A. Sharifi; H. Shirani; A.A. Besalatpour; E. Esfandiarpour
Abstract
Introduction: Interrill erosion is one of the major types of erosion playing key role in the transport of fine particles of the soil, particularly in arid and semi-arid regions, which leads to the decrement of soil fertility and surface water pollution. Land-use change is one of the main ways which reflect ...
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Introduction: Interrill erosion is one of the major types of erosion playing key role in the transport of fine particles of the soil, particularly in arid and semi-arid regions, which leads to the decrement of soil fertility and surface water pollution. Land-use change is one of the main ways which reflect the interaction of human activities and the natural environment and can impact soil aggregation, aggregate stability, and erodibility. Hence, this research aimed to evaluate the susceptibility of soils under different land-use types (four types) to interrill erosion using both rainfall simulation test and soil aggregate stability indexes. The location of study area was around Jiroft city.
Materials and Methods: This study was conducted in four types of land use around Jiroft city in southern Iran, including disturbed pasture, undisturbed pasture, protected forests, and artificial forest. For each land use, 25 points were selected (A total of 100 points for all land uses). To measure soil physical and chemical properties, disturbed and undisturbed soil samples were collected from each point at a depth of 0–20 cm. The samples were transported to the laboratory where these samples were then air-dried. Some soil properties such as texture, organic carbon, electrical conductivity, soil acidity, calcium carbonate equivalent, and bulk density were measured, and available nitrogen, phosphorus, and potassium in the soil and sediment samples were also determined. Furthermore, some characteristics of soil particles, including the geometric mean diameter, geometric standard deviation, particulate organic matter, water-dispersible clay, tensile strength of soil aggregate, mean weight diameter and fractal dimension of aggregates were determined. To assess how susceptible are soils to interrill erosion, rainfall simulator was used to generate rainfall with an average intensity of 60 mm/h.
Results and Discussion: According to the results, the undisturbed pasture revealed the highest content of organic matter, particulate organic matter, clay, and tensile strength, while the minimum values of bulk density, sand percentage, and fractal dimension have been observed in this land use. For this reason, it is assumed that the aggregates of undisturbed pasture (intact rangeland) show more stability than other three land uses. The maximum and minimum values of bulk densities were observed in the protected forest (1.58 g cm-3) and undisturbed pasture (1.43 g cm-3), respectively. On the other hand, the highest value of aggregates fractal dimension, as well as minimum values for mean weight diameter and dispersible clay in the protected forest demonstrated that this land use had either no aggregate or its aggregates were very fine. As a matter of fact, lack of organic matter and insufficient clay content can be considered to be the reasons for poor aggregate stability in this land use. The highest and lowest values for tensile strength of soil aggregate were found in the undisturbed rangeland (64.82 kPa) and protected forest (34.38 kPa), respectively. The variations in the tensile strength of soil aggregate can be attributed to the changes in the contents of clay and organic matter in different land uses. Moreover, despite the maximum amount of total organic matter in the undisturbed pasture (or intact rangeland), the amount of sediment organic matter in this land use was lower than the other three land uses. It is because of the fact that most of the OM in this area was of a stable organic matter type, which was under the soil surface and was accordingly protected from surface erosion. The particle size distribution of sediment was smaller in the undisturbed pasture, whereas it was found to be larger in the protected forest. The reason can be attributed to the coarse-textured soil in the forest compared to the finer-textured soil in the undisturbed pasture (or intact rangeland). In addition, the highest sediment concentration and the highest rate of erosion were observed in the disturbed pasture. The artificial forest accounted for the minimum sediment concentration, while the artificial forest, as well as the protected forest, revealed the lowest erosion rate.
Conclusion: The results of the current research demonstrated the high rate of interrill erosion in all land uses so that the disturbed pasture and artificial forest accounted for the highest and the lowest rate of erosion (7 and 2 ton/ha) respectively. According the results, intrinsic soil characteristics such as soil texture played major role in some land uses, while for the others, the slope impact was more crucial. On the other hand, both erosion rate and sediment concentration revealed the same trend under four different land uses of the study area. Therefore, because of the fact that the highest and the lowest rate of erosion, as well as sediment concentration, were found to be in the disturbed pasture, and the artificial forest, respectively, therefore the sediment concentration can be considered to be an important index for soil erosion. Due to high rates of erosion occurring in the study areas, some measures have to be undertaken to prevent and control soil erosion in this area. To achieve this aim, preventing people from entering the vulnerable area, avoiding livestock grazing, protecting existing plants and restoration of native plants can be mentioned as efficient measures to improve conditions.
