M.R. Ansari; F. Soleimani; A. Ahmadi
Abstract
Introduction: Soil erosion is the most widespread form of soil degradation jeopardizing food security worldwide. In Iran, gully erosion is important because about 90% of the country has arid and semi-arid climates and rainfall is not adequately distributed. In such conditions, the absence or lack of ...
Read More
Introduction: Soil erosion is the most widespread form of soil degradation jeopardizing food security worldwide. In Iran, gully erosion is important because about 90% of the country has arid and semi-arid climates and rainfall is not adequately distributed. In such conditions, the absence or lack of vegetation cover with increasing runoff causes more than 2 billion tons of soil losses annually. Therefore, conducting basic and applied researches on soil erosion via different methods for comprehensive management of natural resources is emphasized. The prerequisite for all kinds of erosion, such as gully erosion, is the prediction of the risk of gully formation in different areas susceptible to erosion. Materials and Methods: The study area is located in Ghaleh Gorg watershed which sub-basin of Shahid Modarres that large part of these farmlands has been destroyed by gully erosion. The purpose of this study was to apply fuzzy logic operators for gully erosion zoning. In this research, six effective parameters on soil erosion including mean weight diameter of aggregate, sodium adsorption ratio, salinity, percent of fine sand, silt and clay were determined according to standard laboratory methods. After re-classification, standardization of prepared layers was carried out by the Fuzzy method. Hence, Fuzzy-based layers were integrated using operators of Fuzzy algebraic sum, Fuzzy algebraic production and Fuzzy gamma with 0.2, 0.5, 0.8, 0.9 values and the obtained results were evaluated. The validation of prepared maps was done based on two methods of map matching percentage of areas with very high and high sensitivity with gullies map of the study area and quality sum index (Qs). Results and Discussion: The Fuzzy results of raster layers showed the relative accumulation of silt, clay and fine sand grains in the middle to western parts of the region due to leaching and soil aggregation of Aghajari formation with a high slope of >20%. The deposition of this sediments was with 0-5% slope in the middle and western part of the basin. Results of layer integration indicated the fact that the fuzzy summation and multiplication method are not suitable approaches for final mapping because of their high increasing and decreasing effects, respectively. About Fuzzy Gamma operator 0.2, the results revealed that about 17.07% of the area was in the high and very high-risk zone and 67.07% of the area was in the low risk zone. In Fuzzy Gamma 0.5, about 31.16% of the area was in high risk and 55.38% in low risk zone. And only 60.38 percent of the gullies was in the high-risk area. Thus, these both operators 0.2 and 0.5 cannot be an acceptable method for preparing the final fuzzy map. The results of gamma operator 0.8 showed that about 43.21% of the area was in high and very high risk classes and 42.45% of the area was in low and very low risk classes. In the gamma operator 0.9, about 60.92% of the area was in high and very high risk zone and 17.1% of the area was in low and very low-risk zone. Also, regarding the distribution range of gullies, 94.93% of gullies was in high and very high risk classes, which is more acceptable and better than gamma 0.8. According to the obtained results, Fuzzy gamma 0.9 with 94.93 matching percentage of areas containing very high and high sensitivity and maximum quality sum index (0.73) among different operators was selected as the best method for preparing Fuzzy map in the study area. Conclusion: According to the results of this study and its comparison with field observations, effective factors contributing to the initiation and development of gully erosion were sensitivity of the geological formations, soil texture type, salinity and alkalinity and non-implementation of biological and biomechanical operations to the soil and vegetation cover restoration. Around 3855 hectares (60.38%) out of 6327.5 hectares of the total studied area were at high and very high erosion risk. Furthermore, 2056 hectares (94.93%) out of the 2166 hectares of the gullies area were at high and very high risk of erosion, denoting the high accuracy of the final map. Among the available methods, Fuzzy Gamma 0.9 with the highest overlap between the area of high and very high-risk classes of the gully map (94.93%), and the highest qualitative sum index (0.73), was selected as the best fuzzy method for zoning in the study area.
