Antecedent Precipitation Index to Estimate Soil Moisture and Correlate as a Triggering Process in the Occurrence of Landslides

Landslides are highly dangerous phenomena that occur in different parts of the world and pose significant threats to human populations. Intense rainfall events are the main triggering process for landslides in urbanized slope regions, especially those considered high-risk areas. Various other factors contribute to the process;thus, it is essential to analyze the causes of such incidents in all possible ways. Soil moisture plays a critical role in the Earth’s surface-atmosphere interaction systems;hence, measurements and their estimations are crucial for understanding all processes involved in the water balance, especially those related to landslides. Soil moisture can be estimated from in-situ measurements using different sensors and techniques, satellite remote sensing, hydrological modeling, and indicators to index moisture conditions. Antecedent soil moisture can significantly impact runoff for the same rainfall event in a watershed. The Antecedent Precipitation Index (API) or “retained rainfall,” along with the antecedent moisture condition from the Natural Resources Conservation Service, is generally applied to estimate runoff in watersheds where data is limited or unavailable. This work aims to explore API in estimating soil moisture and establish thresholds based on landslide occurrences. The estimated soil moisture will be compared and calibrated using measurements obtained through multisensor capacitance probes installed in a high-risk area located in the mountainous region of Campos do Jordão municipality, São Paulo, Brazil. The API used in the calculation has been modified, where the recession coefficient depends on air temperature variability as well as the climatological mean temperature, which can be considered as losses in the water balance due to evapotranspiration. Once the API is calibrated, it will be used to extrapolate to the entire watershed and consequently estimate soil moisture. By utilizing recorded mass movements and comparing them with API and soil moisture, it will be possible to determine thresholds, thus enabling anticipation of landslide occurrences.

Enhancing Deep Learning Soil Moisture Forecasting Models by Integrating Physics-based Models

Accurate soil moisture(SM)prediction is critical for understanding hydrological processes.Physics-based(PB)models exhibit large uncertainties in SM predictions arising from uncertain parameterizations and insufficient representation of land-surface processes.In addition to PB models,deep learning(DL)models have been widely used in SM predictions recently.However,few pure DL models have notably high success rates due to lacking physical information.Thus,we developed hybrid models to effectively integrate the outputs of PB models into DL models to improve SM predictions.To this end,we first developed a hybrid model based on the attention mechanism to take advantage of PB models at each forecast time scale(attention model).We further built an ensemble model that combined the advantages of different hybrid schemes(ensemble model).We utilized SM forecasts from the Global Forecast System to enhance the convolutional long short-term memory(ConvLSTM)model for 1–16 days of SM predictions.The performances of the proposed hybrid models were investigated and compared with two existing hybrid models.The results showed that the attention model could leverage benefits of PB models and achieved the best predictability of drought events among the different hybrid models.Moreover,the ensemble model performed best among all hybrid models at all forecast time scales and different soil conditions.It is highlighted that the ensemble model outperformed the pure DL model over 79.5%of in situ stations for 16-day predictions.These findings suggest that our proposed hybrid models can adequately exploit the benefits of PB model outputs to aid DL models in making SM predictions.

Time-lagged Effects of the Spring Atmospheric Heat Source over the Tibetan Plateau on Summer Precipitation in Northeast China during 1961–2020:Role of Soil Moisture

The spring atmospheric heat source(AHS)over the Tibetan Plateau(TP)has been suggested to affect the Asian summer monsoon and summer precipitation over South China.However,its influence on the summer precipitation in Northeast China(NEC)remains unknown.The connection between spring TP AHS and subsequent summer precipitation over NEC from 1961 to 2020 is analyzed in this study.Results illustrate that stronger spring TP AHS can enhance subsequent summer NEC precipitation,and higher soil moisture in the Yellow River Valley-North China region(YRVNC)acts as a bridge.During spring,the strong TP AHS could strengthen the transportation of water vapor to East China and lead to excessive rainfall in the YRVNC.Thus,soil moisture increases,which regulates local thermal conditions by decreasing local surface skin temperature and sensible heat.Owing to the memory of soil moisture,the lower spring sensible heat over the YRVNC can last until mid-summer,decrease the land–sea thermal contrast,and weaken the southerly winds over the East Asia–western Pacific region and convective activities over the South China Sea and tropical western Pacific.This modulates the East Asia–Pacific teleconnection pattern,which leads to a cyclonic anomaly and excessive summer precipitation over NEC.

