yasin salehi; Alireza vaezi
Abstract
IntroductionSoil erosion is the most important aspect of land degradation and one of the most important environmental, agricultural and food production problems in the world. More than half of the agricultural lands in semi-arid regions are under rainfed cultivation, and the tensions caused by erosion ...
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IntroductionSoil erosion is the most important aspect of land degradation and one of the most important environmental, agricultural and food production problems in the world. More than half of the agricultural lands in semi-arid regions are under rainfed cultivation, and the tensions caused by erosion and destruction of land are important in terms of the effects within the field of erosion, such as soil fertility, and the effects outside the field, such as soil pollution. Information about the size distribution of eroded particles is a substantial step for managing the loss of nutrients and the transfer of pollutants from the soil. For this purpose, this study was conducted to investigate the particle size distribution of sediments resulting from interrill erosion under the influences of slope gradient and soil texture in some soils of the semi-arid region of Zanjan Province. Materials and methodsToward this, four hillslopes having different soil textures (sandy loam, silty loam, sandy clay loam and clay loam) in four north-south slope percent (five, 10, 15 and 20%) were investigated using a simulated rainfall with an intensity of 60 mmh-1 for 60 minutes. In order to monitor the runoff and sediment samples from the beginning of the runoff until reaching a stable state, were taken at 5-min intervals from the initiation of runoff. The particles size distribution of sediment was determined by the method of particle separation using a series of sieves with diameters of 75, two, one, 0.5, 0.25, 0.1 and 0.05 mm. Also, the percentage of finer particles (silt and clay) was calculated by hydrometer method. Then the sediment particles are divided into eight categories: gravel (1-75 mm), very coarse sand (1-2 mm), coarse sand (0.5-1 mm), medium sand (0.25-0.5 mm), fine sand (0.1-0.25 mm), very fine sand (0.05-0.1 mm), silt (0.002-0.05 mm) and clay (<0.002 mm) were categorized. Results and discussionThe results showed that, with the increase in the slope of the land surface, the size distribution of sediment particles changed in all soils. So that, the transport of particles larger than 0.1 mm (including very coarse sand, coarse sand, medium sand and fine sand) increased with increasing slope. While the percentage of silt particles (0.002-0.05 mm) decreased in all textures. Also, particles with the size class of medium sand and fine sand formed between 40 and 50% of the sediment particles for each texture and did not change significantly with the increase of the slope. The highest ratio of particles in the sediment to the main soil was related to silt particles and in silty loam texture (4.33 times) and the lowest was related to clay particles and in silty loam texture (0.26 times). Sand and silt particles in different textures, had high transmission ratios. Silt particles in three textures of sandy loam, clay loam and silty loam had a ratio of more than one and clay particles less than one. Except in clay loam soil, sand particles changed in the range of 0.83 to 1.24 times compared to the main soil and the overall average ratio of its availability in sediment to original soil was 0.98 times. ConclusionIn general, this research showed that with increasing slope, the selectivity of fine particles decreases and the share of coarse particles increases. The effects of these changes are more visible in fine-textured soils. Due to the increase in the destruction of aggregates and flow rate with the increase of the surface slope, it is very important to prevent the removal of vegetation and observe the principles of tillage in order to reduce the direct impact of raindrops on the soil surface and reduce the transportability of particles by the flow. Also, the results show that the ratio of particles in the soil texture and the characteristics of soil structure (abundance and stability of aggregates) are the determining factors of particle transport and it is necessary to consider these characteristics in choosing soil conservation methods.
Ali Reza Vaezi; Ouldouz Bakhshi Rad
Abstract
Runoff is one of the major components of the hydrological cycle, which leads to soil loss from steep slopes and sediment production in watersheds. Investigation of effective factors in runoff coefficient is important in watershed management. The aim of this study was to investigate the effect of soil ...
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Runoff is one of the major components of the hydrological cycle, which leads to soil loss from steep slopes and sediment production in watersheds. Investigation of effective factors in runoff coefficient is important in watershed management. The aim of this study was to investigate the effect of soil properties on runoff coefficient in Alanagh, Livar and Shekaralichay sub-basins in East Azarbaijan Province. After soil sampling, some physicochemical properties were measured and runoff data were obtained from the relevant stations. Based on the results, runoff coefficient in the studied sub-basins is affected by various soil properties such as particle size distribution, gravel, organic matter, lime, aggregate size and stability, and saturated hydraulic conductivity. As the percentage of sand and gravel increases and the percentage of clay and silt decreases, soil permeability increases and runoff coefficient decreases. Organic matter and lime are two important factors in the aggregate formation and stability, and improving the saturation hydraulic conductivity which plays a key role in reducing runoff production. The results of multiple linear regression analysis showed that runoff production in the Alangh sub-basin has a significant relationship with soil organic matter (r=-0.95, p<0.01) and bulk density (r=0.9, p<0.01). Organic matter content has the main role in runoff production in Livar sub-basin (r=-0.94, p<0.01) and Shekaralichay sun-basin (r=-0.95, p<0.01). Runoff coefficient in all sub-basins in the area is strongly related to organic matter content (r=-0.86, p<0.01), soil structure stability (r=-0.68, p<0.01) and stream density (r=0.49, p<0.01). This study showed that preserving and increasing soil organic matter can be an effective strategy in conserving rainwater and reducing runoff by improving soil structure and permeability.
