Citation: Wang, D.; Wang, D.; Mei,Y.; Yang, Q.; Ji, M.; Li, Y.; Liu, S.; Li, B.; Huang, Y.; Mo, C. Estimates of the Land Surface Hydrology from the Community Land Model Version 5 (CLM5) with Three Meteorological Forcing Datasets over China. Remote Sens. 2024, 16, 550. https://doi.org/ 10.3390/rs16030550 Academic Editor: Hatim Sharif Received: 14 December 2023 Revised: 22 January 2024 Accepted: 28 January 2024 Published: 31 January 2024 Copyright: © 2024 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https:// creativecommons.org/licenses/by/ 4.0/). remote sensing Article Estimates of the Land Surface Hydrology from the Community Land Model Version 5 (CLM5) with Three Meteorological Forcing Datasets over China Dayang Wang 1 , Dagang Wang 2, * , Yiwen Mei 2 , Qing Yang 3 , Mingfei Ji 1 , Yuying Li 1 , Shaobo Liu 1 , Bailian Li 4 , Ya Huang 5 and Chongxun Mo 6 1 Overseas Expertise Introduction Center for Discipline Innovation of Watershed Ecological Security in the Water Source Area of the Middle Route of South-to-North Water Diversion, School of Water Resource and Environmental Engineering, Nanyang Normal University, Nanyang 473061, China; wangdy58@mail2.sysu.edu.cn (D.W.); jimfdy@gmail.com (M.J.) 2 School of Geography and Planning, Sun Yat-sen University, Guangzhou 510006, China; meiyw3@mail.sysu.edu.cn 3 School of Freshwater Sciences, University of Wisconsin-Milwaukee, Milwaukee, WI 53201, USA; yang2473@uwm.edu 4 International Center for Ecology and Sustainability, University of California, Riverside, CA 93106, USA 5 State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering, Hohai University, Nanjing 211098, China; hygccw@hhu.edu.cn 6 College of Civil Engineering and Architecture, Guangxi University, Nanning 530004, China * Correspondence: wangdag@mail.sysu.edu.cn Abstract: The land surface model (LSM) is extensively utilized to simulate terrestrial processes be- tween land surface and atmosphere in the Earth system. Hydrology simulation is the key component of the model, which can directly reflect the capability of LSM. In this study, three offline LSM simu- lations were conducted over China using the Community Land Model version 5.0 (CLM5) driven by different meteorological forcing datasets, namely China Meteorological Forcing Dataset (CMFD), Global Soil Wetness Project Phase 3 (GSWP3), and bias-adjusted ERA5 reanalysis (WFDE5), respec- tively. Both gridded and in situ reference data, including evapotranspiration (ET), soil moisture (SM), and runoff, were employed to evaluate the performance levels of three CLM5-based simulations across China and its ten basins. In general, all simulations realistically replicate the magnitudes, spatial patterns, and seasonal cycles of ET over China when compared with remote-sensing-based ET observations. Among ten basins, Yellow River Basin (YRB) is the basin where simulations are the best, supported by the higher KGE value of 0.79. However, substantial biases occur in Northwest Rivers Basin (NWRB) with significant overestimation for CMFD and WFDE5 and underestimation for GSWP3. In addition, both grid-based or site-based evaluations of SM indicate that systematic wet biases exist in all three CLM5 simulations for shallower soil layer over nine basins of China. Comparatively, the performance levels in simulating SM for deeper soil layer are slightly better. Moreover, all three types of CLM5 simulate reasonable runoff spatial patterns, among which CMFD can capture more detailed information, but GSWP3 presents more comparable change trends of runoff when compared to the reference data. In summary, this study explored the capacity of CLM5 driven by different meteorological forcing data, and the assessment results may provide important insights for the future developments and applications of LSM. Keywords: community land model; meteorological forcing; evapotranspiration; soil moisture; runoff; China 1. Introduction Land surface process plays a vital role in connecting the water cycle and energy process at the interface between land and atmosphere [1–3]. For instance, evapotranspiration (ET) Remote Sens. 2024, 16, 550. https://doi.org/10.3390/rs16030550 https://www.mdpi.com/journal/remotesensing