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Azin Howells Supervisors: Prof. Hannah Cloke | Prof. Anne Verhoef | Prof. Florian Pappenberger | Dr. Antje Weisheimer Department of Geography and Environmental Science There is a clear lag between SPI&SPEI compared to Agricultural drought indices and also SGI (Fig. 2). According to the model outputs, maize does not seem a good option to be planted during drought; whereas barley seems to be less susceptible to droughts (Fig. 3). Stakeholders, impact: This research will benefit decision-makers including farmers and water companies in building up resilience via effective drought management. The results from this research can be of interest to reinsurance companies for setting up more realistic weather-indices, and accounting for climate change in their calculations. Future work: CHTESSEL (ECMWF) and JULES (UK Met Office) LSMs will be used in the same manner as SWAP to gain a better understanding of the most important model parameters regarding prediction of droughts. References Bloomfield, J.P. & Marchant, B.P., 2013. Analysis of groundwater drought building on the standardised precipitation index approach. Hydrology and Earth System Sciences, 17(12), pp.4769–4787; Mckee, T.B., Doesken, N.J. & Kleist, J., 1993. The relationship of drought frequency and duration to time scales. AMS 8th Conference on Applied Climatology, (January), pp.179–184. ; Narasimhan, B. & Srinivasan, R., 2005. Development and evaluation of Soil Moisture Deficit Index (SMDI) and Evapotranspiration Deficit Index (ETDI) for agricultural drought monitoring. Agricultural and Forest Meteorology, 133(1-4), pp.69–88. ; Vicente-Serrano, S.M., Beguería, S. & López-Moreno, J.I., 2010. A Multiscalar Drought Index Sensitive to Global Warming: The Standardized Precipitation Evapotranspiration Index. Journal of Climate, 23(7), pp.1696–1718. Rationale Climate extremes have devastating effects on life and the environment. In particular, the impact of droughts on ecosystems, agriculture, societies and economies is significant. Classification of droughts depends on the earth system compartment they affect: Meteorological (rain deficit), Agricultural (available soil water deficit), Hydrological (river flow deficit) and Groundwater (ground water level deficit) droughts. Prediction of drought onset and termination is of great importance for preparedness purposes and for building up resilience against droughts. The aim of this thesis is to: • improve model forecasting skills in terms of UK drought prediction through comparison of parameterisations of 3 land surface models, and associated parameter uncertainties and sensitivities • help improve drought-related decision-making processes Research questions • Which land surface properties and variables (e.g. soil moisture) are most important in seasonal forecasting of droughts? • Can representation of uncertainty in modeled land surface hydrology improve drought forecast skill? • Can soils management and crop choice be manipulated in the context of drought avoidance, management and mitigation? Methodology: Four sites were selected in key drought prone areas of the UK: Heydon (Norfolk, River Wensum), Long Sutton (Somerset, River Yeo and River Parrett), Teston (Kent, river Medway), Shaw (Berkshire, River Lambourn). Atmospheric data for these sites were obtained from ERA-Interim (ECMWF website: http://apps.ecmwf.int/datasets/data/interim-full- daily/levtype=sfc/) database and verified against MIDAS dataset and UKCP09 Met Office gridded data. SWAP (Soil, Water, Atmosphere, and Plant, which is a powerful agro-hydrological model (http:// www.swap.alterra.nl/) was run for the 4 sites with modeled sand/ loam/clay soil types, each with 1/5/10 percent organic matter and 7 types of crops (Spring Barley, Grass, Sugarbeet, Maize, Winter Wheat, Oilseed rape and Potato) as well as bare soil. The following drought indices were calculated: SPI (Standardized Precipitation Index) can be 1,3,6,9,12 or 24 months index, function of precipitation, calculated using pure atmospheric data (Mckee et al. 1993); SPEI (Standardized Precipitation and Evapotranspiration Index) can be 1,3,6,9,12 or 24 months index, function of precipitation and temperature, calculated using pure atmospheric data (Vicente- Serrano et al. 2010); ETDI (Evapotranspiration Deficit Index) weekly index, function of actual evapotranspiration, calculated using model output (Narasimhan & Srinivasan 2005); SMDI (Soil Moisture Deficit Index) weekly index, function of available soil moisture in the rooting zone, calculated using model output (Narasimhan & Srinivasan 2005); SGI (Standardized Groundwater level Index ) monthly index, function of groundwater level, calculated using model output (Bloomfield &Marchant, 2013). Results: Comparison of SPI and SPEI (Fig. 1) for the four sites shows similar results, which means there is not much difference in choice of site regarding atmospheric forcing in England, as meteorological droughts of comparable strengths occurred concurrently in all these areas. The effect of land surface hydrological process representation on drought prediction Acknowledgement This PhD is part of a wider research project led by the University of Reading and funded by the Natural Environment Research Council (NERC): IMPETUS: Improving Predictions of Drought for User Decision-Making. Contact information University of Reading, Department of Geography and Environmental Sciences, Email: [email protected] ; http://www.researchgate.net/profile/Azin_Howells/info https://www.mapcustomizer.com/ Soil Texture of R iver Wensum catchment area. (Geological Map Data, NERC 2016, Crown copy right and database right 2016, Ordnance Survey ( Digimap Licence)). Fig 1: SPI 12 and SPEI 12 for the four sites with ERA-Interim dataset Fig 3: SMDI Drought index for Hungerford soil (near Lambourn) Fig 2: Drought indices for Hungerford soil (near Lambourn) when barley was planted Upper Lambourn Tatcham Shaw Newbury Hungerford Azin Howells University of Reading 0 2 4 6 8 10 12 14 16 18 20 km Hungerford Apr 19, 2016 01:40 Scale 1:150000 Digimap G e o l o g i a l M a p D a a © N E R C 2 0 1 6 © C o w n C o p r i g h a n d D a a b a s e R i g h 2 0 1 6 O d n a n c e S u v e y D i g i m a p L i c e n c e .
