Orthogonal test and regression analysis of the strain on silty soil in Shanghai under metro loading

Cyclic triaxial test by means of the geotechnical digital system is conducted for the soil near the Guoquan Road Station of Metro Line 10 in Shanghai to analyze the strain characteristics and the variation law of saturated silty soil under subway loading. Orthogonal design method is used to arrange the experiment, considering the following factors: frequency ratio f _R, cyclic stress ratio σ _R, vibration time ratio N _R, and the interaction function among them. Results show that the cyclic stress ratio σ _R, the frequency ratio f _R, the vibration time ratio N _R, and the interaction between the cyclic stress ratio σ _R and the vibration time ratio N _R have a significant effect on the axial strain of the subway tunnel. The effect of the interaction between the cyclic stress ratio σ _R and the vibration time ratio N _R is also significant. From the analysis of variance and regression theory, the nonlinear regression equation of the cumulative plastic strain of silty soil under subway loading is established. Residual analysis proves that the equation is ideal and credible. The results have important value for the design of subway tunnels.     

A modified normalized model for predicting effective soil thermal conductivity

Effective soil thermal conductivity (λ _eff) describes the ability of a multiphase soil to transmit heat by conduction under unit temperature gradient. It is a critical parameter for environmental science, earth and planetary science, and engineering applications. Numerous models are available in the literature, but their applicability is generally restricted to certain soil types or water contents (θ). The objective of this study was to develop a new model in the similar form of the Johansen 1975 model to simulate the λ _eff(θ) relationship of soils of various soil textures and water contents. An exponential type model with two parameters is developed and a new function for calculating dry soil thermal conductivity is presented. Performance of the new model and six other normalized models were evaluated with published datasets. The results show that the new model is able to well mimic λ _eff(θ) relationship of soils from sand to silt loam and from oven dry to full saturation. In addition, it has the best performance among the seven models under test (with root-mean-square error of 0.059 W m^?1 °C^?1, average deviations of 0.0009 W m^?1 °C^?1, and Nash–Sutcliffe efficiency of 0.994). The new model has potential to improve the reliability of soil thermal conductivity estimation and be incorporated into numerical modeling for environmental, earth and engineering studies.     

Characterization of locally available soil as a liner material for solid waste landfills in Sri Lanka

This study aimed to develop a low-cost and effective clay liner material for solid waste landfills in Sri Lanka. A locally available clayey soil and its admixtures with 5 and 10% bentonite were examined for this purpose. Laboratory experiments to determine soil plasticity and swell index were carried out on the tested samples. Hydraulic conductivity (k) tests were carried out in the laboratory using water and an aqueous solution of CaCl₂ on unconsolidated samples prepared by either dry or slurry packing and pre-consolidated samples with five different consolidation pressures (p) from 10 to 200 kPa. Measured liquid limits for tested admixtures increased with increasing bentonite contents and correlated well with measured values of the swell index. The difference in permeant solutions had little effect on measured k values for both unconsolidated and pre-consolidated samples. The hydraulic conductivities were highly affected by changing p, i.e., the k values decreased on two orders of magnitude as p increased from 10 to 200 kPa. The Kozeny–Carman equation, a theoretical permeability model that expresses the k-porosity relationship, was applied to measured data including reported values. Results showed the Kozeny–Carman equation captured well the porosity-dependent k values for tested soils and their admixtures with bentonite under a wide range of void ratios, suggesting that the Kozeny–Carman equation is a useful tool to estimate the magnitude of k values for differently compacted soil and its bentonite admixtures.     