Jalal Heidari; Alireza Vaezi; Mohammad amir Delavar
Abstract
The variety of factors affecting soil properties leads to temporal changes in the soil erosion process. This research was conducted to assess short-term changes in runoff and soil loss in rainfed wheat furrows under fallow conditions. To this end, three rainfed lands with 15% slope gradient were selected ...
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The variety of factors affecting soil properties leads to temporal changes in the soil erosion process. This research was conducted to assess short-term changes in runoff and soil loss in rainfed wheat furrows under fallow conditions. To this end, three rainfed lands with 15% slope gradient were selected in south west of Kermanshah Province. In each land, furrows with five m in length and 30 cm in width were created using sowing set. Runoff and soil loss were measured using simulated flows with a discharge of 0.5, 1, 1.5 and 2 L.min-1 at intervals of five minutes to 60 minutes 60 minutes in three replications. Results showed that the lowest soil loss was recorded in flow discharge of 0.5 L.min-1 (2.66 g.m-2) and the highest of soil loss was produced in flow discharge of 2 5 L.min-1 (85.33 g.m-2). Also, the lowest runoff was recorded in flow discharge of 0.5 L.min-1 (0.47 L) and the highest of soil loss was produced in flow discharge of 2 5 L.min-1 (7.65 L). The effect of time on runoff and sediment variables was significant in all flow discharge (p<0.01). Runoff production was low at the beginning of the experiment and increased over time. The pattern of temporal changes in soil loss was different from runoff production, amount of soil loss at the beginning of the experiment was higher values than the final test times, which associated with to supply of erodible soil particles in the rills in the beginning of the experiment. With starting the experiment to 25 minutes, the rate of soil loss changes drastically and then until the end of the experiment, it followed a uniform reduction pattern and in the final stages, it is almost constant. The results showed that rill erosion is strongly influenced by flow intensity and its value changes over time and these changes are independent of flow production and depended on the transmittance of soil particles transferable in the rill.
Adele Alijanpour Shalmani; Alireza Vaezi; Mahmoudreza Tabatabaei
Abstract
Analysis of suspended sediment load data in rivers is the basis for understanding the trend of erosion and sediment in the management and planning of soil and water resources. Due to lack of access to daily suspended sediment loading data with direct measurement, it is important to use methods for modeling ...
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Analysis of suspended sediment load data in rivers is the basis for understanding the trend of erosion and sediment in the management and planning of soil and water resources. Due to lack of access to daily suspended sediment loading data with direct measurement, it is important to use methods for modeling and estimating it in watersheds. One of the best methods used in this field is the use of artificial neural networks. To evaluate daily suspended sediment load, Sira hydrometric station was studied in Karaj River watershed. The number of data used in this study included 624 information records of 31 years (1981–2011) statistical period .Input data to the artificial neural network models included instantaneous flow discharge, average daily flow discharge, average daily flow discharge with a delay of three days, average daily precipitation and average daily precipitation with a delay of three days. Output data to models was daily suspended sediment load. In this research, gamma test and genetic algorithm were used to obtain optimal variables and best combination of variables for entering the model. Then, these combinations with some combination of test and error variables were entered to artificial neural network models. The self-organizing map neural network was used for data clustering and all data were divided into three homogeneous groups: 70 percentage training data, 15 percentage validation data and 15 percentage test data. Then, the combination of variables entered to neural network models with activation functions log sigmoid and tangent sigmoid. The results showed that the neural networks using the optimal variable combinations in comparison with manual combinations have a more accurate estimate for suspended sediment load. In all combinations of inputs to neural network models, a model with tangent sigmoid activation function, with input variables combination including, instantaneous flow discharge (Q), average daily flow discharge (Qi), average daily flow discharge for two day ago (Qi-2), average daily flow discharge for three day ago (Qi-3), average daily precipitation (Pi), average daily precipitation for two day ago (Pi-2) and average daily precipitation for three day ago (Pi-3), was the best model for estimating daily suspended sediment load. This model has the lowest of error (MAE=500.05 (ton/day), RMSE=1995.33(ton/day) and Erel=7%), the highest accuracy (R2=0.96), the highest performance model (NSE=0.96) and has the lowest general standard deviation (GSD=0.97) compared to other models. Also, this model is the best combination with the most influential input variables derived from gamma test and genetic algorithm for estimating SSL.
