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.

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.

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.

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.

A Cloud Framework for High Spatial Resolution Soil Moisture Mapping from Radar and Optical Satellite Imageries

Soil moisture plays an important role in crop yield estimation,irrigation management,etc.Remote sensing technology has potential for large-scale and high spatial soil moisture mapping.However,offline remote sensing data processing is time-consuming and resource-intensive,and significantly hampers the efficiency and timeliness of soil moisture mapping.Due to the high-speed computing capabilities of remote sensing cloud platforms,a High Spatial Resolution Soil Moisture Estimation Framework(HSRSMEF)based on the Google Earth Engine(GEE)platform was developed in this study.The functions of the HSRSMEF include research area and input datasets customization,radar speckle noise filtering,optical-radar image spatio-temporal matching,soil moisture retrieving,soil moisture visualization and exporting.This paper tested the performance of HSRSMEF by combining Sentinel-1,Sentinel-2 images and insitu soil moisture data in the central farmland area of Jilin Province,China.Reconstructed Normalized Difference Vegetation Index(NDVI)based on the Savitzky-Golay algorithm conforms to the crop growth cycle,and its correlation with the original NDVI is about 0.99(P<0.001).The soil moisture accuracy of the random forest model(R 2=0.942,RMSE=0.013 m3/m3)is better than that of the water cloud model(R 2=0.334,RMSE=0.091 m3/m3).HSRSMEF transfers time-consuming offline operations to cloud computing platforms,achieving rapid and simplified high spatial resolution soil moisture mapping.

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.

Enhancing Surface Soil Moisture Estimation through Integration of Artificial Neural Networks Machine Learning and Fusion of Meteorological, Sentinel-1A and Sentinel-2A Satellite Data

For many environmental and agricultural applications, an accurate estimation of surface soil moisture is essential. This study sought to determine whether combining Sentinel-1A, Sentinel-2A, and meteorological data with artificial neural networks (ANN) could improve soil moisture estimation in various land cover types. To train and evaluate the model’s performance, we used field data (provided by La Tuscia University) on the study area collected during time periods between October 2022, and December 2022. Surface soil moisture was measured at 29 locations. The performance of the model was trained, validated, and tested using input features in a 60:10:30 ratio, using the feed-forward ANN model. It was found that the ANN model exhibited high precision in predicting soil moisture. The model achieved a coefficient of determination (R2) of 0.71 and correlation coefficient (R) of 0.84. Furthermore, the incorporation of Random Forest (RF) algorithms for soil moisture prediction resulted in an improved R2 of 0.89. The unique combination of active microwave, meteorological data and multispectral data provides an opportunity to exploit the complementary nature of the datasets. Through preprocessing, fusion, and ANN modeling, this research contributes to advancing soil moisture estimation techniques and providing valuable insights for water resource management and agricultural planning in the study area.

The lateral pressure coefficient at rest of expansive soils in landfill at various vertical stresses and moisture contents

When expansive soils in the original location are artificially transferred to landfill in different seasons,and subject to engineering activities afterwards,the corresponding deformation and stability of retaining structures become unpredictable.This necessitates the determination of lateral pressure coefficient at rest(k_(0) value)for expansive soils in landfill.Considering compaction,excavation of expansive soils,as well as construction of landfill in different seasons,series of stepwise loading and unloading consolidation tests at various moisture contents were carried out in this work to explore the evolution characteristics of k_(0) value and assess the dependence of k_(0) value on vertical stress and moisture content.Besides,scanning electron microscope(SEM)was used to track the change in microstructural features with vertical stresses.The results indicated that the k_(0) value of expansive soil shows a pronounced nonlinearity and is inextricably linked with vertical stress and moisture content,based on which a prediction formula to estimate the variation in k_(0) value with vertical stress during loading stage was proposed;there is a significant exponential increase in k_(0) value with overconsolidation ratio(OCR)during unloading stage,and OCR dominates the release of horizontal stress of expansive soil;SEM results revealed that with an increase in vertical stress,the anisotropy of expansive soil microstructure increases dramatically,causing a significant directional readjustment,which is macroscopically manifested as an initially rapid increase in k_(0) value;but when vertical stress increases to a critical value,the anisotropy of microstructure increases marginally,indicating a stable orientation occurring in the soil microstructure,which causes the k_(0) value to maintain a relatively stable value.