Synergistic Impacts of Indian Ocean SST and Indo-China Peninsula Soil Moisture on the 2020 Record-breaking Mei-yu

The Yangtze River basin(YRB)experienced a record-breaking mei-yu season in June‒July 2020.This unique long-lasting extreme event and its origin have attracted considerable attention.Previous studies have suggested that the Indian Ocean(IO)SST forcing and soil moisture anomaly over the Indochina Peninsula(ICP)were responsible for this unexpected event.However,the relative contributions of IO SST and ICP soil moisture to the 2020 mei-yu rainfall event,especially their linkage with atmospheric circulation changes,remain unclear.By using observations and numerical simulations,this study examines the synergistic impacts of IO SST and ICP soil moisture on the extreme mei-yu in 2020.Results show that the prolonged dry soil moisture led to a warmer surface over the ICP in May under strong IO SST backgrounds.The intensification of the warm condition further magnified the land thermal effects,which in turn facilitated the westward extension of the western North Pacific subtropical high(WNPSH)in June‒July.The intensified WNPSH amplified the water vapor convergence and ascending motion over the YRB,thereby contributing to the 2020 mei-yu.In contrast,the land thermal anomalies diminish during normal IO SST backgrounds due to the limited persistence of soil moisture.The roles of IO SST and ICP soil moisture are verified and quantified using the Community Earth System Model.Their synergistic impacts yield a notable 32%increase in YRB precipitation.Our findings provide evidence for the combined influences of IO SST forcing and ICP soil moisture variability on the occurrence of the 2020 super mei-yu.

Characteristics of In-Situ Soil Water Hysteresis Observed through Multiple-Years Monitoring

A soil water retention curve (SWRC) is an essential soil physical property for analyzing transport and retention of water in a soil layer. A SWRC is often described as a single-valued function that relates the soil water potential ψ to volumetric water content θ of the soil. However, an in-situ ψ − θ relation should show soil water hysteresis, though this fact is often neglected in analyses of field soil water regimes while long-term in-situ soil water hysteresis is not well characterized. This study aimed at probing and characterizing in-situ ψ − θ relations. The developments of large hysteresis in the in-situ ψ − θ relations were observed only a few times during the study period of 82 months. Any of the large hysteretic behaviors in the ψ − θ relations began with an unusually strong continual reduction in ψ. The completion of a hysteresis loop required a recorded maximum rainfall. Because the study field had very small chances to meet such strong rainfall events, it took multiple years to restore the fraction of soil water depleted by the unusually strong continual reduction in ψ. While wetting-drying cycles had occurred within a certain domain of ψ, hysteretic behaviors tended to be so small that the in-situ ψ − θ relation can be approximated as a single-valued function of θ(ψ). These observed patterns of the in-situ ψ − θ relations were characterized by kinds of difference in dθ/dψ between a drying process and a wetting process at a given ψ. Thus, more amounts of experimental facts about wetting SWRCs in parallel with drying SWRCs should be needed for correct modelling, analyzing, and predicting soil water regimes in fields. It is also necessary to increase our understandings about the long-term trends of occurrences of extreme weather conditions associated with possible change in climate.

