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AbstractIntroduction: One of the solutions for flood management is flood zoning in different return periods, which can be an essential tool in determining development strategies and reducing flood damage. Calculating flood damage in existing uses provides useful information for various organizations such as insurance to be aware of the amount of damage in different uses in the event of a flood.Methods: The study area is located in Rudak basin. In this regard, first maps, required hydrological data and DEM of the study area were prepared. Then, according to the flow data, the maximum annual moments in Rudak hydrometric station were fitted with normal log distribution (as the best distribution) and the flow rate was obtained in four return periods. Then, a single hydrograph was obtained by SCS method for different return periods. Then, using the HEC-RAS2D model, the flood zone with the mentioned return period is obtained and finally, based on the global damage-depth functions, the amount of damage in the return period is based on different uses, including residential, commercial, agricultural, roads was calculated.Findings: By comparing the results of flood zoning and damage maps, which with increasing flood return period, the amount of damage and the area of ​​high-risk zone increases. The amount of flood zone in the return periods of 5, 25, 50 and 100 years is equal to 17.9, 18.9, 19.4, 19.9 hectares, respectively. Most of the damage is related to agricultural lands and then lands with commercial use. The rate of increase in damage to the area between floods 5 and 25 return period is about 47%, between floods 25 and 50 return period is about 6%, and between floods 50 and 100 years is about 15%. Therefore, a 50-year flood can be proposed to determine the flood protection plans of the region.

Extreme climatic events are associated with climate changes. Understanding the diversifications in these events is important in planning to reduce their effects. In this research, using daily temperature data of 8 synoptic stations in the north and west of the country, 18 extreme temperature indices as defined by the Expert Team on Climate Change Detection Indices (ETCCDI) were evaluated. The results showed that the temperature intensity indices at night had a higher trend than the temperature intensity indices during the day. The frequency of the hot night index and hot day index in most of the studied stations had a significant increasing trend. Moreover, the cool night frequency index had a negative and significant trend in the north and west of the country and showed a higher trend in the north of the country than in the west. The cool day frequency index was negative for both study areas. Cold extreme indices including the number of cold days, number of frost days, and cold spell duration index were obtained in both regions of the country with a negative trend. While warm indices showed the number of hot days, warm nights, and warm spell duration index with a positive and significant trend.

Accurate information about the amount of moisture and its fluctuations can provide a suitable solution for preparing soil surface moisture maps, predicting the occurrence of soil storms and dust, forecasting floods, droughts, and other climatic phenomena, determining the irrigation time table and the grazing season. In this study, the Perpendicular Soil Moisture Index (PSMI) extracted from Landsat 8 images was used to estimate and determine surface soil moisture. Using field data, the relationship between this index and soil moisture was determined. After radiometric and geometric corrections of images and normalization of field data, processing of satellite images and extraction of PSMI index were performed. Simple regression analysis between field data and index values ​​was performed at different times. Then, the accuracy of produced maps was determined with statistical indicators including coefficient of correlation (R2), root mean square error (RMSE), mean absolute error (MAE) and Nash Sutcliffe efficiency coefficient. The results showed that estimated values with the PSMI index are completely dependent on the season and vegetation status. In the growing season and with high greenness coefficient, the accuracy of estimation was high. In dormant seasons, vegetation had a weak and moderate correlation with field data. The average coefficient of R2 in all sampling times was about 0.65. From the findings of this study, it can be concluded that this index can be used to monitor soil moisture in areas with suitable vegetation, irrigation planning in agricultural areas, and the beginning and end of the livestock grazing season.

