COSMOS-UK: A New Field-scale National

Soil Moisture Measurement Network Jonathan Evans, Lucy Ball, James Blake, Olivia Hitt, Dan

Rylett, George Wright, Hollie Cooper, Helen Vincent, Sarah

Bagnoli, Pete Scarlett, Ross Morrison, Matt Fry, David

Boorman, Andrew Singer and Richie Ellis.

Centre for Hydrology & Ecology, Wallingford, Oxon., UK

SAC Soil Moisture Workshop

25th January 2017

Contact: CosmosUK@ceh.ac.uk

Introduction

• Background & Rationale

• COSMOS measurement

principle

• Station design –

measurements & sensors

• Data

• Results and future work

Scientific Rationale

Why is Soil Moisture Important?

Because:

1) Soil Moisture (SM) controls the land surface energy

balance:Solar radiation (sunlight) warms the earth’s surface– warming the ground (soil heat

flux)- Warming the air (sensible

heat flux)- And evaporating moisture

from soil and plants (evapo-transpiration)

- Soil thermal properties are controlled by SM

- Reflected and emitted radiation depends on soil moisture

Why is Soil Moisture Important …?

Because:

2) Soil Moisture (SM)

controls hydrological

processes

- Runoff- Infiltration- Recharge of groundwater- Evaporation- Availability of water to

plants/crops- Available water resource

Diagram from http://www.brighthubengineering.com/hydraulics-civil-engineering/41692-learn-about-natural-water-movement-through-a-water-cycle-diagram/#imgn_2

From Zreda et. al.Hydrol. Earth Syst. Sci., 16, 4079–4099, 2012www.hydrol-earth-syst-sci.net/16/4079/2012/doi:10.5194/hess-16-4079-2012

(1) A cascade of high-energy (~1 GeV) secondary neutrons are produced by primary cosmic ray protons entering the earth’s magnetosphere

(2) High-energy secondary neutrons collide with nuclei in the atmosphere ‘evaporating’ fast neutrons (~1MeV) – these are scattered in the air and ground, loosing energy to become thermal (0.025 eV) or epithermal neutrons (> 0.5 eV)

Cosmic Rays and Soil Moisture

The COsmic-ray Soil Moisture Observing System

Courtesy of: Marek Zreda, Jim Shuttleworth, Xubin Zeng, Chris Zweck and Ty Ferre

•Naturally occurring high energy neutrons generated by cosmic rays, are at equilibrium above the surface: the balance of supply of fast neutrons and their moderation (thermalisation) by surrounding nuclei.•BF3 or He3 gas discharge tube a.k.a. cosmic ray soil moisture probe) detects reduction in fast neutrons as soil moisture increases (more H). atoms).

Cosmic Ray Soil Moisture Probe (Hydroinnova CRS-2000/B) at HollinHill, N. Yorks.

COSMOS Measurement area (modelled)

By Marek Zreda

• 86% of neutrons detected are from within a radius of 200 m• Footprint is mostly independent of soil moisture• Footprint increases with altitude (decreasing pressure)

COSMOS integrates soil moisture over a 200 m radius

Measurement depth (modelled)

• 86% of neutrons from within 70 cm soil depth for very dry conditions• In very wet soils only neutrons from the top 12 cm reach detector• neutron source soil depths are independent of altitude (pressure)

By Marek Zreda

COSMOS integrates soil moisture from the surface to a depth of 12-70 cm depending on the soil moisture content

Corrections to Neutron Counts

Raw neutron counts (Nraw) and the correction factors applied (Fp, FQ, FC, black lines) to obtain corrected counts (Ncorr) for CHIMN. Relevant variables (p, Q, C) are also shown in each case (green lines, right-hand axes). The temporal resolution of the data is 60 min.

Sensors

• Goal is to measure water and energy balances

• research grade weather station, 4-component radiometer, heat flux plates and soil temperature profile

• Point soil moisture sensors (x2) at 10 cm, and soil moisture profile – for ‘sense’ check.

• High accuracy, low maintenance weighing rain gauge.

