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

Lu Zhuo, Dawei Han, Qiang Dai, Tanvir Islam, Prashant K Srivastava

Research output: Contribution to journalArticle (Academic Journal)peer-review

36 Citations (Scopus)
461 Downloads (Pure)

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.
Original languageEnglish
Pages (from-to)3503-3517
Number of pages15
JournalWater Resources Management
Volume29
Issue number10
Early online date26 Apr 2015
DOIs
Publication statusPublished - Aug 2015

Research Groups and Themes

  • Water and Environmental Engineering

Keywords

  • Hydrological modelling
  • Land surface modelling
  • Xinanjiang
  • Soil moisture deficit
  • NLDAS-2
  • Evaluation

Fingerprint

Dive into the research topics of 'Appraisal of NLDAS-2 Multi-Model Simulated Soil Moistures for Hydrological Modelling'. Together they form a unique fingerprint.

Cite this