MohammadAmin Amini; Ghazaleh Torkan; Saeid Eslamian; Mohammad Javad Zareian; Ali Asghar Besalatpour
Abstract
Introduction: Understanding the concept of water balance is one of the most important prerequisites for sustainable management of water resources in the watersheds. Therefore, the components of water resources in a catchment system should be compared at different time periods, and also the effect of ...
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Introduction: Understanding the concept of water balance is one of the most important prerequisites for sustainable management of water resources in the watersheds. Therefore, the components of water resources in a catchment system should be compared at different time periods, and also the effect of each of them should be identified on varied hydraulic components of the hydrological systems. The SWAT model is an example of a physically based hydrologic model which can be used for large-scale simulating and monitoring of water cycle processes based on the characteristics of the catchment area and its climatic conditions. The main object of this study is the hydrologic simulation and water balance estimation for the period 2000-2009 in the Zayandeh-Rud River Basin.
Materials and Methods: The Zayandeh-Rud River Basin is located in the arid and semi-arid central region of Iran. This area is very variable in terms of rainfall. As well as the state of water resources and water consumption is very complicated in this catchment. In the present study, the soil and water assessment tool (SWAT) used to simulate water balance in the Zayandeh-Rud River Basin. The input required data included digital elevation model, land use map, soil texture map and meteorological information including daily rainfall data and minimum and maximum temperature data were introduced to the model and the model was implemented with these data. The sensitivity of the flow-effective parameters was determined using the p-value and t-state criteria by the SUFI2 algorithm in the SWAT-CUP program. The model was calibrated monthly and validated with the selected parameters in the sensitivity analysis using the Nash-Sutcliff criteria and the coefficient of determination by the application of the data of six stations including. Calibration of the model was conducted for 2000-2006 and validation of the model for the years 2007-2009.
Results and Discussion: The results of sensitivity analysis showed that considering the characteristics of the study area, the SWAT model is more sensitive to the 17 effective parameters on runoff. The selected parameters also confirm the results of previous research carried out in the region. The sensitive parameters selected in the sensitivity analysis step were used to calibrate the model. In the next step, the parameters of SWAT-CUP software were entered. After that, these parameters were repeated 1000 times with the SUFI2 algorithm, and the optimal value for each parameter was determined. The Nash-Sutcliff coefficient and the coefficient of determination in the six hydrometric stations are greater than 0.56 and 0.69 in calibration and verification periods respectively, which indicates that the model has a satisfactory ability to run in runoff simulation. The contribution of the components of the water balance including evapotranspiration, surface runoff, lateral flow, groundwater flow, and deep aquifer recharge was calculated from annual basin precipitation. The amount of extracted water from the hydrological components indicated that the largest share of the water balance was related to actual evapotranspiration, the range of variations in the type of precipitation in the study area ranged from 60.1% (2000) to 92.7 % (2007). After evapotranspiration, surface runoff with a change of 22.2% (2005) to 8.6% (2009) and groundwater flow with a change of 14.2% (2000) to 20.5% (the year 2007) had relatively high fluctuations and a large share in the basin balance. These results indicate that the lateral flow with a range of 3.1 to 1.9% had no significant change in these years. Also, the deep aquifer recharge with the range of 1.2 to1.5% was the lowest in 2003 and 2009, respectively.
Conclusion: The results showed that the calibrated model for the Zayandeh-Rud River Basin had a desirable performance for both calibration and validation periods. Therefore, the SWAT model has acceptable performance for simulating the water balance of the area. In addition, the results of this study showed that 65.98% of the total annual precipitation in the basin is in form of evapotranspiration, which compares to the other water balance components has the highest part. As well as surface runoff with 15%, groundwater flow with 13.7%, lateral flow with 1.5%, and deep aquifer recharge with 0.8% have other parts of the water balance components in Zayandeh-Rud River Basin. The results also indicate that the highest water losses in the soil and groundwater resources of the basin are due to evapotranspiration. Therefore, serious measures to prevent the loss of water through evapotranspiration in the region to be necessary. The results of this research can be used to predict the effects of climate change and the applicable management practices in the region, which are presented in scenarios to the model.
