فصلنامه حفاظت منابع آب و خاک
سال سیزدهم شماره 2 (پیاپی 50، زمستان 1402)

Adding organic matter to the soil is an important method to solve the problem of compaction and consequently penetration resistance and fertility reduction. Mushroom substrate compost (MSC) has many properties that are required for growing organic crops and environmental management. Considering that the ingredients of mushroom substrate compost (including heavy soil, light soil, root soil, wheat straw and stubble, limestone and chicken manure) are different from other types of organic materials, it is necessary to carry out new research to investigate its effect on the physico-chemical properties of the soil. Although different textures behave differently but, the effect of MSC on the penetration resistance and aggregates size distribution in different soils, has not been studied, so far. Therefore, the purpose of this study was to investigate the short-term effect of MSC on the penetration resistance, mean weight diameter of aggregates, aggregates size distribution and organic matter content in three soil types.

A factorial experiment was conducted in a completely randomized design with three replications. Factors consist Soil texture at three levels (sandy loam, loam and clay) was the first factor, and MSC at three levels (0, 3 and 6% W/W) was the second factor. After treatment of the soils, samples were then incubated for 120 days, and they were saturated and dried with urban water, regularly, once a month (saturated from above), during this period. At the end of the incubation period, disturbed and undisturbed soil samples were taken by 5 cm in diameter and 4.5 cm in height steal cylinders. The penetration resistance was measured by a micro-penetrometer on the core samples at the matric suction of 0.3 bar. Organic matter, mean weight diameter of aggregates and aggregates size distribution were measured.

The results showed that the use of 6% level mushroom substrate compost in the sandy loam soil caused a decrease in the penetration resistance compared to the level of 3% and the control, due to the interaction between the compounds in the compost and the creation of stable soil aggregates. Also, the results showed that highest amount of organic matter and mean weight diameter of aggregates at 6% level of MSC was found in loam texture. Also, the order of the mass of aggregates in classes 4-8 and 2-4 mm, was in loam> sandy loam> clay, with significant differences between the textures. Application of MSC at 3 and 6% levels in the loam texture significantly increased the mass of aggregates of 0.25 – 0.5 and 0.5-1 mm in comparison with control. These aggregates did not show significant differences in sandy loam and clay soils at different application levels of the MSC Organic matter, mean weight diameter of aggregates, mass of aggregates of 0.5 to 1, and 0.25 to 0.5 mm increased in the range of 27 to 66%, 16 to 34.5%, 4 to 117.5% and 4 to 170%, respectively, by increasing MSC application levels at different soils. Conclusion This compost is different from other modifiers and can have different effective mechanisms in different textures. The simultaneous addition of lime, clay and organic matter (through compost) to soils with different textures causes cation exchange reactions in the soil. Lime as one of the main additives that has the ability to improve the behavior of fine-grained soils has been noticed for a long time. In this way, in clay and loam soils, the interaction between lime and clay with organic matter plays an important role as soil accumulation factors by forming cationic bridges. The use of lime and gypsum directly improve soil resistance. Therefore, the use of mushroom substrate compost in agricultural lands is useful for improving the soil structure.

Estimation and forecasting of qualitative parameters along with quantitative parameters of water alongside the river to make correct managerial decisions is one of the objectives of managers and planners of the water industry should be accurately simulated. Most of the models for qualitative parameter estimations require very large input parameters that are either difficult to access or require much time and money to determine. Therefore, the use of data-driven models in this field has been developed to save time and money.