Mapping heatwave vulnerability in Korea

Analysis of event-based soil erosion magnitude with special return periods is essential to appropriately design strategies and adopt soil conservation practices. However, the spatiotemporal variations of soil erosion with different return periods, especially at national level, have not been adequately considered. Therefore, the present study aimed to zone rainfall erosivity index (R factor) as the most dynamic factor affecting variability of soil erosion rate, with different return periods in monthly, seasonal and annual time scales in Iran. Toward this attempt, the kinetic energy and maximum 30-min intensity (I ₃₀) over 12,000 available and accessible events of 70 stations were calculated during the common period of 1984–2004 and the corresponding R factor of the Universal Soil Loss Equation was then computed. Subsequently, the best-fitted frequency distributions were determined in all stations in three time scales using the EasyFit Software. The R factor was accordingly estimated for 2-, 5-, 10-, 25- and 50-year return periods. In addition, the inverse distance weighting technique was employed to determine and analyze the spatial variability patterns of R factor in different time scales using geographic information system. The results indicated that the frequency distributions fitted to study data were different in study time scales due to variability of spatiotemporal patterns of R factor. In addition, no specific spatial pattern of R factor could be recognized for different return periods and time scales. The average annual R factor was also found 1.41 MJ mm ha^?1 h^?1, whereas the respective R factor for different respective return periods of 2, 5, 10, 25 and 50 years was obtained 1.47, 2.62, 3.35, 4.48 and 5.54 MJ mm ha^?1 h^?1. These findings can be used for suitable decision making and effective environmental planning for land management Iran countrywide.     

Permeability of granular soil employing flexible wall permeameter

Understanding the changes in permeability of soil, when soil is subjected to high confining pressure and flow pressure, which may alter the textural and geomechanical characteristics of soil, is of great importance to many geo-engineering activities such as, construction of high-rise buildings near the coast or the water bodies, earthen dams, pavement subgrades, reservoir, and shallow repositories. It is now possible to evaluate the changes in permeability of soil samples under varying conditions of confining pressure and flow pressure using flexible wall permeameter (FWP). In the present study, investigation was carried out on a cylindrical sample of granular soil employing FWP under varied conditions of confining pressure (σ₃)—50–300 kPa, which can simulate the stress conditions equivalent to depth of about 20 m under the earth’s crust, and a flow pressure (f_p)—20–120 kPa, which is mainly present near the small earthen embankment dams, landfill liners, and slurry walls near the soft granular soil with high groundwater table. The obtained results indicate a linear relationship between hydraulic conductivity (k) with effective confining pressure (σ_eff.), k, decreasing linearly with an incremental change in σ_eff.. Further, k increases significantly with an increase in f_p corresponding to each σ_eff., and q increases significantly with increase in the f_p corresponding to each (σ₃). It was also observed that corresponding to the low f_p of 20 kPa, the reduction in k is nonlinear with σ_3. The percentage reduction in k is observed to be 9, 13, and 27% corresponding to σ₃ of 50–100, 100–200, and 200-300 kPa, respectively.     

Enhancement of random finite element method in reliability analysis and risk assessment of soil slopes using Subset Simulation

Random finite element method (RFEM) provides a rigorous tool to incorporate spatial variability of soil properties into reliability analysis and risk assessment of slope stability. However, it suffers from a common criticism of requiring extensive computational efforts and a lack of efficiency, particularly at small probability levels (e.g., slope failure probability P _f ?<?0.001). To address this problem, this study integrates RFEM with an advanced Monte Carlo Simulation (MCS) method called “Subset Simulation (SS)” to develop an efficient RFEM (i.e., SS-based RFEM) for reliability analysis and risk assessment of soil slopes. The proposed SS-based RFEM expresses the overall risk of slope failure as a weighed aggregation of slope failure risk at different probability levels and quantifies the relative contributions of slope failure risk at different probability levels to the overall risk of slope failure. Equations are derived for integrating SS with RFEM to evaluate the probability (P _f ) and risk (R) of slope failure. These equations are illustrated using a soil slope example. It is shown that the P _f and R are evaluated properly using the proposed approach. Compared with the original RFEM with direct MCS, the SS-based RFEM improves, significantly, the computational efficiency of evaluating P _f and R. This enhances the applications of RFEM in the reliability analysis and risk assessment of slope stability. With the aid of improved computational efficiency, a sensitivity study is also performed to explore effects of vertical spatial variability of soil properties on R. It is found that the vertical spatial variability affects the slope failure risk significantly.     

