Developing a Lateral Terrestrial Water Flow Scheme to Improve the Representation of Land Surface Hydrological Processes in the Noah‐<scp>MP</scp> of <scp>WRF</scp>‐Hydro

ABSTRACT Lateral terrestrial water flow in the Weather Research and Forecasting (WRF) Model and its hydrologically enhanced version, WRF‐Hydro, is calculated on a routing grid based on infiltration excess in Land Surface Model (LSM) grid disaggregates to the routing grids. However, this design neglects the lateral terrestrial water flow within LSM grids and does not resolve water lateral transport in LSM. In this study, we develop a lateral terrestrial water flow scheme in the Noah with multiparameterization (Noah‐MP) of WRF‐Hydro grids to address this knowledge gap and evaluate its influence on land surface hydrological processes. Our results indicate that lateral terrestrial water flow leads to 62.3% of grid surface water outflow, resulting in a decrease in accumulated water depth by 123.88 mm. In urban areas, the accumulated water depth further reduces by 21.11 mm when considering the pipe discharge scheme. Compared to the default WRF‐Hydro simulation, the lateral terrestrial water flow combined with pipe discharge can effectively advance the calibrated WRF‐Hydro modelling capability and reproduce the water depth reasonably compared to the observation in urban areas. Further, our analysis indicates that the decreasing lateral terrestrial water flow in LSM primarily reduces overland flow and increases streamflow in routing grids, mainly through redistributing water from the steep slopes towards the lower elevations and ultimately converting it to streamflow in the channel network.

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Publication Details

Journal
Hydrological Processes
Published
2024-12-01
DOI
https://doi.org/10.1002/hyp.70021
Citations
1
Primary Topic
Geophysics and Gravity Measurements
Type
article
Field-Weighted Citation Impact
0.48

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article

Developing a Lateral Terrestrial Water Flow Scheme to Improve the Representation of Land Surface Hydrological Processes in the Noah‐MP of WRF‐Hydro

Ashok Kumar Pokharel, C.‐I. Meng, Shiguang Miao, Jie Wang et al.
1 citations
Hydrological Processes
Geophysics and Gravity Measurements
0.48
article

Developing a Lateral Terrestrial Water Flow Scheme to Improve the Representation of Land Surface Hydrological Processes in the Noah‐MP of WRF‐Hydro

Ashok Kumar Pokharel, C.‐I. Meng, Shiguang Miao, Jie Wang, Yuhuan Li, Bin Ma, Jingjing Dou
article en
1 citations

Abstract

ABSTRACT Lateral terrestrial water flow in the Weather Research and Forecasting (WRF) Model and its hydrologically enhanced version, WRF‐Hydro, is calculated on a routing grid based on infiltration excess in Land Surface Model (LSM) grid disaggregates to the routing grids. However, this design neglects the lateral terrestrial water flow within LSM grids and does not resolve water lateral transport in LSM. In this study, we develop a lateral terrestrial water flow scheme in the Noah with multiparameterization (Noah‐MP) of WRF‐Hydro grids to address this knowledge gap and evaluate its influence on land surface hydrological processes. Our results indicate that lateral terrestrial water flow leads to 62.3% of grid surface water outflow, resulting in a decrease in accumulated water depth by 123.88 mm. In urban areas, the accumulated water depth further reduces by 21.11 mm when considering the pipe discharge scheme. Compared to the default WRF‐Hydro simulation, the lateral terrestrial water flow combined with pipe discharge can effectively advance the calibrated WRF‐Hydro modelling capability and reproduce the water depth reasonably compared to the observation in urban areas. Further, our analysis indicates that the decreasing lateral terrestrial water flow in LSM primarily reduces overland flow and increases streamflow in routing grids, mainly through redistributing water from the steep slopes towards the lower elevations and ultimately converting it to streamflow in the channel network.

Hydrological ProcessesVol. 38(12)
China Meteorological Administration (CN), Chinese Academy of Sciences (CN), Institute of Tibetan Plateau Research (CN), Lanzhou University (CN)
National Natural Science Foundation of China
Openalex Percentile: Top 31%
Geophysics and Gravity Measurements
0.48
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