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Appraisal of NLDAS-2 Multi-Model Simulated Soil Moistures for Hydrological Modelling

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  • Lu Zhuo
  • Dawei Han
  • Qiang Dai
  • Tanvir Islam
  • Prashant Srivastava

Abstract

Soil moisture is a key variable in hydrological modelling, which could be estimated by land surface modelling. However the previous studies have focused on evaluating these soil moisture estimates by using point-based measurements, and there is a lack of attention for their appraisal over basin scales particularly for hydrological applications. In this study, we carry out for the first time, a detailed evaluation of five sources of soil moisture products (NLDAS-2 multi-model simulated soil moistures: Noah, VIC, Mosaic and SAC; and a ground observation), against a widely used hydrological model Xinanjiang (XAJ) as a benchmark at a U.S. basin. Generally speaking, all products have good agreements with the hydrological soil moisture simulation, with superior performance obtained from the SAC model and the VIC model. Furthermore, the results indicate that the in-situ measurements in deeper soil layer are still usable for hydrological applications. Nevertheless further improvement is still required on the definition of land surface model layer thicknesses and the related data fusion with the remotely sensed soil moisture. The potential usage of the NLDAS-2 soil moisture datasets in real-time flood forecasting is discussed. Copyright Springer Science+Business Media Dordrecht 2015

Suggested Citation

  • Lu Zhuo & Dawei Han & Qiang Dai & Tanvir Islam & Prashant Srivastava, 2015. "Appraisal of NLDAS-2 Multi-Model Simulated Soil Moistures for Hydrological Modelling," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 29(10), pages 3503-3517, August.
    • Handle: RePEc:spr:waterr:v:29:y:2015:i:10:p:3503-3517
    DOI: 10.1007/s11269-015-1011-1
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    References listed on IDEAS

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    Cited by:

    1. Nayara P. V. Andrade & Marcelo R. Viola & Samuel Beskow & Tamara L. Caldeira & Li Guo & Carlos R. Mello, 2020. "Assessment of Spatial and Temporal Soil Water Storage Using a Distributed Hydrological Model," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 34(15), pages 5031-5046, December.
    2. Ahmet Emre Tekeli & Hesham Fouli, 2017. "Reducing False Flood Warnings of TRMM Rain Rates Thresholds over Riyadh City, Saudi Arabia by Utilizing AMSR-E Soil Moisture Information," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(4), pages 1243-1256, March.
    3. Zhiyong Wu & Huihui Feng & Hai He & Jianhong Zhou & Yuliang Zhang, 2021. "Evaluation of Soil Moisture Climatology and Anomaly Components Derived From ERA5-Land and GLDAS-2.1 in China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 35(2), pages 629-643, January.
    4. Prashant K. Srivastava, 2017. "Satellite Soil Moisture: Review of Theory and Applications in Water Resources," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 31(10), pages 3161-3176, August.

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