A Modified Temperature-Vegetation Dryness Index(MTVDI)for Assessment of Surface Soil Moisture Based on MODIS Data

Spatio-temporal dynamic monitoring of soil moisture is highly important to management of agricultural and vegetation eco-systems.The temperature-vegetation dryness index based on the triangle or trapezoid method has been used widely in previous studies.However,most existing studies simply used linear regression to construct empirical models to fit the edges of the feature space.This requires extensive data from a vast study area,and may lead to subjective results.In this study,a Modified Temperature-Vegetation Dryness Index(MTVDI)was used to monitor surface soil moisture status using MODIS(Moderate-resolution Imaging Spectroradiometer)remote sensing data,in which the dry edge conditions were determined at the pixel scale based on surface energy balance.The MTVDI was validated by field measurements at 30 sites for 10 d and compared with the Temperature-Vegetation Dryness Index(TVDI).The results showed that the R^(2) for MTVDI and soil moisture obviously improved(0.45 for TVDI,0.69 for MTVDI).As for spatial changes,MTVDI can also better reflect the actual soil moisture condition than TVDI.As a result,MTVDI can be considered an effective method to monitor the spatio-temporal changes in surface soil moisture on a regional scale.

Influence of Vegetation Coverage on Surface Runoff and Soil Moisture in Rainy Season in Dry-hot Valley

[Objective]The research aimed to study the effects of vegetation coverage on the changes of soil moisture in rainy season in dry-hot valley.[Method]The surface runoff and soil moisture of slope with vegetation coverage and bare land in rainy reason in Jinsha River at Yuanmou County of Yunnan Province were observed continuously.Moreover,the statistical analysis was made based on the observation data.[Result]The vegetation coverage could decrease surface runoff and the surface runoff on bare land（CK） was 22 times as the plot with vegetation coverage.The soil water content in 0-180 cm layer with vegetation coverage increased by 37.8% than bare land.The stability of soil moisture content in deep layer was enhanced and the physical properties stability of soil was maintained.The soil moisture content in different depth of soil had significant difference and the changes of soil moisture content were obviously different.[Conclusion]The vegetation coverage of slope could change the soil hydrology obviously and keep soil moisture at the higher level,especially at soil layer below 20 cm.

Variability of Soil Moisture and Its Relationship with Surface Albedo and Soil Thermal Parameters over the Loess Plateau

Data from July 2006 to June 2008 observed at SACOL （Semi-Arid Climate and Environment Observatory of Lanzhou University, 35.946°N, 104.137°E, elev. 1961 m）, a semi-arid site in Northwest China, are used to study seasonal variability of soil moisture, along with surface albedo and other soil thermal parameters, such as heat capacity, thermal conductivity and thermal diffusivity, and their relationships to soil moisture content. The results indicate that surface albedo decreases with increases in soil moisture content, showing a typical exponential relation between the surface albedo and the soil moisture. The heat capacity, the soil thermal diffusivity, and soil thermal conductivity show large variations between Julian day 90-212 and 450-578. The soil thermal conductivity is found to increase as a power function of soil moisture. Soil heat capacity and soil thermal diffusivity increase with increases in soil moisture. The SACOL observed soil moisture are also used to validate the AMSR-E/AQUA retrieved soil moisture and there is good agreement between them. The analysis of the relationship between satellite retrieved soil moisture and precipitation suggests that the variability of soil moisture depends on the variation of precipitation over the Loess Plateau.

Relationships Between Surface Albedo,Soil Thermal Parameters and Soil Moisture in the Semi-arid Area of Tongyu,Northeastern China

Continuous observation data collected over the whole year of 2004 on a cropland surtace m Tongyu, a senti-arid area of northeastern China （44°25＇N, 122°52＇E）, have been used to investigate the variations of surface albedo and soil thermal parameters, including heat capacity, thermal conductivity and thermal diffusivity, and their relationships to soil moisture. The diurnal variation of surface albedo appears as a U shape curve on sunny days. Surface albedo decreases with the increase of solar elevation angle, and it tends to be a constant when solar elevation angle is larger than 40°. So the daily average surface albedo was computed using the data when solar elevation angle is larger than 40° Mean daily surface albedo is found to decrease with the increase of soil moisture, showing an exponential dependence on soil moisture. The variations of soil heat capacity are small during Julian days 90 300. Compared with the heat capacity, soil thermal conductivity has very gentle variations during this period, but the soil thermal diffusivity has wide variations during the same period. The soil thermal conductivity is found to increase as a power function of soil moisture. The soil thermal diffusivity increases firstly and then decreases with the increase of soil moisture.