• All sensors logged on a Campbell CR3000 with GPRS telemetry.

Phase 1 Installation Works

Chimney Meadows , Bampton, Oxfordshire (CHIMN)

Gill MetpakAcclima TDT & Soil heat flux plate

IMKO installation, CHIMN

OTT Pluvio II install at SHEEP

Hukseflux STP01 soil temperature profile

Completed Phase 1 Sites

Sheepdrove Organic Farm, Lambourn, West Berkshire (SHEEP)

Waddesdon Manor Farm, Buckinghamshire (WADDN)Note: only moderated CRS-1000 tube installed

Current network

WA

DD

ES

DO

N

Installed

Total 41• UK wide coverage

• Varying spatial density

• Range of climate, land cover, soils, geology, topography

• ‘Simple’ grassland

• Build on existing research / networks

• Pragmatic approach

Data Flows•Automated telemetry of data in real-time•Automated calibration & quality control•Data continuously archived to CEH Oracle database•Data requests currently served manually

Web resources

Other soil moisture sensors (1)

Daily data from Rothamsted

COSMOS Data

Daily averages (lines) and 6-h running means (shading) of COSMOS soil moisture content and modelled effective measurement depth

COSMOS & ASCAT SM Indices

Soil moisture indices from COSMOS and ASCAT data for Chimney Meadows and Sheepdrove Organic Farm (August 2011-December 2013). The resolution of the data is daily. Dashed lines are 1:1; solid lines are linear regressions through the data.

CRS SM compared with JULES

VWC from CRS probes compared to 10 cm SM from the JULES model for Chimney Meadows and Sheepdrove Organic Farm

J. G. Evans et. al., 2016. “Soil water content in southern England derived from a cosmic-ray soil moisture observing system – COSMOS-UK” Hydrological Processes http://onlinelibrary.wiley.com/doi/10.1002/hyp.10929/full

Phenocam Example – Time Lapse Movie

• Useful for interpreting physical measurements

• Gives information on land cover, crop growth, grazing etc.

• Possible uses for biodiversity?

Moor House

Thank you.

Questions..?

Data Assimilation: COSMIC

• The variable measurement depth of the Cosmic-ray Soil Moisture Sensor compared to the constant soil moisture depth layers in land surface models (LSM) could be a disadvantage.

• But by using the predicted soil moisture from the LSM to predict the expected neutron count circumvents this issue.

• The COsmic-ray Soil Moisture Interaction Code (COSMIC1) provides an analytical model to predict neutron counts from the LSM, allowing data assimilation of measured counts.

1.Shuttleworth et.al. 2013, HESS

WHY SOIL MOISTURE IS IMPORTANT?

Outline

- MOTIVATIONS

- THE JULES MODEL - a “land-surface” model(Thanks to Eleanor Blyth and Alberto Martinez-de la Torre)

- THE GRID-TO-GRID MODEL - a “hydrological”

model(Thanks to Vicky Bell)

WHY SOIL MOISTURE IS IMPORTANT?

Soil availability

Land-useAgriculture

Soil moisture effects many human activities

Floods

WHY SOIL MOISTURE MODELLING?

• Traditional field measurement of soil moisture is

time consuming and expensive

• Soil moisture is not routinely monitored over the

long term like precipitation and discharge

• The remotely sensed soil moisture data has its

own uncertainties; e.g. mismatch in scale

between the in situ measurements; surface

estimates only.

• Increasing computational speeds allow for more

accurate numerical modelling techniques

• Models can tell what will be: evaluating effects of

land-use, climate changes

vs

THE LAND-SURFACE MODEL JULES

JULES is a community model of land surface, vegetation and soil processes led by

CEH and the UK Met Office

~200 users across NERC, Met Office,

universities, overseas,…

>40 NERC proposals since 2008 with

JULES activity

Used by the Met Office weather and

climate models (IPCC)

Will be used in NERC/Met Office UK

Earth System Model (UKESM1)

Applications:

THE LAND-SURFACE MODEL JULES

THE LAND-SURFACE MODEL JULES

Energy BudgetPhotosynthesis

Water Budget

Carbon Cycle

Carbon assimilated

from the air, converted

Into leaf, roots and

stem carbon.

