algorithm

Suspended Load Concentration (SLC) estimation is one of the most important environmental and engineering issues in the coastal zone. The SLC distribution pattern near the coast can be determined by in situ measurement and combination with remote sensing products according to the topography and the types of dominant currents in the study area. The research objective was to identify the spatial and temporal variations of the surface SLC in the Hendijan Delta (Northern Persian Gulf) using remote sensing technique. The water samples were taken from more than 60 stations during the passage of the Landsat 8/OLI satellite over the study area on Feb. 20, 2016 and Feb. 6, 2017. The range of SLC variations was obtained between (0-740)  mgl-1. Atmospheric correction was applied using SWIR algorithm on Landsat 8/OLI images to estimate the net water reflectance. There is a high correlation between  provided from satellite data and the measured SLC. The empirical algorithm got an exponential form with the combination of the bands 4 and 5 performed using statistical tests. For developing this algorithm more than 50 types of equations were assessed. The proposed algorithm determines the SLC from the Landsat 8/OLI images with Pearson’s 0.93, root mean square error 28.12 mgl-1 and relative root mean square error 34.24%. The algorithm was applied to timescale of satellite images, and the spatial distribution of suspended sediment concentration has been mapped over the Hendijan Delta. According to this results, the rate of decline in SLC from near the coast to the distance of 5 km of the Hendijan Delta was estimated about 2800 to 20 mgl-1 on Feb 20, 2016 and 800 mgl-1 on Feb 6, 2017. Landsat images can be used effectively to retrieved SLC in the Hendijan River Delta.

Natural phenomena could be recognize through the selection and then produce the appropriate scale. The critical subject in this way that have been less studied in Iran is identifying the multi-scale algorithms and distinguish them from simplification algorithms. In this research, operation of each multi-scale algorithms at certain scales have supposed, then implementation of structural simplifying algorithms- low pass filter and simple average- in order to identify the flood process using three Digital Elevation Models at 1:25000, 1:50000, and 1:1000000 scales in ArcMap software and HEC-HMS model have evaluated. Results demonstrated that different approaches of map production make different results as the generalization and the best approximation of spatial data. Comparing the result of flood simulation proved sensitivity of such algorithms with respect to scale of base map. It has been specified that the effect of generalization algorithms do not necessarily conform the hierarchical structure of scale of input data. Finally, we suggested to investigate the flood phenomena of Jamash watershed, we should use low pass filter and simple average algorithms to simplify DEMs at 1:25000 and 1:1000000 scales but using these algorithms at 1:50000 scale have not suggested.

Two factors of cost and time are related directly to the accurate estimate of runoff in the watersheds. More detailed information on the status of rainfall runoff also facilitate decisions on future programs for watershed managers, a step towards the preservation of natural resources for sustainable development. In this study, in order to achieve optimal amount of runoff in the Shafaroud watershed, first significant rainfall data of four stations during 1998 to 2011 were collected and combined with other maps of the study area, such as DEM, land use and soil as input data in the form of SWAT model was software. After running the model, the SUFI-2 and GLUE algorithms in SWAT-CUP program used to evaluate the data uncertainty and the most accurate simulation. The first three years (1998-2000) of rainfall data for warm-up and the next 7 years (2001-2007) for the calibration and final 4 years (2008-2011) were used for the validation. Finally, with multiple simulations, the uncertainty of the parameters assessed with P-factor, R-factor, and NS coefficients. The results indicated in runoff simulation, the SUFI2 algorithm ( =0.85, NS=0.74) is more accurate than GLUE algorithm ( =0.82, NS=0.71).

The wind plays an important role in different hydrologic phenomenon such as spatial distribution of snow accumulation. In order to compare the function of the wind in different locations of the basin، a magnitude called wind shelter index is being used، which its calculation encounter special difficulties because of its need to various information. An algorithm has been presented in order to reach an efficient method to determine wind shelter index. The results showed that the presented algorithm can be used more easily by the users، and it is more qualified for calculating wind shelter index of all the optional locations placed on the surface of the basin، in comparison to the direct method of calculating wind shelter index.