How water use of <Emphasis Type="Italic">Salix</Emphasis><Emphasis Type="Italic">psammophila</Emphasis> bush depends on groundwater depth in a semi-desert area

To investigate the groundwater levels changes effects on the transpiration of Salix psammophila (S. psammophila) bush, systemic measurements of meteorological conditions, sap flow of S. psammophila, soil water contents and groundwater levels were conducted in the Hailiutu River catchment, NW of China. Based on the collected field data, Hydrus-1D software package was used to calibrate water movement for root uptake in the saturated–unsaturated zone. The soil hydraulic parameters and root uptake function parameters were calibrated. The simulated results of soil water contents and sap flow fitted well with the observed ones. Based on the calibrated hydraulic parameters, different groundwater levels were imposed at the low boundary to simulate the groundwater levels changes effects on the transpiration. The relationship between ratio of actual transpiration and potential (T/T _p) and groundwater water table depth was established. The results shows that the ratio of actual transpiration and potential transpiration decreases with groundwater table depth increase as inverse ‘S’ shape. And the turn point is corresponding to the extinct depth, i.e., no groundwater contribution to S. psammophila transpiration. To further verify this phenomenon is universal, the soil hydraulic parameters were replaced with the other five groups in the calibrated forward model. The results confirmed the similar changes of T _a/T _p with the groundwater levels changed, i.e. inverse ‘S’ shape. However, the extinction depth is different corresponding to different soil hydraulic parameters. So, the research results indicated the relationship between transpiration and groundwater levels is non-linear function.     

Evaluation of the use of legumes for biodegradation of petroleum hydrocarbons in soil

The aim of this research was to evaluate the potential of six legumes: Medicago sativa L., Glycine max, Arachis hypogea, Lablab purpureus, Pheseolus vulgaris and Cajanus cajan to restore within a short period of time soil contaminated with 3% crude oil. The legumes in five replications were grown in crude oil-contaminated and crude oil-uncontaminated soil in a completely randomized design. Plants were assessed for seedling emergence, plant height and leaf number. GC–MS was used to analyze the residual crude oil from the rhizosphere of the legumes. Plant growth parameters were reduced significantly (P < 0.05) for legumes in contaminated soil compared to their controls. In the 4th week after planting (WAP), shoot height increased across the species up to the 8th WAP. However, in the 12 WAP no significant increase in the shoot of all species was observed. Two WAP legumes planted in contaminated soil had significantly (P < 0.05) higher leaf number than these planted in uncontaminated soil with the exception of M. sativa. In the 4th WAP, only A. hypogea and P. vulgaris had increased leaf number, while in the 6th WAP, only L. purpureus had increased leaf number and survived up to the 12th WAP while most of the legumes species died. Chromatographic profiles indicated 100% degradation of the oil fractions in C. cajan and L. purpureus after 90 days. For other legumes however, greater losses of crude oil fractions C₁–C₁₀ and C₁₀–C₂₀ were indicated in rhizosphere soil of P. vulgaris and G. max, respectively. The most effective removal (93.66%) of C₂₁–C₃₀ components was observed in G. max-planted soil even though vegetation was not established. The legumes especially C. cajan, L. purpureus and A. hypogea are promising candidates for phytoremediation of petroleum hydrocarbon-impacted soil.     

