Quantifying the Interactions of Noah‐MP Land Surface Processes on the Simulated Runoff Over the Tibetan Plateau Journal Article uri icon

Overview

abstract

  • AbstractThe quantification of uncertainties in runoff over the Tibetan Plateau (TP), simulated by land surface models (LSMs), is of paramount importance for effective water resources management within this region. However, the interactions of land surface processes on simulated runoff, where the effectiveness of one process depends on the chosen scheme for another, have rarely been studied. To address this gap, we conducted ensemble simulations with the Noah‐MP (Noah with multiparameterization) LSM by varying the optional parameterization schemes of six land surface processes and quantified the sensitivities of the simulated runoff to these processes. Results showed that the simulated runoff over the TP was most sensitive to the RUN (runoff‐groundwater) process. The interplay of RUN and FRO (frozen soil permeability) accounted for up to 30% of the variation in the annual mean surface runoff in the TP's permafrost regions. The interactions of RUN and VEG (dynamic vegetation) on summer and autumn subsurface runoff exceeded 10% in the southeast TP. In regions where these interactions among land surface processes significantly affected simulated runoff, we observed elevated model errors and reduced model controllability. Therefore, this study underscores the imperative need to categorize land regions based on the interactions of land surface processes as a foundational step toward enhancing the performance of LSMs. Prioritizing improvements in model physics should be particularly directed toward regions marked by high interactions.

publication date

  • April 16, 2024

has restriction

  • closed

Date in CU Experts

  • September 4, 2024 9:03 AM

Full Author List

  • Li J; Gan Y; Zhang G; Gou J; Lu X; Miao C

author count

  • 6

Other Profiles

International Standard Serial Number (ISSN)

  • 2169-897X

Electronic International Standard Serial Number (EISSN)

  • 2169-8996

Additional Document Info

volume

  • 129

issue

  • 7