A dynamic soil freezing characteristic curve model for frozen soil

The soil freezing characteristic curve(SFCC)plays a fundamental role in comprehending thermohydraulic behavior and numerical simulation of frozen soil.This study proposes a dynamic model to uniformly express SFCCs amidst varying total water contents throughout the freezing-thawing process.Firstly,a general model is proposed,wherein the unfrozen water content at arbitrary temperature is determined as the lesser of the current total water content and the reference value derived from saturated SFCC.The dynamic performance of this model is verified through test data.Subsequently,in accordance with electric double layer(EDL)theory,the theoretical residual and minimum temperatures in SFCC are calculated to be-14.5℃to-20℃for clay particles and-260℃,respectively.To ensure that the SFCC curve ends at minimum temperature,a correction function is introduced into the general model.Furthermore,a simplified dynamic model is proposed and investigated,necessitating only three parameters inherited from the general model.Additionally,both general and simplified models are evaluated based on a test database and proven to fit the test data exactly across the entire temperature range.Typical recommended parameter values for various types of soils are summarized.Overall,this study provides not only a theoretical basis for most empirical equations but also proposes a new and more general equation to describe the SFCC.

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-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.

Improving model performance in mapping cropland soil organic matter using time-series remote sensing data

Faced with increasing global soil degradation,spatially explicit data on cropland soil organic matter(SOM)provides crucial data for soil carbon pool accounting,cropland quality assessment and the formulation of effective management policies.As a spatial information prediction technique,digital soil mapping(DSM)has been widely used to spatially map soil information at different scales.However,the accuracy of digital SOM maps for cropland is typically lower than for other land cover types due to the inherent difficulty in precisely quantifying human disturbance.To overcome this limitation,this study systematically assessed a framework of“information extractionfeature selection-model averaging”for improving model performance in mapping cropland SOM using 462 cropland soil samples collected in Guangzhou,China in 2021.The results showed that using the framework of dynamic information extraction,feature selection and model averaging could efficiently improve the accuracy of the final predictions(R^(2):0.48 to 0.53)without having obviously negative impacts on uncertainty.Quantifying the dynamic information of the environment was an efficient way to generate covariates that are linearly and nonlinearly related to SOM,which improved the R^(2)of random forest from 0.44 to 0.48 and the R^(2)of extreme gradient boosting from 0.37to 0.43.Forward recursive feature selection(FRFS)is recommended when there are relatively few environmental covariates(<200),whereas Boruta is recommended when there are many environmental covariates(>500).The Granger-Ramanathan model averaging approach could improve the prediction accuracy and average uncertainty.When the structures of initial prediction models are similar,increasing in the number of averaging models did not have significantly positive effects on the final predictions.Given the advantages of these selected strategies over information extraction,feature selection and model averaging have a great potential for high-accuracy soil mapping at any scales,so this approach can provide more reliable references for soil conservation policy-making.

Soil erosion susceptibility mapping of Hangu Region,Kohat Plateau of Pakistan using GIS and RS-based models

Soil erosion is a crucial geo-environmental hazard worldwide that affects water quality and agriculture,decreases reservoir storage capacity due to sedimentation,and increases the danger of flooding and landslides.Thus,this study uses geospatial modeling to produce soil erosion susceptibility maps(SESM)for the Hangu region,Khyber Pakhtunkhwa(KPK),Pakistan.The Hangu region,located in the Kohat Plateau of KPK,Pakistan,is particularly susceptible to soil erosion due to its unique geomorphological and climatic characteristics.Moreover,the Hangu region is characterized by a combination of steep slopes,variable rainfall patterns,diverse land use,and distinct soil types,all of which contribute to the complexity and severity of soil erosion processes.These factors necessitate a detailed and region-specific study to develop effective soil conservation strategies.In this research,we detected and mapped 1013 soil erosion points and prepared 12 predisposing factors(elevation,aspect,slope,Normalized Differentiate Vegetation Index(NDVI),drainage network,curvature,Land Use Land Cover(LULC),rainfall,lithology,contour,soil texture,and road network)of soil erosion using GIS platform.Additionally,GIS-based statistical models like the weight of evidence(WOE)and frequency ratio(FR)were applied to produce the SESM for the study area.The SESM was reclassified into four classes,i.e.,low,medium,high,and very high zone.The results of WOE for SESM show that 16.39%,33.02%,29.27%,and 21.30%of areas are covered by low,medium,high,and very high zones,respectively.In contrast,the FR results revealed that 16.50%,24.33%,35.55%,and 23.59%of the areas are occupied by low,medium,high,and very high classes.Furthermore,the reliability of applied models was evaluated using the Area Under Curve(AUC)technique.The validation results utilizing the area under curve showed that the success rate curve(SRC)and predicted rate curve(PRC)for WOE are 82%and 86%,respectively,while SRC and PRC for FR are 85%and 96%,respectively.The validation results revealed that the FR model performance is better and more reliable than the WOE.

