فصلنامه پژوهش های فرسایش محیطی
سال دهم شماره 4 (پیاپی 40، زمستان 1399)

Climate, terrain condition, vegetation coverage, parent materials, and time are among the factors that affect the soil formation and contribute to such soil properties as porosity, apparent and actual specific gravities, and clay and carbonate contents. The forest soils have been consistently regarded for their high content of organic matter and suitable structure. In the meantime, changes in the management scheme, land use, and soil treatment procedures can significantly alter the organic matter content and other physical and chemical properties of the soil (Hagedorn et al., 2001; Stoate et al., 2001; Dawson and Smith, 2007). The organic matter greatly contributes to improved crop yield by directly affecting the physical and chemical properties of the soil. Considering the importance of the soil and its properties for many managerial programs, the present research aims at investigating the reasons behind the formation of various soil types within the Kasilian Area, Mazandaran Province, Iran. Similar areas can be observed in other places across the so-called Hyrcanian Forests by Quick review of the satellite images. Accordingly, the findings of the present research are important for similar forest areas and forest settlements.

The watershed area range was delineated based on satellite images and topographic maps. The area was then surveyed by selecting and studying a number of soil sections where the soil variations were relatively large across an acceptably large extent. The extents of different formations were identified and the land components were determined by using geological maps. By considering the available geological and geomorphological data and interpretation of the satellite images combined with terrestrial observations and profile descriptions of the profiles and the land component sections, different land components were distinguished. The land components were considered as relatively homogeneous work units, and the pedological studies were focused on these units. The units were relatively identical in terms of the soil, physiography, climate, and the parent materials, with an attempt made to take into consideration about the relation between the transacts and the soil evolution. Seven soil profiles were selected by the studied profiles and sections, as to control for which the experimental results and classification outcomes were presented.

The climatic condition was almost the same across the entire study area, so that its impact on the soil was similar in different parts of the area. The more important factor that mitigated the impact on the climatic condition and contributed to the formation of various soil types across the region was the versatility of the geological formations and the terrain over the study area. So the present-day variations in the soil classification can be greatly linked to the changes in the Mollic horizon thickness. In this research, the maximum organic carbon content was observed in the samples taken from the forest lands, with its value significantly dropped in the deforested areas, especially the farmed lands. Variations of the organic carbon content of the soil is an important indicator of the soil quality for investigating the effects of managerial operations in the farmed and forest lands. The soils formed on top of the Lar (L1J), Delichay (jd), and Shemshak Formations (TR3.JS) were found to be residual soils. Although the Lar and Delichay formations are dominantly composed of lime, their evolution has been interrupted in the region due to the very high slopes to which the formation has been exposed, making the corresponding soils classified as Inceptisol. This is while the Shemshak Formation has been exposed to a relatively slower slope, so that the forest vegetation coverage and more limited horizontal displacement of the soil have provided enough time to form the Mollic horizon and the Mollisols. In the sediments located within the valleys between the quaternary hills and mounts, which were previously covered by forests and now are turned into low-slope pastures, the Mollic horizon has been appropriately preserved, with the lime content of the parent materials transported to underlying horizons to form a calcite horizon. This part of the land is covered by Mollisols that were generally classified as calciudolls considering the moisture regime of the soil. In the sloping lands, as a result of the erosion of the surface soil, the Mollic horizon was degraded, which made the soil classified under Entisols and the great class of Udorthents. On such lands, upon erosion of the overlying soil, the underlying rocks along the soil profile are exposed.

A Comparison of soils in Bare lands with forest lands showed a dramatic declining trend in the soil properties. In this respect, the farmlands were dominantly covered by Entisols while the pastures were most often covered by Inceptisols and the forests were dominated by Mollisols; these showed the soil variations under similar natural conditions as a result of changes in the land use. It is recommended to set the scene not only to limit the deforestation process, but also to suit the pastures for natural forestation in an attempt to prevent further erosion of the invaluable soil and preserve the even more valuable natural resources.

Climate change is a real phenomenon and is the long-term average changes of weather conditions in an area with significant effects on the ecosystem of the region. Given the potential of climate change to increase soil erosion and its associated adverse impacts, modeling future rates of erosion is a fundamental step in its assessment as a potential future environmental problem. Among the increasingly important tools used by resource managers are the climate change scenarios, scenario designs, and other prediction models. These climate scenarios provide resource managers and decision-makers with a plausible representation of future climate to better anticipate potential impacts of climate change. In our case, the prediction models are helpful in assessing the response of soil erosion to future climate change. To provide an effective result for soil erosion hazard assessment and simulation of soil erosion risk in future, remote sensing (RS) and geographical information system (GIS) technologies were adopted and a numerical model was developed using RUSLE method.

