Skip to main content

Advertisement

Log in

Seasonal drought analysis of Akşehir Lake with temporal combined sentinel data between 2017 and 2021 spring and autumn

  • Published:
Environmental Monitoring and Assessment Aims and scope Submit manuscript

Abstract

The threat of drought has been felt almost worldwide in recent years. It is critical to determine the causes of drought and how seasonal changes affect it. Additionally, it is necessary to determine the speed and impact area of drought, monitor drought areas, and attempt to find solutions against drought. With the developing satellite sensing systems, remote sensing methods are being used to investigate topics such as the increase and extent of drought, uncontrolled water consumption in agricultural activities, and the effects of unnatural pollutants on freshwater resources such as lakes and rivers. Using Synthetic Aperture Radar (SAR) satellite data to monitor changes in water bodies is a relatively new area of study in remote sensing. The spatial extent and seasonal change (spring and autumn) of droughts between 2017 and 2021 in Akşehir Lake were determined from Sentinel-1A SAR satellite data, and the Normalized Differential Water Index (NDWI) was calculated using Sentinel-2A optical satellite data and Standardized Precipitation Index (SPI) in this research. In addition, a different approach was applied to determine the change of wetland boundaries more accurately by converting the linear Sigma0 band to the decibel (dB) band and applying a non-linear 3 × 3 maximum filter to the dB band to Sentinel-1A data. Consequently, it has been established that Akşehir Lake, which used to have wetlands during the spring seasons but began to dry up in the autumn seasons, had completely dried up in both periods in 2021.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

Data availability

The data used in this research can be obtained free of charge from the Sentinel Data Hub.

References

  • Abdel-Hamid, A., Dubovyk, O., Graw, V., & Greve, K. (2020). Assessing the impact of drought stress on grasslands using multi-temporal SAR data of Sentinel-1: A case study in Eastern Cape, South Africa. European Journal of Remote Sensing, 53, 3–16.

    Article  Google Scholar 

  • Adedeji, O., Olusola, A., Babamaaji, R., & Adelabu, S. (2021a). An assessment of flood event along Lower Niger using Sentinel-1 imagery. Environmental Monitoring and Assessment, 193, 1–17.

    Article  Google Scholar 

  • Adedeji, O., Olusola, A., Babamaaji, R., & Adelabu, S. (2021b). An assessment of flood event along Lower Niger using Sentinel-1 imagery. Environmental Monitoring Assessment, 193, 1–17.

    Article  Google Scholar 

  • Bahadır, M. (2013). AKŞEHİR GÖLÜ’NDE ALANSAL DEĞİŞİMLERİN UZAKTAN ALGILAMA TEKNİKLERİ İLE BELİRLENMESİ. Marmara Coğrafya Dergisi, 246–275.

  • Ben, O. D., & Abida, H. (2022). Monitoring and mapping of drought in a semi-arid region: Case of the Merguellil watershed, central Tunisia. Environmental Monitoring and Assessment, 194, 1–19.

    Article  CAS  Google Scholar 

  • Calo, F., Notti, D., Galve, J., Abdikan, S., Görüm, T., Orhan, O., Makineci, H., Pepe, A., Yakar, M., & Balik Şanli, F. (2018). A multi-source data approach for the investigation of land subsidence in the Konya basin, Turkey. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 42.

  • Chahal, M., Singh, O., Bhardwaj, P., & Ganapuram, S. (2021). Exploring spatial and temporal drought over the semi-arid Sahibi river basin in Rajasthan, India. Environmental Monitoring and Assessment, 193, 1–25.

    Article  Google Scholar 

  • Chen, L., Singh, V. P., & Guo, S. (2011). Drought analysis based on copulas.

  • Chen, L., Singh, V. P., Guo, S., Mishra, A. K., & Guo, J. (2013). Drought analysis using copulas. Journal of Hydrologic Engineering, 18, 797–808.

    Article  Google Scholar 

  • Çağlayan, E. B., Erel, F., Samur, E. B., Deniz, M., Mobariz, M. A., & Kaplan, G. (2020). Uzaktan Algılama Teknikler ile Akşehir Gölü’ndeki Alansal Değişiminin İzlenmesi. Türkiye Uzaktan Algılama Dergisi, 2, 70–76.

    Google Scholar 

  • De, A., Upadhyaya, D. B., Thiyaku, S., & Tomer, S. K. (2022). Use of multi-sensor satellite remote sensing Data for flood and drought monitoring and mapping in India. Springer.

    Book  Google Scholar 

  • Dönmez, S. (2018). Akşehir Gölü su seviyesinin çekilmesinin meteorolojik ve uydu verileri ile incelenmesi. Gazi Üniversitesi Mühendislik Mimarlık Fakültesi Dergisi, 33.

