جستجوی مقالات مرتبط با کلیدواژه « شاخص بارش استاندارد » در نشریات گروه « آبخیزداری، بیابان، محیط زیست، مرتع »

Drought is one of the most important natural disasters that threaten human societies. Various indices are employed for drought monitoring. The purpose of this study is to evaluate and monitor the drought phenomenon based on two indicators of standardized precipitation (SPI) and standardized precipitation-evapotranspiration (SPEI) in Hormozgan province. SPI index is calculated only based on precipitation data, and SPEI index is calculated based on precipitation data and evapotranspiration potential values Torrent White method) of drought. For this study, monthly precipitation data and average monthly temperature data of five synoptic stations of Bandar Abbas, Bandar Lengeh, Hajiabad, Minab, and Bandar Jask for a period of 30 years (1988-2017) were used. The results showed that although the values of SPI and SPEI index were correlated, SPEI index was more sensitive to drought and faster response to it and showed longer dry and wet periods. Comparison of SPI index values of different climate stations revealed no significant difference between their SPI values. It was also found that there was no considerable difference between SPEI index values for selected stations. Finally, the findings showed that the spatial distribution of the SPI index was more uniform compared to that of the SPEI index in Hormozgan province.

Drought is one of the most important climate phenomena which occurs in all climate conditions and most of the regions on the earth and brings in a lot of injuries to human and natural ecosystems. Therefore, it is important to investigate drought‛s characteristics including intensity, duration and its frequency and to find out their regional risk and forecasting, too. For this reason, some of rain gauge stations in Kheirabad watershed in which their data had been recorded until the end of water years 2011-2012, were selected. Drought conditions for each station were investigated for four different periods including three monthly and one annual periods, using Standardized Prediction Index. Then, drought prediction was performed using SPI values modeling using ARIMA and SARIMA time series. The results showed that in most of the studied time periods, the droughts in the Khyrababad basin are often of medium drought and wet years are of the same type. Study of the persistence of dry and wet periods in selected stations indicates that drought and wet years are more likely to be 1 and 2 years old and have more frequency than other dry and wet periods but the continuity of the normal situation, even for 5 years or more, has been observed in some stations, including the Boyeri and the Nazmakan. The results of drought prediction using time series show that the ARIMA model can better predict SPI values and increase the time interval from 12 months to 48 months more appropriate prediction. Also, the results of the evaluation of the models show that by increasing the time scale from 12 months to 48 months, the slope of the regression line and the MAE and RMSE values are lower.

Drought is a natural phenomenon that occurs in almost all parts of the world. The effects of this crawling phenomenon are more pronounced in arid and semi-arid areas due to their annual rainfall. In contrast to traditional methods based on meteorological stations observations that focus more on weather drought, the use of remote sensing and satellite imagery as a useful tool for monitoring agricultural drought has been considered. In the present study, the aim of comparing and assessing agricultural drought monitoring in Urmia Lake basin using VCI, VHI, TCI vegetation cover indices during the years 2000 to 2011 is using Madison. For this purpose, the NDVI index was first calculated from the images of Madis during June, July, August and September. Then, by comparing the mean of this index during these months, Shahrivar was selected with the maximum value as the month of the indicator. With regard to the minimum and maximum NDVI index in the months of September 2003 and 2008, VCI, VHI, TCI dash mapping maps were prepared. In order to evaluate the performance of agricultural drought indices, correlation coefficients were calculated for VCI, VHI and TCI profiles with SPI Meteorological Index. The results showed that the remote sensing index had a good accuracy in estimating the spatial and temporal dispersion of agricultural drought, so that the correlation coefficient between the VHI and SPI index was 0.86, which indicates that the index is consistent with the SPI meteorological index.

Drought prediction plays an important role in the planning and management of natural resources, water resources and plant water requirements. Wavelet transform is one of the new and highly effective methods for analysing signals and time series. Using the mother wavelet, the standard precipitation index (SPI) signal was analyzed and the results were considered as inputs of the artificial neural network models and the gene expression programming (GEP). Multi-layer perceptron (MLP), radial basis function (RBF), (GEP), as well as the wavelet-artificial neural networks integrated model and multi-layer perceptron (WA-MLP), radial basis function (WA- RBF) and wavelet- gene expression programming (WA- GEP) were used for drought forecasting. The rainfall data collected at the Bidestan Station for a period of 44 years were used on the Shoor Watershed in the Province of Qazvin. Moisture condition was calculated using the SPI in the short-term period of 3 months. To estimate the SPI in each period, the respective amounts were considered from the previous cycles. The results showed that among the six applied models, the WA-GEP predicted the SPI values and the short-term drought condition with a higher accuracy. The WA-GEP model proved to be the best scenario in the validation stage of R2, RMSE, MAE and NS of 0.911, 0.037, 0.022 and 0.845, respectively.

Drought is a natural and recurring phenomenon which causes water scarcity in various sectors. In comparison with other natural hazards and disasters, drought is more important considering intensity and frequency as well as spatial extent and total damage. In the current research, the Standardized Precipitation Index (SPI) and Standardized Discharge Index (SDI) were used to analyze the temporal characteristics of droughts. To this end, monthly precipitation time series of 23 raingauge stations and 7 hydrometry stations across the Atrak River basin were used and SPI and SDI for six time intervals (3, 6, 9, 12, 24 and 48 months) were calculated and analyzed. For assessment of drought impact on surface water resources, first the correlation between rain and discharge time series of different lag times were calculated within the study area. Then, the Pearson correlation method was applied to calculate the correlation between SDI and SPI series for different time intervals at each individual subwatershed and whole watershed of the Atrak River. The results showed that the correlation between meteorological and hydrological droughts was significant at 99 percent confidence level. The maximum correlation was found for SPI and SDI of 3 months time intervals. This indicates that droughts cause decrease in surface flows and this impact is remarkably observed in the discharge values of the same month or one month later. The highest Pearson correlation was found for the Shirabad station and the Darband subwatershed.