habibeh Abbasi; Mohammad Taghi Aalami; Mohammad faraji
Abstract
This article aims to analyze the trend of monthly, seasonal and annual changes in the flow and sediment of the Mordaghchai. located in East-Azerbaijan province. In this regard, using non-parametric methods, discharge and sediment data of Gheshlagh-Amir hydrometric station have been analyzed in three ...
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This article aims to analyze the trend of monthly, seasonal and annual changes in the flow and sediment of the Mordaghchai. located in East-Azerbaijan province. In this regard, using non-parametric methods, discharge and sediment data of Gheshlagh-Amir hydrometric station have been analyzed in three time scales: annual, seasonal and monthly. The modified Mann-Kendall test was used to analyze the trend of gradual changes in discharge and sediment data. Also, the Sen's slope estimator was used to estimate the slope of the trend line and the non-parametric Pettitt test was used to investigate the abrupt changes in the discharge and sediment time series. The modified Mann-Kendall test was used to analyze the trend of gradual changes in discharge and sediment, and the Sen' slope estimator test was used to estimate the slope of trend line. Also, Pettit test was used to investigate abrupt changes in the river discharge and sediment time series. The results show that annual, monthly and spring, summer and winter discharges significantly decrease at the level of 5%. The annual and all-season sediment load data significantly decreased by 5%. There is a significant decrease in sediment load in all months except March, April and October. The results of the Pettitt test show that the average annual discharge in the period after the breaking point (1998) has decreased by 45% compared to the period before the breaking point. Also, the average annual sediment load after the breaking point (1996) has decreased by about 52% compared to the previous period.
hydrogeology
hamzeh saeediyan; Hamid reza Moradi; abdal salehpoor
Abstract
1-IntroductionSoil infiltration situation indicates soil behavior against water reaching the soil surface. This phenomenon determines the amount of both the water reaching the soil surface and rainfall losses. Soil infiltration of a basin has unique parameters based on its climate, soil conditions, and ...
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1-IntroductionSoil infiltration situation indicates soil behavior against water reaching the soil surface. This phenomenon determines the amount of both the water reaching the soil surface and rainfall losses. Soil infiltration of a basin has unique parameters based on its climate, soil conditions, and buildings. Soils are a set of discontinuous particles among which pores exist so that water can move from a point with more energy to a point with less energy; this property is called the passage of water through continuous pores. Gachsaran marl formation has a thickness of about 1600 m and consists of salt, anhydrite, colorful lime marl, and some shale from a lithology point of view. The age of this formation is lower Miocene (Ahmadi, 1999: 714). Estimation of soil infiltration using various erosion components can be a useful method to determine soil infiltration in the shortest time and at the lowest cost.2-MethodologyIn this study, soil infiltration was estimated using erosion different components in different land uses in deposits of Gachsaran formation by selecting a part of the Kuhe Gach watershed of Izeh city with an area of 1202 hectares. The relationship between soil infiltration and erosion different components, such as sediment rate, runoff rate, and runoff and erosion threshold, in different land uses of Gachsaran formation was determined by the multivariate regression. Then, different erosion components were sampled at six points with three replicates and different rainfall intensities of 0.75, 1, and 1.25 mm/min in three land uses of rangeland, residential area, and agricultural land using a rainfall simulator. SPSS and Excel software was used for statistical analysis. A portable Kamphorst rainfall simulator used in this study has a plot size of 625 cm2, which determines the characteristics of soil, erosion, and water infiltration, and is suitable for soil research. It is used as a standard method to determine the soil infiltration of surface deposits in the field. The experimental plot area was selected 625 cm2 with a smooth gradient. The preparation of the testing area was followed by installing and setting the rainfall simulator and then starting a chronometer upon observing the precipitation on the screen. The amount of plot infiltration was determined at 10-min intervals (Kamphorst, 1987: 407).3-Results and DiscussionThe estimation of soil infiltration was acceptable and appropriate in some models in this study, which have a lower regression coefficient. Therefore, it is not possible to make appropriate comments about the estimation of the models only using regression coefficients and other statistical coefficients nor the significance levels of observational and estimated data as well as the minimum square mean of errors (MMSEs); in some cases, the MMSEs are not sufficient and require more studies (Jain and Kumar, 2006: 272). Despite scientific advances and improvement of measuring equipment, regression models are still used by researchers in different fields due to simplicity.4-Conclusions The results showed that the most positive and negative effects of different erosion components on estimating soil infiltration were related to sediment rate, runoff, and erosion threshold in all three mentioned land uses in three precipitation intensities (0.75, 1, and 1.25 mm min). Meanwhile, the role of sediment rate in estimating soil infiltration was slightly higher than runoff, and erosion threshold and runoff rate had no role in estimating soil infiltration in this method due to a high correlation of data.