Using multi-satellite microwave remote sensing observations for retrieval of daily surface soil moisture across China

The objective of this study was to retrieve daily composite soil moisture by jointly using brightness temperature observations from multiple operating satellites for near real-time application with better coverage and higher accuracy.Our approach was to first apply the single-channel brightness radiometric algorithm to estimate soil moisture from the respective brightness temperature observations of the SMAP,SMOS,AMSR2,FY3B,and FY3C satellites on the same day and then produce a daily composite dataset by averaging the individual satellite-retrieved soil moisture.We further evaluated our product,the official soil moisture products of the five satellites,and the ensemble mean (i.e.,arithmetic mean) of the five official satellite soil moisture products against ground observations from two networks in Central Tibet and Anhui Province,China.The results show that our product outperforms the individual released products of the five satellites and their ensemble means in the two validation areas.The root mean square error (RMSE ) values of our product were 0.06 and 0.09 m3/m3 in Central Tibet and Anhui Province,respectively.Relative to the ensemble mean of the five satellite products,our product improves the accuracy by 9.1% and 57.7% in Central Tibet and Anhui Province,respectively.This demonstrates that jointly using brightness temperature observations from multiple satellites to retrieve soil moisture not only improves the spatial coverage of daily observations but also produces better daily composite products.

An analysis on the error structure and mechanism of soil moisture and ocean salinity remotely sensed sea surface salinity products

For the application of soil moisture and ocean salinity（SMOS） remotely sensed sea surface salinity（SSS） products,SMOS SSS global maps and error characteristics have been investigated based on quality control information.The results show that the errors of SMOS SSS products are distributed zonally,i.e.,relatively small in the tropical oceans,but much greater in the southern oceans in the Southern Hemisphere（negative bias） and along the southern,northern and some other oceanic margins（positive or negative bias）.The physical elements responsible for these errors include wind,temperature,and coastal terrain and so on.Errors in the southern oceans are due to the bias in an SSS retrieval algorithm caused by the coexisting high wind speed and low temperature; errors along the oceanic margins are due to the bias in a brightness temperature（TB） reconstruction caused by the high contrast between L-band emissivities from ice or land and from ocean; in addition,some other systematic errors are due to the bias in TB observation caused by a radio frequency interference and a radiometer receivers drift,etc.The findings will contribute to the scientific correction and appropriate application of the SMOS SSS products.

Vertical distribution of soil moisture and surface sandy soil wind erosion for different types of sand dune on the southeastern margin of the Mu Us Sandy Land,China

Soil moisture is a critical state affecting a variety of land surface and subsurface processes. We report investigation results of the factors controlling vertical variation of soil moisture and sand transport rate of three types of dunes on the south- eastern margin of the Mu Us Sandy Land. Samples were taken from holes drilled to a depth of 4 m at different topographic sites on the dunes, and were analyzed for soil moisture, grain-size distribution and surface sediment discharge. The results show that： （1） The average soil moisture varies in different types of dunes, with the following sequences ordered from highest to lowest： in the shrubs-covered dunes and the trees-covered dunes the sequence is from inter-dunes lowland to windward slope to leeward slope. The average moisture in the bare-migratory sand dunes is sequenced from inter-dunes lowland to leeward slope to windward slope. （2） Vegetation form and surface coverage affect the range of soil moisture of different types of dunes in the same topographic position. The coefficient of variation of soil moisture for shrubs-covered dunes is higher than that of other types of dune. （3） The effect of shrubs on dune soil moisture is explained in terms of the greater ability of shrubs to trap fine-grained atmospheric dust and hold moisture. （4） The estimated sand transport rates over sand dunes with sparse shrubs are less than those over bare-migratory dunes or sand dunes with sparse trees, indicating that shrubs are more effective in inhibiting wind erosion in the sandy land area.