The area selected for carrying out the experiment is Kondoran catchment in Kol-Mehran basin in southern part of Iran. The geographical classification of this selected area is arid and has a warm climate with annual precipitation of 57 mm. This watershed area has a minimum and maximum height of 1 and 1409 m, respectively and belongs to southern Zagros with saldome and these formations include Ghachsaran, Mishan and Aghajari. In the following, the soil loss is computed for a basis period (1984-2015) and for two other future periods (2016-2030) and (2031-2050) for each of four sets of downscaled climate data corresponding to two Intergovernmental Panel on Climate Change (IPCC) global emissions scenarios (RCP2.6, RCP4.5, RCP8.5) each modeled using one GCMs (canESM2).

The result of climate change scenarios using SDSM-DC model in Bandare Lenge Station are cited here. By applying RCP2.6 in the first period of stimulated future climate (2015-2030), the precipitation will increase to 126 mm in study area. In the RCP4.5, the precipitation will reduce to 102 mm, and finally, in the third scenario (RCP8.5), precipitation will increase to 86 mm. The results of first and second simulated periods indicate that the annual precipitation level will rise and will be more than the basis period. The same results were gained in the other three stations (Kish Island, Bandar-e charak and Bastak).
In the following, the rainfall erosivity factor (R factor) was generated under RCP2.6, RCP4.5 and RCP6.5 scenarios in two periods of (2016-2030) and (2031-2050). According to the results, the highest amount of R is in the period (2016-2030) under RCP4.5 scenario, which is between 94.14 and 105.07 MJ mm ha-1 h-1 y-1 and in the period (2030-2050) under the RCP4.5 scenario, which is between 94.88 and 106.3 MJ mm ha-1 h-1 y-1. In general, we will see an increase in the trend of R-factor in the future.The result depicts that the average annual soil loss will increase from 9.8 (tons ha-1 year-1) in historical period to 10.23 (tons ha-1 year-1) in future decades. Moreover, according to the results the soil erosion in the base period was lower than all scenarios of climate change during 2030 and 2050 and showed that R-factor in the RUSLE model is directly influenced by climate changes.

According to the results gathered, climate change has an important impact on the rainfall erosivity. Soil erosion was simulated during 1984–2015 to 2016–2050 using RUSLE model and SDSM downscaling models. The developed approach addresses the issue of the impact of climate on soil sustainability. It allows for the assessment of both the soil erosion for various land use and climate change scenarios. The results showed that in all of the scenarios precipitation will increase in the future period, so these changes affect the R-factor and consequently erosion of soil.

One of the important parameters for identifying the erosion-sensitive points is the use of soil erodibility factor, which is determined by two methods; direct and indirect methods. The direct method for calculating soil erodibility has good accuracy. However, it is economically expensive. Therefore, this method is not considered by experts. The indirect and conventional method for calculating the soil erodibility is the Wischmeier nomograph method, which was presented for non-calcareous and semi-wet soils of the United States. Since the majority of the soils in Iran are calcareous, hence in this research, the Vaezi method, which is designed for this type of soil, was used. Loess is one of the most important Quaternary sedimentary formations in northeastern Iran, which has variable sedimentation and erosion potential due to its physicochemical properties. This study was conducted to evaluate and compare the estimated values of soil erodibility (K) from two methods of Wischmeier nomograph and Vaezi method in calcareous-loess soils of Arab-Qareh-Haji watershed in the east of Golestan province.

The study watershed with an area of 2595 hectares is located in the northeast of Golestan province. To perform this research, after the initial studies, the components of the land unit in the study area (including river terrace, loess plateau, and hill) were selected as the working unit. For this purpose, 42 surface samples (0-10 cm depth) were collected from each part of the land unit. In this study, the standard laboratory methods were used to determine the soil physicochemical parameters. Soil physicochemical properties, including soil texture, neutral lime, organic matter, coarse sand, very fine sand+silt, and soil structure, were measured in the laboratory. The saturation hydraulic conductivity of soil in the laboratory was estimated using the falling head method. In this research, the actual soil erodibility was measured using a rain simulator in the field (in plots of 1 m2). Then, spatial changes of soil erodibility in the study area were plotted using GIS software and inverse distance weighting (IDW) method. F-test and Games-Howell at the probability level of 0.05 were used to compare and determine the statistical difference between the estimated erodibility values (the Wischmeier nomograph and Vaezi methods) with actual data. To estimate the most effective parameter in the soil erodibility using the Vaezi method, multiple linear regression and stepwise methods were used. Statistical tests were performed using Minitab software.

