OR/14/018 Modelling approach adopted

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Mansour, M M, Hughes, A G. 2014. Land Use, Climate Change and Water Availability: Preliminary modelling of impacts of climate change and land use change on groundwater recharge for England and Wales. British Geological Survey Internal Report, OR/14/018.


The distributed recharge model ZOODRM (Mansour et al., 2011[1]) is used to calculate the soil moisture deficit and soil storage. ZOODRM belongs to the suite of object oriented models ZOOM (Jackson and Spink, 2004[2]) developed at BGS. ZOODRM calculates distributed potential recharge values using rainfall and potential evaporation data, crop root constant, and soil characteristics such as the moisture content at field capacity and, moisture content at wilting. The recharge algorithm applied in this work is the simplified FAO method (Griffiths et al., 2006[3]).

Whilst ZOODRM has been developed as a recharge model, for this project it has been used to calculate Hydrologically Effective Rainfall (HER). HER being defined as the component of rainfall left after actual evaporation has been taken off. The FAO56 method has been used to produce a surplus from the soil store, this is split into runoff and recharge using a runoff coefficient to define the ratio between the two.

Three sets of runs have been undertaken for this project: historical simulation, Climate Change using the FFGWL hydrology and land use change.

Table 1. Summary of data used for each set of runs.
Variable Historical simulation FFGWL Land use change
Rainfall Daily 1 km2 gridded rainfall for January 1961 to December 2010 Daily 1 km2 gridded rainfall appropriate climate runs from a-k for three time slices: 2020s, 2050s and 2080s Same as for Hist. Sim.
Potential Evaporation MORECS 40 x 40 km2 monthly PE from January 1961 to December 2012 PE for appropriate climate runs from a-k for three time slices: 2020s, 2050s and 2080s Same as for Hist. Sim.
Digital Elevation Model (DEM) CEH DTM 50 m Resolution Same as for Hist. Sim. Same as for Hist. Sim.
Land Cover Map LCM 2000 1 km Resolution Same as for Hist. Sim. Modified for each run.
Soil data HOST soil data 1 km Resolution Same as for Hist. Sim. Same as for Hist. Sim.
Runoff coefficients Calibrated, but distributed by geological outcrop Same as for Hist. Sim. Same as for Hist. Sim.
Crop coefficients See Table for RAW/TAW Same as for Hist. Sim. Same as for Hist. Sim.

Further explanation of the data is provided in the section below.

Data used


Figure 3 shows the LTA rainfall distribution (1961–2008) across England and Wales. The UK has a Maritime Climate characterised by a predominantly westerly wind direction. This leads to a 'conveyer' of frontal systems off the Atlantic which brings moisture preferentially to Wales and the West of England. Orographic effects (higher ground enhancing rainfall) means there is rainfall gradient from higher ground in the west to lower lying areas in the east. The highest rainfall totals occurring in Wales, Cornwall, North Devon and further north in Lancashire and the Lake District (Cumbria).

Potential Evaporation

Figure 4 illustrates the MORECs (Hough and Jones, 1997[4]) results for 1961 to 2008. Potential Evaporation is controlled by temperature, windspeed and direction combined with sunshine hours. The spatial distribution of long-term average PE is the inverse of rainfall, decreasing from west to east. The minimum PE occurs in Wales and the Lake District whilst the highest PE is observed to the east of the country.


The majority land use for England and Wales is presented in Figure 5. There is a roughly east-west split in terms of land-use across England, with the land cover mapped in north-western and south-western England being improved and semi-natural grassland. With the exception of urban areas, central and eastern England is predominantly arable. Parts of southern, central and north-western England are heavily urbanised, containing the London, Birmingham and Liverpool/Manchester conurbations respectively. Wales has a similar land cover for north-western and south-western England that is predominantly improved and semi-natural grassland.


The HOST soil map (Boorman et al., 1995[5]), as presented in Figure 6, reflects the underlying geology with the soil types in the south and east of England dominated by Cretaceous Chalk and Jurassic Limestones. The western part of England along with Wales is predominantly derived from shales, siltstones and clays or hard rocks.

Implications for recharge calculation

Rainfall, PE, land use (and subsequent crop growth) along with soil type all act in combination to control potential recharge. The rainfall decreases from west to east, whilst the PE increases. Mitigated by land use and the distribution of soils, this means that recharge generally decreases eastwards. Distribution of long-term average potential recharge maps for England and Wales are presented and discussed in Historical simulation, see for example, Figure 8.

Figure 3 Long-term average rainfall.
Figure 4 Long-term average potential evaporation calculated from MORECs.
Figure 5 Majority land use (LCM2000).
Figure 6 HOST soil map.

Description of ZOODRM

The grid resolution is 2 km by 2 km and Figure 7 shows the model grid for the whole of England and Wales. Due to the resolution of the figure, the details of the grid can’t be seen over England and Wales so details are provide for a northern catchment the Tees and a catchment in the south of England, the River Thames. A soil water balance is calculated at nodes which are located where the grid lines cross. Land use mapping (Figure 5) is used to inform the choice of crop coefficients (Table 2) for the FAO method of calculating a soil balance (Allen et al., 1998[6]). When the soil moisture deficit reduces to zero any additional water is then split between runoff and potential recharge using the runoff coefficient to determine the proportion. Overlaid on this is the river network to which water is routed by the direction of the DEM. Once runoff is generated then it is routed down topographic gradient until it reaches the river where it is routed towards the sea.

For the historical simulation, the model is run from 1st January 1962 to 31st December 1992 using a daily time step.