Validation and application of soil moisture active passive sea surface salinity observation over the Changjiang River Estuary

Using sea surface salinity(SSS)observation from the soil moisture active passive(SMAP)mission,we analyzed the spatial distribution and seasonal variation of SSS around Changjiang River(Yangtze River)Estuary for the period of September 2015 to August 2018.First,we found that the SSS from SMAP is more accurate than soil moisture and ocean salinity(SMOS)mission observation when comparing with the in situ observations.Then,the SSS signature of the Changjiang River freshwater was analyzed using SMAP data and the river discharge data from the Datong hydrological station.The results show that the SSS around the Changjiang River Estuary is significantly lower than that of the open ocean,and shows significant seasonal variation.The minimum value of SSS appears in July and maximum SSS in December.The root mean square difference of daily SSS between SMAP observation and in situ observation is around 3 in both summer and winter,which is much lower than the annual range of SSS variation.In summer,the diffusion direction of the Changjiang River freshwater depicted by SSS from SMAP is consistent with the path of freshwater from in situ observation,suggesting that SMAP observation may be used in coastal seas in monitoring the diffusion and advection of freshwater discharge.

Utilizing a new soil effective temperature scheme and archived satellite microwave brightness temperature data to estimate surface soil moisture in the Nagqu region, Tibetan Plateau of China

Since the early 2000s, many satellite passive microwave brightness temperature （BT） archives, such as the Advanced Microwave Scanning Radiometer for the Earth Observing System （AMSR-E） BTs, have become the useful resources for assessing the changes in the surface and deep soil moistures over both arid and semi-arid regions. In this study, we used a new soil effective temperature （T scheme and the archived AMSR-E BTs to estimate surface soil moisture （SM） over the Nagqu region in the central Tibetan Plateau, China. The surface and deep soil temperatures required for the calculation of regional-scale T were obtained from outputs of the Community Land Model version 4.5 （CLM4.5）. In situ SM measurements at the CEOP-CAMP/Tibet （Coordinated Enhanced Observing Period Asia-Australia Monsoon Project on the Tibetan Plateau） experimental sites were used to validate the AMSR-E-based SM estimations at regional and single-site scales. Furthermore, the spatial distribution of monthly mean surface SM over the Nagqu region was obtained from 16 daytime AMSR-E BT observations in July 2004 over the Nagqu region. Results revealed that the AMSR-E-based surface SM estimations agreed well with the in situ-based surface SM measurements, with the root mean square error （RMSE） ranging from 0.042 to 0.066 m3/m3 and the coefficient of determination （R2） ranging from 0.71 to 0.92 during the nighttime and daytime. The regional surface soil water state map showed a clear spatial pattern related to the terrain. It indicated that the lower surface SM values occurred in the mountainous areas of the northern, mid-western and southeastern parts of Nagqu region, while the higher surface SM values appeared in the low elevation areas such as the Tongtian River Basin, Namco Lake and bog meadows in the central part of Nagqu region. Our analysis also showed that the new T^scheme does not require special fitting parameters or additional assumptions, which simplifies the data requirements for regional-scale applications. This scheme combined with the archived satellite passive microwave BT observations can be used to estimate the historical surface SM for hydrological process studies over the Tibetan Plateau regions.

Land surface temperature andcharacteristics for a raingarden insoil moisture distributionFitzroy Gardens, Melbourne

To better understand the cooling effect of raingarden in Fitzroy Gardens, Melbourne, as well as it benefits for an urban microclimate, two rounds of 36-h microclimate monitoring at the raingarden were conducted.Land surface temperature and soil moisture were analyzed according to monitoring data. The results showa clea raingarden cooling effect in summer. The largest difference o land surface temperatures inside and outside the raingarden can reach 23. 6 ℃, and the diurnal variation in temperature insid the raingarden was much less than that outside the raingarden.The soil moisture increased rapidly after irrigation, with th increase in the volumetric water content( VWC) of 2% to3. 6%. The soil moistures of adjacent irrigated garden bed and grass were higher than those inside the raingarden.Monitoring soil moisture helps guide raingarden irrigation.