Ahmad Nohegar; Mohamad Kazemi; S.Javad Ahmadi
Volume 4, Issue 12 , December 2017, , Pages 67-87
Abstract
Extent Abstract Introduction Considering the impact of accelerated rates of sediment yield and soil erosion on catchments, which results from land clearance and poor land management (Palazón et al., 2015) including soil degradation, environmental pollution, and sedimentation in dam reservoirs, ...
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Extent Abstract Introduction Considering the impact of accelerated rates of sediment yield and soil erosion on catchments, which results from land clearance and poor land management (Palazón et al., 2015) including soil degradation, environmental pollution, and sedimentation in dam reservoirs, the reduction of the sedimentation is required to implement appropriate methods of sediment control and soil conservation in the critical areas of sediment resources in the catchment (Patrick et al, 2015). In addition, the recognition and identification of the relative importance of the sediment resources and their contribution (Chen et al., 2016) to sedimentation are necessary for identifying appropriate methods and proper implementation of soil conservation programs. The sediment finger printing is a direct approach to identify the relative contribution of each source and provides a direct approach for quantifying sources of sediment. A fingerprint of sediment sources is obtained using radionuclides, tracer metals, or other sediment properties, which enables the determination of the relative source contributions (Motha et al., 2004). Including the erosion and sediment, the important thing is to choose a model or method to estimate the actual loss or erosion of soil and the contribution of each source to its value. There are few studies estimating the level of GOF and ME on sediment fingerprinting approach to determine the relative contribution of each of the resources. GOF and ME allow making better informed decisions on sediment management (Minella et al., 2008) and can reliably determine mixing the contribution of each sediment source in mixing models (Collins et al., 2010). Methodology The study area, Tange Bostank catchment, covers an area of 81.73 km2 and is located at about 80 km far from the Northwest of Shiraz, at the geographical location of 52° 03' 43'' to 52° 13' 36'' in the East and 30° 16' 33'' to 30° 25' 18'' in the North. Geological formations maps were provided as Razak, Kashkan, Bakhtiari, Quaternary, PabdehGurpi, and Asmari formations using SFF method. Land use maps were also provided as rangelands, forests, gardens, and irrigations using ML method with Landsat satellite image 8 of OLI sensor. Discriminating sediment sources to confirm the discrimination of the potential sediment sources was done in two steps. The first step was based on the use of the Kruskal–Wallis H-test to discriminate the potential sources by the fingerprint properties. In the second step, stepwise multivariate discriminant function analysis (DFA) was used to identify the optimum combination of the tracers passing the Kruskal–Wallis H-test and to maximize discriminating between the potential sources. The multivariate mixing model (Walling, 2005) involves minimizing the sum of the squares of the residuals between predicted tracer values for each source in sediment samples and the observed values. The sediment source apportionment involved a comparison of the results obtained using several multivariate mixing models. Using an optimization source proportion minimizes the errors in mixing models. We minimized the sum of the squares of the relative errors (R) in the objective functions( Eq.s 1-5). Eq.1: Eq. 2: Eq. 3: Eq. 4: Eq. 5: where: ci = concentration of fingerprint property (i) in sediment samples; Sij = concentration of fingerprint property (i) in source category (j); X j = percentage contribution from source category (j); Z j = particle size correction factor for source category (j); Oj = organic matter content correction factor for source category (j); Wi = tracer discriminatory weighting or tracer specific weighting; SVji = weighting representing the within-source variability of fingerprint property (i) in source category (j); VARij = variance of the measured values of tracer in source area j; mj = the total number of