تحلیل و پایش منابع آب و خشک‌سالی با بهره‌گیری از ترکیب تصاویر ماهواره‌‌ای گریس، مادیس و لندست 8 (مطالعه موردی: شهرستان همدان)

نوع مقاله : مقاله پژوهشی

نویسندگان

1 کارشناس ارشد، گروه مهندسی عمران، دانشکده فنی و مهندسی، دانشگاه قم، قم، ایران.

2 گروه زمین‌شناسی، دانشگاه اصفهان، اصفهان، ایران.

3 گروه مهندسی عمران، دانشکده فنی و مهندسی، دانشگاه آیت‌الله بروجردی، بروجرد، ایران.

4 کارشناس ارشد، گروه مهندسی عمران، دانشکده مهندسی عمران و محیط زیست، دانشگاه صنعتی امیرکبیر، تهران، ایران.

چکیده

امروزه، به‌کارگیری روش‌های ماهواره‌ای در مطالعه پدیده‌های آب‌شناسی به‌عنوان ابزاری مؤثر برای نظارت بر وضعیت منابع آبی شناخته شده و به‌دلیل کمبود داده‌های ایستگاه‌های زمینی یا عدم وجود اطلاعات کافی، می‌توان از سنجش از راه دور برای جمع‌آوری داده‌ها در مقیاس وسیع استفاده کرد. هم‌چنین با به‌کارگیری الگوریتم‌های مناسب، می‌توان تأثیر توزیع خشک‌سالی بر مراتع و گیاهان را براساس تصاویر ماهواره‌ای مورد بررسی قرار داد. با در دست داشتن اطلاعات مربوط به توزیع خشک‌سالی در یک منطقه، می‌توان از آثار منفی آن بر پوشش گیاهی مطلع شده و اقداماتی برای مقابله با آن انجام داد. در این پژوهش، با استفاده از ترکیب تصاویر ماهواره‌ای لندست 8، مادیس (ترا) و گریس، تغییرات شاخص‌های خشک‌سالی، رواناب و تغییرات آب زیرزمینی در دشت همدان در بازه زمانی 2003 تا 2016 مورد بررسی قرار گرفت. نتایج نشان می‌دهند که متوسط بلندمدت رواناب در دشت همدان براساس داده‌های ماهواره‌ای 0.512 مترمکعب بر ثانیه بوده و تغییرات تراز آب زیرزمینی به‌ازای سه خروجی پایگاه داده (الگوریتم) CSR، GFZ و JPL به‌ترتیب 29.52، 31.05 و 35.11  سانتی‌متر به‌دست آمد. هم‌چنین با بررسی نقشه توزیع خشک‌سالی NVDI دشت همدان در حالت خشک‌سالی با شدت متوسط بوده که نشان‌دهنده وضعیت نرمال از لحاظ پوشش گیاهی است.

کلیدواژه‌ها

موضوعات


عنوان مقاله [English]

Analysis and Monitoring of Water Resources and Drought Using a Combination of GRACE, MODIS, and Landsat 8 Satellite Images (Case Study: Hamedan City)

نویسندگان [English]

  • Mahdieh Kalhori 1
  • Meisam Tadayon 2
  • Emad Kahrizi 3
  • Mohammad Ghiasvand 4
1 Ph.D. Student, Department of Civil Engineering, Faculty of Engineering, University of Qom, Qom, Iran.
2 Department of Geology, University of Isfahan, Isfahan, Iran.
3 Department of Civil Engineering, Faculty of Technical and Engineering, University of Ayatollah Boroujerdi, Boroujerd, Iran.
4 Master's Degree, Department of Civil Engineering and Environment, Faculty of Civil Engineering, Amirkabir University of Technology, Tehran, Iran.
چکیده [English]