Numerical Study of Initial Soil Moisture Impacts on Regional Surface Climate

In this paper, the impacts of initial soil moisture (SM) over the Huaihe River Basin of China on the summertime climate have been investigated with a regional climate model. Three fourth-month-long simulations are made for two summers, the abnormal flooding in 2003 and normal climate in 2004. Besides control simulations (noted as CTL), sensitivity experiments have been conducted by assigning the initial soil moisture equals to 50% and 150% of the simulated soil moisture while keeping the others unchanged, which are noted as SM50 and SM150, respectively.The results show that effects of initial SM anomalies at late spring can last for the whole summer, and the increase of initial soil moisture (SM150) has more significant effects than the decreased one (SM50). The differences between sensitivity experiments and CTL mainly appear at surface and near-surface atmosphere. When increasing the initial SM, the latent heat flux and surface soil moisture are increased, correspondingly the sensible heat flux, temperature and radiation are all decreased. The changes of rainfall are not distinct between SM50 and SM150, which might be related to the processes within atmosphere, especially the humidity pattern.

Predicting Surface Roughness and Moisture of Bare Soils Using Multi- band Spectral Reflectance Under Field Conditions

Soil surface roughness, denoted by the root mean square height(RMSH), and soil moisture(SM) are critical factors that affect the accuracy of quantitative remote sensing research due to their combined influence on spectral reflectance(SR). In regards to this issue, three SM levels and four RMSH levels were artificially designed in this study; a total of 12 plots was used, each plot had a size of 3 m × 3 m. Eight spectral observations were conducted from 14 to 30 October 2017 to investigate the correlation between RMSH, SM, and SR. On this basis, 6 commonly used bands of optical satellite sensors were selected in this study, which are red(675 nm), green(555 nm), blue(485 nm), near infrared(845 nm), shortwave infrared 1(1600 nm), and shortwave infrared 2(2200 nm). A negative correlation was found between SR and RMSH, and between SR and SM. The bands with higher coefficient of determination R^2 values were selected for stepwise multiple nonlinear regression analysis. Four characterized bands(i.e., blue, green, near infrared, and shortwave infrared 2) were chosen as the independent variables to estimate SM with R^2 and root mean square error(RMSE) values equal to 0.62 and 2.6%, respectively. Similarly, the four bands(green, red, near infrared, and shortwave infrared 1) were used to estimate RMSH with R^2 and RMSE values equal to 0.48 and 0.69 cm, respectively. These results indicate that the method used is not only suitable for estimating SM but can also be extended to the prediction of RMSH. Finally, the evaluation approach presented in this paper highly restores the real situation of the natural farmland surface on the one hand, and obtains high precision values of SM and RMSH on the other. The method can be further applied to the prediction of farmland SM and RMSH based on satellite and unmanned aerial vehicle(UAV) optical imagery.

A Multimodel Ensemble-based Kalman Filter for the Retrieval of Soil Moisture Profiles

With the combination of three land surface models （LSMs） and the ensemble Kalman filter （EnKF）, a multimodel EnKF is proposed in which the multimodel background superensemble error covariance matrix is estimated by two different algorithms： the Simple Model Average （SMA） and the Weighted Average Method （WAM）. The two algorithms are tested and compared in terms of their abilities to retrieve the true soil moisture profile by respectively assimilating both synthetically-generated and actual near-surface soil moisture measurements. The results from the synthetic experiment show that the performances of the SMA and WAM algorithms were quite different. The SMA algorithm did not help to improve the estimates of soil moisture at the deep layers, although its performance was not the worst when compared with the results from the single-model EnKF. On the contrary, the results from the WAM algorithm were better than those from any single-model EnKF. The tested results from assimilating the field measurements show that the performance of the two multimodel EnKF algorithms was very stable compared with the single-model EnKF. Although comparisons could only be made at three shallow layers, on average, the performance of the WAM algorithm was still slightly better than that of the SMA algorithm. As a result, the WAM algorithm should be adopted to approximate the multimodel background superensemble error covariance and hence used to estimate soil moisture states at the relatively deep layers.