Fractal features of soil particle-size distributions and their relationships with soil properties in gravel-mulched fields

Soil particle-size distribution (PSD) is an important index for soil classification because it has large influences on soil hydrological characteristics, salinity, fertility, erodibility, nutrient content, swelling/shrinking, and degradation. We present a case study of the fractal characteristics of soil PSD and its relationship with soil properties of gravel-mulched fields in an arid area of northwestern China using single-fractal calculation. Particle size was unimodally distributed within the narrow range of 20–100 μm, with silt as the most common component. Horizontally, silt content was the highest, followed by sand and clay contents. Vertically, clay content increased with depth, while there were no obvious change rules for both silt and sand contents. The volume fractal dimension (D) of PSD ranged from 2.4307 to 2.5260, increased with the content of fine particles but decreased with the content of coarse particles. D was correlated positively with soil-water content and salt content and negatively with bulk density. The saturated soil-water content was strongly correlated negatively with silt content (p < 0.01) and positively with sand content (p < 0.01). The results indicate that D can be a potential indicator of the physical and chemical properties of soil and can also provide a theoretical basis and technical guidance for the effective use and management of the region.     

Modeling and mapping of solar radiation using geostatistical analysis methods in Iran

Because of economic and technical limitations, measuring solar energy received at ground level (R _s ) isn’t possible in all parts of the country, and in only 12% of synoptic stations is this parameter measured and recorded. Thus, it should be estimated and modeled spatially based on other climatic variables using mathematical methods. In this research, many attempts have been made to introduce an air temperature-based model for Rs estimation, and then, based on the output of the mentioned models, several geostatistical methods have been tested, and finally an elegant spatial model is proposed for (Rs) zoning in Iran. In this regard, the relationships between the measured amounts of monthly solar radiation and other climatic parameters, such as a monthly average, maximum and minimum temperature, precipitation, relative humidity, and the number of sunny hours during the period 1970–2010, are examined and modeled. It was revealed that based on the linear relationship between the monthly average air temperatures and solar radiation values recorded in each of the stations, that the best-fit linear model, with R ²  = 0.822, MAE = 1.81, RMSE = 2.51%, and MAPE = 10.08, can be introduced for Rs estimation. Then, using the outputs of the proposed model, the amounts of (R _s ) are estimated in another 171 meteorological stations (a total of 192 stations), and eight geostatistical methods (IDW, GPI, RBF, LPI, OK, SK, UK, and EBK) were investigated for zoning. Comparing the resulting variograms showed that in addition to proof of spatial correlation between solar radiation data, they can be applied for modeling changes in various directions. Analyzing the ratio of the nugget effect on the roof of the variograms showed that the Gaussian model with the lowest ratio (Co/Co + C = 0.883) and (R ²  = 0.972), could model the highest correlation between the data and, therefore, it was used for data interpolation. To select the best geostatistical model, R2, MAE, and RMSE were used. On this basis, it was found that the RBF method with R ²  = 0.904, MAE = 3.02, RMSE = 0.39% is the most effective. Also, the IDW method with R ²  = 0.90, MAE = 3.08, RMSE = 0.391%, compared to other methods is the most effective. In addition, for data validation, correlations between observed and estimated values of solar radiation were studied and found R ²  = 0.86.     

Estimating groundwater evapotranspiration rates using diurnal water-table fluctuations in a semi-arid riparian zone

In semi-arid climates, phreatophytes draw on shallow aquifers, and groundwater evapotranspiration (ET_G) is a principal component of groundwater budgets. Diurnal water table fluctuations, which often are a product of ET_G, were monitored in the riparian zone of Red Canyon Creek, Wyoming, USA. These fluctuations were higher in a riparian wetland (2–36 mm) than a grass-covered meadow (1–6 mm). The onset and cessation of water-table fluctuations correspond to daily temperatures relative to freezing. Spatial differences were due to vegetation type and specific yield, while temporal changes were due to vegetation dormancy. Ratios of ET_G to potential evapotranspiration (PET), K _c,GW, were similar to ratios of actual evapotranspiration (ET) to PET, K _c, in semi-arid rangelands. Before vegetation senescence, K _c,GW increased between precipitation events, suggesting phreatophytes pull more water from the saturated zone as soil moisture decreases. In contrast, K _c decreases with soil moisture following precipitation events as ET becomes increasingly water-limited. Error in ET_G is primarily from estimates of specific yield (S _y), which is difficult to quantify in heterogeneous sediments. ET_G values may be more reliable because the range of acceptable S _y is smaller than K _c and S _y does not change with vegetation type or soil moisture.     

