JWSS - Journal of Water and Soil Science

One of the major issues in the contemporary world is climate change. The behavior and characteristics of parameters affecting climate change can cause them to be seen and hidden. As one of the effective ways to detect overt and covert behaviors for periodic climatic data series, Spectral analysis can be used. It is the analysis of each of the wavelengths series, making this behavior clear. Accordingly, the present study was an attempt to use the method of spectral analysis, data cycles in the minimum temperature, maximum temperature and precipitation in Ramsar station (located in the western regions of Mazandaran province) an nd Babolsar (located in the central parts of this province) in a period from1961 to 2014. For this purpose, temperature and precipitation data were obtained from these stations; MATLAB software environment and the environment for the software were logged for each of the variable in the stations. The results revealed that the minimum temperature at both stations had significant cycles, with the return period being 2 to 5 years; Remote Link could be fit into the cycle parameters such as NAO, AO and ENSO. Analysis of the period gram showed cycles 8 and 5/13-year-old and 5-year-old period in Ramsar and Babolsar. During the rainy cycles, the difference between the two stations and the difference in the geographical position affected systems, and rain accounted for the difference in speed dual-zone climate indicator for Remote Link.

In recent years, the joint distribution properties of drought including severity and duration have been widely evaluated using copula. Few studies, however, have worked on drought modeling based on stream flow, especially in semi-arid regions such as the southern regions of Iran. This study followed two purposes. The first purpose was to find the appropriate marginal distribution function for hydrologic drought duration and severity, and the other one was to find appropriate copulas. First, the severity and duration of hydrological droughts in the hydrometery stations in the Karkhe basin were extracted by the run’s theorem, and the absence of trends was tested using the modified Mann-Kendall trend test. Appropriate marginal distribution functions for duration and severity drought were derived by using the linear moment's method. In addition, copula’s parameters for Frank, Clyton and Gumbel families were calculated by both direct and indirect methods. The best copulas were selected by the goodness of fit tests. Finally, the joint and conditional return periods for duration and severity drought were derived for each station. The results showed that drought severity and duration for all hydrometery stations in Karkhe basin followed both the generalized extreme value marginal distribution function and Gumbel copulas family, which could be used for regional copulas modeling.

Flood discharge estimation with different return periods is one of important factors for water structures design and installation. On the other hand, a lot of rivers existing in Iran watersheds have no complete and accurate hydrometric data. In these cases, one of the suitable solutions to estimate peak discharges with different return periods is the regional flood analysis. In this research, 55 hydrometric stations were used. For this purpose, at first, peak discharges in different return periods were estimated using the EasyFit software. Then, the effective variables on the peak discharges were collected and the input variables of the models were selected by using gamma test with the help of the WinGamma software. Finally, data modeling was performed using the support vector machine, artificial neural networks and nonlinear multivariate regression techniques. Quantitative and qualitative assessment of the results using various indices including Nash-Sutcliffe Efficiency Coefficient (NSC) showed that SVM modeling method had the most accuracy in comparison to the other two modeling methods to predict the peak discharges in the Namak Lake Watershed.

Changes in Climate parameters have been accelerated in the coming age, which can affect agricultural activities directly and indirectly. Temperature and precipitation are the most complex climatic factors. Spectral analysis is a scientific and efficient technique used to recognize and detect the hidden behaviors of these variables. In this research, in order to study and analyze the temperature and precipitation return periods using spectral analysis, the statistics of climate parameters (precipitation, mean, maximum and minimum temperature) for a period of 27 years (1989-2015) were used for the sustainable land management. For this purpose, the climatic data of temperature and precipitation entered the MATLAB software environment and Periodogram of each of the climatic parameters was drawn in a separate way. The results of each Periodogram study showed that the absolute minimum of temperature had significant cycles with the return periods of 3.8 and 2.4 years; the absolute maximum of temperature had a significant cycle with a return period of 2.1 years and the mean temperature was significant with a return period of 2.7 years. Also, the review of the Periodogram related to precipitation showed a significant cycle with a return period of 3.4 years. The Results from studying cycles indicated the existence of short-term return periods for climate variables in the region. Given this issue and the need to protect agricultural products, especially garden products, it should be done by applying water and soil resources management methods, including creating terraces and increasing soil roughness; Also, cultivation of appropriate plant species for the suitable regional climatic conditions, Drought resistant and low water requirement, the most optimal conditions could be created for the cultivation of horticultural and agricultural products.

Simulation of the hydraulic behaviour of the river basin boundaries is important for river engineering projects, prediction of flood damages in different conditions and economic feasibility studies, flood control, and other social programs related to the system of the river. In this study, river bed and flood zoning map in the range of over 155 km from the Zayandehrud dam to Nekouabad Diversion Dam were addressed by using the software's ArcGIS, HEC-RAS and HEC-GeoRAS extension. For this purpose, a digital elevation map in 1: 250,000 scale was provided and cross-sectional area was divided in 1085. Manning roughness coefficient was determined by Cowan. Finally, data entered into the software HEC-RAS and was analysed. After determining the area of flood in the return periods of 2, 5, 10, 25, 50, 100 and 200 years in all cross sections, the results were entered into the ArcGIS environment and flood zoning maps were obtained. The results showed that of the 200-year flood lands, 96% of the land flood was related to the return period of 25 years.