CO2 and CH4

release from soil

Water flows between the

atmosphere and the surface

Carbon and water flows

through the stomata

between the surface and

the atmosphere:

photosynthesis, respiration

and transpiration

The snow pack

can have up to 3

layers

Water and heat

flows:

ice formation effect

Energy flows

between the

surface and the

atmosphere:

radiation, heat

and latent heat

modified from: JULES: Best et al, 2011, Clark et al, 2011, GMD. http://JULES.JCHMR.ORG

THE LAND-SURFACE MODEL JULES

Energy BudgetPhotosynthesis

Water Budget

Carbon Cycle

Carbon assimilated

from the air, converted

Into leaf, roots and

stem carbon.

CO2 and CH4

release from soil

Water flows between the

atmosphere and the surface

Carbon and water flows

through the stomata

between the surface and

the atmosphere:

photosynthesis, respiration

and transpiration

The snow pack

can have up to 3

layers

Water and heat

flows:

ice formation effect

Energy flows

between the

surface and the

atmosphere:

radiation, heat

and latent heat

modified from: JULES: Best et al, 2011, Clark et al, 2011, GMD. http://JULES.JCHMR.ORG

Plants grows

and compete

with each

other for light,

changing the

land cover

1. Incoming moisture is split into runoff and water absorbed.

Runoff is diverted in rivers.

2. There is a constant redistribution of water within the soil column

as it tries to reach a state of equilibrium. This is determined

using the Darcy’s law:

𝑞 = 𝐾𝜕Ψ

𝜕𝑧+ 1

3. At the bottom of the soil layers (3m), water is taken out at a rate

assuming only gravitational effects – free drainage.

4. This drainage joins the surface runoff in rivers.

THE LAND-SURFACE MODEL JULES

Model INPUT

Soil moisture and runoff component

• Incoming solar radiation

• Relative humidity

• Atmospheric pressure

• Air temperature

• Precipitation

• Wind speed

Model soil moisture OUTPUT

10 cm35 cm

100 cm

300 cm

• Averaged soil moisture

typically at 4 depths

THE LAND-SURFACE MODEL JULESSoil moisture content for all UK at 1km

resolution: mean for the 1961-2012 period

Plot scale soil moisture content

evolution in time for different layers.

Available at http://earth2observe.github.io/water-

resource-reanalysis-v1/results/table_sma.html

0-10 cm

depth

100-300

cm depth

Standard deviation of the soil moisture content anomalies at

global scale at ~50km resolution for the 2002-2012

CHESS (1km resolution)

driving data available thought

the CEH webpage

The Grid-to-Grid hydrological model

Energy BudgetPhotosynthesis

Water Budget

Carbon Cycle

Carbon assimilated from

the air, converted Into leaf,

roots and stem carbon.

CO2 and CH4

release from soil

Water flows between the surface and the

atmosphere: precipitation

Carbon and water flows

through the stomata

between the surface and

the atmosphere:

photosynthesis, respiration

and transpiration

The snow pack can

have up to 2 layers

Surface and sub-surface runoff

routed laterally to estimate

downstream rive flows

Energy flows

between the

surface and the

atmosphere:

radiation, heat and

latent heat

Dry snow

Wet snow

Unsaturated zone

Saturated zone

The Grid-to-Grid hydrological model

River

Soil column

depth, L s0

Percolation,

QP

Lateral

drainage,

QD

Groundwater

flow (sub-

surface runoff),

QG

Subsurface

flow

Saturation-

excess surface

runoff, q

• A spatially distributed grid-based model

• Driven by gridded rainfall and potential evaporation data

• Estimates naturalised river flows on a 1km grid at 15 min t-step

• Gridded spatial datasets of landscape properties (soil, land-cover, topography, geology) reduces the need for calibrating model parameters

Bell et al. (2009). Journal of Hydrology, 377 (3-4), 335-350

Data available on request:

• daily/monthly/annual 1km grids of depth averaged soil moisture

• monthly grids should be freely available soon.

