DelegatePack_DroughtConference_20-21March2019

Speakers
Day 1: Parallel Session 1 Climatology and Hydrology – Pichette Auditorium continued
Elizabeth Brock Met Office & Katharine Smart Anglian Water
What does stochastic rainfall generation and Bayesian extreme value analysis mean for Water
Resource Planning
For the Water Resources Management Plan 2019 (WRMP19), Anglian Water assessed the return period of historical
and stochastic droughts with particular reference to ‘severe’ or 1 in 200 year return period events. This required reanalysis
of historical events using up-to-date extreme value techniques, as well as the development and analysis of
stochastically-generated droughts which were different in nature and severity to historical references. This talk
discusses the Met Office’s role as a leader in weather and climate science, with advanced expertise in statistical
analysis of extreme events such as multi-year drought, in providing supporting information to Anglian Water for their
WRMP19 which addresses current and future risk of water scarcity in their catchment areas. This includes: An
evaluation of a stochastic rainfall dataset using a spatially and temporally coherent generator1 in the context of
drought planning and an outline of further statistical methods that were applied to the generator configuration
regarding application of an atmospheric climate pressure index; Discussion of the difficulties associated with evaluation
of return levels for multi-year drought events and introduction of the prototype Bayesian extreme value analysis
method it has used in order to overcome these challenges; Potential further developments of the Bayesian Extreme
Value analysis technique and other statistical analysis techniques available to drought planners to assess drought in the
context of a changing climate will be discussed; A final word on methods applied to the rainfall generator dataset so
that Anglian Water could evaluate the potential risk associated with future climate change using UKCP09 and how
this might differ given the more recent outputs of the UKCP18 project. 1. Serinaldi, F. and Kilsby, C.G., 2012. A
modular class of multisite monthly rainfall generators for water resources management and impact studies. Journal of
Hydrology 464-465, p. 528-540
Dr Christopher Nankervis Weather Logistics Ltd
Use of Copernicus seasonal climate forecast model data to improve the accuracy of long-term
forecasts: the UK Summer Rainfall Insights project
Summer rainfall variability is the most common cause of agricultural losses, accounting for production losses of up to
30%. Salads and field vegetables are especially prone to dry summers with demand on water resources. Combined
with high temperatures that stunt crop growth, summer droughts can wreak havoc for the supply of fresh produce to
our supermarkets. With access to Copernicus seasonal climate forecast model data, we now have the ability to
improve the accuracy of long-term forecasts by combining open source model data with field- level climate and
historical daily data records. This stands to revolutionise the way that farmers operate to better optimise their crop
production through actionable decisions. With more accurate long-term forecasts large-scale growers can better
select sites based on soil moisture availability, delay sowing, select drought tolerant crops or better plan their water
resources. The result is a future of farming less vulnerable to the seasonal weather variability, higher yields and
sustainable produce for British supermarkets. Our European Space Agency-funded project, UK Summer Rainfall
Insights (UKSRI), aims to develop a new summer rainfall forecasting service for release in summer 2019. This will
provide daily rainfall analytics at the field-level, providing early information about upcoming droughts in the UK.
Ragab Ragab CEH
Study of the drought risk in different UK catchments under future climate and land use changes.
Ragab, Ragab; Afzal, Muhammad1; Blake, James1 and Kaelin, Alexandra.1
This study aimed at investigating the impact of climate and land-use changes on drought severity for different
catchments across the UK from North to South and from West to East namely, Eden, Don, Frome, Bevills Leam,
Pang, Ebbw and Fowey. A physically based distributed catchment-scale model (DiCaSM) was applied. The catchment
area of the studied catchments varied from over 150 km2 to over 300 km2. In all studied catchments the severity of
the historic droughts was most obvious in the 1970s, as well as those of the late 1980s, the 1990s, 2003 and 2012.
The severity of the drought varied from one catchment to another, mainly due to the geographical location of the
catchment, seasonal variability of the rainfall, prevailing temperature and land use practices. The DiCaSM model was
calibrated using the measured stream flow. For most of the studied catchments the Nash- Sutcliffe efficiency factor
(NSE), as an indicator of goodness of fit, gave a value of above 0.9 during the model calibration period, and a NSE
value above 0.80 over the entire study period (approx.1961-2012) during the validation process. The uncertainty
analysis supported the good model performance result as the measured streamflow fell within the model envelope of
5 and 95% likelihood-weighted quantiles with acceptable containment ratio (CR).
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