Saeideh Bardsirizadeh; Isa Esfandiarpour Borujeni; Ali Asghar Besalatpour; Peyman Abbaszadeh Dahaji
Abstract
Introduction: Aggregate, as the basic unit of soil structure,represents a collection of primary particles which their adherence to each other is more than their connection to environ soilparticles. Aggregate stability is a highly complex parameter influencing a wide range of soil properties, including ...
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Introduction: Aggregate, as the basic unit of soil structure,represents a collection of primary particles which their adherence to each other is more than their connection to environ soilparticles. Aggregate stability is a highly complex parameter influencing a wide range of soil properties, including carbon stabilization, soil porosity, water infiltration, aeration, compatibility, water retention, hydraulic conductivity andresistance to erosion by water and overland flows. Maintaining high stability of soil aggregate is essential for preserving soil productivity, minimizing soil erosion and degradation and thus minimizing environmental pollution as well. Nevertheless, aggregate stability is described as one of the soil properties that can serve as an indicator of soil quality.The main purpose of this study is to determine the most important component of soil aggregate (macro and/ormicro) in estimating the soil structural stability in the Rabor region, Kerman province, using geostatistical method.
Materials and Methods: Ninetysurface soil samples (0 to 10 cm) were taken on a 200 m square sampling grid in the study area for the geostatistical studies.After air drying the soil samples and passing them through a 4 mm sieve, the percentage of aggregates belong tothree parts of total, macro, and micro classes and aggregate staility were calculated in both dry and wet conditions.Some stability indices were calculated and their spatial variabilities were investigated using two variography and estimation stages methods. Finally, the kriged map of each aggregate stability indicator was produced. To determine the compatibility of kriged maps of the soil aggregates stability indices calculated for the macro and micro aggregates with aggregates stability index (i.e., AS index) calculated forthe total aggregates, the overall accuracy related to each aggregate component (i.e., macro and micro) was calculatedafter creating an error matrix.
Results and Discussion: The results showed that total aggregate stability in the dry condition and macro aggregate stability in the wet condition had the lowest and highest coefficients of variability,respectively. The highest percentage of total aggregate stability (i.e., 89.90 %)was observed in the north and southeast positions of the study areain the dryconditionwhich had the highest amount of organic matter(i.e., 2.30 %). Also, the variograms of all investigated variables were exponentially and their ranges were varied between 380 to 450 m. Although the obtainedranges were different, a sampling distance more or less equal to 420 m is reasonable to study the most of the variables in the area. This can be a good indicator to decrease the sampling tasks for monitoring of these parameters in future.An overall look at the obtained root mean square standardized error (RMSSE) values indicated a high correlation between the measured and estimated values of all investigatedvariables (except for macro aggregate stability in the wet condition). However, all variables had a strong spatial correlation class. The percentage of overall accuracy obtained from crossing the total and macro aggregate kriged maps in the dry condition (i.e., 51.75 %), was more than its percentage for similar maps in the wet condition (i.e., 32.17 %). In return, the percentage of overall accuracy obtained from crossing the total and micro aggregate kriged maps in the wet condition (i.e., 17.31 %)was greater than its percentage for the mentioned maps in the dry condition (i.e., 10.93 %). Because of macro aggregate sensitivities to the amount of pressure imposed on them (as in the wet sieving method, the aggregates are under pressure caused by water energyin addition to tensions related to mechanical motion of sieving), the conformities of above two mentioned maps were less than those in the dry sieving method.
Conclusions: In general, the soil aggregates stability depends strongly on the amount of pressure imposed on them. Besides, the study of spatial variability of macro and micro aggregate stabilities and relative effects of each on the soil structure stability can be useful for choosing proper land management activities in future studies. According to theeffect of aggregation on nutrient cycling, capture, storage and water movement, and also other soil characteristics affecting plant growth and sustainable agriculture on one hand, and the effect of organic matter on aggregation on the other hand, it can be concluded thatall human activities that have a role in reducing or removing organic matter from the soil (e.g., grazing, deforestation, and intensive cultivation etc.) may reduce soil aggregate stability and finally can jeopardize human life in a near future.