The meteorological drought phenomenon and its relationship to the hydrological response of the catchments are of particular importance in the development of programs related to the comprehensive water management of the basin. In this study, a common period (1982-2017) in five corresponding hydrometric and rainfall stations in the Kashkan watershed was considered. The regression relationship between rainfall and discharge was investigated. Then, the standardized precipitation index (SPI) and the standardized discharge index (SDI) were calculated in time scales of 3, 6, 9, 12, 18, and 24 months. The interrelationships of SPI and SDI in sub- catchments were analyzed using the correlation method. The results showed that in more than 50% of the study period, the meteorological drought was close to normal. hydrological drought investigation of the sub-catchments showed that in the catchments with fewer karst formations, the frequency of years with severe drought was higher. The maximum drought with a severe situation in the Afrine catchment was 20% and the minimum was 6% in the Cham-Anjir catchment. The trend of changes in correlation coefficients between SPI and SDI in Sarab- Seyed Ali, Pol-e Dokhtar, and Cham-Anjir were similar and the maximum was at 18- and 24-month time scale with a coefficient determination of 0.67.

Low flows are one of the most important hydrological parameters required for quantitative and qualitative analysis of watersheds and play an important role in water resources engineering and management. In this study, 9 low flow indices including mean annual 3,7,15,30, days average minimum flow, flow duration curve indices (FDC) and exceeded 95, 90, 75 and 25% of the time respectively, and base flow index (BFI) were used. Daily stream flow of 20 hydrometric stations with a period of 30 years were used. BFI was extracted using One-parameter recursive digital filter algorithm and FDC indices were determined by plotting FDC. Then, the relationships between selected indices were analyzed. The results showed that there was a good correlation between base flow and FDC indices with a coefficient of determination above 68%. MAM3, MAM7 and MAM30 indices had a good correlation with a coefficient of determination higher than 0.90 and a suitable standard error for FDC indices that can be used for regional analysis of low flow. The MAM30 low flow showed the minimum standard error and the maximum coefficient of determination with FDC indices. The MAM15 low flow index had no correlation with FDC indices and not recommended for regional analysis of low flow in the research area.

One of the climate change impacts is an increase in the severe drought frequencies. Recently, low flow frequency analysis has been considered in the study of hydrological drought. This study aims to forecast low flow by 2099 in the Kan River Basin in order to assess climate change impacts on low flow in this region. For this purpose, temperature and precipitation data were simulated by HadCM3 model using SDSM downscaling model under the scenarios A2 and B2 by 2099. Runoff simulation was estimated using SWAT while calibration and validation were implemented using the SWAT-CUP software and SUFI-2 algorithm. The optimal parameters obtained from monthly and daily calibration were projected via SUFI-2 algorithm. The results showed an increase in temperature but decrease in precipitation rate, which in the most pessimistic scenario, proves an increase in maximum temperature up to 4.2 °C and for the precipitation, a decrease down to 10.8% by 2099 is expected, as well. Furthermore, the accuracy analysis of the simulated runoff based on the monthly and daily calibration results showed a good fit between observed and simulated values. In fact, their correlation coefficient with the measured values differed less than 0.03. Meanwhile for maximum flow values, daily calibration led to a more accuracy. The results of runoff forecasts showed a decrease in runoff, which is expected for spring and summer however an increase would be for autumn and winter. Overall, a 15 to 21 percent reduction in runoff was projected by 2099.

Flow duration curve (FDC) is one of the most appropriate criteria for recognizing the hydrological response of catchments. Understanding the interaction of drought phenomenon along with FDC indices is a suitable tool for optimal water resources management of catchment. The aim of this study was to investigate the temporal relationship between drought and FDC indices in the Kaka-Reza, karstic catchment. In this study, the common period (1982-2017) was considered for the corresponding hydrometric and rain gauge stations. The standardized precipitation index (SPI) and standardized discharge index (SDI) were then calculated at time scales of 3, 6, 9, and 12 months. Precipitation duration curve (PDC) and FDC were plotted and curve indices were calculated and standardized. The relationships between drought index and FDC indices were investigated and analyzed. The results showed the general trend of changes in SPI and SDI in the respective time scales follow each other. However, the most consistent trends are related to the time step of three months. The rate of relative changes in the section of low flow indices (Q90/Q50) were very small and around 0.6% and in the high flow (Q25/Q50) was around 4.41%. The correlation between FDC and PDC showed coefficient of determination of 0.904. The rate of slope change was from 0.5 to 5% and trend of its changes was a slight upward slope during the research period. The small amount changes of FDC indices and slope of FDC showed the role of karst phenomenon in determining the shape of FDC as well as controlling flow fluctuations and providing stable flow during the drought period.

