Fundamentals of Data Assimilation and Theoretical Advances

  • Hamid Moradkhani
  • Grey S. Nearing
  • Peyman Abbaszadeh
  • Sahani Pathiraja
Reference work entry


Hydrometeorological predictions are not perfect as models often suffer either from inadequate conceptualization of underlying physics or non-uniqueness of model parameters or inaccurate initialization. During the past two decades, Data Assimilation (DA) has received increased prominence among researchers and practitioners as an effective and reliable method to integrate the hydrometeorological observations from in situ measure and remotely-sensed sensors into predictive models for enhancing the forecast skills while taking into account all sources of uncertainties. The successful application of DA in different disciplines has resulted in an ever-increasing publications. This chapter provides a progressive essay covering fundamental and theoretical underpinnings of DA techniques and their applications in a variety of scientific fields. More detailed examples of applications are presented in following chapters in this section.


Hydrometeorological predictions Uncertainty Data Assimilation (DA) 


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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  • Hamid Moradkhani
    • 1
  • Grey S. Nearing
    • 2
  • Peyman Abbaszadeh
    • 1
  • Sahani Pathiraja
    • 3
  1. 1.Department of Civil, Construction and Environmental EngineeringThe University of AlabamaTuscaloosaUSA
  2. 2.Department of Geological SciencesUniversity of AlabamaTuscaloosaUSA
  3. 3.Institute for Mathematics, University of PotsdamPotsdamGermany

Section editors and affiliations

  • Hamid Moradkhani
    • 1
  • Albrecht Weerts
    • 2
  1. 1.Department of Civil & Environmental EngineeringPortland State UniversityPortlandUSA
  2. 2.Inland Water SystemsDeltaresThe Netherlands

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