چکیده:
اطلاع از میزان و شدت خشکسالی در یک منطقه و برنامهریزی جهت کاهش اثرات آن یکی از مهمترین اصول مبارزه با خشکسالی است. پایش و مدیریت خشکسالی در یک منطقه با استفاده از دادههای سنجش از دور و تصاویر ماهوارهای به عنوان یک ابزار مناسب در پایش زمانی و مکانی خشکسالی کشاورزی میباشد. هدف از انجام این پژوهش بررسی کارآیی دادههای سنجش از دور و تصاویر ماهوارهای در پهنهبندی خشکسالی کشاورزی در سالهای 1379 تا 1400 در شهرستان نیریز میباشد. برای این منظور سه شاخص وضعیت پوشش گیاهی (VCI)، شاخص وضعیت دمایی (TCI) و شاخص سلامت پوشش گیاهی (VHI) از روی تصاویر ماهوارهای مودیس برای برای دوره زمانی مورد نظر استخراج و نتایج حاصل از این شاخصها با مقادیر شاخص بارش استاندارد (SPI)، در دورههای زمانی 1، 3 6، 9، 12، 18، 24 و 48 ماهه مقایسه گردید. نتایج نشان داد از بین شاخصهای مورد مطالعه، شاخص VCI در طی فصل رشد بیشترین همبستگی با مقادیر SPI در دورههای زمانی مختلف را داراست و همبستگی آن در سطح یک درصد معنی-دار است. بنابراین شاخص VCI به عنوان شاخص ماهوارهای مطلوب جهت پایش خشکسالی کشاورزی در شهرستان نیریز انتخاب گردید.
Background and Objective Knowing the extent and severity of drought in a region and planning to reduce its effects is one of the most important principles of management in regional planning to combat drought. Drought monitoring and management in an area using remote sensing data and satellite imagery as a suitable tool in temporal and spatial monitoring of agricultural drought has always been the focus of regional managers. The purpose of this study is to investigate the efficiency of remote sensing data and satellite images in the zoning of agricultural drought in the years 2000 to 2021 in Neyriz city. For this purpose, three vegetation condition index (VCI), temperature condition index (TCI), and vegetation health index (VHI) were extracted from MODIS satellite images for the desired time period. The results of these indices were compared with the values of the standard precipitation index (SPI) in time series of 1, 3, 6, 9, 12, 18, 24, and 48 months.Materials and Methods The study area in this study is Neyriz city located in the southeast of Fars province with an area of 10787 Km2 and is part of one of the watersheds of Bakhtegan Lake. The average altitude of the region is 1798 meters, the maximum altitude of the region is 3235 meters and the minimum altitude is 1476 meters above sea level. The average annual rainfall, temperature, and evapotranspiration of the basin are 204.8 mm, 19 °C, and 1058.3 mm, respectively. In this study, the rainfall data of Neyriz synoptic station during the statistical period of 22 years (2000-2021) were used to calculate the SPI index in time series of 1, 3, 6, 9, 12, 18, 24, and 48 months. Then, 3 indices based on satellite imagery including vegetation condition (VCI), temperature condition index (TCI), and plant health index (VHI) were extracted from Modis measured data for May month from 2008 to 2021 and with standard precipitation index (SPI) were compared in time series of 1, 3, 6, 9, 12, 18, 24 and 48 months based on the correlation coefficient. Finally, the most appropriate drought index based on satellite images was selected from the indices and the percentage of drought classes was determined based on the selected index in the study area.Results and Discussion The results of calculating the values of the SPI index using DIP software in time series of 1, 3, 6, 9, 12, 18, 24, and 48 months in the statistical period of 2000-2021 showed that the trend of curves in some years is decreasing, in some years it has been increasing and in most years it has been almost normal. On average, the incidence of droughts and wetlands according to the SPI index in different time series during the statistical period is 68% in normal conditions, 18% in wet conditions, and 16% in drought conditions. The results of calculating the SPI index in different ground series were analyzed based on data from synoptic stations and remote sensing data. For this purpose, the values obtained from all indices based on satellite images including VCI, TCI, and VHI are extracted and compared and their correlation coefficient with the ground SPI index in time series 1, 3, 6, 9, 12, 18, 24, and 48 became. VCI index values in 2000 have the lowest value (32.1%) and in 2020 have the highest value (41.3%) during May. Therefore, based on the value of the VCI index during the statistical period in 2008, severe drought conditions prevailed in the region, and in 2020, more favorable vegetation and wetting conditions prevailed in the region. The results obtained from the SPI index in different time series also confirm the fact that the most severe drought and wet season during the statistical period studied in the two years 2000 and 2020, respectively, in the region. In addition, the VCI index is most correlated with the SPI index in different series and the SPI relationship is significant with the all-time series. TCI index has no significant correlation with any of the time series and has a weak correlation with the SPI index in different time series. In addition, the VHI index has a significant correlation with time series of one, three, six, and twelve months only at the level of 5% and its correlation with the SPI index in different time series is much less than the VCI index. Spatial distribution of drought intensity based on the values of the studied indices in May 2008 showed that the eastern parts of the region, which is also located at low altitudes, have been more affected by drought. The study of the area affected by drought classes based on the TCI index in 2008 showed that there is no very severe drought in the study area, 11% of the area suffers from moderate drought, 22% of the area suffers from mild drought and 67% has no drought. According to the VCI index, the level of severe drought on the date is 0.14%, severe at 0.33%, moderate at 17%, mild at 77%, and no drought at 6%. Also, according to the VHI index, there is no severe or severe drought in the study area only 9% of the area suffers from moderate drought and 91% does not have a drought. Spatial distribution of drought severity based on the values of the studied indices in May 2020 shows that in the study area according to the TCI index there is no very severe drought on the target date and 5% of the area has moderate drought, 22% drought Mild and 73% lack drought. According to the VCI index on the target date, the percentage of drought is very severe 0.5%, severe 0.8%, moderate 5%, mild 31%, and no drought 62%. Also, according to the VHI index in May 1999, 0.2% of the area has a moderate drought, 30% has a mild drought and 69% has no drought. According to this index, there is no very severe drought in the region.Conclusion Drought is one of the most important natural disasters that affect millions of people and large parts of the world every year. This phenomenon, which starts slowly and has a creeping nature, can cause a lot of damage to agriculture, natural resources, and the environment. Knowing how to occur and preparing drought severity maps based on new methods has a very positive and serious impact on drought management in an area. One of the new and widely used methods in temporal and spatial monitoring of drought is the use of drought indices based on satellite images, which has recently been used in drought-related topics. The results of the SPI index analysis showed that in most time series, the most severe drought and wet season during the study period occurred in 2000 and 2020, respectively. The results also showed that the temperature condition index (TCI) has no significant correlation with any of the time series and has a weak correlation with the SPI index in different time series. The plant health index (VHI) with time series of one, three, six, and twelve months has a significant correlation at the level of 5% and its correlation with the SPI index in different time series is less than the vegetation condition index (VCI). The value of the VCI index in 2008 had the lowest value (32.1%) and in 2020 had the highest value (41.3%) during May, which is consistent with the results obtained from the SPI index in the region. A comparison of the results of this study with the results of other researchers shows the excellent accuracy of remote sensing indices in drought monitoring. Therefore, the use of remote sensing technology in drought monitoring in areas that do not have meteorological stations or have meteorological stations with low density or scattered is recommended.