Comparison Of Environmental Controls On The Spatiotemporal Variability Of Soil Moisture: Observational Evidence From Field And Regional Scales

As a key state variable in terrestrial water cycles,soil moisture(SM)plays a vital role in modulating a multitude of land surface and hydrological processes.For various research and application purposes,it is often of great value to understand the characteristics of SM patterns over different spatiotemporal scales.The characteristics of SM patterns could reflect an integrated effect of a variety of environmental factors on SM dynamics.Knowing the SM spatiotemporal variability can provide scientific support for irrigation scheduling and modern agricultural management,and also helps to improve the water use efficiency of farmland at field scales.Furthermore,the SM exerts significant impacts on atmosphere-land surface interactions through complex feedback mechanisms,understanding SM spatiotemporal patterns and particularly their influencing factors can provide valuable information for improving forecast skills of weather and climate models at regional scales.In this study,the spatiotemporal patterns of SM and soil matric potential(SMP)were jointly investigated by field monitoring and laboratory experiments at field scales,which was essential to improve soil water management and guide irrigation applications.The spatiotemporal patterns of SM and their influencing factors were analyzed under different climatic conditions,the intricate interactions between SM and precipitation(P)were also evaluated at regional scales.Accordingly,the results could provide theoretical support for the development of soil,hydrology,meteorology and other disciplines.The main conclusions were drawn as follows:(1)1-yr SM and SMP data at 30 and 60 cm depths across bare land and crop land were investigated at field scales in the North China Plain.The results clearly revealed that the relationship between the spatial mean and spatial variance of SM and SMP showed an upward convex shape,and the SM and SMP under bare land displayed greater spatial variability.Furthermore,the SMP had higher temporal stability at 30 cm,while the SM exhibited larger temporal stable at 60 cm.In general,the temporal stability of SM and SMP spatial patterns was generally higher in crop land than in bare land at all depths.The results showed obviously that the land use types influenced the spatiotemporal variability of SM and SMP patterns,while soil textures only influenced the spatiotemporal variability of SM.The results of this study had implications for improving water use efficiency and optimizing the point-based observations at field scales.(2)To elucidate the meteorological and local factors which controlled SM spatial variability at regional scales.The long-term SM data from East and Northwest China were examined in this study,using two statistical methods of temporal stability analysis and empirical orthogonal function(EOF)analysis.The temporal stability analysis results showed that the spatial distributions of mean relative difference(MRD)of SM had statistically significant correlations with mean annual precipitation(?)and soil texture in both study regions;however,the spatial correlation between MRD and ?was much stronger in the Northwest region,suggesting that P played a more important role in determining the spatial distribution of SM in Northwest China.Moreover,the EOF analysis revealed that the primary SM spatial structure was mostly related with soil texture in the East region while with ? in the Northwest region,which was also consistent with the temporal stability analysis results.The observational evidence from this study demonstrated that the relative importance of meteorological and local factors in controlling mesoscale SM spatial variability might vary considerably across regions,primarily depending on the spatial variability in those influencing factors across the region under consideration.(3)Long-term SM data were obtained from three regional monitoring networks across the continental United States with contrasting climatic conditions,including the Enviro-weather Automated Weather Station Network(EAWSN)in Michigan,the Nebraska Mesonet(NM),and the Soil Climate Analysis Network(SCAN)in Utah.Both SM spatial variance and temporal variance were decomposed into time-invariant and time-variant components.To evaluate the impacts of different environmental factors on SM spatiotemporal variability and its contribution components,meteorological and local environmental factors were also compiled for the stations of each network.The results showed that the time-invariant component was the leading factor for controlling the SM spatial variance in all study regions with marked seasonal variations due to changes in SM wetness conditions.More importantly,the SM spatial variance and its contribution components were shown to be affected by both soil properties and climatic conditions with varying degrees of impacts among the study regions.Meanwhile,the results further revealed that depending on the region under consideration,meteorological and local environmental factors could play important roles in determining SM temporal dynamics and its contribution components at regional scales.Overall,this study provided additional observational evidence,which underscored the importance of local factors in determining SM spatiotemporal variability at regional scales.(4)Knowledge of the interplays between SM and P across different temporal scales is crucial to understand the land-atmosphere interactions.To examine the factors influencing SM-P interactions,observed long-term SM and P datasets were obtained from two regional networks within the continental United States.We evaluated the intricate SM-P interactions by checking high-and low-frequency components using wavelet analysis.The analysis revealed that the global coherence coefficients(GCCs)between SM and P at all frequencies tended to be greater under wetter climatic conditions,suggesting that higher P could promote the SM-P coherences.Moreover,GCCs were more correlated with meteorological factors in Nebraska with wetter climates;whereas,strong correlations emerged between GCCs and soil texture at all frequency periodicities in Utah.Part of the reason for the impact of soil texture in Utah was that as the P periodicities weakened with increasing climatic dryness in Utah,soil texture played a more important role in controlling infiltration processes,which directly affected SM-P interactions.Overall,this study demonstrates that SM-P coherences at regional scales were determined by the relative importance of meteorological and local land surface conditions in controlling SM dynamics.The above conclusions indicate that soil texture is playing an increasingly important role in determining SM spatiotemporal variability at field and regional scales.At field scales,the land use types influence the spatiotemporal variability in SM and SMP patterns,while soil texture just influences the spatiotemporal variability of SM.At regional scales,the relative importance of P and soil texture in controlling SM spatiotemporal patterns might vary across climatic regions,primarily depending on the spatial variability in those influencing factors across the region under consideration.The conclusions that the SM-P coherences were influenced by soil texture at regional scales open a window into the broader field of soil research,and explore new ideas and ways for further investigation of SM.