samples for an individual source; n = number of fingerprint properties; m = number of sediment source categories. Genetic Algorithm optimization (GA) was employed to find the optimal source sediments contribution. In addition, goodness of fit (GOF) equation and Mean Error (ME) were used to determine the results of each of the mixing models (Eq.6 and Eq.7) Eq.6: Discussion Soil erosion and sediment yield are the most destructive phenomena that cause a lot of damages in different regions. However, in order to combat them, it is needed to be aware of the sediment sources location in the region. Sediment fingerprinting technique, based on geochemical tracers, organic and isotopic ratios, and various mixing models, is used in the recognition of the contribution of the different sediment sources in an area. In this study, the optimum combination of organic and rare tracers was used to separate the different sources. In addition, to determine the contribution of this erosion and sediment yield resource, Collins, Collins modified, Motha, Landwehr and Slattery models associated with genetic algorithm optimization were used. The results of the discriminant analysis showed Compounds of C, Cu Si, and Ti as tracers for land uses and four tracers (Nd143/144, Cu, Si,Ti) to discriminate between geology formation’s source categories. To determine the best model, GOF and ME indexes were used. Tables1-4 render the results of applying the ME and GOF indices to select the best models in formation and land use units. The M Collins and Collins mixing models with GOF and ME indices of 99.95%, 99.996% and 99.16%, 99.977% were respectively selected as the best models in land use and formation units. According to ME and GOF results, the calculated relative contributions of the range lands and the Asmari formation with 65% and 56.5% were the highest. Moreover, sedimentation rates of sub basins number 6 and 5 with 59.11% and 58.7% were very important in the management of the soil conservation (the highest proportion in sediment and erosion basins) and sub basins number 31 with 7.54% were not important in the management of the soil conservation (minimal role in Sediment yield of Tange Bostanak watershed). Conclusion Soil erosion and sediment yield are the most destructive phenomena that cause a lot of damages in different regions. However, in order to combat them, it is needed to be aware of the sediment sources location in the region. Sediment fingerprinting technique, based on geochemical tracers, organic and isotopic ratios, and various mixing models, is used in the recognition of the contribution of the different sediment sources in an area. In this study, the optimum combination of organic and rare tracers was used to separate the different sources. In addition, to determine the contribution of this erosion and sediment yield resource, Collins, Collins modified, Motha, Landwehr and Slattery models associated with genetic algorithm optimization were used. The results of the discriminant analysis showed Compounds of C, Cu Si, and Ti as tracers for land uses and four tracers (Nd143/144, Cu, Si,Ti) to discriminate between geology formation’s source categories. The M Collins and Collins mixing models with GOF and ME indices of 99.95%, 99.996% and 99.16%, 99.977% were respectively selected as the best models in land use and formation units. According to ME and GOF results, the calculated relative contributions of the range lands and the Asmari formation with 65% and 56.5% were the highest. Moreover, sedimentation rates of sub basins number 6 and 5 with 59.11% and 58.7% were very important in the management of the soil conservation (the highest proportion in sediment and erosion basins) and sub basins number 31 with 7.54% were not important in the management of the soil conservation (minimal role in Sediment yield of Tange Bostanak watershed).
Manuchehr Farajzadeh; Ali Asghar Hodaei; Maryam Mollashahi; Neda Rajabi Rostam Abadi
Volume 4, Issue 11 , September 2017, , Pages 59-81
Abstract
Introduction
Soil erosion as one of the most important natural hazards of each country usually results in reduced fertility, crop reduction, and desertification, particularly in arid and semi-arid areas. Two-thirds of Iran is located in the arid and semi-arid areas and one of its climatic features is ...