The Grid-to-Grid applications

• Flood forecasting - used countrywide for operational flood forecasting and warning for the EA and SEPA

• Models national river flows 24/7, forecasts out to 5 days

• Surface water flooding

• Estimating projected future change in UK river flows (collaboration with Met Office Hadley Centre)

• Seasonal forecasting of river flows and subsurface water storage: http://www.hydoutuk.net/

• Sensitivity to rainfall map used in EA/FFC’s Flood Outlook (used by operational flood managers)

Flood forecasting with G2G

Soil moisture (%)Soil moisture (%)

Applications: Sensitivity to rainfall map

This map uses the G2G estimates of subsurface storage to highlight areas where water storage, s, is below or above the monthly mean (smean),

and by how much (mm)

This map highlights areas where the ground is WET relative to the

long term – now used by EA/FFC in their fortnightly “Flood Outlook”

Soil moisture

Collaboration with EA and Met Office

Bell VA, Davies HN, Kay AL, Marsh TJ, Brookshaw A, Jenkins A. 2013. Developing a large-scale

water-balance approach to seasonal forecasting: application to the 2012 drought in Britain.

Hydrological Processes, 27(20), 3003–3012.

Applications: seasonal hydrological forecasts

• The most recent end of month G2G sub-surface storage estimate is used as the initial condition for a water-balance forecast of the next 1- and 3-months sub-surface storage using Met Office GloSea5 rainfall forecast ensemble members and climatological PE as input (Bell et al. 2013).

• Corresponding ensembles of regional river flow estimates for the next 1- and 3-months ahead can be estimated using the water balance (WB) hydrological model using historical and spatial information from the G2G.

Present day

G2G run WB model run for 1-3 months ahead

Observed rain+ PE Ensemble forecast monthly rain + mean PE

Bell, V. A., Davies, H. N., Kay, A. L., Brookshaw, A. &

A.A, Scaife. A national-scale seasonal hydrological

forecast system: Development and evaluation over

Britain, HESS (2017, in preparation)

To summarise….

Land Surface Models (e.g. JULES)Self-consistent representation of energy and evaporationModels many processes (Temperature, CO2, snow etc.)Complex formulation, slow, can lack accuracyLimited assessment against observations

Hydrological Models (e.g. Grid-to-Grid, PDM)Required to be fast and accurateRealistic representation of river flow processesGood for modelling floods & droughts in river basinsAssessed against observations

Groundwat

er storage

Surface

storageDirect

runoff

Probability-

distributed soil

moisture

storage

Surface

runoff

Baseflow

Recharg

e

P

E

S1

qs

qb

S3

S2

q

Groundwat

er storage

Surface

storageDirect

runoff

Probability-

distributed soil

moisture

storage

Surface

runoff

Baseflow

Recharg

e

P

E

S1

qs

qb

S3

S2

q

Often used for research into large scale feedbacks

Often used for civil engineering applications e.g. flood forecasting

To summarize….

Land Surface Models (e.g. JULES)Self-consistent representation of energy and evaporationModels many processes (Temperature, CO2, snow etc.)Complex formulation, slow, can lack accuracyLimited assessment against observations

Hydrological Models (e.g. Grid-to-Grid, PDM)Required to be fast and accurateRealistic representation of river flow processesGood for modelling floods & droughts in river basinsAssessed against observations

Groundwat

er storage

Surface

storageDirect

runoff

Probability-

distributed soil

moisture

storage

Surface

runoff

Baseflow

Recharg

e

P

E

S1

qs

qb

S3

S2

q

Groundwat

er storage

Surface

storageDirect

runoff

Probability-

distributed soil

moisture

storage

Surface

runoff

Baseflow

Recharg

e

P

E

S1

qs

qb

S3

S2

q

Often used for research into large scale feedbacks

hydrology

evaporation

Often used for civil engineering applications e.g. flood forecasting