ارزیابی روند تغییرات مکانی و زمانی خشکسالی بر اساس داده‌های سری‌های زمانی سنجش از دور در مرکز استان خوزستان

خشکسالی به یکی از رایج‌ترین و پیچیده‌ترین بلایای طبیعی تبدیل شده است که تاثیر زیادی بر روی توسعۀ پایدار جوامع دارد. سنجش از دور با داشتن اطلاعات مکانی و زمانی، ابزار مناسبی برای ارزیابی و بررسی این پدیده‌ است. در پژوهش حاضر روند مکانی و زمانی تغییرات خشکسالی در مرکز استان خوزستان مورد بررسی قرار گرفته است. به این منظور از تصاویر سنجندۀ +etm طی یک دورۀ 20 ساله استفاده شد. پس از انجام پیش‌پردازش‌ها، ابتدا 411 نقطۀ تصادفی روی تصاویر انتخاب و ارزش‌های پیکسل‌های مربوط به باند‌های قرمز و مادون قرمز نزدیک استخراج و در مقابل هم پلات شد و شیب بهترین خط برازش‌شده موسوم به خط خاک به دست آمد. سپس با استفاده از این شیب و مقادیر باند‌های ذکرشده، مقادیر شاخص خشکسالی pdi محاسبه شد. سپس با کاربرد روش طبقه‌بندی شکست طبیعی درجات مختلف از هم تفکیک شد و روند تغییرات مکانی و زمانی خشکسالی با استفاده از آزمون روند من کندال فصلی در سطوح مختلف معنی‌داری تعیین گردید. نتایج نشان داد تغییرات مکانی درجۀ بدون خشکسالی در سطح 5% و 10% و در درجۀ خشکسالی کم در سطح 10% معنی‌دار بودند و درجات دیگر هیچ‌گونه روندی در سطوح معنی‌داری مختلف نداشتند. در مقابل تغییرات زمانی درجۀ بدون خشکسالی در سطوح معناداری 1%، 5 % و 10% دارای روند معناداری نبود و درجات خشکسالی کم در سطح 5 % و 10%، خشکسالی متوسط در سطح 1%، 5% و 10% و خشکسالی شدید در سطح 5% و 10% دارای روند معنادار بودند که حاکی از افزایش شدت خشکسالی در منطقه طی دورۀ مورد مطالعه بود.

assessing the trend of spatio-temporal drought changes using remote sensing time series data in central khuzestan province

introduction: as a dreadful natural disaster caused by a severe reduction in precipitation rate, drought brings about, compared with other natural disasters, farreaching spatial and temporal consequences, incurring severe damages. on the other hand, in late the 20th century, drought monitoring approaches underwent a paradigm shift, and advances in remote sensing and earth observation technologies allowed observations and monitoring of key droughtrelated variables over larger temporal and spatial scales than what the then conventional methods had already made possible. there are different remote sensing indices used to assess drought, including the pdi index which has been developed based on the spectral patterns of soil moisture changes in the nirred space using the red and nearinfrared bands of the etm+ sensor. therefore, as khuzestan province is suffering from drought consequences, including but not limited to dust storms and economic difficulties, this study sought to identify the spatial and temporal trends of drought in the center of khuzestan province.materials and methods: the study area is located in southwestern iran and the center of khuzestan province at 31° 0ʹ 17ʺ to 31° 43ʹ 69ʺ n latitudes and 48° 35ʹ 51ʺ to 49° 32ʹ 2ʺ e longitudes covering an area of 7635/36 km2. to conduct the study, some twenty etm+ remote sensing images of level1 data taken from 1999 to 2018, (path/row 168/35) were collected from the united states geological survey website.after gathering the required data, some 411 random points were selected on the collected images, the pixel values of red and nearinfrared bands were extracted and plotted against each other, and the slope of the bestfitted line, known as the soil line, was obtained. then, the pdi drought index values were calculated using the slope and the values of the aforementioned bands. finally, by applying a natural break classification method, different degrees were separated, and the drought’s trend of spatial and temporal changes was identified using mannkendall’s seasonal trend test at different significance levels.results: the results of the spatial trend analysis of drought suggested that the trend was significant only in low drought and nondrought conditions. for the nondrought conditions, the probability of spatial changes was lower than the confidence level at 5% and 10% significant levels, indicating the significance of the conditions at these two levels, and thus, rejecting the null hypothesis at merely the 1% level. on the other hand, as the low drought conditions showed significant spatial changes only at the 10% significant level, the null hypothesis is rejected at the 1% and 5% levels. however, moderate and severe drought conditions revealed no trends in terms of spatial changes due to the higher probability values ​​of 0.28 and 0.3, respectively, which were higher than the determined significance levels. moreover, the results of temporal trend analysis indicated no trend for the nondrought conditions, considering the fact that the null hypothesis was rejected at all significant levels. on the contrary, in the moderate drought conditions, a temporal trend was confirmed at all significant levels with the probability rate of 0.006 which was lower than all the assigned levels. also, a temporal trend was found at low and severe drought conditions at 5% and 10% significance levels with a probability rate of 0.023 and 0.014.discussion and conclusion: the spatial analysis of the drought trend suggested that only the area with nondrought conditions had a significant increasing trend, which could be justified by the increase in the area of ​​irrigated land around water bodies in the area, especially around the karun river in the west of the study area. the reduction in the area of land in the northeast of the study area with the lowdrought conditions could be attributed to the rangeland degradation containing low and moderately dense vegetation.