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Introduction
Soil erosion as one of the most important natural hazards of each country usually results in reduced fertility, crop reduction, and desertification, particularly in arid and semi-arid areas. Two-thirds of Iran is located in the arid and semi-arid areas and one of its climatic features is flood. Consequently, soil erosion is one of its environmental problems. Nowadays, since soil is important for the life of products and is directly related to the balance of the ecosystem and the water cycle, its protection and fertility are two important factors that shouldn't be ignored. The purpose of this study was to compare the suspended sediment in two drainage basins of the Caspian Sea, with a humid climate, and central Iran, with an arid climate.
Methodology
For research surveys, pluviometersdata, sediment and discharge assessment, slope, topography with land use, and lithology were used. Maps were obtained from survey organization, geological survey and mineral exploration, and Natural Rescues of Iran. To this end, land use maps, based on the land use type, were classified into six categories including urban area, forests land, pasture land, agricultural land, swamp land, and arid land, without vegetation cover. In addition, the geological maps, based on the stone resistance and amount of sediment production, were classified into ten categories including the hardest stones, very hard stones, so hard stones, enough hard stones, mediocre stones, enough soft stones, partly soft stones, powder stones, loose stones, and so loose stones. Finally, the data was analyzed using the SPSS software.
Results and Discussion
The results indicated a high and significant correlation between the rainfall and sediment. There was also a direct and significant correlation between the rainfalls, discharge, and yearly sediment of the field. In addition, a fairly good model was achieved from the rainfall, discharge, and sediments variables.
Considering the distribution of the sediment in central Iran, the highest sediment volume was seen in the west of the basin at Shahrokh, Chamriz station. The lowest sediment volume, in contrast, was seen in its north and south. In the Caspian basin, the highest sediment volume was seen in Gharasou and Ran basin at Ghezaghli station. The second highest sediment volume was seen in Gharaghoni station at Sefidrood basin. The lowest sediment volume was seen in Talesh basin and in the southern stations of the Caspian Sea.
Ali Dastranj; Omid Asadin Nelivan; Sanaz Falah; Aboutaleb Salehnasab; Shirkou Jafari
Volume 2, Issue 4 , January 2017, , Pages 39-55
Abstract
Ali Dastranj[1]* Omid Asadi Nelivan[2] Sanaz Falah[3] Aboutaleb Salehnasab[4] Shirkou Jafari[5] Abstract Estimation of sedimentation and erosion without sediment statistics serves as one of the main issues of basins and requires the application of empirical approaches to utilize data for managing plans. ...
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Ali Dastranj[1]* Omid Asadi Nelivan[2] Sanaz Falah[3] Aboutaleb Salehnasab[4] Shirkou Jafari[5] Abstract Estimation of sedimentation and erosion without sediment statistics serves as one of the main issues of basins and requires the application of empirical approaches to utilize data for managing plans. EPM model is one of the empirical methods widely used in the study of watersheds all over country. The main objective of the present study is to evaluate the effect of geological formations on annual erosion and sedimentation using EPM model and GIS and the investigation of its efficiency in erosion and sediment studies. Rock formation erosion and entering of huge sediments to Taleghan reservoir clarify importance of investigation on how sediments are produced and transported. In respect to the above results, it is worthy to note that Zidasht basin is moderate in terms of erosions and sedimentation and its erosion coefficient is 0.69. In addition, classification of erosion intensity showed that this basin has two intense and moderate classes implying that considering sediment and erosion is essential in soil and water conservation projects. The highest and lowest erosion intensity coefficients are observed in Dint2 and D1 respectively mainly due to presence of formations Ngm, Q1g, and orchards in sub-basin Dint2 and resistant formations of Ekta and Ekv and suitable rangeland land use in D1. [1]- Ph.D Student; Watershed Management; University of Hormozgan (Corresponding author), Email:dastraj66@gmail.com. [2]- Ph.D Student; Watershed Management; University of Agriculture sciences and Natural Resource Gorgan. [3]- MSc Student of desertification, Department of Rangeland & Watershed Management Saravan University. [4]- PhD Student Forest Mnaagment, University of Tehran. [5]- Ph.D Student University of Tehran.