  • Evkaya, O., Yozgatligil, C., Sevtap, S. -K., & Applications,. (2019). Drought analysis using copula approach: A case study for Turkey. Communications in Statistics: Case Studies, Data Analysis, 5, 243–260.

    Google Scholar 

  • Filipponi, F. (2019). Sentinel-1 GRD preprocessing workflow. Multidisciplinary Digital Publishing Institute Proceedings, 11.

  • Gao, B. -C. (1996). NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space. Remote Sensing of Environment, 58, 257–266.

    Article  Google Scholar 

  • Ghale, Y., & a. G., Baykara M. & Unal A. (2019). Investigating the interaction between agricultural lands and Urmia Lake ecosystem using remote sensing techniques and hydro-climatic data analysis. Agricultural Water Management, 221, 566–579.

    Article  Google Scholar 

  • Ghazaryan, G., Dubovyk, O., Graw, V., Kussul, N., & Schellberg, J. (2020). Local-scale agricultural drought monitoring with satellite-based multi-sensor time-series. Giscience & Remote Sensing, 57, 704–718.

    Article  Google Scholar 

  • Hu, Z., Wu, Z., Zhang, Y., Li, Q., Islam, A., & Pan, C. (2021). Risk assessment of drought disaster in summer maize cultivated areas of the Huang-Huai-Hai plain, eastern China. Environmental Monitoring and Assessment, 193, 1–15.

    Article  Google Scholar 

  • Javed, T., Li, Y., Rashid, S., Li, F., Hu, Q., Feng, H., Chen, X., Ahmad, S., Liu, F., & Pulatov, B. (2021). Performance and relationship of four different agricultural drought indices for drought monitoring in China’s mainland using remote sensing data. Science of the Total Environment, 759, 143530.

    Article  CAS  Google Scholar 

  • Kaplan, G., & Avdan, U. (2017). Object-based water body extraction model using Sentinel-2 satellite imagery. European Journal of Remote Sensing, 50, 137–143.

    Article  Google Scholar 

  • Kaplan G., Avdan, U., Avdan, Z. Y., & D Yildiz, N. (2016). Landsat uydu görüntüleri kullanılarak kuraklık izlenmesi (Akşehir gölü örneği). 6.UZAKTAN ALGILAMA-CBS SEMPOZYUMU. Adana.

  • Karaman, M., & Özelkan, E. (2022). Comparative assessment of remote sensing–based water dynamic in a dam lake using a combination of Sentinel-2 data and digital elevation model. Environmental Monitoring Assessment, 194, 1–20.

    Article  Google Scholar 

  • Keyantash, J. (2018). The climate data guide: Standardized precipitation index (SPI). National Center for Atmospheric Research Staff, 8.

  • Kimwatu, D. M., Mundia, C. N., & Makokha, G. O. (2021). Developing a new socio-economic drought index for monitoring drought proliferation: A case study of Upper Ewaso Ngiro River Basin in Kenya. Environmental Monitoring and Assessment, 193, 1–22.

    Article  Google Scholar 

  • Kirtiloglu, O., Orhan, O., & Ekercin, S. (2016). A map mash-up application: Investigation the temporal effects of climate change on Salt Lake basin. International Archives of the Photogrammetry, Remote Sensing & Spatial Information Sciences, 41.

  • Liu, Y., Qian, J., & Yue, H. (2020). Combined Sentinel-1A with Sentinel-2A to estimate soil moisture in farmland. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 14, 1292–1310.

    Article  Google Scholar 

  • Mcfeeters, S. K. (2013). Using the normalized difference water index (NDWI) within a geographic information system to detect swimming pools for mosquito abatement: A practical approach. Remote Sensing, 5, 3544–3561.

    Article  Google Scholar 

  • Mckee, T. B., Doesken, N. J., & Kleist, J. (1993). The relationship of drought frequency and duration to time scales. Proceedings of the 8th Conference on Applied Climatology, Boston, 179–183.

  • Moharrami, M., Javanbakht, M., & Attarchi, S. (2021). Automatic flood detection using sentinel-1 images on the Google Earth engine. Environmental Monitoring and Assessment, 193, 1–17.

    Article  Google Scholar 

  • Mutlu, A. Z., Kazancı, B., Özçetin, A. Y., & Sariyilmaz, F. B. (2020). Akşehir gölü zamansal değişiminin bant oranlama yöntemleri ile belirlenmesi. Türkiye Uzaktan Algılama Dergisi, 2, 22–28.

    Google Scholar 

  • Nayak, A., Biswal, B., & Sudheer, K. (2022). Drought hotspot maps and regional drought characteristics curves: Development of a novel framework and its application to an Indian River basin undergoing climatic changes. Science of the Total Environment, 807, 151083.