Amin zoratipour; mohammad moazami; mohammadreza ansari
Abstract
Introduction: During the last decades, important research efforts were conducted to identify and quantify the contribution of different sources delivering suspended sediment to the rivers. This knowledge also proved to be essential to provide estimations of catchment sediment budgets. The type of sources ...
Read More
Introduction: During the last decades, important research efforts were conducted to identify and quantify the contribution of different sources delivering suspended sediment to the rivers. This knowledge also proved to be essential to provide estimations of catchment sediment budgets. The type of sources (i.e. soil types, rock types, and land uses) to discriminate depends on the local catchment context. Generally, the targeting of sediment management strategies is a key requirement in developing countries because of the limited resources available. Proper implementation of the soil conservation plans and sediment control programs should be done to inform of the relative importance of contribution the sediment resources as well as identification of crisis centers in the watersheds. During the last decades, this approach has been increasingly applied to identify and ‘trace’ several distinctive characteristics of the source material that can be compared to the same characteristics measured on river suspended sediment samples. Todays, fingerprinting techniques, provide an appropriate method for rapid and low cost information on main sources of sediment.
Materials and Methods: in this study, the mentioned technique in the contribution of sediment resources, identify the critical units using the seven geochemical tracers' properties in the Dare Anar basin of Baghmalek in the Khuzestan province. The focus of this paper is upon quantifying the sources of suspended sediment transported on the Bakhmalek River in order to help guide future surface water sediment reduction efforts for turbidity-impaired streams. The statistical methods were used by the comparison of means and discriminant analysis, to select the optimal combination of tracers and contribution sediment sources. The geochemical tracers tested for their ability to distinguish between sediment sources with the Kruskal–Wallis one-way analysis of variance H test, which is able to test for the independence of more than two variables without presuming either normal or non-normal distributions. Tracers proving significance (p<0.05) between sources were retained. Tracers passing the Kruskal–Wallis H test that were non-conservative (suspended sediment tracer values that were not bracketed by sediment source tracer values) and removed before the performance of the mixing analysis. Tracers passing the first stage of statistical analysis were entered into a stepwise Discriminant Function Analysis (DFA) intended to optimize the number used in the mixing model. This analysis results in the smallest combination of tracers that are capable of correctly distinguishing 100% of the sources through the minimization of Wilks’ Lambda (Collins et al.1998). The analysis was run separately for each drainage basin using IBM SPSS Statistics v. 20.0. From the seven measurement fingerprinting properties, three of them were selected for geology formations and land use by statistics method such as discriminate analysis and compare means tests. Then, a portion of each source determinate by mixed models.
Results: Outputs from the discriminant function analysis show the discriminatory power of the final composite of tracers to be 100% successful in the sources classification for Catchment. Finally, among the seven selected tracer included the Lead, Zinc, Copper, Iron, Manganese, Nickel, and Chromium, have identified sediment sources by three elements included the Copper, Manganese, and Iron the amount 54.7, 31 and 14.3 percent respectively. Quaternary and Gachsaran formations, having the highest share in the sedimentary; the aspect ratio was 1.4 and 1.38 respectively. The poor pasture and forest land uses were responsible the highest and the lowest values of the basin sediment with 71.5 and 0.3 percent, respectively.
Conclusion: The mitigation of nonpoint-source pollutants, such as sediment, in larger basins is rarely a straightforward procedure due to the number of sources and erosional processes contributing to their concentration in waterways. Therefore, the fingerprinting techniques with the relative efficiency 98.2 percent, having the high accuracy and precision in determinate appropriate method to sediment sources basin and separated of the sediment active units. Low relative error and high model efficiency coefficient confirm the results. Also the field observation is the same as model results. The results were indicating the environmental management strategies must be comprehensive for the study area, that need to reduce surface erosion and hill-slope/channel connectivity and the control gullies development by the commercial cultivation and the range reclamation. Sediment fingerprinting revealed that stream bank erosion in general, and of legacy sediments in particular, from Quaternary and Gachsaran formations to Baghmalek River is at the root of the regional sediment loading problem.
