r. modarres

This study was conducted to present rangeland bioclimatic zoning for Iran based on the changes in the power spectrum of the average monthly Net Primary Production (NPP) of the rangelands of Iran. Fluctuations of the mean monthly power spectrum of the NPP signal of rangelands of Iran from 2000 to 2022 were analyzed using the Power Spectrum Density (PSD) method in the frequency band between 0-100 Hz. In 24 bioclimatic subzones, there are four common periods in all sites at frequencies of 0 (no change is repeated), 8.34 (3.59 days), 16.66 (1.80 days), and 25 (1.2 days) Hz observed, which shows that the major data changes occur in those periods and that the NPP changes of Iranian rangeland are more influenced by global and regional effects than local effects. The maximum power of these spectra is concentrated in high time scales. Therefore, cycles with lower frequency (higher time scale) are more important than cycles with higher frequency (shorter time scale) and show that the changes of NPP in Iranian rangelands have long-duration cycles under climate fluctuations. In the present research, Iran was classified into 5+1 rangeland bioclimatic zones using the results of the monthly mean power spectrum of the NPP signal of rangelands, the Wards clustering method, and the Euclidean square distance. It seems that this method provides a proper match between biological boundaries and climate. Pearson correlation coefficient was used to investigate the coherence of rangeland bioclimatic regions within each homogeneous group. Correlation results showed a significant spectral density similarity within groups at the significance level of 0.01% between rangeland bioclimatic regions, especially in the second and fifth clusters.

Drought is one of the most destructive and important climate phenomena, whose effect is usually more important on a regional scale. The importance of this phenomenon is more evident in the Karkheh basin due to its size and important role in providing the country's water resources. We aim to monitor hydrologic drought using the accurate calculation of standardizes streamflow index (SSI) in one month time scale based on fitting frequency distribution to monthly data and goodness of fit test for each station in Karkheh basin for 30 years (1986-2016). The findings of this research showed that the generalized Pareto distribution was selected as the most appropriate distribution in most months, unlike the previous research that fitted and used only the Gama distribution on the data. The time series of the standard flow index indicated the occurrence of super-drought in 2008 to 2015 years. Also, the significant impact of the construction of hydraulic structures upstream of the basin on the average flow rate was observed in some stations. The results of direct and annual monitoring of the drought situation showed that the Karkheh basin has experienced hydrological drought in recent years, and the drought trend is increasing.

Environmental flow of the Beshar River was evaluated using Tennant's hydrological method, the comparison of the depth and speed of the water in the transverse sections of the river, and the needs of indicator fish species in different stages of the life cycle. Field samplings were conducted in October and January 2021 to monitor the status of fishes in the Beshar River and to collect cross-sections of the river. Indicator species were selected based on the expert judgement survey method. Among 23 fish species of the Beshar River, five species from the Cyprinidae family recieved the highest scores. The biological requirements of these species were extracted and used as the basis of comparison with the data of cross sections of the river. The obtained results showed that in the upper reaches of the river (between the two hydrometric stations of Qalat and Shah Mokhtar) the good class of the Tennant method, that includes 40% of the average annual discharge for the period of high flow (April to May) and 20% of the average annual discharge for the period of low flow (June to November), is suitable to provide the biological requirements of adult and larva of cyprinid species of the Beshar River, respectively.

Vegetation cover is an important component of terrestrial ecosystems that changes seasonally. Accurate parameterization of vegetation cover dynamics through developing indicators of periodic patterns can assist our understanding of vegetation-climate interactions. The current study was conducted to investigate and model vegetation changes in some phytogeographical regions of Iran including, Khazari, Baluchi, semi-desert, temperate steppe, warm semi-steppe and arid forest and to compare their stochastic behavior. To study the vegetation changes the net primary production (NPP) was used, based on the products of Moderate Resolution Imaging Spectroradiometer (MODIS) sensor (MOD17A2 series). Seasonal Auto Regressive Integrated Moving Average (SARIMA) time series model was used for modeling NPP. The Autocorrelation Function (ACF) and Partial Autocorrelation Function (PACF) of time series showed that these areas were static with seasonality in 12-month periods. It also showed that the vegetation in Khazari region was more stable, which indicates a stable environmental condition with the least deviation in water, light and nutrients. We also found that most of the vegetative regions of Iran can be modeled with SARIMA and its changes can be reliably predicted. Estimated models for Khazari (Root-Mean-Square Error, (RMSE) = 0.12, R2 = 0.87, Mean Relative Absolute Error (MARE) = 0.083) and semi-desert (RMSE = 0.12, R2 = 0.95, MARE = 0.048) were more suitable models than other regions.

Dust storms in arid and semi-arid regions have harmful impacts on the environment, the economy, and the health of local and global communities. In this study, the frequency of annual dust events in twenty-five stations and five climatic variables including rainfall, maximum annual wind speed, average annual wind speed, maximum annual temperature, and average annual temperature in arid regions of Iran up to 2014 were used to show the effects of climatic change on dust storms. Annual correlation coefficient time series between climatic variables and dust storms were first calculated based on monthly observations. Then, the trend in climatic variables, dust storm frequency, and their correlation were assessed using the Mann-Kendal method. Results indicated that the correlation coefficients had fluctuations in time and are both significant and insignificant in different years that reach from 0.6 to 0.9 for wind speed and temperature and -0.2 to -0.6 for precipitation. This trend in correlation has the same direction with climatic variables and shows co-movement between climatic change and dust storm fluctuations in central Iran. Results also showed that wind speed and temperature have a high impact on dust storm fluctuations and rainfall reduction has an increasing effect on dust storms.

Several indices are used for drought identification and quantification. In this paper, the new Standardized Palmer Drought index (SPDI) was introduced and then the drought condition of Chaharmahal-Va-Bakhtiari Province was studied using this index. For this study, 11 synoptic, climatology, and evaporation meteorology stations were selected. Essential information in this investigation includes monthly temperature, monthly precipitation, and soil moisture measurement. To estimate SPDI, moisture departure, was first calculated on a monthly time scale. Then, converted to cumulative moisture departure values in different time scales including 3, 6, 9, 12, and 24 months. The best statistical distribution (GEV) was then fitted to cumulative departure. These values were then standardized to have the SPDI. The results showed that, as soil moisture affects SPDI estimation, it will be more valid for analyzing and monitoring drought conditions, especially for agricultural drought. Also, the results showed that 2000, 2001, and 2008 years were the driest time in this Province from 1988 to 2012. Moreover, drought frequency was found out in the western half of the Province more than in the other parts.

Drought, as one of the most complicated natural events, causes many direct and indirect damages each year. Hence, single variable identification and monitoring of drought may not be appropriate enough for decision-making and management. In this study, in order to monitor the meteorological-agricultural drought in Chaharmahal and Bakhtiari province, Multivariate Standardized Drought Index (MSDI) was calculated using precipitation and soil moisture variables. In addition, to evaluate the performance of MSDI in drought identification and monitoring, Standardized Precipitation Index (SPI) and Standardized Soil Moisture Index (SSI) were used for meteorological and agricultural drought monitoring, respectively. MSDI was calculated based on the soil moisture and precipitation joint probabilities. We used the Gringorten probability as an empirical method and Archimedean copulas as the parametric method to calculate the joint probability between soil moisture and precipitation time series. The results indicated that MSDI was twice more capable of detecting drought as SSI and SPI. Furthermore, the MSDI-based drought monitoring results showed Charmahal and Bakhtiari province had experienced severe meteorological-agricultural drought in 2000, 2008, 2011 and 2014.