    Article  CAS  Google Scholar 

  • Neto, R. M. B., Santos, C., & a. G., Da Silva R. M., Dos Santos C. a. C., Liu Z. & Quinn N. W. (2021). Geospatial cluster analysis of the state, duration and severity of drought over Paraíba State, northeastern Brazil. Science of the Total Environment, 799, 149492.

    Article  CAS  Google Scholar 

  • Onojeghuo, A. O., Blackburn, G. A., Huang, J., Kindred, D., & Huang, W. (2018). Applications of satellite ‘hyper-sensing’in Chinese agriculture: Challenges and opportunities. International Journal of Applied Earth Observation and Geoinformation, 64, 62–86.

    Article  Google Scholar 

  • Orhan, O. (2021). Monitoring of land subsidence due to excessive groundwater extraction using small baseline subset technique in Konya, Turkey. Environmental Monitoring Assessment, 193, 1–17.

    Article  Google Scholar 

  • Orhan, O., Ekercin, S., & Dadaser-Celik, F. (2014). Use of landsat land surface temperature and vegetation indices for monitoring drought in the Salt Lake Basin Area, Turkey. The Scientific World Journal.

  • Orhan, O., Oliver-Cabrera, T., Wdowinski, S., Yalvac, S., & Yakar, M. (2021). Land subsidence and its relations with sinkhole activity in Karapınar region, Turkey: A multi-sensor InSAR time series study. Sensors, 21, 774.

    Article  Google Scholar 

  • Park, J. -W., Korosov, A. A., Babiker, M., Sandven, S., & Won, J. -S. (2017). Efficient thermal noise removal for Sentinel-1 TOPSAR cross-polarization channel. IEEE Transactions on Geoscience and Remote Sensing, 56, 1555–1565.

    Article  Google Scholar 

  • Peker, E. A. (2019). Spatio-temporal changes of lake water extents in lakes region (Turkey) using remote sensing.

  • Rostammiri, A., Malmasi, S., Yosefvand, F., Hoseini, S. A., & Etminan, A. (2022). Presenting the spatial–temporal model for assessing and predicting qualitative changes of the groundwater resources in Shahriar, Tehran. Iran. Environmental Monitoring Assessment, 194, 1–12.

    Article  CAS  Google Scholar 

  • Shaik, R., & NT, M. (2020). Estimation of annual regional drought index considering the joint effects of climate and water budget for Krishna River basin, India. Environmental Monitoring and Assessment192(7), 1-18.

    Article  Google Scholar 

  • Tekeli, A. E. (2018). Augmenting in situ lake level measurements with Earth observation satellites. Teknik Dergi, 29, 8675–8689.

    Google Scholar 

  • Torbick, N., Hession, S., Hagen, S., Wiangwang, N., Becker, B., & Qi, J. (2013). Mapping inland lake water quality across the Lower Peninsula of Michigan using Landsat TM imagery. International Journal of Remote Sensing, 34, 7607–7624.

    Article  Google Scholar 

  • Tufaner, F., & Özbeyaz, A. (2020). Estimation and easy calculation of the Palmer Drought Severity Index from the meteorological data by using the advanced machine learning algorithms. Environmental Monitoring and Assessment, 192, 1–14.

    Article  Google Scholar 

  • Yang, R. -M., & Guo, W. -W. (2019). Using time-series Sentinel-1 data for soil prediction on invaded coastal wetlands. Environmental Monitoring and Assessment, 191, 1–14.

    Google Scholar 

  • Zhang, Q., Shi, R., Singh, V. P., Xu, C. -Y., Yu, H., Fan, K., & Wu, Z. (2022). Droughts across China: Drought factors, prediction and impacts. Science of the Total Environment, 803, 150018.

    Article  CAS  Google Scholar 

Download references

Acknowledgements

The author is eternally grateful to the European Space Agency (ESA) for extensive use of Sentinel Mission data for this work and Copernicus European Drought Observatory (EDO) for Standardized Precipitation Index (SPI) data and the Research and User Support for Sentinel Core Products platform for the information used in the application. The author also likes to thank the General Directorate of State Hydraulic Works, the General Directorate of Meteorology, and the Ministry of Environment and Urbanization for all their contributions, which provide data at the national level.

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Hasan Bilgehan Makineci.

Ethics declarations

Conflict of interest

The author declares no competing interests.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Makineci, H.B. Seasonal drought analysis of Akşehir Lake with temporal combined sentinel data between 2017 and 2021 spring and autumn. Environ Monit Assess 194, 529 (2022). https://doi.org/10.1007/s10661-022-10207-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s10661-022-10207-4

Keywords

Navigation