In this paper, the application of artificial neural networks and its combination with the firefly algorithm to predict the amount of Total dissolved solids (TDS) of water in the Gavehrood River located in Iran, Kermanshah has been trained and validated. with this purpose, water quality data of hydrometric station upstream of the Gavoshan reservoir dam are used for the statistical period (1991-2010). Based on different inputs, the multilayer perceptron (MLP) artificial neural network and its combination with the firefly algorithm are tested. The best algorithm of the inputs, the number of hidden layers and the number of neurons in each layer in the artificial neural network are determined. The input data imported to the models include the flow rate (Q), Sodium (Na), Magnesium (Mg), Calcium (Ca), Sulfate (So4), Chloride (Cl), Bicarbonate (Ho3), Electrical conductivity (EC) and Total Dissolved Solides of the river in the previous period (TDSt-1) and the output data of TDS. The number of hidden layers is obtained to be 1 and the number of hidden layer neurons is achieved to be 9. Also, the neural network function in this study is considered as a waterfall type and the results are compared by combining artificial neural networks with the firefly algorithm. The model outputs are compared with measurement data using the error measurement criteria.

In this regard, the values of the used error evaluation indices including the observed standard deviation (RSR), Nash Sutcliffe coefficient (NSC), correlation coefficient (R) and root mean square error (MSE) for artificial neural network are yielded 0.154, 0.976, 0.989 and 25.27, respectively and in the case of the neural network combination with the firefly algorithm, are achieved to be 0.129, 0.983, 0.992 and 17.8, respectively.

Therefore, the performance of the hybrid method of artificial neural networks by using the firefly algorithm in predicting TDS is more appropriate than artificial neural networks.

Puddling process is a part of land preparation in rice cultivation. In other words, puddling is an important method of soil management, which is done to disturb the structure of the surface layer of the soil and prepare the field for rice transplanting. Usually, in this process, the soil is flooded and tillage is done on it. The soil texture and the soil moisture conditions before flooding are factors that affect the process of the puddling. Therefore, this study was conducted to determine the effect of initial soil moisture and soil texture on some properties of paddy soils puddling process in Guilan province.

The experiment was conducted as a factorial based on a randomized complete block design in three replications. Three textures (silt, silty clay, and clay) of paddy soils were prepared under four initial soil moisture treatments (85, 90, 95, and 100% degrees of saturation). After preparing the soil samples, they were puddled using a laboratory panel. During and after the puddling process, the amount of net water consumed, the depth of water collected on the soil 2 and 6 days after puddling, the soil swelling at the end of the operation, the depth of soil settlement after 2, 4 and 6 days and the final depth of the soil were measured. Statistical analysis of the effect of the experimental treatments on the measured properties and their mean comparison was done with LSD test using SPSS 23 software. Calculations and graphs were done using EXCEL software.

The results showed that the independent effects of initial soil moisture and soil texture on all of the measured properties except the depth of soil after 6 days were statistically significant at 1%. With increasing initial soil moisture, the amount of net water consumption and the final depth of soil decreased and other measured parameters increased. On the other hand, the effect of soil texture on net water consumption, water collected on the soil 2 and 6 days after puddling, soil amass at the end of the operation, depth of soil after 2 and 4 days, and the final depth of the soil were statistically significant at 1%. The interaction effect of initial soil moisture and soil texture on soil amass at the end of the operation and final soil depth was statistically significant at 1%, and for the depth of water accumulated on the soil 2 days after puddling and the depth of soil after 2 days was statistically significant at 5%. By increasing the initial soil moisture content from 85 to 100% of saturation degree, the amount of water used for the puddling process decreased by 61%.

According to the results, the features of the puddling process are affected by the initial moisture and soil texture. Therefore, the results of this research can be used in the agricultural management of paddy fields in Guilan province. With increasing soil clay content, the measured parameters include the amount of net water consumed, the depth of water collected on the soil 2 and 6 days after puddling, the soil swelling at the end of the operation, the depth of soil settlement after 2, 4 and 6 days and the final depth of the soil were increased. The range of net water consumed in the puddling process for experimental treatments varied between 31 and 114 mm, and the lowest was obtained in silty soil texture with 20% clay and initial moisture treatment of 100% degree of saturation. Estimating water consumption in the puddling process and its correlation with initial soil moisture and clay percentage can inform the management of the agricultural calendar and water allocation program in the Sefidroud irrigation network for paddy fields. This information can help optimize water usage, especially in light of rainfall events at the start of the irrigation season, with the goal of reducing overall water consumption.

