Soil Moisture Workshop LARGE SCALE SOIL MOISTURE MODELLING Giuseppe Formetta, Vicky Bell, and Eleanor Blyth giufor@nerc.ac.uk Centre for Ecology and Hydrology, Wallingford, UK Wednesday 25 th January 2017 Satellite Applications Catapult Electron Building, Fermi Avenue, Harwell
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 moisture effects many human activities Floods Agriculture Land-use Soil availability
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. vs Increasing computational speeds allow for more accurate numerical modelling techniques Models can tell what will be: evaluating effects of land-use, climate changes
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 Applications: ~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)
THE LAND-SURFACE MODEL JULES
THE LAND-SURFACE MODEL JULES Energy Budget Energy flows between the surface and the atmosphere: radiation, heat and latent heat Carbon Cycle Carbon assimilated from the air, converted Into leaf, roots and stem carbon. Photosynthesis Carbon and water flows through the stomata between the surface and the atmosphere: photosynthesis, respiration and transpiration Water Budget Water flows between the atmosphere and the surface The snow pack can have up to 3 layers Water and heat flows: ice formation effect CO2 and CH4 release from soil modified from: JULES: Best et al, 2011, Clark et al, 2011, GMD. http://jules.jchmr.org
THE LAND-SURFACE MODEL JULES Energy Budget Energy flows between the surface and the atmosphere: radiation, heat and latent heat Plants grows and compete with each other for light, changing the land cover Carbon Cycle Carbon assimilated from the air, converted Into leaf, roots and stem carbon. Photosynthesis Carbon and water flows through the stomata between the surface and the atmosphere: photosynthesis, respiration and transpiration Water Budget Water flows between the atmosphere and the surface The snow pack can have up to 3 layers Water and heat flows: ice formation effect CO2 and CH4 release from soil modified from: JULES: Best et al, 2011, Clark et al, 2011, GMD. http://jules.jchmr.org
THE LAND-SURFACE MODEL JULES Model INPUT Incoming solar radiation Relative humidity Atmospheric pressure Air temperature Precipitation Wind speed Soil moisture and runoff component Model soil moisture OUTPUT Averaged soil moisture typically at 4 depths 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. 10 cm 35 cm 100 cm 300 cm
THE LAND-SURFACE MODEL JULES Soil moisture content for all UK at 1km resolution: mean for the 1961-2012 period Standard deviation of the soil moisture content anomalies at global scale at ~50km resolution for the 2002-2012 0-10 cm depth 100-300 cm depth Available at http://earth2observe.github.io/waterresource-reanalysis-v1/results/table_sma.html Plot scale soil moisture content evolution in time for different layers. CHESS (1km resolution) driving data available thought the CEH webpage
The Grid-to-Grid hydrological model Energy Budget Energy flows between the surface and the atmosphere: radiation, heat and latent heat Photosynthesis Carbon and water flows through the stomata between the surface and the atmosphere: photosynthesis, respiration and transpiration Water Budget Water flows between the surface and the atmosphere: precipitation Carbon Cycle Carbon assimilated from the air, converted Into leaf, roots and stem carbon. CO2 and CH4 release from soil Dry snow Wet snow Unsaturated zone Saturated zone The snow pack can have up to 2 layers Surface and sub-surface runoff routed laterally to estimate downstream rive flows
The Grid-to-Grid hydrological model 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 Data available on request: Soil column depth, L River s 0 Saturationexcess surface runoff, q Lateral drainage, Q D Percolation, Q P Groundwater flow (subsurface runoff), Q G daily/monthly/annual 1km grids of depth averaged soil moisture monthly grids should be freely available soon. Subsurface flow Bell et al. (2009). Journal of Hydrology, 377 (3-4), 335-350
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 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. Soil moisture This map uses the G2G estimates of subsurface storage to highlight areas where water storage, s, is below or above the monthly mean (s mean ), 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 Collaboration with EA and Met Office
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). G2G run Observed rain+ PE Present day WB model run for 1-3 months ahead Ensemble forecast monthly rain + mean PE 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. 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 evaporation Models many processes (Temperature, CO 2, snow etc.) Complex formulation, slow, can lack accuracy Limited assessment against observations P Direct runoff Surface storage S 2 E q Surface s runoff q Probabilitydistributed soil moisture storage S 1 Recharg e Groundwat er storage S 3 q b Baseflow Hydrological Models (e.g. Grid-to-Grid, PDM) Required to be fast and accurate Realistic representation of river flow processes Good for modelling floods & droughts in river basins Assessed against observations Often used for research into large scale feedbacks Often used for civil engineering applications e.g. flood forecasting
To summarize. hydrology Land Surface Models (e.g. JULES) Self-consistent representation of energy and evaporation Models many processes (Temperature, CO 2, snow etc.) Complex formulation, slow, can lack accuracy Limited assessment against observations P Direct runoff Surface storage S 2 E q Surface s runoff q Probabilitydistributed soil moisture storage S 1 Recharg e Groundwat er storage S 3 q b Baseflow Hydrological Models (e.g. Grid-to-Grid, PDM) Required to be fast and accurate Realistic representation of river flow processes Good for modelling floods & droughts in river basins Assessed against observations evaporation Often used for research into large scale feedbacks Often used for civil engineering applications e.g. flood forecasting
Thanks for your attention