Abstract
Objective: In recent years, the application of satellite-based techniques in the study of hydrological phenomena has been recognized as an effective tool for monitoring water resource conditions. Due to the scarcity of ground-based station data or the lack of sufficient in-situ observations, remote sensing provides a reliable means for collecting large-scale spatial and temporal data. Moreover, by applying appropriate algorithms, the impacts of drought distribution on rangelands and vegetation can be assessed using satellite imagery.
Method: Having access to information on drought spatial distribution within a region enables the identification of its adverse effects on vegetation cover and supports the implementation of mitigation and management strategies. In this study, a combination of Landsat 8, MODIS (Terra), and GRACE satellite imagery was used to investigate variations in drought indices, runoff, and groundwater storage changes in the Hamedan Plain over the period 2003-2016.
Results: The results indicate that the long-term mean runoff in the Hamedan Plain, derived from satellite data, was approximately 0.512 m³/s. In addition, groundwater level variations estimated from the three GRACE data processing centers-CSR, GFZ, and JPL-were 29.52, 31.05, and 35.11 cm, respectively.
Conclusion: Analysis of the NDVI-based drought distribution map revealed that the Hamedan Plain experienced predominantly moderate drought conditions, indicating a generally normal status of vegetation cover during the study period. 
 
 
 
English Extended Abstract
Introduction
Due to the special climatic conditions of arid and semi-arid regions such as Iran, groundwater is considered a vital and strategic resource. Population growth and increasing need for water, coupled with limited surface water resources, put severe pressure on groundwater resources. This can lead to irreversible consequences for ecosystems and hydrological cycles. Therefore, proper management and careful planning in watersheds are essential to ensure the sustainability of water resources and the preservation of ecosystems dependent on it. The spatial distribution of vegetation is strongly influenced by climatic conditions, especially precipitation and temperature. A drought is a prolonged dry period in the natural weather cycle that can occur anywhere in the world and is a slow-onset disaster characterized by a lack of rainfall and therefore a lack of water.
According to studies, it is estimated that 55 million people worldwide are affected by drought annually, and this drought is the most serious risk to livestock and agricultural products in almost every part of the world. Rising temperatures caused by climate change are making arid regions drier and humid areas wetter. In this study, this study aims to investigate surface and groundwater resources and the distribution and classification of drought in the study area of Hamadan Plain. For this purpose, using extracted images from the MODIS and Grace and Landsat 8 satellites, we investigated the trend of changes in each of the parameters in the period from 2003 to 2016.
 
Method
Landsat satellites with low spatial resolution and high temporal resolution make it possible to monitor atmospheric changes on a large scale. Climate satellites also play an important role in measuring atmospheric parameters. These data provide researchers with actual evapotranspiration, cumulative precipitation, and runoff. Groundwater is a vital and strategic resource for communities, and it requires careful and continuous management and monitoring. Grace satellite images are an efficient and effective method of monitoring groundwater level fluctuations. In this study, 168 Grace Satellite images from the Hamedan Plain from 2003 to 2016 were analyzed. The Grace satellite, an advanced dual-gravity satellite, was launched by NASA and DLR in 2002, and its scientific mission ended in 2017. The study examines and analyzes satellite images with special precision. This research includes the following stages:

Benefit from the advanced Google Earth Platform and JavaScript programming language for satellite image processing. Google Earth Engine, as a powerful and free tool, provides researchers with a wide range of possibilities.
Selection and processing of satellite images related to the study area (Hamedan Plain) in a specific period (2003 to 2016), and applying appropriate spatial and temporal filters for the desired area.
Analysis of gravitational images of Grace Satellites processed by different centers. Each center processes raw data with its own algorithms, but due to differences in methods, the resulting values also vary. Therefore, the use of multiple average values and algorithms increases the accuracy of the results.
Improving the quality of results by resampling processed data at high spatial resolution (e.g. 300 meters).

To conduct the present study, the Google Earth Engine system and the JavaScript programming language have been used. Google Earth Engine enables users to perform their calculations on large amounts of data without the need for powerful systems. After recalling the Modis product and applying spatial and temporal filters in the first place, in the second place, the cloud mask from the collection of images was taken. In the third place, after selecting the NDVI band, the NDVI average image was created for all months of the year. In the fourth place, after calculating the minimum and maximum values of the NDVI index, the VCI index for 2003 to 2016 was calculated. Finally, to analyze the values of this index and the vegetation status of the region, the VCI map was classified into three classes: no vegetation, medium vegetation, and rich vegetation, and the area of each class was calculated in terms of percentage.
 