Straw return increases crop production by improving soil organic carbon sequestration and soil aggregation in a long-term wheat-cotton cropping system

Straw return is a promising strategy for managing soil organic carbon(SOC)and improving yield stability.However,the optimal straw return strategy for sustainable crop production in the wheat(Triticum aestivum L.)-cotton(Gossypium hirsutum L.)cropping system remains uncertain.The objective of this study was to quantify the long-term(10 years)impact of carbon(C)input on SOC sequestration,soil aggregation and crop yields in a wheat-cotton cropping system in the Yangtze River Valley,China.Five treatments were arranged with a single-factor randomized design as follows:no straw return(Control),return of wheat straw only(Wt),return of cotton straw only(Ct),return of 50%wheat and 50%cotton straw(Wh-Ch)and return of 100%wheat and 100%cotton straw(Wt-Ct).In comparison to the Control,the SOC content increased by 8.4 to 20.2%under straw return.A significant linear positive correlation between SOC sequestration and C input(1.42-7.19 Mg ha^(−1)yr^(−1))(P<0.05)was detected.The percentages of aggregates of sizes>2 and 1-2 mm at the 0-20 cm soil depth were also significantly elevated under straw return,with the greatest increase of the aggregate stability in the Wt-Ct treatment(28.1%).The average wheat yields increased by 12.4-36.0%and cotton yields increased by 29.4-73.7%,and significantly linear positive correlations were also detected between C input and the yields of wheat and cotton.The average sustainable yield index(SYI)reached a maximum value of 0.69 when the C input was 7.08 Mg ha^(−1)yr^(−1),which was close to the maximum value(SYI of 0.69,C input of 7.19 Mg ha^(−1)yr^(-1))in the Wt-Ct treatment.Overall,the return of both wheat and cotton straw was the best strategy for improving SOC sequestration,soil aggregation,yields and their sustainability in the wheat-cotton rotation system.

An overview of soil moisture drought research in China:Progress and perspective

论文回顾了中国土壤湿度干旱(SMD)历史重建和季节预测研究进展,并对未来研究进行了展望,自1950s年代以来,全国整体干旱频率增加,持续时间延长,且有明显区域特征.SMD预测多是利用土壤湿度与气候变量之间的统计关系,而少量基于动力学方法的干旱预测研究强调了初始条件和大气强迫数据对季节尺度干旱预测的重要性,本论文提出:1)加强多时间尺度,跨区域的SMD研究;2)联合气候预测系统,陆面模式和多源土壤湿度数据研制SMD预测系统。

Manure substitution improves maize yield by promoting soil fertility and mediating the microbial community in lime concretion black soil

Synthetic nitrogen(N)fertilizer has made a great contribution to the improvement of soil fertility and productivity,but excessive application of synthetic N fertilizer may cause agroecosystem risks,such as soil acidification,groundwater contamination and biodiversity reduction.Meanwhile,organic substitution has received increasing attention for its ecologically and environmentally friendly and productivity benefits.However,the linkages between manure substitution,crop yield and the underlying microbial mechanisms remain uncertain.To bridge this gap,a three-year field experiment was conducted with five fertilization regimes:i)Control,non-fertilization;CF,conventional synthetic fertilizer application;CF_(1/2)M_(1/2),1/2 N input via synthetic fertilizer and 1/2 N input via manure;CF_(1/4)M_(3/4),1/4 N input synthetic fertilizer and 3/4 N input via manure;M,manure application.All fertilization treatments were designed to have equal N input.Our results showed that all manure substituted treatments achieved high soil fertility indexes(SFI)and productivities by increasing the soil organic carbon(SOC),total N(TN)and available phosphorus(AP)concentrations,and by altering the bacterial community diversity and composition compared with CF.SOC,AP,and the soil C:N ratio were mainly responsible for microbial community variations.The co-occurrence network revealed that SOC and AP had strong positive associations with Rhodospirillales and Burkholderiales,while TN and C:N ratio had positive and negative associations with Micromonosporaceae,respectively.These specific taxa are implicated in soil macroelement turnover.Random Forest analysis predicted that both biotic(bacterial composition and Micromonosporaceae)and abiotic(AP,SOC,SFI,and TN)factors had significant effects on crop yield.The present work strengthens our understanding of the effects of manure substitution on crop yield and provides theoretical support for optimizing fertilization strategies.