A bounding surface visco-plasticity model considering generalized spacing ratio of soils

The non-unique critical state of soils with time-dependent behaviors is a significant issue in geotechnical engineering problems.However,previous bounding surface plasticity models cannot predict accurately the non-unique critical state of soils,because the distance between the compression line and critical state line charged by strain-rate effect is basically neglected.To fill this gap,a generalized spacing ratio of soils is defined in the elasto-viscoplastic framework,and a bounding surface visco-plasticity model is formulated and verified,which can consider the generalized spacing ratio.Specifically,the generalized spacing ratio of soils reflects the distance between the compression line and the critical state line of soils with time-dependent behaviors.Then,the generalized spacing ratio is introduced into an improved anisotropic bounding surface.A new expression of the visco-plastic multiplier is derived by solving the consistency equation of an anisotropic bounding surface.In the expression,a strain rate index is proposed to account for the strain-rate effect on visco-plastic strain increment,and a visco-plastic hardening modulus is derived to predict the visco-plastic response of soils in overconsolidation conditions.The model is then verified through constant strain rate tests and creep tests.Notably,it can capture the non-unique critical states of soils with time-dependent behaviors due to the generalized spacing ratio and the creep rupture of soils due to the visco-plastic multiplier that considers the stress ratio and visco-plastic strain rate.

Evaluation of soil erosion vulnerability in Hubei Province of China using RUSLE model and combination weighting method

Soil erosion has been recognized as a critical environmental issue worldwide.While previous studies have primarily focused on watershed-scale soil erosion vulnerability from a natural factor perspective,there is a notable gap in understanding the intricate interplay between natural and socio-economic factors,especially in the context of spatial heterogeneity and nonlinear impacts of human-land interactions.To address this,our study evaluates the soil erosion vulnerability at a provincial scale,taking Hubei Province as a case study to explore the combined effects of natural and socio-economic factors.We developed an evaluation index system based on 15 indicators of soil erosion vulnerability:exposure,sensitivity,and adaptability.In addition,the combination weighting method was applied to determine index weights,and the spatial interaction was analyzed using spatial autocorrelation,geographical temporally weighted regression and geographical detector.The results showed an overall decreasing soil erosion intensity in Hubei Province during 2000 and 2020.The soil erosion vulnerability increased before 2000 and then.The areas with high soil erosion vulnerability were mainly confined in the central and southern regions of Hubei Province(Xiantao,Tianmen,Qianjiang and Ezhou)with obvious spatial aggregation that intensified over time.Natural factors(habitat quality index)had negative impacts on soil erosion vulnerability,whereas socio-economic factors(population density)showed substantial spatial variability in their influences.There was a positive correlation between soil erosion vulnerability and erosion intensity,with the correlation coefficients ranging from-0.41 and 0.93.The increase of slope was found to enhance the positive correlation between soil erosion vulnerability and intensity.

Analytical model for predicting time-dependent lateral deformation of geosynthetics-reinforced soil walls with modular block facing

To date,few models are available in the literature to consider the creep behavior of geosynthetics when predicting the lateral deformation(d)of geosynthetics-reinforced soil(GRS)retaining walls.In this study,a general hyperbolic creep model was first introduced to describe the long-term deformation of geosynthetics,which is a function of elapsed time and two empirical parameters a and b.The conventional creep tests with three different tensile loads(Pr)were conducted on two uniaxial geogrids to determine their creep behavior,as well as the a-Pr and b-Pr relationships.The test results show that increasing Pr accelerates the development of creep deformation for both geogrids.Meanwhile,a and b respectively show exponential and negatively linear relationships with Pr,which were confirmed by abundant experimental data available in other studies.Based on the above creep model and relationships,an accurate and reliable analytical model was then proposed for predicting the time-dependent d of GRS walls with modular block facing,which was further validated using a relevant numerical investigation from the previous literature.Performance evaluation and comparison of the proposed model with six available prediction models were performed.Then a parametric study was carried out to evaluate the effects of wall height,vertical spacing of geogrids,unit weight and internal friction angle of backfills,and factor of safety against pullout on d at the end of construction and 5 years afterwards.The findings show that the creep effect not only promotes d but also raises the elevation of the maximum d along the wall height.Finally,the limitations and application prospects of the proposed model were discussed and analyzed.