Enhanced soil moisture improves vegetation growth in an arid grassland of Inner Mongolia Autonomous Region, China

Climate change impacts on grasslands that cover a quarter of the global land area, have become unprecedented during the 21~(st) century. One of the important ecological realms, arid grasslands of northern China, which occupy more than 70% of the region's land area. However, the impact of climate change on vegetation growth in these arid grasslands is not consistent and lacks corresponding quantitative research. In this study, NDVI(normalized difference vegetation index) and climate factors including temperature, precipitation, solar radiation, soil moisture, and meteorological drought were analyzed to explore the determinants of changes in grassland greenness in Inner Mongolia Autonomous Region(northern China) during 1982–2016. The results showed that grasslands in Inner Mongolia witnessed an obvious trend of seasonal greening during the study period. Two prominent climatic factors,precipitation and soil moisture accounted for approximately 33% and 27% of grassland NDVI trends in the region based on multiple linear regression and boosted regression tree methods. This finding highlights the impact of water constraints to vegetation growth in Inner Mongolia's grasslands. The dominant role of precipitation in regulating grassland NDVI trends in Inner Mongolia significantly weakened from 1982 to 1996, and the role of soil moisture strengthened after 1996. Our findings emphasize the enhanced importance of soil moisture in driving vegetation growth in arid grasslands of Inner Mongolia, which should be thoroughly investigated in the future.

SENSITIVITY OF MESOSCALE CONVECTIVE SYSTEMS AND ASSOCIATED HEAVY RAINFALL TO SOIL MOISTURE OVER SOUTH CHINA

The impacts of soil moisture(SM) on heavy rainfall and the development of Mesoscale Convection Systems(MCSs) are investigated through 24-h numerical simulations of two heavy rainfall events that occurred respectively on28 March 2009(Case 1) and 6 May 2010(Case 2) over southern China. The numerical simulations were carried out with WRF and its coupled Noah LSM(Land Surface Model). First, comparative experiments were driven by two different SM data sources from NCEP-FNL and NASA-GLDAS. Secondary, with the run driven by NASA-GLDAS data as a control one, a series of sensitivity tests with different degree of(20%, 60%) increase or decrease in the initial SM were performed to examine the impact of SM on the simulations. Comparative experiment results show that the 24-h simulated cumulative rainfall distributions are not substantially affected by the application of the two different SM data,while the precipitation intensity is changed to some extent. Forecast skill scores show that simulation with NASA-GLDAS SM data can lead to some improvement, especially in the heavy rain(芏50 mm) forecast, where there is up to 5% increase in the TS score. Sensitivity test analysis found that a predominantly positive feedback of SM on precipitation existed in these two heavy rain events but not with completely the same features. Organization of the heavy rainfall-producing MCS seems to have an impact on the feedback process between SM and precipitation. For Case 1, the MCS was poorly organized and occurred locally in late afternoon, and the increase of SM only caused a slight enhancement of precipitation. Drier soil was found to result in an apparent decrease of rainfall intensity,indicating that precipitation is more sensitive to SM reduction. For Case 2, as the heavy rain was caused by a well-organized MCS with sustained precipitation, the rainfall is more sensitive to SM increase, which brings more rainfall. Additionally, distinctive feedback effects were identified from different stages and different organization of MCS, with strong feedback between SM and precipitation mainly appearing in the early stages of the poorly organized MCS and during the late period of the well-organized MCS.

Architectural Plasticity in Response to Soil Moisture in the Stoloniferous Herb, Duchesnea indica

Architectural plasticity of clonal plants may enhance exploitation of soil moisture heterogeneity by the plants. The plasticity of clonal architecture in response to soil moisture in the stoloniferous herb, Duchesnea indica Focke, was investigated in an experiment with different soil moisture contents as treatments, i.e. 40%, 60%, 80%, 100% of the maximum moisture content of soil (MMCS). As soil moisture content increased, the spacer length, ramet density, branching intensity and branching angle of D. indica plants changed by quadratic curve. And the optimum habitat for the plants was at 80% of the MMCS. This architectural plasticity in D. indica was simulated through the Dynamic Logistic Model. The imitative effect was statistically satisfactory. Its architectural plasticity observed here may allow the species to show foraging behavior in its habitat where soil moisture is patchily distributed.