Semi-analytical solution for drained expansion analysis of a hollow cylinder of critical state soils

The expansion of a thick-walled hollow cylinder in soil is of non-self-similar nature that the stress/deformation paths are not the same for different soil material points.As a result,this problem cannot be solved by the common self-similar-based similarity techniques.This paper proposes a novel,exact solution for rigorous drained expansion analysis of a hollow cylinder of critical state soils.Considering stress-dependent elastic moduli of soils,new analytical stress and displacement solutions for the nonself-similar problem are developed taking the small strain assumption in the elastic zone.In the plastic zone,the cavity expansion response is formulated into a set of first-order partial differential equations(PDEs)with the combination use of Eulerian and Lagrangian descriptions,and a novel solution algorithm is developed to efficiently solve this complex boundary value problem.The solution is presented in a general form and thus can be useful for a wide range of soils.With the new solution,the non-self-similar nature induced by the finite outer boundary is clearly demonstrated and highlighted,which is found to be greatly different to the behaviour of cavity expansion in infinite soil mass.The present solution may serve as a benchmark for verifying the performance of advanced numerical techniques with critical state soil models and be used to capture the finite boundary effect for pressuremeter tests in small-sized calibration chambers.

Impact of mica on geotechnical behavior of weathered granitic soil using macro and micro investigations

The micaceous weathered granitic soil(WGS)is frequently encountered in civil engineering worldwide,unfortunately little information is available regarding how mica affects the physico-mechanical behaviors of WGS.This study prepares reconstituted WGS with different mica contents by removing natural mica in theWGS,and then mixes it with commercial mica powders.The geotechnical behavior as well as the microstructures of the mixtures are characterized.The addition of mica enables the physical indices of WGS to be specific combinations of coarser gradation and high permeability but high Atterberg limits.However,high mica content in WGS was found to be associated with undesirable mechanical properties,including increased compressibility,disintegration,and swelling potential,as well as poor compactability and low effective frictional angle.Microstructural analysis indicates that the influence of mica on the responses of mixtures originates from the intrinsic nature of mica as well as the particle packing being formed withinWGS.Mica exists in the mixture as stacks of plates that form a spongy structure with high compressibility and swelling potential.Pores among the plates give the soil high water retention and high Atterberg limits.Large pores are also generated by soil particles with bridging packing,which enhances the permeability and water-soil interactions upon immersion.This study provides a microlevel understanding of how mica dominates the behavior of WGS and provides new insights into the effective stabilization and improvement of micaceous soils.

Physical and mechanical properties and microstructures of submarine soils in the Yellow Sea

In recent years,the exploration of seabed has been intensified,but the submarine soils of silt and sand in the Yellow Sea area have not been well investigated so far.In this study,the physical and mechanical properties of silt and sand from the Yellow Sea were measured using a direct shear apparatus and their microstructures were observed using a scanning electron microscope.The test results suggest that the shear strength of silt and sand increases linearly with the increase of normal stress.Based on the direct shear test,the scanning electron microscope was used to observe the section surface of sand.It is observed that the section surface becomes rough,with many“V”‐shaped cracks.Many particles appear on the surface of the silt structure and tend to be disintegrated.The X‐ray diffraction experiment reveals that the sand and silt have different compositions.The shear strength of sand is slightly greater than that of silt under high stress,which is related to the shape of soil particles and the mineral composition.These results can be a reference for further study of other soils in the Yellow Sea;meanwhile,they can serve as soil parameters for the stability and durability analyses of offshore infrastructure construction.

Liquefaction susceptibility and deformation characteristics of saturated coral sandy soils subjected to cyclic loadings-a critical review