Evidence for shock generation in the solar corona in the absence of coronal mass ejections

The solar event SOL2012–10–23T03:13, which was associated with a X1.8 flare without an accompanying coronal mass ejection (CME) and with a Type II radio burst, is analyzed. A method for constructing the spatial and temporal profiles of the difference brightness detected in the AIA/SDOUVand EUV channels is used together with the analysis of the Type II radio burst. The formation and propagation of a region of compression preceded by a collisional shock detected at distances R < 1.3R _⊙ from the center of the Sun is observed in this event (R _⊙ is the solar radius). Comparison with a similar event studied earlier, SOL2011–02–28T07:34 [1], suggests that the region of compression and shock could be due to a transient (impulsive) action exerted on the surrounding plasma by an eruptive, high-temperature magnetic rope. The initial instability and eruption of this rope could be initiated by emerging magnetic flux, and its heating from magnetic reconnection. The cessation of the eruption of the rope could result from its interaction with surrounding magnetic structures (coronal loops).     

Fluid–rock interaction during seprentinization of oceanic ultramafic rocks hosting the Lost City hydrothermal field, 30° N,MAR

The estimation of the fluid/rock (W/R) ratio during serpentinization on the basis of oxygen isotope characteristics is peculiar, because this process is accompanied by not only changes in the stoichiometric proportions of oxygen in fluid and rock, but also by the formation of associated minerals. These factors should be taken into account for environments when the volume of aqueous fluid is limited, for instance, for serpentinization of the deep-seated rocks of oceanic lithosphere under low spreading rates. We studied isotope characteristics of samples collected in dives of submersible MIR during Cruise 50 of the R/V Akademik Mstislav Keldysh along vertical profile on the southern slope of the Atlantis Massif, which hosts the Lost City hydrothermal field. Almost all studied serpentinites have homogenous strontium isotope composition corresponding to the composition of the modern seawater. Oxygen isotope composition of these serpentinites shows systematic variations from 2. 6 to 6.1‰ with sampling depth, which indicates the preservation of stratigraphic position of samples in the sequence of the Atlantis Massif and the global serpentinization of the entire plutonic sequence. The value of the fluid–rock ratio during serpentinization in a system closed to fluid was estimated using the dissolution–crystallization model. This model takes into account the variable stoichiometry of oxygen and the effect of the simultaneous crystallization of brucite on the oxygen isotope composition of newly formed serpentine. The results show that at moderately elevated temperatures (≈300°C) and 0.1 < W/R < 5, fluid, crystallizing serpentine, and brucite are characterized by sharp variations in oxygen isotope composition: 1.3–7.8, 2.5–8.9, and 4.5–1.9‰, respectively. The model explains the observed range of δ¹⁸O in the serpentinized harzburgites of the Atlantis Massif. According to our estimates, the rocks of the studied sequence of the Atlantis Massif were serpentinized at 270–350°C and W/R = 0.7–3. For lower temperature serpentinization, for instance, at T = 250°C, the W/R ratio can be as high as 6. The present-day serpentinization of the deepseated zones of the Atlantis Massif with the Lost City fluid participance proceeds at T > 270°C and W/R ratio <1. These conditions are similar to those of serpentinization of harzburgites from the lower parts of the studied sequence of the Atlantis Massif.     