Evaluating the Capabilities of Soil Enthalpy, Soil Moisture and Soil Temperature in Predicting Seasonal Precipitation

Soil enthalpy （H） contains the combined effects of both soil moisture （w） and soil temperature （T） in the land surface hydrothermal process. In this study, the sensitivities of H to w and T are investigated using the multi-linear regression method. Results indicate that T generally makes positive contributions to H, while w exhibits different （positive or negative） impacts due to soil ice effects. For example, w negatively contributes to H if soil contains more ice; however, after soil ice melts, w exerts positive contributions. In particular, due to lower w interannual variabilities in the deep soil layer （i.e., the fifth layer）, H is more sensitive to T than to w. Moreover, to compare the potential capabilities of H, w and T in precipitation （P） prediction, the Huanghe-Huaihe Basin （HHB） and Southeast China （SEC）, with similar sensitivities of H to w and T, are selected. Analyses show that, despite similar spatial distributions of H-P and T-P correlation coefficients, the former values are always higher than the latter ones. Furthermore, H provides the most effective signals for P prediction over HHB and SEC, i.e., a significant leading correlation between May H and early summer （June） P. In summary, H, which integrates the effects of T and w as an independent variable, has greater capabilities in monitoring land surface heating and improving seasonal P prediction relative to individual land surface factors （e.g., T and w）.

CLM3-simulated soil moisture in East Asia and its possible response to global warming during 1979 through 2003

Hydrological processes related to soil moisture play an important role in determining regional and global climate. In this study, using a state-of-art Community Land Model (CLM) developed by the National Center for Atmospheric Research (NCAR), we simulated soil moisture in East Asia and its possible response to global warming through a long off-line experiment under 0.5° (longitude) × 0.5° (latitude) resolution and real atmospheric forcing of the National Center for Environmental Protection/ Department of Energy (NCEP/DOE) reanalysis during 1979 through 2003. The 25-year simulation is examined and compared with limited observations. The results can be summarized as follows: (1) Soil moisture takes time in response to the atmospheric forcing. The equilibration time depends on the depth of the soil and is as much as 20 years in deep layers (>1.5 m); (2) In comparison with observations, the CLM reasonably reproduces the seasonal and inter-annual variability, spatial structure, and vertical pattern of soil moisture in East Asia; (3) The soil tends to be drier in the past 25 years in northeastern Asia—including northern China north of 30°N—while wetter in the southern China and the Tibetan Plateau, especially in summer. Our analysis shows that the regional drying is attributed to increase of the land-surface evaporation induced by global warming.

Subdaily to Seasonal Change of Surface Energy and Water Flux of the Haihe River Basin in China: Noah and Noah-MP Assessment

The land surface processes of the Noah-MP and Noah models are evaluated over four typical landscapes in the Haihe River Basin(HRB) using in-situ observations. The simulated soil temperature and moisture in the two land surface models(LSMs) is consistent with the observation, especially in the rainy season. The models reproduce the mean values and seasonality of the energy fluxes of the croplands, despite the obvious underestimated total evaporation. Noah shows the lower deep soil temperature. The net radiation is well simulated for the diurnal time scale. The daytime latent heat fluxes are always underestimated, while the sensible heat fluxes are overestimated to some degree. Compared with Noah, Noah-MP has improved daily average soil heat flux with diurnal variations. Generally, Noah-MP performs fairly well for different landscapes of the HRB. The simulated cold bias in soil temperature is possibly linked with the parameterized partition of the energy into surface fluxes. Thus, further improvement of these LSMs remains a major challenge.

Influence of Vegetation Cover on the Oh Soil Moisture Retrieval Model: A Case Study of the Malinda Wetland, Tanzania

Soil moisture is an important parameter that drives agriculture, climate and hydrological systems. In addition, retrieval of soil moisture is important in the analysis as well as its influence on these systems. Radar imagery is best suited for this retrieval due to its all-weather capability and independence from solar irradiation. Soil moisture retrieval was done for the Malinda Wetland, Tanzania, during two time periods, March and September 2013. The aim of this paper was to analyze soil moisture retrieval performance when vegetation contribution is taken into account. Backscatter values were obtained from TerraSAR-X Spotlight mode imagery taken in March and September 2013. The backscatter values recorded by SAR imagery are influenced by vegetation, soil roughness and soil moisture. Thus, in order to obtain the backscatter due to soil moisture, the roughness and vegetation contribution are determined and decoupled from total backscatter. The roughness parameters were obtained from a Digital Surface Model (DSM) from Unmanned Aerial Vehicle (UAV) photographs whereas the vegetation parameter was obtained by inverting the Water Cloud Model (WCM). Lastly, soil moisture was retrieved using the Oh Model. The coefficient of correlation between the observed and retrieved was 0.39 for the month of March and 0.65 in the month of August. When the vegetation contribution was considered, the r2 for March was 0.64 and that in August was 0.74. The results revealed that accounting for vegetation improved soil moisture retrieval.