Effects of Periodical Soil Drying and Leaf Water Potential on the Sensitivity of Stomatal Response to Xylem ABA

The study on the changes of stomatal sensitivity in relation to xylem ABA during periodical soil drying and the effect of leaf water status on the stomatal sensitivity has confirmed that xylem ABA concentration is a good indicator of soil water status around roots and the relation between xylem ABA concentration and predawn leaf water potential remained constant during the three consecutive soil drying cycles based on the slopes of the fitted lines. The sensitivity of stomata to xylem ABA increased substantially as the soil drying cycles progressed, and the xylem ABA concentration needed to cause a 50% decrease of stomatal conductance was as low as 550 nmol/L in the next two soil drying cycle, as compared with the 750 nmol/L ABA in the first cycle of soil drying. The results using the split_root system showed that leaf water deficit significantly enhanced the stomatal response to xylem ABA and the xylem ABA concentration needed to cause a 50% decrease in stomatal conductance was 2 to 4 times smaller in the whole_root_drying treatment than those in the semi_root_drying treatment. These results suggested that the sensitivity of stomata to xylem ABA concentration is not a fixed characteristic.

The Response of Transpiration Rate of Malus pumila cv.Goldspur to Illumination and Soil Moisture

We tested the transpiration rate ( Tr ) of seven\|year\|old field and two\|year\|old potted Malus pumila cv.Goldspur under different conditions of illumination and soil water. The results showed that the interrelationship between Tr of Malus pumila cv.Goldspur and illumination and soil water content ( SWC ) was quite remarkable. Tr increased with the increase of light intensity and SWC . However, when one of the environmental stresses of illumination and water existed, the improvement of the other condition couldn't make Tr rise greatly. Only when SWC was higher than 11%, which arrived at over 55% of the field content ( FC ), or the photosynthetic active radiation ( PAR ) higher than 400?μmol·s -1 m -2 , Tr could rise greatly with the increase of PAR or SWC . But when SWC was higher than 15%, which reached over 75% of FC or PAR higher than 1?000?μmol·s -1 ·m -2 , Tr would not change a lot with the change of PAR or SWC . That PAR and SWC influenced the magnitude of stomatic resistance( RS ) and leaf water potential ( Ψ l) was the basic reason for the Tr responded to them. Light stress reduced the open degree of stomas, so when severe light stress existed ( PAR <100?μmol·s -1 ·m -2 ), RS was larger ( RS >2 0?s·cm -1 ), which led to the decrease of Tr(Tr <5?μgH 2O·s -1 ·cm -2 ). When severe water stress existed( SWC <11% and<55% of FC and soil water potential Ψ ws <-1 15?MPa), RS was higher than 4 00?s·cm -1 and Ψ l lower than -2 10?MPa, which led to Tr lower than 11?μgH 2O·s -1 ·cm -2 . When soil water was adequate( SWC >15% amd over 75% of FC , and Ψ ws >-0 50?MPa), RS was lower than 2 00?s·cm -1 , Ψ l higher than -1 65?MPa and Tr would be higher than 15?μgH 2O·s -1 ·m -2 . The range of SWC , 11%～15%, which accounted for 55% to 75% of FC , and correspond RS (2 00～4 00?s·cm -1 ) were the turning area, where the variable curve of Tr transited from a variable trend to another variable one. It could be considered as the range to control soil water.

Real-time Monitoring Scheme of Soil Moisture Content in Paddy Field

The monitoring of soil moisture content in paddy field is one of important parts and contents of regional soil moisture monitoring. But a good monitoring scheme hasn’t been established. A real-time monitoring scheme of soil moisture content in paddy field was put forward from two key links of soil moisture content monitoring and field water-layer monitoring. This scheme could meet the alternative monitoring requirements of soil moisture content in water layer and none-water layer. It had a good maneuverability and could provide references for practical work.