The average silt particles in the soil were measured about 60% in the Arab-Qareh-Haji watershed, which plays an important role in the soil erodibility. In this watershed, the ratio of fine sand to coarse sand was calculated about 18, and this can be one of the main causes of runoff in this area. Soil texture assessment in this watershed revealed that around 90 percent of soil samples have silt loam texture, and the rest of the samples has loam one. Also, the average lime in study area was estimated at about 29%. This amount is higher than the standard lime (15%) in the soil to create stable aggregates in the wet state. Then, soil erodibility values were determined by three methods Wischmeier nomograph, Vaezi method, and rain simulator (actual data). The results showed that the value of soil erodibility using Wischmeier nomograph was estimated at about 30.4 and 18.8 times higher than for the Vaezi method and actual data, respectively. The results of F-test and Games-Howell test with 95% probability showed that there was no significant difference between the soil erodibility from the Vaezi method and the actual data, while there was a significant difference between the Wischmeier method and the actual data. Results of multiple linear regression and stepwise methods showed that the most important variables in estimating the soil erodibility are silt, organic matter, neutral lime factors, and coarse sand, respectively (R2 = 0.9648, R2-adj = 0.9539). In this study, it was not possible to estimate the soil erodibility factor by Vaezi method due to the high percentage of neutral lime for a number of samples.

In this study, the average lime was estimated at about 29%. This amount is higher than the standard lime (15%) in the soil to create stable aggregates in the wet state. Therefore, it seems that excess lime in the wet soil can reduce the stability of aggregates. In this watershed, a large number of tunnels and gully were observed, which indicates that this soil is erodible. The statistical analysis results showed that the soil erodibility values from the Vaezi method in this watershed were relatively close to the actual data but were less estimates, while the Wischmeier nomograph method was significantly different from the actual data and was overestimated. However, for areas where the amount of neutral lime was over 30%, the Vaezi method was not able to calculate the soil erodibility factor. Hence, for the areas where the percentage of neutral lime is lower than 30%, the use of the Vaezi method is more suitable than the Wischmeier nomograph method, and for areas where the percentage of neutral lime is higher than 30%, the model needs to be calibrated and updated.

In recent decades, the excessive use of groundwater resources has led to a drop in groundwater levels in most plains of Iran. To this end, the use of remote sensing techniques has recently expanded to study the fluctuations of groundwater levels. GRACE satellite data is a valuable new tool for groundwater monitoring and is currently the only remote sensing satellite which is capable of monitoring groundwater level changes. Hence, considering the special and critical conditions of Jiroft plain from the point of view of water resources, the study on the identification of the change of groundwater resources (as the main water resource in the region) have special importance. Therefore, the purpose of this study is to investigate and analyze the fluctuations of groundwater levels in Jiroft plain using GRACE satellite images from 2003 to 2016

This study investigates the trend of groundwater level changes in Jiroft plain using GRACE satellite images during 2003-2016. In this regard, the data was firstly processed in Google Earth Engine based on three algorithms, including JPL, GFZ, and CSR, and their results were compared with observational data (piezometric) from 2003 to 2016. This comparison was performed by examining the linear correlation between the changes obtained based on the GRACE satellite algorithms and the observational data. Also, for temporal and spatial analysis, the aquifer water level was mapped using Kriging method in ARCGIS software.

The results showed a good correlation between algorithms and observational data. According to the results, JPL algorithm with 64% correlation was the most suitable model for monitoring the quantity of groundwater in Jiroft plain. The results of groundwater mapping from 2003 to 2016 indicated the most drop of groundwater level in the central, western and southwestern parts of Jiroft plain, due to more wells and the expansion of agricultural activities in these regions. The examination of groundwater change trend showed that both observational data and JPL, CSR, and GFZ algorithms had a significant decreasing trend at the level of 5%. The similarity trend of observational data and algorithms also indicated the relatively good accuracy of GRACE images to investigate the groundwater level fluctuations.