Effect of meteorological drought on vegetation conditions and their relationships with each other was investigated in the Province of Lorestan. The standard precipitation index (SPI) as a meteorological drought index was used for 28 rain gauging stations during the years 1987-2017 in that province. Benefiting from the remote sensing and MODIS images, the normalized difference vegetation index (NDVI) was extracted for the years 2000-2017 and the vegetation condition index (VCI) was calculated. Using the SPI results, the dry, normal and wet years were identified and the index year was selected for them. The correlation between the SPI and VCI was investigated using linear regression. The results indicated that the highest correlation coefficient of Pearson was related to the VCI in March with a 9-month SPI in November was equal to 0.64; the correlation coefficient between the multivariate linear regressions of the SPI with VCI in June was 0.7. The results of multivariate linear regression indicated that the SPI had a significant correlation with the VCI at the five percent level over a period of 9 and 12 months. A confusion matrix was used to evaluate the compatibility of the SPI drought classes with the VCI; the results also indicated that the highest compliance of the VCI with the SPI was in the moderate drought class. Furthermore, the results of this study indicated a 9-month delay in the meteorological drought index with satellite drought index at the 5 % level significance of the SPI with the VCI, which indicates that the VCI may be used in the absence of meteorological indicators for the study area.

In recent years, over using of water, climate and land use changing in different river basins, have had different impacts on the river flow, particularly low-flow. With respect to the extraction of the groundwater resources and its effect on event time and the length of this time, it is essential to study the low-flow in different stations. The purpose of this study was to investigate and determine the trend of spatio-temporal low-flow in selected hydrometric stations in Alborz south mountains basins. For this purpose, daily discharge data were collected for different hydrometeric stations within the study area and 39 stations were selected. Daily discharge of these stations were reconstructed with correlation method and outliers were eliminated. Then, the time series of 5, 7, 10, 15, 30, 60 days of stations were calculated. Basins were then clustered into two classes including plain and no plain. The trend of low flows was calculated using Mann Kendall, Teil-sen, and spearman tests. For each cluster, a regression relationship was established between the low flow trend and basin upstream area. Results showed that about 10 stations had no significant trend and other stations found have significant negative trend at 1, 5, 10% levels. Plain basins experienced lower negative low flow trends as the basin area increased, which could be attributed to the over extraction of groundwater resources, but in no plain basins direct correlation was obtained as area increased.

Introduction and Background: Precipitation is the most important parameter affecting various aspects of social, economic and natural resources. A study of future changes in rainfall is possible through the prediction of climate models. Aims: In the present study, future changes in the rainfall of the southern coasts were investigated for proper planning in the southern coast of the Caspian Sea. Methodology: The future precipitation of selected stations in the southern shores of the Caspian Sea using the LARS-WG model and observations of precipitation data during the base period and using climatic fluctuations derived from the HadCM3 general circulation model under the scenarios A2, B1 and A1B during the period was modeled in the period between 2011-2039. Conclusion: Results showed that simulated rainfall has a high correlation with observational precipitation in the base period. Based on the MBE and MAE criteria, the error rates obtained for simulated precipitation during the base period are high in the fall season. According to the results, the model of rainfall changes in southern shores in the following period was drawn using scenarios A2, B1 and A1B, according to which the rainfall will increase in all stations of the region. The percentage of precipitation increase in stations Anzali, Astara, Babolsar, Gorgan, Noshahr, Ramsar and Rasht based on scenario A2 will 0.3, 7.9, 2. 2, 1.4, 8.7, 0.8 , 7.6%, and based on the A1B scenario, 9.3%, 12.12%, 12.4%, 4.7%, 13.9%, respectively and based on the B1 scenario will be 8.7, 9.7, 6, 5/11, 7/3, 3/5, 6/13 percent.