Effects of planting patterns plastic film mulching on soil temperature,moisture, functional bacteria and yield of winter wheat in the Loess Plateau of China

The yield of winter wheat is hindered by drought and low temperature in the Loess Plateau of China.Two common mulching methods to conserve soil moisture,ridge furrows with plastic film mulching (RP) and flat soil surfaces with plastic film mulching (FP) are helpful for wheat production.Our previous study indicated that FP could improve wheat yield more effectively than RP,but the reason remains unclear.The effect of mulching method on functional bacteria also needs to be further studied.In this study,winter wheat was employed to evaluate the impacts of mulching method on soil temperature,moisture content,microorganisms and grain yield.The results showed that FP had a warming effect when the soil temperature was low and a cooling effect when the temperature was too high.However,the ability to regulate soil temperature in the RP method was unstable and varied with year.The lowest negative accumulated soil temperature was found in the FP treatment,which was 20–89 and 43–99%lower than that of the RP and flat sowing with non-film mulching control (NP) treatments,respectively.Deep soil moisture was better transferred to topsoil for wheat growth in the FP and RP treatments than the NP treatment,which made the topsoil moisture in the two treatments (especially FP) more sufficient than that in the NP treatment during the early growing stage of wheat.However,due to the limited water resources in the study area,there was almost no difference between treatments in topsoil water storage during the later stage.The wheat yield in the FP treatment was significantly higher,by 12–16and 23–56%,respectively,than in the RP and NP treatments.Significant positive correlations were observed among the negative accumulated soil temperature,spike number and wheat yield.The Chao1 and Shannon indices in the RP treatment were 17 and 3.9%higher than those in the NP treatment,respectively.However,according to network relationship analysis,the interspecific relationships of bacteria were weakened in the RP treatment.Phosphorus solubilizing,ammonification and nitrification bacteria were more active in the RP than in the FP treatment,and microbes with nitrate reduction ability and plant pathogens were inhibited in the RP treatment,which improved nutrient availability and habitat for wheat.

Enhanced Seasonal Predictability of Spring Soil Moisture over the Indo-China Peninsula for Eastern China Summer Precipitation under Non-ENSO Conditions

Seasonal prediction of summer precipitation over eastern China is closely linked to the East Asian monsoon circulation,which is largely affected by the El Niño-Southern Oscillation(ENSO).In this study,results show that spring soil moisture(SM)over the Indo-China peninsula(ICP)could be a reliable seasonal predictor for eastern China summer precipitation under non-ENSO conditions.When springtime SM anomalies are present over the ICP,they trigger a structured response in summertime precipitation over most of eastern China.The resultant south-to-north,tri-polar configuration of precipitation anomalies has a tendency to yield increased(decreased)precipitation in the Yangtze River basin and decreased(increased)in South and North China with a drier(wetter)spring soil condition in the ICP.The analyses show that ENSO exerts a powerful control on the East Asian circulation system in the ENSO-decaying summer.In the case of ENSO forcing,the seasonal predictability of the ICP spring SM for eastern China summer precipitation is suppressed.However,in the absence of the influence of ENSO sea surface temperature anomalies from the preceding winter,the SM anomalies over the ICP induce abnormal local heating and a consequent geopotential height response owing to its sustained control on local temperature,which could,in turn,lead to abnormal eastern China summer precipitation by affecting the East Asian summer monsoon circulation.The present findings provide a better understanding of the complexity of summer climate predictability over eastern China,which is of potential significance for improving the livelihood of the people.

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.

Modeling spatio-temporal distribution of soil moisture by deep learning-based cellular automata model