A new climate scenario for assessing the climate change impacts on soil moisture over the Huang-Huai-Hai Plain region of China

To assess the impacts of temperature and precipitation changes on surface soil moisture CSSM） in the Huang-Huai-Hai Plain （3H） region of China, the approach of conditional nonlinear optimal perturbation related to parameters （CNOP-P） and the Common Land Model are employed. Based on the CNOP-P method and climate change projections derived from 22 global climate models from CMIP5 under a moderate emissions scenario （RCP4.5）, a new climate change scenario that leads to the maximal change magnitudes of SSM is acquired, referred to as the CNOP-P type temperature or precipitation change scenario. Different from the hypothesized climate change scenario, the CNOP-P-type scenario considers the variation of the temperature or precipitation variability. Under the CNOP-P-type temperature change, the SSM changes in the last year of the study period mainly fluctuate in the range from ,0.014 to ＋0.012 m^3 m^-3 （-5.0% to ＋10.0%）, and from ＋0.005 to ＋0.018 m^3 m^-3 （＋1.5% to ＋9.6%） under the CNOP-P-type precipitation change scenario. By analyzing the difference of the SSM changes between different types of climate change scenarios, it is found that this difference associated with SSM is obvious only when precipitation changes are considered. Besides, the greater difference mainly occurs in north of 35°N, where the semi-arid zone is mainly situated. It demonstrates that, in the semi-arid region, SSM is more sensitive to the precipitation variability. Compared with precipitation variability, temperature variability seems to play little role in the variations of SSM.

Applications of a Surface Runoff Model with Horton and Dunne Runoff for VIC

Surface runoff is mainly generated by two mechanisms, infiltration excess (Horton) runoff and saturation excess (Dunne) runoff; and the spatial variability of soil properties, antecedent soil moisture, topography, and rainfall will result in different surface runoff generation mechanisms. For a large area (e.g., a model grid size of a regional climate model or a general circulation model), these runoff generation mechanisms are commonly present at different portions of a grid cell simultaneously. Missing one of the two major runoff generation mechanisms and failing to consider spatial soil variability can result in significant under/over estimation of surface runoff which can directly introduce large errors in soil moisture states over each model grid cell. Therefore, proper modeling of surface runoff is essential to a reasonable representation of feedbacks in a land-atmosphere system. This paper presents a new surface runoff parameterization with the Philip infiltration formulation that dynamically represents both the Horton and Dunne runoff generation mechanisms within a model grid cell. The parameterization takes into account the effects of soil heterogeneity on Horton and Dunne runoff. The new parameterization is implemented into the current version of the hydrologically based Variable Infiltration Capacity (VIC) land surface model and tested over one watershed in Pennsylvania, USA and over the Shiguanhe Basin in the Huaihe Watershed in China. Results show that the new parameterization plays a very important role in partitioning the water budget between surface runoff and soil moisture in the atmosphere-land coupling system, and has potential applications on large hydrological simulations and land-atmospheric interactions. It is further found that the Horton runoff mechanism should be considered within the context of subgrid-scale spatial variability of soil properties and precipitation.

A Study on Parameterization of Surface Albedo over Grassland Surface in the Northern Tibetan Plateau

The relationship of surface albedo with the solar altitude angle and soil moisture is analyzed based on two-year （January 2002 to December 2003） observational data from the AWS （Automatic Weather Station） at MS3478 in the northern Tibetan Plateau during the experimental period of CEOP/CAMP-Tibet （Coordinated Enhanced Observing Period Asia-Australia Monsoon Project on the Tibetan Plateau）. As a double-variable （solar altitude angle and soil moisture） function, surface albedo varies inconspicuously with any single factor. By using the method of approximately separating the double-variable function into two, one-factor functions （product and addition）, the relationship of albedo with these two factors presents much better. The product and additional empirical formulae of albedo are then preliminarily fitted based on long-term experimental data. By comparison with observed values, it is found that the parameterization formulae fitted by using observational data are mostly reliable and their correlation coefficients are both over 0.6. The empirical formulae of albedo though, for the northern Tibetan Plateau, need to be tested by much more representative observational data with the help of numerical models and the retrieval of remote sensing data. It is practical until it is changed into effective parameterization formulae representing a grid scale in models.