The recent droughts and increasing the number of exploitation wells have led to the decrease in groundwater levels. Therefore, the assessment of groundwater level fluctuations of Jiroft plain is necessary. In this study, GRACE satellite data were used to evaluate groundwater level fluctuations in Jiroft plain. The results of groundwater mapping from 2003 to 2016 indicated the most drop of groundwater was related to regions with more wells and more agricultural activities that are in line with Hao et al., 2019. The study of linear correlation between the results of the three algorithms of GFZ, CSR, JPL, and piezometers, showed a good correlation between the algorithms and the observational data. According to the results of JPL model with 64% correlation, it was the most suitable model for monitoring the groundwater level in Jiroft plain. Considering the appropriate correlation obtained, it can be concluded that researchers and organizations can apply GRACE data as a low-cost and easy method to monitor and analyze groundwater level fluctuations that are compatible with the findings of Farokhnia and Morid (2014); Faraji et al., (2017) and Nabavi et al., (2020). Investigating the change trend of groundwater showed that both observational data and JPL, CSR, and GFZ algorithms have a significant decreasing trend at the level of 5%. The similarity trend of observational data and algorithms also indicated the relatively good accuracy of GRACE images to investigate the groundwater level fluctuations. The findings of Farokhnia et al., (2014) also showed the similarity of changes trend of the total water balance of the basin by the Grace satellite and the observational data.

The purpose of this essay is to investigate the morphometry of catchment areas in the Zagros morphotectonic unit using the Horton principle of erosion status. Erosion is a natural phenomenon that has always been associated with the Earth since the formation of it, but over recent centuries it has taken an upward trend because of population growth, resources constraints, industry development and increasing human interference in natural ecosystems (Ghodsipour, 1395: 143). By eroding their bed for adjusting the bed profile, rivers increase their sedimentary load and its amount depends on the type of bed and the factors influencing the river speed (Majnoonian, 1378: 4). Production has always been expected to increase with the use of advanced agricultural methods, but unfortunately, this increase has been accompanied by a decrease in soil fertility due to erosion (Hudson, 1394: 469). The term “river morphometry” can be used to measure the geometric characteristics of a river. In fact, morphometry is a quantitative analysis of the geomorphic characteristics of the landforms of a region (Bayati Khatibi, 1388: 25). Morphometric analysis is one of the effective methods for prioritizing sub-basins, which can indicate the status of the basin drainage network (Mousavi et al., 1396: 250).

For this purpose, the whole geomorphic unit of Zagros was first divided into eleven water basins. These water basins were then extracted in 271 sub-basins. The next step was to rank the channels using the Horton and Strahler methods. The Horton principle and the other researchers’ terms were used to investigate the erosion status of sub-basins. Morphometric characteristics divided into three categories: formal, linear, and topographic parameters. In order to obtain the erosion classes, after calculating the parameters, all the factors for calculating erosion were averaged and classified. According to calculations conducted, the coefficients were obtained that had to be classified and analyzed. The difference between the maximum quantity and the minimum quantity of the coefficients was obtained and the result was divided by five, and then it was summed with the minimum quantity of calculations and the obtained quantity, which was the smallest number, was coded as 1 and similarly, the next number was summed with the quantity obtained from (Max - Min / 5) and the code 2 was assigned to the answer obtained and all the numbers smaller than that. In the same way, up to 5 classes were classified.

The result shows an inverse relationship between occurrence of erosion and average quantity of total morphometric parameters. In other words, a lower average quantity of the total morphometric parameters indicates a more prepared condition for erosion; therefore the situation will be more critical and threatening. The classification shows that many factors have affected erosion, including; the area and length of the channel, permeability and inequality.
In the Zagros morphotectonic unit, the length of the dry stream is also directly related to erosion. Morphometric analysis shows the drainage network of the dendritic basin. A change in slope and topography might be a change in the flow-length ratio. Lithology, tectonics and the climate of that region have had a great impact on the erodibility of this unit. Also, the increase in the number of channels and their length in the drainage basin indicate an increase in erosion. Basins with very high ranking are likely to have high altitude, high slope and deep valley topography, which indicates a strong drainage structure and thus they are more exposed to intense motion of the brae.

Separate geological facies and lack of cement between particles and soil granules are major factors leading to erosion, sedimentation and debris flows. Moreover, lack of cement between particles and granules in channels can cause lateral erosion, increased amount of sediment and reduced stability of soil aggregate and formations. The erosion status of the Zagros morphotectonic unit was estimated based on the results and was classified into 5 groups. According to Figure (3), it can be stated that in this unit the erosion status is predominant, high and medium, which has been affected by lithological, tectonic and climatic factors. According to figure (4), very low erosion prevails over the coastal sub-basins of the Zagros unit, while low erosion is more centralized in some springhead and coastal sub-basins. Figure (7) indicates that many sub-basins with moderate erosion have a larger area than sub-basins with high erosion. As the sub-basins area shrinks, high erosion has prevailed. Very high erosion is scattered throughout the unit. In the sub-basins of this erosion status, the same logic prevails as in the sub-basins with high erosion and with the shrinking of the sub-basins, erosion has become too high.