Soil moisture content （SMC） is a key hydrological parameter in agriculture,meteorology and climate change,and understanding of spatio-temporal distributions of SMC in farmlands is important to address the precise irrigation scheduling.However,the hybrid interaction of static and dynamic environmental parameters makes it particularly difficult to accurately and reliably model the distribution of SMC.At present,deep learning wins numerous contests in machine learning and hence deep belief network （DBN） ,a breakthrough in deep learning is trained to extract the transition functions for the simulation of the cell state changes.In this study,we used a novel macroscopic cellular automata （MCA） model by combining DBN to predict the SMC over an irrigated corn field （an area of 22 km^2） in the Zhangye oasis,Northwest China.Static and dynamic environmental variables were prepared with regard to the complex hydrological processes.The widely used neural network,multi-layer perceptron （MLP） ,was utilized for comparison to DBN.The hybrid models （MLP-MCA and DBN-MCA） were calibrated and validated on SMC data within four months,i.e.June to September 2012,which were automatically observed by a wireless sensor network （WSN） .Compared with MLP-MCA,the DBN-MCA model led to a decrease in root mean squared error （RMSE） by 18%.Thus,the differences of prediction errors increased due to the propagating errors of variables,difficulties of knowing soil properties and recording irrigation amount in practice.The sequential Gaussian simulation （s Gs） was performed to assess the uncertainty of soil moisture estimations.Calculated with a threshold of SMC for each grid cell,the local uncertainty of simulated results in the post processing suggested that the probability of SMC less than 25% will be difference in different areas at different time periods.The current results showed that the DBN-MCA model performs better than the MLP-MCA model,and the DBN-MCA model provides a powerful tool for predicting SMC in highly non-linear forms.Moreover,because modeling soil moisture by using environmental variables is gaining increasing popularity,DBN techniques could contribute a lot to enhancing the calibration of MCA-based SMC estimations and hence provide an alternative approach for SMC monitoring in irrigation systems on the basis of canals.

Soil Moisture Retrieval from Satellite Images and Its Application to Heavy Rainfall Simulation in Eastern China

The soil water index （SWI） from satellite remote sensing and the observational soil moisture from agricultural meteorological stations in eastern China are used to retrieve soil moisture. The analysis of correlation coefficient （CORR）, root-mean-square-error （RMSE） and bias （BIAS） shows that the retrieved soil moisture is convincible and close to the observation. The method can overcome the difficulties in soil moisture observation on a large scale and the retrieved soil moisture may reflect the distribution of the real soil moisture objectively. The retrieved soil moisture is used as an initial scheme to replace initial conditions of soil moisture （NCEP） in the model MM5V3 to simulate the heavy rainfall in 1998. Three heavy rainfall processes during 13-14 June, 18-22 June, and 21-26 July 1998 in the Yangtze River valley are analyzed. The first two processes show that the intensity and location of simulated precipitation from SWI are better than those from NCEP and closer to the observed values. The simulated heavy rainfall for 21-26 July shows that the update of soil moisture initial conditions can improve the model＇s performance. The relationship between soil moisture and rainfall may explain that the stronger rainfall intensity for SWI in the Yangtze River valley is the result of the greater simulated soil moisture from SWI prior to the heavy rainfall date than that from NCEP, and leads to the decline of temperature in the corresponding area in the heavy rainfall days. Detailed analysis of the heavy rainfall on 13-14 June shows that both land-atmosphere interactions and atmospheric circulation were responsible for the heavy ralnfall, and it shows how the SWI simulation improves the simulation. The development of mesoscale systems plays an important role in the simulation regarding the change of initial soil moisture for SWI.

Use of a Land Surface Model to Evaluate the Observed Soil Moisture of Grassland at the Tongyu Reference Site

A land surface model driven by the continuous three-year observed meteorological data with a time interval of 30 minutes at the Tongyu station, a reference site of the Coordinated Enhanced Observing Period （CEOP）, was used to evaluate the observation bias of soil moisture （SM） data and analyze the variation of SM at different time scales. The saline-alkaline soil of the grassland at the Tongyu site makes the measured SM too high, especially in boreal summer of 2003-05. The simulated annual mean SM has the lowest value in 2004 and its three-year variation corresponds to the change of precipitation, whereas the observation shows the increasing trend from 2003 to 2005. Compared to the variation range between -60% and 40% for the anomaly percentage of the simulated daily mean SM during May-October of 2004, the measured data show the higher values more than 40%. The magnitude of the variation trend of the observed daily mean SM in 2003 and 2005 is generally consistent with the simulation. The largest deficiency for the soil moisture observation of the grassland is the overestimated value in the drought year with less precipitation. The simulated monthly mean SM has the lowest value in March due to the large contribution of evaporation relative to precipitation and this phenomenon can not be reproduced in the observation.

