of sediment organic content particle size

Duerdoth et al. (2015) Geomorphology 230: 37–50

Duerdoth et al. (2015) Geomorphology 230: 37–50

Fine sediment sampling

Reach scale confidence intervals and reproducibility quantified

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site mean log10

surface sediment mass (g m-2) site mean log10

total sediment mass (g m-2)

site mean log10

surface non-volatile sediment mass (g m-2) site mean log10

total non-volatile sediment mass (g m-2)

site mean log10

surface volatile sediment mass (g m-2) site mean log10

total volatile sediment mass (g m-2)

surface drape total

sam

ple

log 10

sur

face

sed

imen

t mas

s (g

m-2

)sa

mpl

e lo

g 10 s

urfa

ce n

on-v

olat

ile

sedi

men

t mas

s (g

m-2

)

sam

ple

log 10

sur

face

vol

atile

sed

imen

t

mas

s (g

m-2

)

sam

ple

log 10

tota

l sed

imen

t mas

s (g

m-2

)sa

mpl

e lo

g 10 to

tal n

on-v

olat

ile

sedi

men

t mas

s (g

m-2

)

sam

ple

log 10

tota

l vol

atile

sed

imen

t

mas

s (g

m-2

)a)

b)

c)

95% Confidenceintervals = ±0.237

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95% Confidenceintervals = ±0.236

95% Confidenceintervals = ±0.188

95% Confidenceintervals = ±0.235

95% Confidenceintervals = ±0.227

95% Confidenceintervals = ±0.169

Comparison with visual estimatesof bed composition

surface drape: average

mean substratum size phi

sedi

men

t mas

s g/

m2

-8 -4 0 4 8

100

101

102

103

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total sediment: average

mean substratum size phi

sedi

men

t mas

s g/

m2

-8 -4 0 4 8

100

101

102

103

104

105

Visual estimates only explain 50-60% of the variation in fine sedimentmass

Analytical Approach

Predicted Sediment LoadPredicted Sediment RetentionMeasured Retained SedimentMeasured Sediment Quality

Invertebrate communityrange of sediment loadings

within river types

Analytical Approach

• Association between variation in the macroinvertebratecommunity and the fine sediment stressor gradienthaving first factored out that portion of the biologicalvariation correlated with natural background variation

• Empirical basis for a diagnostic biotic index• Relationship between modelled agricultural fine

sediment inputs, retentiveness of stream reach andbiological condition of the reach quantified

• Link land-use models to WFD water quality status.

Unconfoundedstress gradients

Invertebrate response to fine sediment stress comprises twodistinct components

ToFSIsp – index of response to organic component of finesediment

oFSIsp – index of response to organic component of finesediment

The results of these two indices are then combined

CoFSIsp – combined index of fine sediment stress

Index Development

Index response (development sites)

54321

6.5

6.0

5.5

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4.0

log Fine Sediment Mass (g m-2)

cFSI

sp

S 0.348063R-Sq 56.3%R-Sq(adj) 56.1%

cFSIsp = 6.553 - 0.5467 logSedMass

CoF

SIsp

Independent test26 sites retained from the survey and 57 streamsites in Wales

Independent test26 sites retained from the survey and 57 streamsites in Wales

Sediment Experiments in ArtificialStream Channels

Jones et al. (2015) Freshwater BiologyGrowns et al. (submitted)

Response variablesTurbidityDeposited Sediment MassOxygen PenetrationHyporheic ChemistryInteraction with Flow

DriftCommunity CompositionIndex ValuesTrait CompositionHyporheic Invertebrates

CONTROL MODERATE HIGH

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Log 10

Indi

vidu

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PT

cFS

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ToFS

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CoFSIsp index performs wellPSI index unstable

Linking to sediment pressure models

6.05.55.04.54.03.5

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Observed cFSIsp

Mo

del

led

cFS

Isp

(F= 65.5, P< 0.001, R2 = 52.1%).M

odel

led

CoF

SIsp

Observed CoFSIsp

Outputs• Quantified changes in macroinvertebrate

community across a gradient of fine sedimentpressure.– Identify taxa sensitive and tolerant to fine sediment stress

• Developed and tested a new diagnostic biotic index• Linked diagnostic index to estimates of sediment

pressure

New Modelling Framework daily time step

use of weather data (as opposed to climatic mean) explicit representation of pathways (tramlines,

compaction, etc) explicit representation of crops and rotations drain flow connectivity and retention:

field boundaries types particle size distribution and selectivity

Conceptual flow pathways in catchments

Preferential flow todrains

Slow flow to drainsTo groundwater

Plot-scalerunoffinitiation

Field boundaryretention

LandscaperetentionIn-field

retention

MITIGATION

Simulation at catchment scale

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Sedi

men

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g/l)

PredictedObserved

• Downscale catchment scale processes to the channel reachand redd scales

• use of a hydraulic sediment routing model to link network toreach scales

In-channel sediment routing

Catchment Reach Redd> 1 km2 100-50 m

< 1 m

Psychic SIDO-UKRouting

Revising estimates of good ecologicalstatus for sediment

Use of the modelling toolkit

• catchment-specificrevised sediment targets

• implications for meetingrevised targets of– mitigation programmes– climate change

projections for 2020,2030, 2050, 2080

Mitigation methods for inorganic sediment

Establish cover crops in the autumn

Early harvesting and establishment of crops in the autumn

Cultivate land for crops in spring rather than autumn

Adopt reduced cultivation systems

Cultivate compacted tillage soils

Cultivate and drill across the slope

Leave autumn seedbeds rough

Manage over-winter tramlines

Establish in-field grass buffer strips

Establish riparian buffer strips

Re-site gateways away from high-risk areas

Modelling toolkit for managing theproblem

• Ecological status linked to land-use modelsto enable managers to explore outcome ofagricultural mitigation options

• Better targeting of mitigation

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Clean

Dirty

Num

bero

ftax

a

Flow

Number of taxaPERMANOVA results

Significant factor % Variance explained

Flow 35

Sediment 14

Interaction with flow

Fluorescence composite fingerprints