Heavy and consecutive rains at early April of 2018 led to severe floods in large parts of Iran, especially in the Karkheh basin, which was accompanied by huge damages. The average rainfall in the Karkhe dam basin for the event of April 4-7, 2018 was about 87 mm, and for the event of April 11-17, 2018, it was nearly 108 mm. For the flood management by the reservoir, estimation of the peak discharge and flood hydrograph is essential in order to predict the hydrological behavior of the basin. Rainfall-runoff models that are used to simulate flood hydrographs are one of the methods of estimating runoff and a suitable tool for investigating and evaluating hydrological processes, water resources, and flood management.

Since the estimation of peak discharge and flood hydrograph has great important to predict the hydrological behavior of the basin and also to take the necessary measures to reduce the flood risk, the present study was conducted by using HEC-HMS model to simulate the rainfall-runoff events during 2007-2018 in the Karkheh Basin .By using this model capabilities and the data from some hydrometric and meteorological stations in the basin, the volume and peak discharge of floods in that period were estimated. Because Seymareh dam impoundment has started since 2013; two separate basin models were developed and for running the model, 11 flood events were obtained then, the basin parameters were calibrated based on six events and the others were used for validation. In the process of developing the basin model, the SCS Curve Number method is used to calculate basin runoff losses and convert rainfall to runoff, the Clark Unit Hydrograph method and the Return flow method to calculate the base flow, the Muskingum method for hydrological routing, and the Weighted average method for spatial data analysis of rainfall. The Outlet Structure method was used for routing the reservoirs of Karkheh and Seymareh dams.

Comparing the initial simulation results of the model with the observed values at the outlet of the basin and some hydrometric stations of the basin showed that the hydrograph model overestimates the flow. Therefore, using the residual squaredsum objective function, basin parameters (CN, time concentration, storage coefficient, initial absorption, and recession constant) were calibrated. After calibration of parameters, the results showed that the calculated hydrographs were in good agreement with the Observational hydrographs in the Karkheh and Seymareh dams. Next, to check the accuracy and confirm the results, the model was validated by the five new rainfall events and to evaluate the efficiency of the model used in this stage, the Nash-Sutcliffe indices and the simulated variance coefficient were used.

Comparing the calculated results with the flood observational values (peak discharge) using the correlation coefficient (R2) showed that there is a relatively good agreement between simulation and observation in sub-basins 5, 2, 7, and 1 (0.92, 0.73, 0.73 and 0.70, respectively). Also, the model efficiency index values in the validation period for the Nash-Sutcliffe index (0.33-0.99) and simulation variance coefficient (0-0.73) for the outlet of sub-basins 9, 6, 5, 1, and 8 are favorable and the HEC-HMS model approximately can provide an acceptable estimation of the flood hydrograph. So, it can be well-analyzed how the way flood events are formed in the Karkheh basin. Also, the sensitivity analysis of the model parameters showed that the curve number parameter (CN) has a greater effect on the changes in the objective function than other basin parameters.

Due to the sharp decline of the underground water in the country's plains due to their indiscriminate extraction for agricultural purposes, managers are looking for solutions to manage and restore underground water tables. One of the solutions to compensate for the drop in the underground water level, which is one of the most effective factors in destroying the discharge capacity and increasing the quality in the underground water area, scenarios of reducing withdrawal of farming wells and prepare prohibition plans with the least uncertainty based on the regional sensitivity to pollution. The purpose of this research is to predict the flow and pollution conditions of the area based on numerical models, so that the level network and the direction of the underground water flow of the plain using MODFLOW software in a long-term period and the development of the prediction model using Calibration and validation operations should be performed on the base period of the studies in order to be able to implement the forecast scenarios by applying restrictions and reducing harvesting on aquifer exploitation resources, and specifically agricultural wells, until the stage of stable hydrograph extraction of the plain.