Table 2. Crop coefficients used for the model simulations.
Crop Maximum Root Depth (mm) Depletion factor (-)
Deciduous 2000 0.8
Coniferous 1512 0.7
Arable 750 0.8
Grass 450 0.5
Upland 120 0.37
Urban 900 0.5
Open Water 3000 0.999

Further details of the calculation method is provided in Appendix 1.

Figure 7 ZOODRM grid.

Runs undertaken


As stated above there is a basecase and two sets of runs: climate change based on the FFGWL hydrology dataset and a second to investigate the impacts of land use change. Table 3 details the runs undertaken, the rainfall, PE and land use data sets used as input data.

Table 3. Summary of runs undertaken.
Series Run Rainfall PE Land use Notes
Historical Simulation Basecase Daily 1 km2 gridded rainfall for January 1961 to December 2011 MORECS 40 x 40 km2 monthly PE from January 1961 to December 2012 LCM2000 Basecase for all runs; run from 1962–1992
Climate Change a

FFGWL : Afgcx

LCM2000 Three time slices: 2010–2039 2030–2069 and 2070–2099

FFGWL : Afixa


FFGWL : Afixc


FFGWL : Afixh


FFGWL : Afixi


FFGWL : Afixj


FFGWL : Afixk


FFGWL : Afixl


FFGWL : Afixm


FFGWL : Afixo


FFGWL : Afixq

Land use LCM2007 Daily 1 km2 gridded rainfall for January 1961 to December 2010 MORECS 40 x 40km2 monthly PE from January 1961 to December 2012 LCM2007 All land use runs are from 1962–1992
All woodland Woodland Crops coefficients for trees used everywhere
All grass Grass Crops coefficients for grass used everywhere
All arable Arable Crops coefficients for arable used everywhere
50% woodland to arable Modifying 50% woodland to arable at the grid node where it occurs
50% woodland to grass Modifying 50% woodland to grass at the grid node where it occurs
50% grass to arable Modifying 50% grass to arable at the grid node where it occurs
50% grass to woodland Modifying 50% grass to woodland at the grid node where it occurs
50% arable to woodland Modifying 50% arable to woodland at the grid node where it occurs
50% arable to grass Modifying 50% arable to grass at the grid node where it occurs

Historical simulation

The calibration of the recharge model is performed by comparing the simulated overland flows at selected gauging stations to the observed flows. ZOODRM calculates runoff values based on the runoff coefficient values assigned to runoff zones that are derived from hydrogeological and geological maps. 56 gauging stations were selected from The Hydrometric Register and Statistics books published by the Centre of Ecology and Hydrology (NERC, 2003[7]) to calibrate the model. A list of these catchments and their locations are shown in Appendix 2. These are the gauging stations that have the largest catchment areas and are located at the major rivers. In general, the period of record spans over 40 years (1960s–2000s) and consequently the recorded river flows are treated as long term average (LTA) river flows. Because the recharge model ZOODRM does not account for groundwater flows and consequently calculates only the surface water component of the total river flows, the observed LTA surface water components of river flows were used in the model calibrations. These were calculated from the Hydrometric Register book by multiplying average total flows by the residual of 1 minus the baseflow index for each gauging station.

The simulated long term average distributed recharge values provide a baseline to which recharge values calculated using future climate and socio-economic (represented by changes in the land cover map) data can be compared to. However, the distributed recharge model ZOODRM does not account for some processes such as snow melt. These processes are taken into account during the generation of future climate data. The comparison between the results produced using future climate data and historic data produced inconsistent observations mainly at elevated grounds. The LTA historic results are used, therefore, to study the impact of socio-economic changes only

Climate Change

The Future Flows climate data is a set of climate projections, the development of which is described by Prudhomme et al. (2013)[8]. They are an 11 member ensemble of transient climate projections based on HadRM3-PEE-UK, which has been used as part of the derivation of the UKCP09 scenarios (Murphy et al., 2007, Prudhomme et al., 2013[8]). 148 years of gridded rainfall and evaporation data for 11 scenarios are available. These are divided into four time horizons. These are: the simulated historic time horizon (1962–1992), the first, second and third time horizons, which are also labelled 30s, 50s, and 70s and covers up to years 2039, 2069, and 2099 respectively.

Land use change

The socio-economic impact on the calculated recharge values are investigated though the use of two different land use cover maps — the LCM2000 (Fuller et al., 2002[9]) and LCM2007 (Morton et al., 2011[10]) in addition to three scenarios where the whole of the country is assumed to be covered by one land use type consisting of either arable, grass, or woodland. It was recognised that changing land use for the whole of England and Wales was unrealistic. Various land use scenarios have been developed including four by the Environment Agency (2009)[11] and six for the National Ecosystem Assessment (NEA, 2011[12]). The latter scenarios show a maximum change of 50% of each land use category related to the baseline.

Whilst it would have been idea to use the NEA scenarios, these were not available in an appropriate form during the project lifetime. Therefore, to assess the impacts of a more realistic set of future land use scenarios, six additional runs have been performed, however, to investigate theoretical, but more likely changes in percentage land use cover. The land use for these six runs is created by replacing 50% of one class where it occurs in the LCM2000 by another class. The classes are replaced in pairs taken from woodland, grass and arable classes.


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  3. GRIFFITHS, J., YOUNG, A R and KELLER, V. 2006. Model scheme for representing rainfall interception and soil moisture. Environment Agency Environment Agency R & D Project W6-101 Continuous Estimation of River Flows (CERF). UK.
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