Damage constitutive model of lunar soil simulant geopolymer under impact loading

Lunar base construction is a crucial component of the lunar exploration program,and considering the dynamic characteristics of lunar soil is important for moon construction.Therefore,investigating the dynamic properties of lunar soil by establishing a constitutive relationship is critical for providing a theoretical basis for its damage evolution.In this paper,a split Hopkinson pressure bar(SHPB)device was used to perform three sets of impact tests under different pressures on a lunar soil simulant geopolymer(LSSG)with sodium silicate(Na_(2)SiO_(3))contents of 1%,3%,5%and 7%.The dynamic stressestrain curves,failure modes,and energy variation rules of LSSG under different pressures were obtained.The equation was modified based on the ZWT viscoelastic constitutive model and was combined with the damage variable.The damage element obeys the Weibull distribution and the constitutive equation that can describe the mechanical properties of LSSG under dynamic loading was obtained.The results demonstrate that the dynamic compressive strength of LSSG has a marked strain-rate strengthening effect.Na_(2)SiO_(3) has both strengthening and deterioration effects on the dynamic compressive strength of LSSG.As Na_(2)SiO_(3) grows,the dynamic compressive strength of LSSG first increases and then decreases.At a fixed air pressure,5%Na_(2)SiO_(3) had the largest dynamic compressive strength,the largest incident energy,the smallest absorbed energy,and the lightest damage.The ZWT equation was modified according to the stress response properties of LSSG and the range of the SHPB strain rate to obtain the constitutive equation of the LSSG,and the model’s correctness was confirmed.

A rate-dependent constitutive model for saturated frozen soil considering local breakage mechanism

A rate-dependent constitutive model for saturated frozen soil is vital in frozen soil mechanics,especially when simultaneously describing the nonlinearity,dilatancy and strain-softening characteristics.The distribution of the non-uniform strain rate of saturated frozen soil at the meso-scale due to the local icecementation breakage is described by a newly binary-medium-based homogenization equation.Based on the field-equation-based approach of the meso-mechanics theory,the interaction expression of the strain rate at macro-and meso-scale is derived,which can give the strain rate concentration tensor at different crushed degrees.With the thermodynamics and empirical assumption,a breakage ratio in the rate-dependent form is determined.This overcomes the limitations of the existing binary-medium-based models that are difficult to simulate rate-dependent mechanical response.Based on these assumptions,a newly binary-medium-based rate-dependent model is proposed considering both the ice bond breakage and material composition characteristics of saturated frozen soil.The proposed constitutive model has been validated by the test results on frozen soils with different temperatures and strain rates.

Novel Hybrid X GBoost Model to Forecast Soil Shear Strength Based on Some Soil Index Tests

When building geotechnical constructions like retaining walls and dams is of interest,one of the most important factors to consider is the soil’s shear strength parameters.This study makes an effort to propose a novel predictive model of shear strength.The study implements an extreme gradient boosting(XGBoost)technique coupled with a powerful optimization algorithm,the salp swarm algorithm(SSA),to predict the shear strength of various soils.To do this,a database consisting of 152 sets of data is prepared where the shear strength(τ)of the soil is considered as the model output and some soil index tests(e.g.,dry unit weight,water content,and plasticity index)are set as model inputs.Themodel is designed and tuned using both effective parameters of XGBoost and SSA,and themost accuratemodel is introduced in this study.Thepredictionperformanceof theSSA-XGBoostmodel is assessedbased on the coefficient of determination(R2)and variance account for(VAF).Overall,the obtained values of R^(2) and VAF(0.977 and 0.849)and(97.714%and 84.936%)for training and testing sets,respectively,confirm the workability of the developed model in forecasting the soil shear strength.To investigate the model generalization,the prediction performance of the model is tested for another 30 sets of data(validation data).The validation results(e.g.,R^(2) of 0.805)suggest the workability of the proposed model.Overall,findings suggest that when the shear strength of the soil cannot be determined directly,the proposed hybrid XGBoost-SSA model can be utilized to assess this parameter.