This research was carried out with the aim of estimating and predicting the state of pollution in the urban pollution site, using MODFLOW and MODPATH computer programs in GMS software. To achieve this goal, in the first step, the numerical model of the aquifer flow was prepared and calibrated by the MODFLOW code. Then, the MODPATH code was used to track the contaminated particles in the steady-state progressive method. In the second stage, the impact of the scenario of increasing and decreasing the pumping from the exploitation wells on the travel time, the length of the path and the catchment area of the leachate particles leading to them was predicted and evaluated by the regressive method. In the third step, the tracking of particles leading to qualitative sampling wells in the plain was predicted and evaluated by regressive method in steady state.

According to the automatic calibration and validation approach, the underground water flow model produced the least statistical deviation on the optimization parameters. Also, the particle transfer quality model was correctly implemented on the groundwater flow prediction model. In the Babol aquifer, the waste disposal area outside the designated aquifer is saturated. It was observed that, by adjusting the parameters of the simulation of the transfer of residual pollution cloud particles, an estimate of the concentration was applied to the permeable boundaries and the channel network. This means that in the simulation of particle transport, here the source of pollution spread is the channel network and permeable boundaries, which will be directly affected by pollution during periods of rainfall and especially floods. The concentration limit was given to the model in the form of variable figures based on discharge and precipitation in the range and equal to the primary stable threshold of the research subject (landfill). Based on the cumulative diagram of the outlet concentration from the permeable boundary and flow channel in the southeast region, the trend of changes in the cloud pollution concentration diagram, in the qualitative modeling of the plain, shows that in the forecast period, the increase in concentration will increase linearly. Considering that the waste disposal location is outside the plain, the rate of increase in pollution was not very high until the end of the initial simulation. However, the reason for the increase in concentration accumulation volume can be related to the existence of permeable boundaries and severe drop of underground water in this area. In other words, when the underground water level drops too much in the saturation area of the plain, the direction of the flow will move the volume of polluted water towards the aquifer at a higher speed.

If the situation of groundwater withdrawals continues in the same way, in addition to the reduction of the groundwater storage of the plain, the quality of the remaining water storage will also decrease. This causes more serious problems in the agricultural situation of the region. The results of the implementation of quantitative and qualitative model in order to investigate the infiltration of polluted water from the landfill based on the concentration of pollution, showed that there is a high probability of the infiltration of polluted particles from the south wall side to the aquifer during periods of rainfall Event that current is run in the channels accidently. and then the expansion to the sea will actually occur due to the drop in the water level of the Caspian Sea. Water infiltration is more likely in the eastern regions than in the western regions. The reason for choosing the spread of pollution from the eastern waste disposal site in order to show the accumulation of polluted particles and the repulsion from the sea was the same. It is suggested that in the field of policy making, in order to control the plain's leachate crisis, appropriate bed construction and walling of the waste accumulation area should be applied based on the flow direction.

In recent years, some farmers in the plains of Saman in the province of Chaharmahal and Bakhtiari have changed the use of almond orchards in this area to agricultural land and pastures in order to provide food and fodder. Since these activities are mostly carried out without sufficient knowledge of the soil environment, there can be a serious threat to reduce soil quality. Therefore, studies on the effect of different managements on different soil characteristics and in the direction of a sustainable soil resource are very important. In this research, the effect of land use change in these areas on some physical and chemical indicators of soil quality was investigated.

In order to investigate the effect of land use change on some physical and chemical indicators of the soil quality of three land use systems comprising a permanent almond orchard, permanent pasture and almond orchard converted to land were selected in the plain of Saman. 15 samples of soil (45 samples in total) were taken from 0 to 30 cm in the form of networks (30 x 30 meters) in each of the three land use systems considered. Some physical and chemical parameters of studied soil samples measured by standard methods.After collecting and saving data in Excel, a one-side analysis of variance (ANOVA) was performed on using the SPSS18 software and the comparison of the means was also carried out on the basis of the LSD test at a probability level of 1%.