Results
In the surface runoff section, the average discharge of Hamedan Plain from June 2003 to December 2016 was 0.512 m3/s and the highest runoff was related to February, March, and April of each year. Also, a decrease was shown in groundwater level in the Hamadan-Bahar plain by 31.05, 29.52, and 35.11 cm, respectively. Finally, according to the NDVI index, which is the basis for calculating the VCI index, the overall Geezi result was obtained as follows: The area is in a low to moderate vegetation state. Also, according to the results of the VCI classification, the worst conditions were related to June 17, 2008 with a rate of 4.1%, and the best conditions were related to April 23, 2010 with a rate of 86.2%. Also, by examining the indices of VCI, TCI, VHI, SVI, the drought severity of the study area was in the medium category according to the two indices of VCI and TCI and the results of the other two indices indicated severe drought.
 
Conclusion
This study aimed to investigate the changes in surface and subsurface water resources, considering the severity of drought from 2003 to 2016 in Hamadan city. In summary, based on the results of the Landsat satellite, the long-term average runoff value of the region was 0.512 m3/s, with the highest discharge in proportion to the highest rainfall months in the region in February, March, and April. In the analysis of the results of groundwater level changes based on three databases GFZ, CSR, and JPL, the distance between the maximum and the lowest level changes was 29.52, 31.05, and 35.11 cm, respectively. In the last part, TCI drought indices indicate moderate drought and based on vegetation indices, are classified as high drought intensity. Also, based on the classification map, most of the land in Hamadan city was classified as barren and with low vegetation.

کلیدواژه‌ها [English]

