Surface Water Change Detection via Water Indices and Predictive Modeling Using Remote Sensing Imagery: A Case Study of Nuntasi-Tuzla Lake, Romania

Cristina Șerban,Carmen Maftei,Gabriel Dobrică

doi:10.3390/w14040556

Cristina Șerban, Carmen Maftei + Show 1 more

Open Access

https://doi.org/10.3390/w14040556

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Journal: Water	Publication Date: Feb 12, 2022
Citations: 20	License type: CC BY 4.0

Affiliation: Ovidius University, Transylvania University of Brașov

Abstract

Water body feature extraction using a remote sensing technique represents an important tool in the investigation of water resources and hydrological drought assessment. Nuntasi-Tuzla Lake, a component of the Danube Delta Natural Reserve, is located on the Romanian Black Sea littoral. On account of an event in summer 2020, when the lake surface water decreased significantly, this study aims to identify the variation of the Nuntasi-Tuzla Lake surface water over a long-term period in correlation with human intervention and climate change. To this end, it provides an analysis in the period 1965–2021 via hydrological drought indices and data mining classification. The latter approach is based on several water indices derived from Landsat TM/ETM+/OLI and MODIS full-time series datasets: Normalized Difference Vegetation Index (NDVI), Normalized Difference Vegetation Index (NDVI), Modified NDWI (MNDWI), Weighted Normalized Difference Water Index (WNDWI), and Water Ratio Index (WRI). The experimental results indicate that the proposed classification methods can extract relevant features from waterbodies using remote sensing imagery with a high accuracy. Moreover, the study shows a similarity in the evolution of surface water cover identified with the data mining classification and the drought periods detected in the flow data series for the Nuntasi and Sacele Rivers that supply the Nuntasi-Tuzla Lake. Overall, the results of our investigation show that human intervention and hydrological drought had an extensive impact on the long-term changes in surface water of the Nuntasi-Tuzla Lake.

Highlights

Climatic changes can induce modification of lake surfaces and riverbeds with severe implications for agricultural and economic activities [1,2,3]
The purpose of this paper is to: (i) analyze the hydrological data in order to understand the response of surface water to climate change or/and human intervention and (ii) evaluate the performance of the most commonly used water indices using time series Landsat data in order to capture the variation in surface water during 1984–2021 period
Gheorghe arm and the Razim-Sinoe Lake was made in order to improve the fresh water circulation [41]; work began in 1905 with the Dunavat canal and was continued with the Dranov (1912) and Crasnicol canals; (ii) in 1930–1948 and (iii) 1950–1963, a great number of canals were excavated in order to connect the Danube with the lakes (Lipoveni, Fundea, Mustaca canals) and these lakes with each other; (iv) in 1963–1985, the existing canals were broadened and deepened [37] and a water gate at Portita mouth was built [39]

Summary

Introduction

Climatic changes can induce modification of lake surfaces and riverbeds with severe implications for agricultural and economic activities [1,2,3]. The NDVI (Normalized Difference Vegetation Index) was an indicator used to efficiently monitor vegetation condition [9] and drought activity [10,11] This index was used to extract water features [12]. McFetters [13] developed a new method to delineate water bodies based on the spectral characteristics of water which refers to the capability of a water body to absorb near infrared radiation (NIR) and allows visible green light to penetrate the water body.

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Conclusion