Evaluation of ORCHIDEE-MICT-simulated soil moisture over China and impacts of different atmospheric forcing data

Zun Yin,Hyungjun Kim,Jan Polcher,Feng Zhou,Other China-Trend-Stream Project Members ,Dan Zhu,Catherine Ottlé,Shilong Piao,Xuhui Wang,Matthieu Guimberteau,Philippe Ciais,Shushi Peng,Fabienne Maignan

doi:10.5194/hess-22-5463-2018

Abstract

Abstract. Soil moisture is a key variable of land surface hydrology, and its correct representation in land surface models is crucial for local to global climate predictions. The errors may come from the model itself (structure and parameterization) but also from the meteorological forcing used. In order to separate the two source of errors, four atmospheric forcing datasets, GSWP3 (Global Soil Wetness Project Phase 3), PGF (Princeton Global meteorological Forcing), CRU-NCEP (Climatic Research Unit-National Center for Environmental Prediction), and WFDEI (WATCH Forcing Data methodology applied to ERA-Interim reanalysis data), were used to drive simulations in China by the land surface model ORCHIDEE-MICT(ORganizing Carbon and Hydrology in Dynamic EcosystEms: aMeliorated Interactions between Carbon and Temperature). Simulated soil moisture was compared with in situ and satellite datasets at different spatial and temporal scales in order to (1) estimate the ability of ORCHIDEE-MICT to represent soil moisture dynamics in China; (2) demonstrate the most suitable forcing dataset for further hydrological studies in Yangtze and Yellow River basins; and (3) understand the discrepancies of simulated soil moisture among simulations. Results showed that ORCHIDEE-MICT can simulate reasonable soil moisture dynamics in China, but the quality varies with forcing data. Simulated soil moisture driven by GSWP3 and WFDEI shows the best performance according to the root mean square error (RMSE) and correlation coefficient, respectively, suggesting that both GSWP3 and WFDEI are good choices for further hydrological studies in the two catchments. The mismatch between simulated and observed soil moisture is mainly explained by the bias of magnitude, suggesting that the parameterization in ORCHIDEE-MICT should be revised for further simulations in China. Underestimated soil moisture in the North China Plain demonstrates possible significant impacts of human activities like irrigation on soil moisture variation, which was not considered in our simulations. Finally, the discrepancies of meteorological variables and simulated soil moisture among the four simulations are analyzed. The result shows that the discrepancy of soil moisture is mainly explained by differences in precipitation frequency and air humidity rather than differences in precipitation amount.

Highlights

Climate change strongly influences the hydrological cycle, which in turn affects ecosystems services, food security, and water resources (Bonan, 2008; Piao et al, 2010; Seneviratne et al, 2010; Zhu et al, 2016)
Xinxian is located in the North China Plain with similar MAP (580 mm yr−1) to Xifeng, but in a traditional irrigation region (Wang et al, 2016). θt at Xinxian is underestimated, possibly because irrigation is not included in our simulations
Note that this study only provides the evaluation of soil moisture (SM), but other hydrological components should be compared with observations to confirm the superiority of GSWP3 and WFDEI

Summary

Introduction

Climate change strongly influences the hydrological cycle, which in turn affects ecosystems services, food security, and water resources (Bonan, 2008; Piao et al, 2010; Seneviratne et al, 2010; Zhu et al, 2016). In China, annual precipitation has increased in the south but declined in the north over the last several decades (Ye et al, 2013; Zhai et al, 2005). This dipole of precipitation trends is partly reflected in the discharge trends of Yangtze and Yellow rivers (Piao et al, 2010), but other factors than precipitation changes affect river discharge including changes in rainfall intensity, land surface state or condition, and water management (Ayalew et al, 2014; Grillakis et al, 2016; Williams et al, 2015). A prerequisite to understand how precipitation changes transfer into river discharge changes is to analyze and evaluate the various components of the surface water budget and especially the key variable relationships between precipitation and soil moisture (SM), the result of the partition of precipitation among evapotranspiration, infiltration, and runoff

Results

Discussion

Conclusion