The results of analysis of variance data showed that changing land use (changing of almond orchards to agricultural land) had significant effect on the indeces examined physical and chemical of at 0.01 level. The Land use change did not change the surface soil texture of the study areas. The soil texture of all three-study system was almost the same (clay loam inclined to sandy clay loam). According to the findings of the mean comparison, when almond orchards were converted to agricultural land, there was a significant reduction in total porosity, mean weighted diameter of soil aggregates (MWD), base infiltration rate, and soil organic carbon by 12%, 56%, 50%, and 54%, respectively. Conversely, there was a notable increase of 10%, 5%, 44%, and 18% in bulk density, pH, electrical conductivity, and soil lime percentage at a significance level of 0.01 (pr<0.01).In this study, substituting improved pasture plants with land grazed pasture significantly augmented the average of soil organic carbon, total porosity, solidity of soil aggregates (MWD) and base infiltration rate by 48%, 14%, 69%, and 40%, respectively, as compared to agricultural land at a significance level of 0.01 (pr<0.01). However, no significant difference was observed at a significance level of 0.01 (pr>0.01) between almond orchard and pasture land concerning the evaluated indicators.

Overall, the parameters analyzed indicate that organic carbon, mean weighted diameter of soil aggregates (MWD), and bulk density are reliable indicators of soil quality in the study area. The average values of these indicators provide an optimal alternative for management and tillage practices in various land uses. Moreover, due to the delicate and vulnerable ecosystems of Saman Plain, it is recommended to avoid converting garden lands (such as almond orchards) into agricultural lands within the study area. This approach will help prevent soil erosion in one of the most sensitive areas of the country.

Because of its high specific surface area and high cation exchange capacity (CEC), as well as its availability and low price, sodium montmorillonite (Mt) is used as an adsorbent for a wide range of pollutants, including heavy metals and organic compounds; but the structure of this type of natural clay, however, is unstable, and usually damaged by harmful substances of sewage liquid in the process of infiltration. The organic surfactant hexadecyltrimethylammonium bromide (HDTMA) was used to modify montmorillonite clay to solve this problem. The next step was to investigate lead removal using modified montmorillonite clay (Mt-H).

In this study, sodium montmorillonite organic clays modified with hexadecyltrimethylammonium bromide with a CEC two times greater than clay (Mt-H) were prepared. These modified clays were identified using X-ray diffraction, Fourier transform infrared spectroscopy, and field emission scanning electron microscopy. The effect of initial lead concentration on lead absorption from aqueous solution by two adsorbents (montmorillonite clay and modified montmorillonite clay) was investigated. The lead adsorption process was studied using Langmuir and Freundlich adsorption isotherm models. The mechanisms of lead adsorption were investigated and compared using pseudo-first-order, pseudo-second-order, Elovich, and intraparticle diffusion models.

The results showed that the organic surfactant hexadecyltrimethylammonium bromide (Mt-H) successfully modified montmorillonite clay, and the interlayer space of the first order peak in montmorillonite clay increased from 11 to 19.7 Å after modification. According to the findings of this study, increasing the initial concentration of lead increased the amount of lead absorption (Qi) in both adsorbents, sodium montmorillonite clay (Mt) and modified montmorillonite clay (Mt-H). Surface adsorption of lead in montmorillonite clay (Mt) with the Langmuir model and surface adsorption in modified montmorillonite clay (MtH) with the Freundlich model both showed good agreement with experimental data. According to the results, montmorillonite clay (Mt) absorbed approximately 40% of the lead ions in the first 80 minutes of the reaction, but surface absorption of lead by modified montmorillonite clay (Mt-H) reached approximately 40% after 1280 minutes. The maximum monolayer absorption capacity calculated from the Langmuir model at 30°C in modified montmorillonite clay (Mt-H) was 32.54 mg/g, which was approximately 34% lower than the value obtained in montmorillonite clay (Mt). Surface adsorption in montmorillonite clay (Mt) showed the best fit with the Elovich kinetic model, but modified montmorillonite clay (Mt-H) showed the best fit with the intraparticle diffusion kinetic model.

