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SUMMARY:EESS talk on "Towards educated decision-making on water resources 
 in the face of uncertainty of climate projections"
DTSTART:20230314T121500
DTEND:20230314T131500
DTSTAMP:20260510T025342Z
UID:dc172d93fbd61a208a0956755f62b94e29bd7820e006019dce29158c
CATEGORIES:Conferences - Seminars
DESCRIPTION:Prof. Paolo Reggiani\, Department of Civil Engineering\, Unive
 rsity of Siegen\nAbstract:\nOngoing global warming requires to periodicall
 y revisit and validate adaptation strategies in water resources planning a
 nd management to address resource scarcity challenges in the not-to-distan
 t future.  This concerns especially the agricultural sector\, which in ma
 ny parts of the world is heavily dependent on freshwater for irrigation\, 
 but can be extended to related areas like renewable energy. The main chall
 enge in proposing mitigating actions lies in the uncertainty of climate pr
 ojections\, especially the non-stationarity of the change process.  Conti
 nuing to assume stationarity or applying simple trend extrapolation to pro
 ject current states into the future is not to be considered satisfactory a
 nd is therefore entrusted to Earth-system model ensembles\, which are gene
 rated across international model inter-comparison projects (e.g. CMIP5 and
  CMIP6).\nDecision-making in water resources planning can be supported by 
 stochastic optimization approaches\, like for instance stochastic-dynamic 
 programming (SDP)\, which take uncertain temperature\, precipitation or su
 rface runoff signals as input to optimize the management of reservoirs or 
 irrigation systems managed through a set operational rules and/or chosen b
 est cropping practices. A sharp and calibrated specification of the uncert
 ainty affecting climate forcing variables through a predictive probability
  density or approximated via appropriately derived ensembles constitutes t
 he most important prerequisite for reaching optimal decisions. The ensembl
 e spread provided by multiple raw Earth-system model outputs\, which is of
 ten interpreted as representing true climate uncertainty\, requires furthe
 r processing to obtain a useful predictive density through Bayesian condit
 ioning on observations\, under the assumption of weakly stationary process
 es.\nThrough an application to rainfall and seasonal temperature over Nort
 hern Italy\, we show the difference between the probability distributions 
 derived directly from the projection ensembles and those derived after con
 ditioning raw projections on observations. These distributions\, directly 
 or in the form of derived ensembles\, will be the basis for rationally imp
 lementing any further decision-making process.\n\nShort biography:\nP. Reg
 giani holds of the Chair of Water Resources Management and Climate Impact 
 Research at the University of Siegen\, Germany. P. Reggiani graduated in E
 nvironmental Engineering at the University of Trento\, Italy\, in 1994.  
  He completed his Ph.D. at the University of Western Australia. Between 1
 999 and 2000 P. Reggiani worked at CSIRO Land and Water\, where he develop
 ed modeling approaches to assess dryland salinity in Australia. After his 
 return to Europe in late 2000 he worked as “Marie Curie Fellow” at the
  soil science lab LTHE in Grenoble\, France. In 2002 he took up an appoint
 ment as researcher and scientific consultant at the Dutch Institute Deltar
 es. In 2014 he was appointed Full Professor at the University of Sieger. D
 uring his career\, P. Reggiani worked in various applied scientific and co
 nsulting projects in Asia\, Africa and Europe. Am important focal point of
  his scientific work has been the interface between numerical weather pred
 iction and hydrological forecasting\, including the area of forecasting un
 certainty\, as well as operational water management in data-poor areas.  
 P. Reggiani has published more than 50 papers in different areas of hydrol
 ogy\, climate change impacts on water resources\, flood forecasting\, chan
 nel hydraulics and soil science. He also acted as coordinator for several 
 projects\, among which the EU FP5 R&D initiative “European Flood Forecas
 ting System (EFFS)”. P. Reggiani partakes in several scientific boards o
 n water resources issues. He is part of the standing Committee on Hydrolog
 ical Services (Sercom-HYD) at the World Meteorological Organization.\n 
LOCATION:GR A1 402 https://plan.epfl.ch/?room==GR%20A1%20402 https://epfl.
 zoom.us/j/69011077410
STATUS:CONFIRMED
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