Simulation of the rainfall-runoff process for planning and management of water resources and watersheds requires using a conceptual optimized hydrological model. Models of different types provide a means of quantitative extrapolation or prediction that will hopefully be helpful in decision-making. Recently, the application of models has become an essential tool for understanding the natural processes that have occurred in the watershed. KINEROS2 (Kinematic runoff and Erosion), or K2, originated at the USDA Agricultural Research Service (ARS) in the late 1960s as a model that routed runoff from hillslopes is represented by a cascade of overland-flow planes using the stream path analogy proposed by Onstad and Brakensiek (1968), laterally into channels. Manual calibration of hydrological models has been used since the early 1960s, but due to its complexity and being time-consuming, automatic calibration has been available since the end of the 1960s. Auto-calibration needs an appropriate objective function, search algorithm, and a criterion to complete the algorithm. The particle swarm optimization (PSO) algorithm, due to its flexibility, easy implementation, and high performance, has been favored by many researchers in recent years. This method has a high rate of convergence and suitable computational cost.

In this study, the hydroPSO package was employed to optimize KINEROS2 (K2) parameters applied in the Bar watershed, Neyshabour, Iran. The hydroPSO package in R software environment was utilized to implement the PSO optimization algorithm. The possibility to develop R capabilities by adding the produced packages by the users is one of the most important specifications of this software. The statistical measures used in model validation analysis were model bias (MB), modified correlation coefficient (rmod), and Nash-Sutcliffe Efficiency (NSE). These metrics are the most common evaluation criteria in the literature. The capability of the model in water discharge estimation can be assessed by MB, while rmod signifies the differences both in hydrograph size and shape. In this work, 16 parameters have been introduced as the effective parameters on flood simulation by K2. These parameters were calibrated using the hydroPSO optimization package within R environment, which benefits from a parallel processing capability and a higher speed of computations, as compared with other software environments like MATLAB. The common parameters in the calibration process involved in the main code of K2 program include Ks, n, CV, G, and In. In this study, by changing some codes in K2 through the FORTRAN programming language, calibration parameters were increased by 16 parameters. Therefore, the response of a watershed to the variations of these parameters, separated for channel and plane, can be well evaluated. Due to semi-distributed simulation of K2, changing the amount of each parameter was done through “relative changes” in the initial value using a multiplier approach. Five storm events were utilized in hydrograph simulation, as well.

Results indicated the better efficiency of K2 based on the event 1992/03/31 with the coefficient of determination and Nash-Sutcliffe Efficiency (NSE) of 0.96 and 0.96, respectively. The events dated 1991/03/07, 1991/05/11,1992/03/16,1994/12/04, respectively, with the NSEs of 0.90, 0.90,0.89, and 0.43, showed the excellent, excellent, excellent, and good fitness of simulated flow compared to observed flow, respectively. Sensitivity analysis established that the parameters Ks_c, n_c, Rock, G_p, Ks_p, Por_p, and Sat were the most effective parameters in K2 calibration, respectively. The posterior distributions of some parameters such as n_c and Smax appeared to be more sharply peaked than other parameters which established less uncertainty in hydrological modeling. Visual inspection of boxplots showed that for 8 out of 16 parameters (Ks_p, n_c, G_p, In, Rock, Por_p, Por_c, and Sat), the optimum values found during the optimization coincided with the median of all the sampled values; confirming that most of the particles converged into a small region of the solution space. Dotty plots showed that the optimum values found for n_c define a narrow range of the parameter space with a high model performance. On the other hand, the model performance was more impacted by the interaction of Ks and n parameters. Correlation analysis revealed that the highest linear correlation between NSE and K2 parameters was obtained for the parameters Ks_p, Ks_c, n_p, CV_p, G_c, In, Por_p, Dist_p, Dist_c, Smax, and Sat.

In comparison with manual calibration, the HydroPSO R package could compensate for the shortage of K2 proficiency, due to the lack of enough observed rainfall records, in hydrologic modeling of semi-arid watersheds. Thus, it can be successfully integrated with the K2 model to harness the combined benefits of a distributed hydrological model and flexible computing capability of the open-source R software. However, the performance of HydroPSO in K2 calibration should be assessed for several semi-arid watersheds which have the similar conditions to Bar watershed.