Detailseite
Projekt Druckansicht

Predicting hydrological fluxes in the Haihe river basin using remote sensing and data assimilation methods

Fachliche Zuordnung Hydrogeologie, Hydrologie, Limnologie, Siedlungswasserwirtschaft, Wasserchemie, Integrierte Wasserressourcen-Bewirtschaftung
Förderung Förderung von 2010 bis 2012
Projektkennung Deutsche Forschungsgemeinschaft (DFG) - Projektnummer 162231035
 
Erstellungsjahr 2013

Zusammenfassung der Projektergebnisse

In order to close the water balance and to estimate groundwater recharge and evapotranspiration at an experimental site in the Hai river basin, two lysimeter systems were installed. In an agricultural region in Huailai county, 70 km northwest of Beijing, the lysimeters record hydrological states and fluxes. The whole setup can be compared to the Terrestrial Environmental Observatories (TERENO) SoilCan Initiative. Measurement indicate no significant groundwater recharge in this region. The whole data set recorded can be used for numerical experiments. In a synthetic experiment, the assimilation of soil moisture observations to the HYDRUS-1D model with the Sampling Importance Resampling Particle Filter shows an improved prediction of the soil moisture profile. This is mainly driven by the dual state-parameter estimation procedure significantly reducing uncertainty not only in the state space but also in the space of the Mualem-van Genuchten hydraulic parameters. Moreover, results indicate the ability of the system to improve the simulation of hydrological fluxes. Evapotranspiration as well as leachate can be estimated with high accuracy. Because a lightning damaged the soil moisture logger, this experiment could not be conducted for real observations recorded at the two lysimeters. This is planned as soon as a significant time series is recorded.

Projektbezogene Publikationen (Auswahl)

  • (2010): Estimation of Hydraulic Parameters by Simulated Remotely-Sensed Top Soil Moisture Observations with the Particle Filter. Workshop on Remote Sensing Methods for Change Detection and Process Modelling, Cologne, 18 - 19 November 2010
    Montzka, C., H. Moradkhani, L. Weihermüller, H.-J. Hendricks Franssen, M. Canty and H. Vereecken
  • (2012): Assimilation of Soil Moisture and Eddy Covariance Data by Particle Filter to Improve Predictions with HYDRUS-1D. 5th International Workshop on Catchment Hydrological Modeling and Data Assimilation (CAHMDA-V), Enschede, The Netherlands, 9 - 13 July 2012
    Kessomkiat, W., H.-J. Hendricks Franssen, C. Montzka, L. Weihermüller and H. Vereecken
  • (2012): Multivariate and multiscale data assimilation in terrestrial systems: A review. Sensors 12(12), 16291-16333
    C. Montzka, V. R. N. Pauwels, H.-J. Hendricks Franssen, X. Han and H. Vereecken
    (Siehe online unter https://doi.org/10.3390/s121216291)
  • (2013): Measurements of evapotranspiration from eddy-covariance systems and large aperture scintillometers in the Hai River Basin, China. Journal of Hydrology 487, 24–38
    S.M. Liu, Z.W. Xu, Z.L. Zhu, Z.Z. Jia and M.J. Zhu
 
 

Zusatzinformationen

Textvergrößerung und Kontrastanpassung