Amirhosein Aghakhani Afshar; Yousef Hassanzadeh; Ali Asghar Besalatpour; Mohsen Pourreza Bilondi
Abstract
Introduction: Hydrology cycle of river basins and water resources availability in arid and semi-arid regions are highly affected by climate changes, so that recently the increase of temperature due to the increase of greenhouse gases have led to anomaly in the Earth’ climate system. At present, General ...
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Introduction: Hydrology cycle of river basins and water resources availability in arid and semi-arid regions are highly affected by climate changes, so that recently the increase of temperature due to the increase of greenhouse gases have led to anomaly in the Earth’ climate system. At present, General Circulation Models (GCMs) are the most frequently used models for projection of different climatic change scenarios. Up to now, IPCC has released four different versions of GCM models, including First Assessment Report models (FAR) in 1990, Second Assessment Report models (SAR) in 1996, Third Assessment Report models (TAR) in 2001 and Fourth Assessment Report models (AR4) in 2007. In 2011, new generation of GCM, known as phase five of the Coupled Model Intercomparison Project (CMIP5) released which it has been actively participated in the preparation of Intergovernmental Panel on Climate Change (IPCC) fifth Assessment report (AR5). A set of experiments such as simulations of 20th and projections of 21st century climate under the new emission scenarios (so called Representative Concentration Pathways (RCPs)) are included in CMIP5. Iran is a country that located in arid and semi-arid climates mostly characterized by low rainfall and high temperature. Anomalies in precipitation and temperature in Iran play a significant role in this agricultural and quickly developing country. Growing population, extensive urbanization and rapid economic development shows that Iran faces intensive challenges in available water resources at present and especially in the future. The first purpose of this study is to analyze the seasonal trends of future climate components over the Kashafrood Watershed Basin (KWB) located in the northeastern part of Iran and in the Khorsan-e Razavi province using fifth report of Intergovernmental Panel on climate change (IPCC) under new emission scenarios with Mann-Kendall (MK) test. Mann-Kendall is one of the most commonly used nonparametric tests to detect climatic changes in time series and trend analysis. The second purpose of this study is to compare CMIP5 models with each other and determine the changes in rainfall and temperature in the future periods in compare with base period on seasonal scale in all parts of this basin.
Materials and Methods: In this research, keeping in view the importance of precipitation and temperature parameters, fourteen models obtained from the General Circulation Models (GCMs) of the newest generation in the Coupled Model Intercomparison Project Phase 5 (CMIP5) were used to forecast the future climate changes in the study area. In historical time (1992-2005), simulated data of these models were compared with observed data (34 rainfall and 12 temperature stations) using four evaluation criteria for goodness-of-fit including Nash-Sutcliffe (NS), Percent of Bias (PBIAS), coefficient of determination (R2) and the ratio of the root mean square error to the standard deviation of measured data (RSR). Furthermore, all models have a very good rating performance for all of the evaluation criteria and therefore investigation is done for precipitation data as an important component in survey of climate subject to select the optimum models in kashafrood watershed basin.
Results and Discussion: By comparing four evaluation criteria for fourteen models of CMIP5 during historical time, finally, four climate models, including GFDL-ESM2G, IPSL-CM5A-MR, MIROC-ESM and NorESM1-M which indicated more agreement with observed data according to the evaluation criteria were selected. Furthermore, four Representative Concentration Pathways (RCPs) of new emission scenario, namely RCP2.6, RCP4.5, RCP6.0 and RCP8.5 were extracted, interpolated and then under three future periods, including near-century (2006-2037), mid-century (2037-2070) and late-century (2070-2100) were investigated and compered.
Conclusions: The results of Mann-Kendall test which was applied to examine the trend, revealed that the precipitation have variable positive and negative trends which were statistically significant. In addition, mean temperature have a significant positive trend with 90, 99 and 99.9% confidence level. In seasonal scale, survey of climatic variable (rainfall and mean temperature) showed that the maximum and minimum of precipitations occur during spring and summer and mean temperature in all seasons is higher than historical baseline, respectively. Maximum and minimum of mean temperature occur in summer and winter, and the amount of seasonal precipitation in these seasons will be reduced. Finally, across all parts of kashafrood watershed basin, rainfall and mean temperature will be reduced and increased, respectively. In conclusion, models of CMIP5 can simulate the future climate change in this region and four models of CMIP5 can be used for this region.
