Drought Analysis for the Seyhan Basin with Vegetation Indices and Comparison with Meteorological Different Indices

Abstract

Various drought indices have been developed to monitor drought, which is a result of climate change, and mitigate its adverse effects on water resources, especially in agriculture. Vegetation indices determined by remote sensing were examined by many recent studies and shed light on drought risk management. In the current study, one of the 25 drainage basins in Turkey—the Seyhan Basin, located in the south of the country—was investigated. The Normalized Difference Vegetation Index (NDVI) and the Vegetation Condition Index (VCI) are the most widely used vegetation indices and are very useful because they give results only based on satellite images. This study examined the Seyhan Basin using satellite data in which the vegetation transformation occurring due to the decline of agricultural and forest areas was seen. An increase in drought frequency was detected in the Seyhan Basin using the NDVI and VCI indices and compared with different indices. The results obtained revealed that climate change and drought is increasing with a linear uptrend. It is recommended that decision-makers take the necessary measures by considering the drought risk maps. Long-term drought management plans should also be prepared and implemented.

Investigation of vegetation dynamics with a focus on agricultural land cover and its relation with meteorological parameters based on the remote sensing techniques: a case study of the Gavkhoni watershed

“…6 In Figure 7, the relationship between spring vegetation and drought severity, which was computed using the EVI and the VCI in the Gavkhouni catchment area during the period spanning from 2001 to 2021, is presented. Drought areas, as delineated in the research conducted by Dikici (2022) are characterized by values ranging from 0 to 37.5, whereas areas without drought are identified by values exceeding 37.5. Within the entirety of the Gavkhouni catchment area, the spring season produces fluctuations each year, with an average vegetation area of 9276.3 km 2 (accounting for 22.32% of the total study area) during the entire period under examination.…”

Assessing the performance of machine learning algorithms in Google Earth Engine for land use and land cover analysis: A case study of Muğla province, Türkiye

“…NDVI is one of the most preferred data for monitoring vegetation (Julien & Sobrino, 2009;Ozyavuz, Bilgili, & Salici, 2015;Mutti, Lúcio, Dubreuil, & Bezerra, 2020). NDVI analysis, which is performed using various bands of satellite imagery, is often used in many studies such as monitoring drought, determining the health of plants, the productivity of agricultural lands, and the effects of forest fires (Ozenen Kavlak, Cabuk, & Cetin, 2021;Dikici, 2022). On the other hand, NDWI developed by McFeeters (1996) and Gao (1996) is relevant in identifying water components from satellite images.…”

Drought Monitoring and Forecasting across Turkey: A Contemporary Review

“…Visible wavelengths between 390 nm and 700 nm, especially the red wavelengths between 620 nm and 700 nm, are absorbed by the pigments in plant leaves during photosynthesis, while the near-infrared wavelengths within the range from 760 nm to 900 nm are reflected by spongy mesophyll in the plant. Considering the normalization of this difference for different ranges using satellite images enable us to find the NDVI [54,55]. The pattern of the vegetation change can be determined by comparing the NDVI values obtained from satellite images at different times.…”

“…While low vegetation and bare soil correspond to a negative value or close to zero, water, clouds, and snow indicate low values of NDVI. The areas with a low NDVI value where agriculture is intensive indicate poor plant growth owing to several causes, for instance, redundant moisture, drought, pests, or disease [55].…”

“…Afshar et al [14] MD SPI Ankara Province Danandeh Mehr et al [15] MD SPI, SPEI Ankara Province Dabanlı et al [18] MD SPI Turkey Dursun and Babalık [34] MD SPI, DMGI Isparta Dikici [55] MD, AD, HD NDVI, VCI, DI, SPI, SPEI, SRI Seyhan basin Bacanli et al [66] MD PDSI, EDI, DMI CAR Yıldız [67] MD SPI CAR Karabulut [68] MD SPI Antakya-Kahramanmaraş Topçu and Seçkin [69] MD SPI Seyhan basin Tosuno glu and Kisi [70] HD AMS, AMD Çoruh basin Gumus and Algin [71] MD and HD SPI, SDI Seyhan and Ceyhan River basins Bacanlı [72] MD SPI Aegean region Payab and Turker [73] MD SPI Turkish Republic of Northern Cyprus Kumanlıo glu [74] MD and HD SPI, SPEI, SRI Gediz River basin Bacanlı and Akşan [ Dabanlı et al [18] examined the spatial and temporal patterns of drought to monitor the variability of drought across Turkey. To this end, precipitation records were obtained from 250 meteorological stations for the period between 1931 and 2010 (80 years).…”