جستجوی مقالات مرتبط با کلیدواژه "drought prediction" در نشریات گروه "جغرافیا"

Drought is an inseparable part of climatic fluctuations which caused a lot of damages to different sections annually. Prediction of drought is recognized really useful in management of crisis and reduction of damages due to its the effect on different parts of environment, agricultural sections, natural resources, and wild life. In this research, monthly drought in 12 synoptic stations located in southeast of Iran during 1980 -2014 were calculated based on SPI index, Then, using Markov chain method, monthly drought during 2015- 2020 were predicted. Based on the results, in the most synoptic stations, normal, moderate dry and severe dry classes of drought have the highest frequency of occurrence. Transition probability matrix showed that, in all synoptic stations, probability of passing from a specific drought condition to the same drought condition and probability of passing from wet conditions to dry conditions were high, but the probability of passing from the dry conditions to wet conditions were low. Results of prediction in different synoptic stations with different of accuracy level (In Iran Shahe, Zabol, Zahedan, Bam and Saravan stations accuracy of prediction were 75%, In Jask, Kerman, Bandar Abbas and Shahr Babak stations accuracy of prediction were 79.1% and In Bandar Lengeh, Chahbahar and Sirjan stations the accuracy of prediction were 83.3%,) showed that, from 2015 to 2020 the normal, moderate and severe drought classes will be the highest probability of drought occurrence. In the study area, the classes of drought (from 1 to 7) are 13.3, 25.81, 26.74, 36.11, 4.75, 2.87 respectively and 0.69 percent of predicted months will be appropriated.

The prediction of probability of drought occurrence in different years and its mitigation measures are at the peak of drought management decisions. The aim of present research is the prediction of drought by the use of downscaling statistical methods and artificial data creation technique. For getting the work done, a synthetic study was carried out by utilization of meteorological stations data, the outputs of statistical analyses and finally using SPI drought index. First, artificial data was produced through CLIMGEN, then SPI value was predicted. Then Minitab software was used for the calculation and drawing of the trends in selected stations of the North West.  For validity approval the model was adapted by observational and produced data. The correlation between artificially created data and observed data was estimated by SPSS software. Results indicated a suitable validity for most of the stations. Accordingly, Ardebil, Jolfa, and Tekab show a smooth precipitation declining and drought increasing trend. Khoy, Mianeh, and Sardasht are among the stations which prove a moderate precipitation and increasing wet conditions, while there were not seen any changes in Tabriz, Urmia, and Parsabad stations.