  • Satellite Image
  • Drought Index
  • Water Resources Management
  • Runoff
  • Groundwater Level
[1] Oki T, Kanae Sh. Global hydrological cycles and world water resources. Science. 2006 Aug 25; 313 (5790): 1068-1072. https://doi.org/10.1007/s11269-023-03564-3.
[2] Jackson RB, Carpenter SR, Dahm CN, McKnight DM, Naiman RJ, Postel SL, Running SW. Water in a changing world. Ecological Applications. 2001 Aug 01; 11 (4): 1027-1045. https://doi.org/10.1890/1051-0761(2001)011[1027:WIACW]2.0.CO;2.
[3] Sophocleous M. Interactions between groundwater and surface water: The state of the science. Hydrogeology Journal. 2003 Jan 11; 10: 52-67. https://doi.org/10.1007/s10040-001-0170-8.
[4] Gleeson T, Wada Y, Bierkens MFP, van Beek LPH. Water balance of global aquifers revealed by groundwater footprint. Nature. 2012 Aug 8; 488: 197-200. https://doi.org/10.1038/nature11295.
[5] Brocca L, Melone F, Moramarco T, Wagner W, Naeimi V, Bartalis Z. Hasenauer S. Improving runoff prediction through the assimilation of the ASCAT soil moisture product. Hydrology and Earth System Sciences. 2010 Oct 12; 14 (10):1881-1893. https://doi.org/10.5194/hess-14-1881-2010.
[6] Berhan G, Hill Sh, Tadesse T, Atnafu S. Using satellite images for drought monitoring: a knowledge discovery approach. Journal of Strategic Innovation and Sustainability. 2011 May 1; 7 (1):135-153.
[7] Ahmadi M, Dadashi Roudbari A, Deyrmajai A. Runoff estimation using IHACRES model based on CHIRPS satellite data and CMIP5 models (Case study: Gorganroud Basin-Aq Qala area). Iranian Journal of Soil and Water Research. 2020 Jun 3; 51 (3): 659-671. https://doi.org/10.22059/ijswr.2019.289144.668316 [In Persian].
[8] Collignon B. A new tool for the remote sensing of groundwater tables: Satellite images of pastoral wells. Open Geospatial Data, Software and Standards. 2020 Sep 30; 5 (4): 1-10. https://doi.org/10.1186/s40965-020-00077-3.
[9] Najafi N, Arbabi A. Drought monitoring in Tehran Province using TRMM satellite data. Iranian Journal of Eco Hydrology, 2021 Oct; 8 (3): 819-827. https://doi.org/10.22059/ije.2021.329001.1540 [In Persian].
[10] Liu P-W, Famiglietti JS, Purdy AJ, Adams KH, McEvoy AL, Reager JT, Bindlish R, Wiese DN, David CH, Rodel M. Groundwater depletion in California’s Central Valley accelerates during megadrought. Nature Communications. 2022 Dec 19; 13 (7825): 1-11. https://doi.org/10.1038/s41467-022-35582-x.
[11] Vasco DW, Farr TG, Jeanne P, Doughty C, Nico P. Satellite-based monitoring of groundwater depletion in California’s Central Valley. Scientific Reports. 2019 Nov 5; 9 (16053): 1-14. https://doi.org/10.1038/s41598-019-52371.
[12] Yeditha PK, Rathinasamy M, Neelamsetty SS, Bhattacharya B, Agarwal A. Investigation of satellite precipitation product driven rainfall-runoff model using deep learning approaches in two different catchments of India. Journal of Hydroinformatics. 2022 Jan 1; 24 (1): 16-37. https://doi.org/10.2166/hydro.2021.067.
[13] Ghazaryan G, Dubovyk O, Graw V, Kussul N, Schellberg J. Local-scale agricultural drought monitoring with satellite-based multi-sensor time-series. GIScience and Remote Sensing. 2020 Jun 16; 57 (5): 704-718. https://doi.org/10.1080/15481603.2020.1778332.
[14] Esmaeili H, Mirmousavi SH, Soheili E. Investigation of agricultural drought time series in Darab city using remote sensing and Google Earth engine system. Journal of Geography and Environmental Hazards. 2022 Feb; 10 (4): 175-192. ‏https://doi.org/10.22067/geoeh.2021.69186.1029 [In Persian].
[15] Arekhia S, Savasarib MB, Emadaddiana S. Investigating the indicators resulting from remote sensing technology in drought assessment using MODIS images (Case study: Qom, Isfahan, Chaharmahal and Bakhtiari, and Markazi Provinces). Journal of Geography and Environmental Hazards. 2022 Nov; 11 (3), 189-224.‏ https://doi.org/10.22067/geoeh.2021.72253.1102 [In Persian].
[16] Eshraghi SA and Mahmoudi Gharai M. Geology map of Tuyserkan, scale 1:100000, geological survey of Iran. Tehran. 2003.
[17] Stuart MB, McGonigle AJS, Willmott JR. Hyperspectral imaging in environmental monitoring: A review of recent developments and technological advances in compact field deployable systems. Sensors. 2019 Jul 11; 19 (14): 1-17. https://doi.org/10.3390/s19143071.
[18] Vishwakarma CA, Rena V, Singh D, Mukherjee S. Exploration of water resources using remote sensing and geographic information system. Groundwater Geochemistry. John Wiley & Sons Ltd.; 2021 Jun 18; https://doi.org/10.1002/9781119709732.ch18.
[19] NASA, Gravity Recovery and Climate Experiment (GRACE), https://earth.gsfc.nasa.gov/geo/missions/grace, 2004.
[20] King MD, Kaufman YJ, Menzel WP, Tanre D. Remote sensing of cloud, aerosol, and water vapor properties from the moderate resolution imaging spectrometer (MODIS). in IEEE Transactions on Geoscience and Remote Sensing. 1992 Jan; 30(1): 2-27. https://doi.org/10.1109/36.124212.
[21] Kogan FN. Application of vegetation index and brightness temperature for drought detection. Advances in Space Research. 1995; 15(11): 91-100.‏ https://doi.org/10.1016/0273-1177(95)00079-T.
[22] Zeng J, Zhou T, Qu Y. et al. An improved global vegetation health index dataset in detecting vegetation drought. Scientific Data. 2023 May 31; 10: 1-12. https://doi.org/10.1038/s41597-023-02255-3.
[23] Tucker CJ. Red and photographic infrared linear combinations for monitoring vegetation. Remote Sensing of Environment. 1979 May; 8(2): 127-150.‏ https://doi.org/10.1016/0034-4257(79)90013-0.
 
دوره 1، شماره 1
فروردین 1404
صفحه 59-72
  • تاریخ دریافت: 10 مهر 1403
  • تاریخ بازنگری: 09 دی 1403
  • تاریخ پذیرش: 20 دی 1403
  • تاریخ اولین انتشار: 20 دی 1403
  • تاریخ انتشار: 05 فروردین 1404