Satellite evidence for no change in terrestrial latent heat flux in the Three-River Headwaters region of China over the past three decades

Terrestrial latent heat flux (LE) in the Three-River Headwaters region (TRHR) of China plays an essential role in quantifying the amount of water evaporation and carbon sink over the high altitude Tibetan Plateau (TP). Global warming is expected to accelerate terrestrial hydrological cycle and to increase evaporation. However, direct field observations are lacking in this region and the long-term variability in LE remains uncertain. In this study, we have revised a semi-empirical Penman LE algorithm based on ground eddy covariance (EC) observations from an alpine grass site and provided new satellite-based evidence to assess LE change in the TRHR during 1982–2010. Our results show that the average annual terrestrial LE in the TRHR is about 38.8 W/m ² and there is no statistically significant change in annual LE from 1982 to 2010. We also found that during the same time period, terrestrial LE over the east region of the TRHR significantly decreased, on average, by 0.7 W/m ² per decade, which was driven primarily by the surface incident solar radiation (R_s) limitation, offsetting the increased LE over the west region of the TRHR caused by the increased precipitation (P) and soil moisture (SM).     

Influence of physico-chemical components on the consolidation behavior of soft kaolinites

Pore solution salinity has important bearing on engineering behavior of marine sediments as they influence electrochemical stress (A–R) and differential osmotic stress (?π) of the salt-enriched clays. The electrochemical stress (A–R) is contributed by van der Waals (A) attraction and diffuse ion layer repulsion (R), while the differential osmotic stress (?π) is governed by the differences in dissolved salt concentrations in solutions separated by osmotic membrane. The paper examines the relative influence of differential osmotic stress (Δπ) and electrochemical stress (A–R) on the consolidation behavior of slurry consolidated kaolinite specimens, which are known to be encountered in recent alluvial marine sediments. Methods are described to evaluate the magnitudes of these physico-chemical components and their incorporation in true effective stress. Results of the study demonstrate that differential osmotic stress finitely contributes to true effective stress. The contribution from differential osmotic stress enables kaolinite specimens to sustain larger void ratio during consolidation.     

Assessing the vegetation canopy influences on wind flow using wind tunnel experiments with artificial plants

Wind erosion causes serious problems and considerable threat in most regions of the world. Vegetation on the ground has an important role in controlling wind erosion by covering soil surface and absorbing wind momentum. A set of wind tunnel experiments was performed to quantitatively examine the effect of canopy structure on wind movement. Artificial plastic vegetations with different porosity and canopy shape were introduced as the model canopy. Normalized roughness length (Z ₀/H) and shear velocity ratio (R) were analyzed as a function of roughness density (λ). Experiments showed that Z ₀/H increases and R decreases as λ reaches a maximum value, λ _max, while the values of Z ₀/H and R showed little change with λ value beyond as λ _max.     

Simulating climate change impact on soil erosion using RUSLE model <Emphasis Type="BoldItalic">−</Emphasis> A case study in a watershed of mid-Himalayan landscape

Climate change, particularly due to the changed precipitation trend, can have a severe impact on soil erosion. The effect is more pronounced on the higher slopes of the Himalayan region. The goal of this study was to estimate the impact of climate change on soil erosion in a watershed of the Himalayan region using RUSLE model. The GCM (general circulation model) derived emission scenarios (HadCM3 A2a and B2a SRES) were used for climate projection. The statistical downscaling model (SDSM) was used to downscale the precipitation for three future periods, 2011–2040, 2041–2070, and 2071–2099, at large scale. Rainfall erosivity (R) was calculated for future periods using the SDSM downscaled precipitation data. ASTER digital elevation model (DEM) and Indian Remote Sensing data – IRS LISS IV satellite data were used to generate the spatial input parameters required by RUSLE model. A digital soil-landscape map was prepared to generate spatially distributed soil erodibility (K) factor map of the watershed. Topographic factors, slope length (L) and steepness (S) were derived from DEM. Normalised difference vegetation index (NDVI) derived from the satellite data was used to represent spatial variation vegetation density and condition under various land use/land cover. This variation was used to represent spatial vegetation cover factor. Analysis revealed that the average annual soil loss may increase by 28.38, 25.64 and 20.33% in the 2020s, 2050s and 2080s, respectively under A2 scenario, while under B2 scenario, it may increase by 27.06, 25.31 and 23.38% in the 2020s, 2050s and 2080s, respectively, from the base period (1985–2013). The study provides a comprehensive understanding of the possible future scenario of soil erosion in the mid-Himalaya for scientists and policy makers.     