Combining RUSLE model and the vegetation health index to unravel the relationship between soil erosion and droughts in southeastern Tunisia

Droughts and soil erosion are among the most prominent climatic driven hazards in drylands,leading to detrimental environmental impacts,such as degraded lands,deteriorated ecosystem services and biodiversity,and increased greenhouse gas emissions.In response to the current lack of studies combining drought conditions and soil erosion processes,in this study,we developed a comprehensive Geographic Information System(GIS)-based approach to assess soil erosion and droughts,thereby revealing the relationship between soil erosion and droughts under an arid climate.The vegetation condition index(VCI)and temperature condition index(TCI)derived respectively from the enhanced vegetation index(EVI)MOD13A2 and land surface temperature(LST)MOD11A2 products were combined to generate the vegetation health index(VHI).The VHI has been conceived as an efficient tool to monitor droughts in the Negueb watershed,southeastern Tunisia.The revised universal soil loss equation(RUSLE)model was applied to quantitatively estimate soil erosion.The relationship between soil erosion and droughts was investigated through Pearson correlation.Results exhibited that the Negueb watershed experienced recurrent mild to extreme drought during 2000–2016.The average soil erosion rate was determined to be 1.8 t/(hm2•a).The mountainous western part of the watershed was the most vulnerable not only to soil erosion but also to droughts.The slope length and steepness factor was shown to be the most significant controlling parameter driving soil erosion.The relationship between droughts and soil erosion had a positive correlation(r=0.3);however,the correlation was highly varied spatially across the watershed.Drought was linked to soil erosion in the Negueb watershed.The current study provides insight for natural disaster risk assessment,land managers,and stake-holders to apply appropriate management measures to promote sustainable development goals in fragile environments.

Predicting and validating the load-settlement behavior of large-scale geosynthetic-reinforced soil abutments using hybrid intelligent modeling

Settlement prediction of geosynthetic-reinforced soil(GRS)abutments under service loading conditions is an arduous and challenging task for practicing geotechnical/civil engineers.Hence,in this paper,a novel hybrid artificial intelligence(AI)-based model was developed by the combination of artificial neural network(ANN)and Harris hawks’optimisation(HHO),that is,ANN-HHO,to predict the settlement of the GRS abutments.Five other robust intelligent models such as support vector regression(SVR),Gaussian process regression(GPR),relevance vector machine(RVM),sequential minimal optimisation regression(SMOR),and least-median square regression(LMSR)were constructed and compared to the ANN-HHO model.The predictive strength,relalibility and robustness of the model were evaluated based on rigorous statistical testing,ranking criteria,multi-criteria approach,uncertainity analysis and sensitivity analysis(SA).Moreover,the predictive veracity of the model was also substantiated against several large-scale independent experimental studies on GRS abutments reported in the scientific literature.The acquired findings demonstrated that the ANN-HHO model predicted the settlement of GRS abutments with reasonable accuracy and yielded superior performance in comparison to counterpart models.Therefore,it becomes one of predictive tools employed by geotechnical/civil engineers in preliminary decision-making when investigating the in-service performance of GRS abutments.Finally,the model has been converted into a simple mathematical formulation for easy hand calculations,and it is proved cost-effective and less time-consuming in comparison to experimental tests and numerical simulations.

Strength Model of Soda Residue Soil Considering Consolidation Stress and Structural Influence

Soda residue(SR)is a type of industrial waste produced in the soda process with the ammonia-soda method.Applying SR to backfilling solves the land occupation and environmental pollution problems in coastal areas and saves material costs for foundation engineering.The strength characteristics of soda residue soil(SRS)under different consolidation conditions are the key points to be solved in the engineering application of SRS.Triaxial compression tests were performed on the undisturbed SRS of Tianjin Port.The shear properties of SRS under different consolidation conditions were then discussed.Meanwhile,a structural strength model(SSM)based on Mohr-Coulomb theory was proposed.SSM reflects the influence of soil structure on undrained strength(Cu)and divides the Cu into the following two parts:friction strength(C_(uf))and original structural strength(C_(u0)).C_(uf)characterizes the magnitude of friction between soil particles,which is related to the consolidation stress.Meanwhile,C_(u0)represents the structural effect on soil strength,which is related to the soil deposition and consolidation processes.SSM was validated by the test data of undisturbed soils.Results reveal that the undisturbed soil generally had a certain C_(u0).Therefore,the SRS strength model was established by combining the experimental law of SRS with SSM.Error analysis shows that the SRS strength model can effectively predict the Cu of undisturbed SRS in Tianjin Port under different consolidation conditions.