Coral sandy soils widely exist in coral island reefs and seashores in tropical and subtropical regions.Due to the unique marine depositional environment of coral sandy soils,the engineering characteristics and responses of these soils subjected to monotonic and cyclic loadings have been a subject of intense interest among the geotechnical and earthquake engineering communities.This paper critically reviews the progress of experimental investigations on the undrained behavior of coral sandy soils under monotonic and cyclic loadings over the last three decades.The focus of coverage includes the contractive-dilative behavior,the pattern of excess pore-water pressure(EPWP)generation and the liquefaction mechanism and liquefaction resistance,the small-strain shear modulus and strain-dependent shear modulus and damping,the cyclic softening feature,and the anisotropic characteristics of undrained responses of saturated coral sandy soils.In particular,the advances made in the past decades are reviewed from the following aspects:(1)the characterization of factors that impact the mechanism and patterns of EPWP build-up;(2)the identification of liquefaction triggering in terms of the apparent viscosity and the average flow coefficient;(3)the establishment of the invariable form of strain-based,stress-based,or energy-based EPWP ratio formulas and the unique relationship between the new proxy of liquefaction resistance and the number of cycles required to reach liquefaction;(4)the establishment of the invariable form of the predictive formulas of small strain modulus and strain-dependent shear modulus;and(5)the investigation on the effects of stress-induced anisotropy on liquefaction susceptibility and dynamic deformation characteristics.Insights gained through the critical review of these advances in the past decades offer a perspective for future research to further resolve the fundamental issues concerning the liquefaction mechanism and responses of coral sandy sites subjected to cyclic loadings associated with seismic events in marine environments.

Time-domain dynamic constitutive model suitable for mucky soil site seismic response

Soil nonlinear behavior displays noticeable effects on the site seismic response.This study proposes a new functional expression of the skeleton curve to replace the hyperbolic skeleton curve.By integrating shear modulus and combining the dynamic skeleton curve and the damping degradation coefficient,the constitutive equation of the logarithmic dynamic skeleton can be obtained,which considers the damping effect in a soil dynamics problem.Based on the finite difference method and the multi-transmitting boundary condition,a 1D site seismic response analysis program called Soilresp1D has been developed herein and used to analyze the time-domain seismic response in three types of sites.At the same time,this study also provides numerical simulation results based on the hyperbolic constitutive model and the equivalent linear method.The results verify the rationality of the new soil dynamic constitutive model.It can analyze the mucky soil site nonlinear seismic response,reflecting the deformation characteristics and damping effect of the silty soil.The hysteresis loop area is more extensive,and the residual strain is evident.

Mesoscale soil moisture survey by mobile cosmic-ray neutron sensor across various landscapes in the Heihe River Basin

The cosmic-ray neutron technology is a novel method for upscaling soil moisture,holding significant importance in drought monitoring,soil water storage estimation,calibration of remote sensing products,and data assimilation of land surface models.However,most studies conducted soil moisture measurement experiments using static Cosmic-Ray Neutron Sensors(CRNS)and are often limited to a single landscape,lacking in-situ measurement for the cosmic-ray neutron rover across various landscapes.This study carried out soil moisture observation experiments using a cosmic-ray neutron rover in nine grassland plots,nine farmland plots,and nine desert plots of the Heihe River Basin,Northwest China.The neutron counts displayed clear variations among different plots,and an equation could represent the relationship between neutron intensity and multiple variables near the ground.The parameter N0 was the smallest for grassland and greatest for desert,and there was a significant negative correlation between Normalized Difference Vegetation Index and N0(P<0.05).Furthermore,the performance of CRNS notably improved after considering soil lattice water and soil organic matter.The Root Mean Square Error(RMSE)between the measured and oven-dried soil moisture increased with radius.Soil moisture measured by CRNS strongly supported the 100 m diameter footprint assumption(RMSE<0.044 g/g).The study offers valuable insights into the application and promotion of cosmic-ray neutron technology across various landscapes within a basin.

Extended wet sieving method for determination of complete particle size distribution of general soils

The traditional standard wet sieving method uses steel sieves with aperture?0.063 mm and can only determine the particle size distribution(PSD)of gravel and sand in general soil.This paper extends the traditional method and presents an extended wet sieving method.The extended method uses both the steel sieves and the nylon filter cloth sieves.The apertures of the cloth sieves are smaller than 0.063 mm and equal 0.048 mm,0.038 mm,0.014 mm,0.012 mm,0.0063 mm,0.004 mm,0.003 mm,0.002 mm,and 0.001 mm,respectively.The extended method uses five steps to separate the general soil into many material sub-groups of gravel,sand,silt and clay with known particle size ranges.The complete PSD of the general soil is then calculated from the dry masses of the individual material sub-groups.The extended method is demonstrated with a general soil of completely decomposed granite(CDG)in Hong Kong,China.The silt and clay materials with different particle size ranges are further examined,checked and verified using stereomicroscopic observation,physical and chemical property tests.The results further confirm the correctness of the extended wet sieving method.