Predicting saturated hydraulic conductivity using particle swarm optimization and genetic algorithm

Soil saturated hydraulic conductivity (K_s) is considered as soil basic hydraulic property, and its precision estimation is a key element in modeling water flow and solute transport processes both in the saturated and vadose zones. Although some predictive methods (e.g., pedotransfer functions, PTFs) have been proposed to indirectly predict K_s, the accuracy of these methods still needs to be improved. In this study, some easily available soil properties (e.g., particle size distribution, organic carbon, calcium carbonate content, electrical conductivity, and soil bulk density) are employed as input variables to predict K_s using a fuzzy inference system (FIS) trained by two different optimization techniques: particle swarm optimization (PSO) and genetic algorithm (GA). To verify the derived FIS, 113 soil samples were taken, and their required physical properties were measured (113 sample points?×?7 factors?=?791 input data). The initial FIS is compared with two methods: FIS trained by PSO (PSO-FIS) and FIS trained by GA (GA-FIS). Based on experimental results, all three methods are compared according to some evaluation criteria including correlation coefficient (r), modeling efficiency (EF), coefficient of determination (CD), root mean square error (RMSE), and maximum error (ME) statistics. The results showed that the PSO-FIS model achieved a higher level of modeling efficiency and coefficient of determination (R²) in comparison with the initial FIS and the GA-FIS model. EF and R² values obtained by the developed PSO-FIS model were 0.69 and 0.72, whereas they were 0.63 and 0.54 for the GA-FIS model. Moreover, the results of ME and RMSE indices showed that the PSO-FIS model can estimate soil saturated hydraulic conductivity more accurate than the GA-FIS model with ME?=?10.4 versus 11.5 and RMSE?=?5.2 versus 5.5 for PSO-FIS and GA-FIS, respectively.     

Accuracy assessment of near-shore bathymetry information retrieved from Landsat-8 imagery

The improvement in the capabilities of Landsat-8 imagery to retrieve bathymetric information in shallow coastal waters was examined. Landsat-8 images have an additional band named coastal/aerosol, Band 1: 435–451 nm in comparison with former generation of Landsat imagery. The selected Landsat-8 operational land image (OLI) was of Chabahar Bay, located in the southern part of Iran (acquired on February 22, 2014 in calm weather and relatively low turbidity). Accurate and high resolution bathymetric data from the study area, produced by field surveys using a single beam echo-sounder, were selected for calibrating the models and validating the results. Three methods, including traditional linear and ratio transform techniques, as well as a novel proposed integrated method, were used to determine depth values. All possible combinations of the three bands [coastal/aerosol (CB), blue (B), and green (G)] have been considered (11 options) using the traditional linear and ratio transform techniques, together with five model options for the integrated method. The accuracy of each model was assessed by comparing the determined bathymetric information with field measured values. The standard error of the estimates, correlation coefficients (R ² ) for both calibration and validation points, and root mean square errors (RMSE) were calculated for all cases. When compared with the ratio transform method, the method employing linear transformation with a combination of CB, B, and G bands yielded more accurate results (standard error = 1.712 m, R ² _calibration = 0.594, R ² _validation = 0.551, and RMSE =1.80 m). Adding the CB band to the ratio transform methodology also dramatically increased the accuracy of the estimated depths, whereas this increment was not statistically significant when using the linear transform methodology. The integrated transform method in form of Depth = b ₀  + b ₁ X _CB  + b ₂ X _B  + b ₅ ln(R _CB )/ln(R _G ) + b ₆ ln(R _B )/ln(R _G ) yielded the highest accuracy (standard error = 1.634 m, R ² _calibration = 0.634, R ² _validation = 0.595, and RMSE = 1.71 m), where R _i (i = CB, B, or G) refers to atmospherically corrected reflectance values in the i ^th band [X _i  = ln(R _i -R _{deep water})].