Fractional derivative statistical damage model of unsaturated expansive soil based on unified hydraulic effect

Unsaturated expansive soil is widely distributed in China and has complex engineering properties.This paper proposes the unified hydraulic effect shear strength theory of unsaturated expansive soil based on the effective stress principle,swelling force principle,and soil–water characteristics.Considering the viscoelasticity and structural damage of unsaturated expansive soil during loading,a fractional hardening–damage model of unsaturated expansive soil was established.The model parameters were established on the basis of the proposed calculation method of shear strength and the triaxial shear experiment on unsaturated expansive soil.The proposed model was verified by the experimental data and a traditional damage model.The proposed model can satisfactorily describe the entire process of the strain-hardening law of unsaturated expansive soil.Finally,by investigating the damage variables of the proposed model,it was found that:(a)when the values of confining pressure and matric suction are close,the coupling of confining pressure and matric suction contributes more to the shear strength;(b)there is a damage threshold for unsaturated expansive soil,and is mainly reflected by strength criterion of infinitesimal body;(c)the strain hardening law of unsaturated expansive soil is mainly reflected by fractional derivative operator.

A Modified Model for Soil–Structure Interface Considering Random Damage of Mesoscopic Contact Elements

The interaction between soil and marine structures like submarine pipeline/pipe pile/suction caisson is a complicated geotechnical mechanism process.In this study,the interface is discretized into multiple mesoscopic contact elements that are damaged randomly throughout the shearing process due to the natural heterogeneity.The evolution equation of damage variable is developed based on the Weibull function,which is able to cover a rather wide range of distribution shapes by only two parameters,making it applicable for varying scenarios.Accordingly,a statistical damage model is established by incorporating Mohr–Coulomb strength criterion,in which the interfacial residual strength is considered whereby the strain softening behavior can be described.A concept of“semi-softening”characteristic point on shear stress–displacement curve is proposed for effectively modeling the evolution of strain softening.Finally,a series of ring shear tests of the interfaces between fine sea sand and smooth/rough steel surfaces are conducted.The predicted results using the proposed model are compared with experimental data of this study as well as some results from existing literature,indicating that the model has a good performance in modeling the progressive failure and strain softening behavior for various types of soil–structure interfaces.

Hyperspectral Inversion Model of Available Potassium Content in Red Soil of Eucalyptus Plantation in Northern Guangxi

Soil information is the basis of soil management and precise variable fertilization. The traditional method of obtaining soil information through chemical detection of laboratory has high cost and poor timeliness, which is difficult to meet the needs of digital forestry, soil monitoring and real-time management of nutrients. Taking red soil of Eucalyptus plantation in northern Guangxi as the research object, the spectral data of samples with different soil available potassium contents were measured, and the spectral characteristics were analyzed, and the inversion model was established by using PLS method. The results showed that the spectral sensitive bands of available potassium content in red soil of the region mainly concentrated in 400-600, 1 450, 2 200 nm and so on. After the first derivative transformation, the redundant information in the original spectral data can be significantly reduced, and the correlation between spectral indexes and soil available potassium content can be improved. The full-band modeling results of R and FDR were better than those of significant bands. The optimal model was full-band-FDR-PLS, R2=0.862, and RMSE=2.718. The results of this study can be used for the application of near-earth remote sensing in Guangxi, such as soil digital mapping, precise variable fertilization and real-time monitoring of soil available potassium.

The potential for an old-growth forest to store carbon in the topsoil:A case study at Sasso Fratino,Italy

