مقاله انگلیسی رایگان در مورد سنجش از دور و شاخص‌های خشکسالی برای کشف و آنالیز خشکسالی – تیلور و فرانسیس 2022

Abstract

1. Introduction

2. Methodology

3. Results

4. Discussions

5. Conclusions

Author’s contributions

Author’s statements

Data availability statement

References

Abstract

     Under the severe impacts of climate change, drought has become one of the most undesirable and complex natural phenomena with critical consequences for the environment, economy and society. The orthodox drought monitoring approaches use observations of meteorological stations, which are typically restricted in time and space. Remote sensing, conversely, provides continuous global coverage of a variety of hydro-meteorological variables that are influential in drought, and data extracted from remote sensing and modeling missions are now considered more practical and alluring for researchers. In this study, we applied a combination of field data, remotely sensed data and modeled data to detect and quantitatively analyze drought phenomena. To achieve this objective, we utilized Terrestrial Water Storage Anomalies (TWSA) estimations from GRACE mission, Normalized Difference Vegetation Index (NDVI) from MODIS mission, Surface Runoff (R) and Evapotranspiration from ERA5 reanalysis datasets and Soil Moisture (SM) from GLDAS data model to evaluate their feasibility in detecting recent droughts over Turkey. We validated the accuracy of several remote sensing-based indices (GRACE Drought Severity Index, Water Storage Deficit Index [WSDI], Soil Moisture Index, Standardized Runoff Index and NDVI) with the traditional indices (SPI and SPEI) calculated from in situ observations of precipitation.

Methodology

     Turkey is located between the latitudes 36
N and 42
N and longitudes 26
E and 45
E. The country is situated at mid-latitudes that define its climatic characteristics together with its highly variable topography. Despite its Mediterranean geographic location, where mild climatic conditions are dominant (Sensoy et al. 2008), the diversity of its topography as well as proximity to the Black Sea, Aegean Sea and the Mediterranean in the north, west and south, respectively, lead to significant variations in climatic conditions in seven different regions of the country (Figure 1). Thus, coastal zones demonstrate different characteristics from inland plateaus of central, eastern and southeastern Anatolia.

     Regardless of the climatic variability of different regions of Turkey, the general climatic pattern of Turkey follows the characteristics of a generic semi-arid climate, which defines its water resources potential that in turn shapes its agriculture and industry (Selek and Aksu 2020). The variability of hydro-climatic parameters in Turkey introduces some challenges regarding water accessibility at proper times and space all over the country.

Conclusions

     Drought studies are traditionally based on field observations of hydro-meteorological parameters. These are typically limited in time and geographic space, which lowers the spatial and temporal accuracy of the studies. In this study, we used the remotely sensed and simulated data in an integrated manner to evaluate the recent droughts over the semi-arid climatic region of Turkey, for which there is no comprehensive comparative study from the viewpoint of the effectiveness of different drought indices available for the scientific community use

     The results indicated that among different RS indices, notwithstanding its coarse resolution estimates, the GRACE-driven WSDI index had the best performance in detecting the monthly dry periods while SRI relatively outperformed WSDI in the detection of yearly droughts in Turkey from 2003 to 2016. The correlations achieved between used indices indicated that RS and model-based indicators had, in general, better agreement with SPI rather than SPEI even though the differences between the correlation values achieved for these two indices were not so high. This can be ascribed to the fact that SPI was more dependent on precipitation than SPEI and the fluctuations of precipitation were more influential on the climatic condition of Turkey, which made SPI perform more effectively