Reduced Soil Moisture Contributes to More Intense and More Frequent Heat Waves in Northern China

Heat waves have attracted increasing attention in recent years due to their frequent occurrence.The present study investigates the heat wave intensity and duration in China using daily maximum temperature from 753 weather stations from 1960 to 2010.In addition,its relationships with soil moisture local forcing on the ten-day period and monthly scales in spring and summer are analyzed using soil moisture data from weather stations and ERA40 reanalysis data.And finally,a mechanistic analysis is carried out using CAM5.1（Community Atmosphere Model,version 5.1） coupled with CLM2（Community Land Model,version 2）.It is found that the heat wave frequency and duration show a sandwich distribution across China,with high occurrence rates in Southeast China and Northwest China,where the maximum frequency and duration exceeded 2.1 times and 9 days per year,respectively.The increasing trends in both duration and intensity occurred to the north of 35°N.The relationships between heat wave frequency in northern China in July（having peak distribution） and soil moisture in the earlier stage（from March to June） and corresponding period（July） are further analyzed,revealing a strong negative correlation in March,June and July,and thus showing that soil moisture in spring and early summer could be an important contributor to heat waves in July via positive subtropical high anomalies.However,the time scales of influence were relatively short in the semi-humid and humid regions,and longer in the arid region.The contribution in the corresponding period took place via positive subtropical high anomalies and positive surface skin temperature and sensible heat flux anomalies.

Comparisons of Soil Moisture Datasets over the Tibetan Plateau and Application to the Simulation of Asia Summer Monsoon Onset

The influence of soil moisture on Asian monsoon simulation/prediction was less studied, partly due to a lack of available and reliable soil moisture datasets. In this study, we firstly compare several soil moisture datasets over the Tibetan Plateau, and find that the remote sensing products from the Advanced Microwave Scanning Radiometer for Earth Observing System （AMSR-E） can capture realistic temporal variations of soil moisture better than the two reanalyses （NCEP and ECMWF） during the pre-monsoon seasons. Using the AMSR-E soil moisture product, we investigate the impacts of soil moisture over the Tibetan Plateau on Asian summer monsoon onset based on a Spectral Atmospheric Model developed at IAP/LASG （SAMIL）. Comparison between results with and without the assimilation of remotely sensed soil moisture data demonstrates that with soil moisture assimilated into SAMIL, the land-sea thermal contrast during pre-monsoon seasons is more realistic. Accordingly, the simulation of summer monsoon onset dates over both the Bay of Bengal and South China Sea regions are more accurate with AMSR-E soil moisture assimilated. This study reveals that the application of the soil moisture remote sensing products in a numerical model could potentially improve prediction of the Asian summer monsoon onset.

Evapotranspiration and Soil Moisture Balance for Vegetative Restoration in a Gully Catchment on the Loess Plateau, China

Evapotranspiration, soil moisture balance and the dynamics in a gully catchment of the Loess Plateau in China were determined with 6 land use treatments including natural grassland, shrubs （Caragana rnicrophylla）, two woodlands （Prunus armeniaca var. ansu and Pinus tabulaeformis）, cultivated fallow, and farmland （Triticum aestiuum L.） in order to obtain a better understanding of soil moisture balance principles and to improve vegetation restoration efficiency for ecological rebuilding on the plateau. Average runoff from cultivated fallow was very high, reaching 10.3% of the seasonal rainfall. Evapotranspiration under T. aestivurn was not significantly different from natural grasslands. Compared with natural grass, evapotranspiration was significantly greater （P 〈 0.05） in 2002 and there was an increase in soil moisture depleted in the 1-3 m soil under P. armeniaca, P. tabulaeformis and C. microphylla. During the two years of the study the average soil moisture （0-100 cm soil profile） of T. aestivurn was generally the highest, with P. armeniaca, P. tabulaeformis and C. rnicrophylla usually the lowest. Thus, according to the soil moisture balance principle for this area the planned reforestation project was not ecologically reasonable. Reducing human disturbance and restoration with grass could be more effective.