The results showed that adding hexadecyltrimethylammonium organic surfactant to sodium montmorillonite clay reduced its lead adsorption capacity. However, the lead in the modified clay (Mt-H) was more stable

Ecosystems nowadays play a unique role in meeting human demands and offering a variety of services to their stakeholders. However, occurrence of various happening, including population increase and rising demand for basic human requirements, have created problems for Ecosystem Services (ES). As a result, land degradation is a significant environmental issue that is impacted by a variety of elements and factors. Soil conservation and erosion prevention can benefit from management and conservation measures, as well as the development of plant cover in a watershed. Therefore, an effort has been made in this study to assess how the Sharghong Watershed in Southern Khorasan, Iran, and its biological and management activities affect soil erosion at various rainfall intensities.

The Sharghong Watershed, with an area of 94.87 km2 , is located in Birjand Township, South Khorasan Province, Iran. The mean annual precipitation in the watershed is approximately 210 mm. Due to its steep slopes in the eastern and southeastern parts, the presence of residential areas and barberry orchards in the floodplain, and intense precipitation in the spring, the Sharghong Watershed has a good potential for flooding. for evaluating. The role of biological restoration operations in soil erosion processes in study watershed InVEST Model was used. Annual precipitation data from the Qaen, Birjand, Mousavieh, and Mansourabad stations were utilized for the period between 2002 and 2020, with return periods of 2, 5, 10, and 50 years, to generate the inputs for the InVEST model. The erosivity, erodibility, crop management and land maintenance factor were then determined.

The maximum rainfall erosivity index (R) values for return periods of 2, 5, 10, and 50 years were 47.08, 63.68, 85.01, and 98.94 MJ mm ha-1 h -1 , respectively. The minimum values of R for the same return periods were 42.88, 56.68, 74.47, and 85.85 MJ mm ha-1 h -1 , respectively. The annual sediment yield for return periods of 2, 5, 10, and 50 years were 6699.27, 9024.56, 17452.27, and 20862.30 t, respectively. Following the implementation of the management scenario in different sub-watersheds, sediment yield reached 6439.39, 8668.37, 16892.94, and 17390.87 t, respectively. The obtained results indicated reductions of 3.9, 3.9, 3.2, and 1.7%, respectively, for return periods of 2, 5, 10, and 50 years.

In this research, the role of biological management in controlling erosion and sedimentation in the Sharghonj Watershed during the different return periods of rainfall has been evaluated. The results of the research indicate that with the increase in the intensity of rainfall, in the current land use, the amount of erosion and sedimentation has increased, but with the application of management scenarios at the level of different sub-catchment, erosion and sedimentation has slightly decreased during the different return periods of rainfall. Due to the fact that the intensity of rainfall in the region plays an important role in creating erosion and its effect is intensified by the combination of sloping lands, the principled use of land in accordance with its potential can play an effective role in preventing land degradation. Therefore, the approaches of this research can be beneficial for providing a suitable management model for managers, operators and beneficiaries of watersheds.

The scarcity of data poses a significant challenge for drought studies. Alternative datasets are created to supplement existing data sources. Despite the inherent uncertainties associated with alternative datasets, the gridded datasets provide long-term, spatially-continuous weather data, making them suitable for drought assessment under climate changes. Several studies have been conducted to characterize dry spells across Iran using both point datasets and gridded products. However, most of these studies have focused primarily on identifying errors in absolute values of drought indices and drought detection

In the present study, we evaluated the performance of three gridded datasets in characterizing droughts across different climatic conditions in Iran. The datasets under consideration were the fifth generation of the European Centre for Medium-Range Weather Forecasts (ERA5), Climate Hazards Group InfraRed Precipitation with Station data (CHIRPS), and Precipitation Estimation from Remotely Sensed Information using Artificial Neural Networks-Climate Data Record (PERSIANN-CDR). The Standardized Precipitation Index in 3-, 6-, and 12- month scales (i.e., SPI3, SPI6, and SPI12) was applied. The precipitation observations were obtained from the Iran Meteorological Organization (IRIMO) for 35 sites spanning the period from 1988 to 2017. The study sites covered a range of climatic conditions, including hyper-arid, arid, semi-arid, and humid/semihumid regions. To analyze the long-term trend in precipitation, two statistical methods, namely, the Sen’s slope estimator (SSE) and the Mann-Kendall nonparametric test (MKZ) were employed