There is considerable interest devoted to oldgrowth forests and their capacity to store carbon(C)in biomass and soil.Inventories of C stocks in old-growth forests are carried out worldwide,although there is a lack of information on their actual potential for C sequestration.To further understand this,soil organic carbon(SOC)was measured in one of Italy's best-preserved old-growth forests,the Sasso Fratino Integral Nature Reserve.This reserve is on the World Heritage List along with other ancient beech forests of Europe,and it is virtually untouched due to the steepness of the terrain,even before legal constraints were imposed.Although the sandstone-derived soils are often shallow,they are rich in organic matter.However,no quantification had been carried out.By systematically sampling the topsoil across the forest,we accurately determined the average amount of SOC(62.0±16.9 Mg ha^(–1))and nitrogen(4.0±1.2 Mg ha^(–1))in the top 20 cm.Using the CENTURY model,future dynamics of SOC stocks were predicted to 2050 according to two climate scenarios,A1F1 and B2,the first of high concern and the second more optimistic.The model projected an increase of 0.2 and 0.3 Mg ha^(–1)a^(–1)by 2030 under the A1F1 and B2 scenarios,respectively,suggesting that the topsoil in old-growth forests does not reach equilibrium but continues accumulating SOC.However,from 2030 to 2050,a decline in SOC accumulation is predicted,indicating SOC net loss at high altitudes under the worst-case scenario.This study confirms that soils in oldgrowth forests play a significant role in carbon sequestration.It also suggests that climate change may affect the potential of these forests to store SOC not only in the long term but also in the coming years.

Integrated Hydrological Modeling of the Godavari River Basin in Maharashtra Using the SWAT Model: Streamflow Simulation and Analysis

Hydrological modeling plays a crucial role in efficiently managing water resources and understanding the hydrologic behavior of watersheds. This study aims to simulate daily streamflow in the Godavari River Basin in Maharashtra using the Soil and Water Assessment Tool (SWAT). SWAT is a process-based hydrological model used to predict water balance components, sediment levels, and nutrient contamination. In this research, we used integrated remote sensing and GIS data, including Digital Elevation Models (DEM), land use and land cover (LULC) maps, soil maps, and observed precipitation and temperature data, as input for developing the SWAT model to assess surface runoff in this large river basin. The Godavari River Basin under study was divided into 25 sub-basins, comprising 151 hydrological response units categorized by unique land cover, soil, and slope characteristics using the SWAT model. The model was calibrated and validated against observed runoff data for two time periods: 2003-2006 and 2007-2010 respectively. Model performance was assessed using the Nash-Sutcliffe efficiency (NSE) and the coefficient of determination (R2). The results show the effectiveness of the SWAT2012 model, with R2 value of 0.84 during calibration and 0.86 during validation. NSE values also ranged from 0.84 during calibration to 0.85 during validation. These findings enhance our understanding of surface runoff dynamics in the Godavari River Basin under study and highlight the suit-ability of the SWAT model for this region.

Effects of gravel on the water absorption characteristics and hydraulic parameters of stony soil

The eastern foothills of the Helan Mountains in China are a typical mountainous region of soil and gravel,where gravel could affect the water movement process in the soil.This study focused on the effects of different gravel contents on the water absorption characteristics and hydraulic parameters of stony soil.The stony soil samples were collected from the eastern foothills of the Helan Mountains in April 2023 and used as the experimental materials to conduct a one-dimensional horizontal soil column absorption experiment.Six experimental groups with gravel contents of 0%,10%,20%,30%,40%,and 50%were established to determine the saturated hydraulic conductivity(K_(s)),saturated water content(θ_(s)),initial water content(θ_(i)),and retention water content(θ_(r)),and explore the changes in the wetting front depth and cumulative absorption volume during the absorption experiment.The Philip model was used to fit the soil absorption process and determine the soil water absorption rate.Then the length of the characteristic wetting front depth,shape coefficient,empirical parameter,inverse intake suction and soil water suction were derived from the van Genuchten model.Finally,the hydraulic parameters mentioned above were used to fit the soil water characteristic curves,unsaturated hydraulic conductivity(K_(θ))and specific water capacity(C(h)).The results showed that the wetting front depth and cumulative absorption volume of each treatment gradually decreased with increasing gravel content.Compared with control check treatment with gravel content of 0%,soil water absorption rates in the treatments with gravel contents of 10%,20%,30%,40%,and 50%decreased by 11.47%,17.97%,25.24%,29.83%,and 42.45%,respectively.As the gravel content increased,inverse intake suction gradually increased,and shape coefficient,K_(s),θ_(s),andθ_(r)gradually decreased.For the same soil water content,soil water suction and K_(θ)gradually decreased with increasing gravel content.At the same soil water suction,C(h)decreased with increasing gravel content,and the water use efficiency worsened.Overall,the water holding capacity,hydraulic conductivity,and water use efficiency of stony soil in the eastern foothills of the Helan Mountains decreased with increasing gravel content.This study could provide data support for improving soil water use efficiency in the eastern foothills of the Helan Mountains and other similar rocky mountainous areas.