Ali Asghar Besalatpour; Hossein Shirani; Isa Esfandiarpour Borujeni
Abstract
Introduction: Soil aggregate stability is a key factor in soil resistivity to mechanical stresses, including the impacts of rainfall and surface runoff, and thus to water erosion (Canasveras et al., 2010). Various indicators have been proposed to characterize and quantify soil aggregate stability, for ...
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Introduction: Soil aggregate stability is a key factor in soil resistivity to mechanical stresses, including the impacts of rainfall and surface runoff, and thus to water erosion (Canasveras et al., 2010). Various indicators have been proposed to characterize and quantify soil aggregate stability, for example percentage of water-stable aggregates (WSA), mean weight diameter (MWD), geometric mean diameter (GMD) of aggregates, and water-dispersible clay (WDC) content (Calero et al., 2008). Unfortunately, the experimental methods available to determine these indicators are laborious, time-consuming and difficult to standardize (Canasveras et al., 2010). Therefore, it would be advantageous if aggregate stability could be predicted indirectly from more easily available data (Besalatpour et al., 2014). The main objective of this study is to investigate the potential use of support vector machines (SVMs) method for estimating soil aggregate stability (as quantified by GMD) as compared to multiple linear regression approach.
Materials and Methods: The study area was part of the Bazoft watershed (31° 37′ to 32° 39′ N and 49° 34′ to 50° 32′ E), which is located in the Northern part of the Karun river basin in central Iran. A total of 160 soil samples were collected from the top 5 cm of soil surface. Some easily available characteristics including topographic, vegetation, and soil properties were used as inputs. Soil organic matter (SOM) content was determined by the Walkley-Black method (Nelson & Sommers, 1986). Particle size distribution in the soil samples (clay, silt, sand, fine sand, and very fine sand) were measured using the procedure described by Gee & Bauder (1986) and calcium carbonate equivalent (CCE) content was determined by the back-titration method (Nelson, 1982). The modified Kemper & Rosenau (1986) method was used to determine wet-aggregate stability (GMD). The topographic attributes of elevation, slope, and aspect were characterized using a 20-m by 20-m digital elevation model (DEM). The data set was divided into two subsets of training and testing. The training subset was randomly chosen from 70% of the total set of the data and the remaining samples (30% of the data) were used as the testing set. The correlation coefficient (r), mean square error (MSE), and error percentage (ERROR%) between the measured and the predicted GMD values were used to evaluate the performance of the models.
Results and Discussion: The description statistics showed that there was little variability in the sample distributions of the variables used in this study to develop the GMD prediction models, indicating that their values were all normally distributed. The constructed SVM model had better performance in predicting GMD compared to the traditional multiple linear regression model. The obtained MSE and r values for the developed SVM model for soil aggregate stability prediction were 0.005 and 0.86, respectively. The obtained ERROR% value for soil aggregate stability prediction using the SVM model was 10.7% while it was 15.7% for the regression model. The scatter plot figures also showed that the SVM model was more accurate in GMD estimation than the MLR model, since the predicted GMD values were closer in agreement with the measured values for most of the samples. The worse performance of the MLR model might be due to the larger amount of data that is required for developing a sustainable regression model compared to intelligent systems. Furthermore, only the linear effects of the predictors on the dependent variable can be extracted by linear models while in many cases the effects may not be linear in nature. Meanwhile, the SVM model is suitable for modelling nonlinear relationships and its major advantage is that the method can be developed without knowing the exact form of the analytical function on which the model should be built. All these indicate that the SVM approach would be a better choice for predicting soil aggregate stability.
Conclusion: The pixel-scale soil aggregate stability predicted that using the developed SVM and MLR models demonstrates the usefulness of incorporating topographic and vegetation information along with the soil properties as predictors. However, the SVM model achieved more accuracy in predicting soil aggregate stability compared to the MLR model. Therefore, it appears that support vector machines can be used for prediction of some soil physical properties such as geometric mean diameter of soil aggregates in the study area. Furthermore, despite the high predictive accuracy of the SVM method compared to the MLR technique which was confirmed by the obtained results in the current study, the advantages of the SVM method such as its intrinsic effectiveness with respect to traditional prediction methods, less effort in setting up the control parameters for architecture design, the possibility of solving the learning problem according to constrained quadratic programming methods, etc., should motivate soil scientists to work on it further in the future.