Results revealed that the gridded datasets performed poorly in detecting dry months and estimating SPI values in humid/semi-humid regions. However, ERA5 estimated SPI3, SPI6, and SPI12 with sufficient accuracy in more than the two-third of arid and semi-arid areas. Moreover, ERA5 detected dry months accurately based on SPI12 in the majority of arid and semi-arid cases. Specifically, ERA5 accurately detected severe and long-lasting dry events that occurred in drylands during the periods of 1998-2001 and 2007-2009. These intense dry epochs detected by ERA5 have had significant negative impacts on the agricultural sectors in the Middle East, highlighting the critical need for accurate drought monitoring and management. However, CHIRPS and PERSIANN-CDR performed poorly in estimating SPI and detecting dry months in arid and semi-arid regions. Furthermore, ERA5 provided reliable estimates of the significance and direction of the slope of SPI3, SPI6, and SPI12 in more than half of arid and semi-arid regions, while CHIRPS and PERSIANN-CDR yielded inaccurate estimates in most areas. However, in some cases where SPI values and drought months were not accurately modeled, the significance and direction of slopes were estimated accurately. These findings suggest that while inaccurate SPI estimates from gridded datasets may indicate limitations in their skill to characterize drought; they do not necessarily imply their unsuitability for trend analysis and climate change assessments.

The results suggest that ERA5 outperformed the other alternate datasets evaluated in terms of estimating SPI values, detecting drought events, and estimating the significance and slope of SPI in drylands. As such, ERA5 precipitation products may be suitable for drought characterization and monitoring under climate change in drought-prone arid and semi-arid regions of Iran

The particle-size distribution (PSD) curve is one of the most important soil properties, and many models have been presented for fittng to the measurd data of this curve. Also, there are some methods for estimating of this curve including its estimation using more easily available soil properties which can be called parametric pedotransfer functions. The main objective of this study was the estimation of PSD curve with some different models based on the parametric pedotransfer functions.

In this study, the models of Haverkamp and Parlange (1986) with two conditions, Assouline et al. (1998), and Fredlund et al. (2000) were employed for fittng to the measued data of this curve. All mentioned models contain several parameters, and the estimation of PSD curve may be accomplished by knowing the models parameters. To do this, some equations were derived for estimating the parameters of the model of Haverkamp and Parlange (1986) in two assumptions, and the model of Assouline et al. (1998). Also, the equations for estimating Fredlund et al. (2000) model were computed from Fooladmand and Mansuri (2013). All estimated equations for the model parameters have been obtained only based on soil texture data (amounts of clay, silt, sand, geometric mean and geometric standard deviation of the particle-size diameter) which are available easily and common in measuring and computing for soil samples. For this purpose, 30 soil samples were collected from different locations in Fars Province, south of Iran to calibrate the equation, and 10 soils in this area plus 30 soils of UNSODA soil data bases were used to validate the obtained results. 40 soils in validation stage have been divided into three groups containing fine, medium and course textures. The best derived equations for estimating the parameters of the model of Haverkamp and Parlange (1986) with two assumptions, and the model of Assouline et al. (1998) were obtained by using the step by step linear regression procudure. Then, the root mean square error (RMSE), geometric mean error ratio (GMER) and geometric standard deviation of the error ratio (GSDER) have been used to evaluate the obtained results in the validation stage.

The results indicated that the model of Fredlund et al. (2000) was appropriate for soils with fine and course textures, and the model of Assouline et al. (1998) was appropriate for soils with medium texture. Also, the results indicated that two conditions of the model of Haverkamp and Parlange (1986) were not appropriate for estimating the PSD curve.