Almustafa A. Ayek ¹*; Bilel Zerouali ²

1, Department of Topography, Faculty of Civil Engineering, University of Aleppo, Aleppo 12212, Syria

2, Laboratory of Architecture, Cities, and Environment, Department of Hydraulic, Faculty of Civil Engineering and Architecture, Hassiba Benbouali University of Chlef, Chlef B.P. 78C, Algeria

 

Manuscript link
http://dx.doi.org/10.30493/DAS.2021.476854

Abstract

Water resource management is an essential aspect of sustainable development. Monitoring water sources through conventional field methods is arduous and demands considerable time and effort. Landsat 8 and 9 data, characterized by moderate spatial resolution, serve as an efficient tool for large-scale environmental change monitoring. This research employed the Google Earth Engine (GEE) platform to examine Landsat 8 and 9 data and assess temporal variations in water bodies within the Qattinah Lake Basin. The results indicated a significant decrease in the expanse of water bodies during the summer months from 2013 to 2018, amounting to a reduction of 9.24 square kilometers. Between 2018 and 2024, there was a significant increase during the summer months, with the area expanding by 7.33 square kilometers. The results indicated GEE’s exceptional ability to efficiently extract and process information from remote sensing data, facilitating thorough analyses over prolonged durations. The findings are significant for researchers and policymakers in water management and sustainable development, underscoring the efficacy of remote sensing techniques in tackling water resource issues and guiding policy decisions.

Keywords: Water Bodies, Google Earth Engine, Landsat, Qattinah Lake, Syria

Introduction

Water scarcity is an increasing global issue that presents considerable challenges to sustainable development, food security, and the health of ecosystems [1][2]. Significant factors contributing to this issue including climate change, population growth, and the rising demand for water in agricultural and industrial sectors [3][4]. As these challenges escalate, the effective monitoring and management of water resources are crucial for guaranteeing long-term sustainability and adaptability.

The dynamics of surface water bodies, including lakes, rivers, and reservoirs, exhibit notable sensitivity to both climate change and human activities [5][6]. The variations in these bodies can significantly impact local ecosystems, agriculture, and human communities [7]. Traditional methods of monitoring water resources, including field surveys and on-site measurements, yield precise data; however, they frequently require considerable time and financial investment, and their spatial coverage is often restricted [8][9].

Recent advancements in remote sensing techniques and data analysis have significantly transformed the management of water resources. Environmental monitoring via satellite, especially through initiatives such as Landsat, is regarded as a crucial data source owing to its high spatial resolution and consistent global coverage [10]. This has developed into an effective instrument for observing environmental changes on a broad scale. The introduction of Landsat 8 in 2013 and Landsat 9 in 2021 has markedly improved the capacity to observe and assess the Earth’s surface, offering enhanced spectral and spatial accuracy.

The Operational Land Imager (OLI 1 and 2) sensors on the Landsat 8 and 9 satellites facilitate the acquisition of important data regarding the Earth’s surface, thereby greatly improving the ability of researchers to conduct environmental analysis. The Normalized Difference Water Index (NDWI) is recognized as one of the most effective spectral indices for the monitoring of water bodies, specifically designed to identify and differentiate open water from adjacent regions [11][12]. NDWI significantly diminishes the influence of vegetation cover on the analysis, facilitating more precise estimations of open water areas [13-15]. Although NDWI serves as a useful instrument for water extraction, it may not represent the most effective option in urban settings. Consequently, various modified indices have been created to overcome these limitations. [16-18].

A variety of studies have employed open remote sensing data in Geographic Information Systems (GIS) or via the Google Earth Engine (GEE) platform to examine the effects of climate change on surface water variations. For instance, Landsat images were utilized to analyze surface water changes over a span of three decades, uncovering notable reductions in certain regions while observing increases in others [19]. These data was used on the GEE platform to detect changes in global land and water, underscoring the significant capabilities of cloud-based geographic analysis. Consequently, GEE has emerged as a vital resource for scholars investigating temporal variations [14].

Historically, the analysis of satellite images necessitated the acquiring of substantial amounts of data, which were then processed utilizing local computing resources [20-22]. This method required considerable time investment and necessitated substantial technical knowledge along with advanced computational resources. Nonetheless, the advent of cloud platforms such as Google Earth Engine has addressed numerous challenges, allowing researchers to access and effectively process extensive geographic data [23]. Despite these advancements, there continues to be an increasing demand for accessible tools that allow a broader spectrum of stakeholders—such as local water managers and decision-makers—to take advantage of satellite-based monitoring.

In light of these developments and ongoing challenges this study aims to address are:

1. Create a user-friendly application that enables the monitoring and analysis of temporal changes in water bodies by applying the Normalized Difference Water Index (NDWI) to accurately extract and assess water bodies over time using Landsat 8 and Landsat 9 data within the Google Earth Engine platform.
2. Demonstrate the effectiveness of combining satellite imagery, spectral indices, and cloud computing for large-scale monitoring of water resources.

This study represents a step toward leveraging these capabilities to monitor environmental changes and support water sustainability by providing a free application for tracking water body areas in the study region, thereby facilitating the monitoring of changes within the basin.

Material and Methods

Study area

Qattinah Lake basin is located in the Syrian-Lebanese region, to the southwest of the city of Homs in Syria. The area is situated between the latitudes of 34.4541673° N and 34.7586882° N, and the longitudes of 36.4041678° E and 36.82257423° E (Fig. 1). The region is characterized by a Mediterranean climate, featuring hot, arid summers and mild, rainy winters. The average summer temperatures may surpass 35°C, whereas winter temperatures generally fall between 5°C and 15°C. The yearly average of precipitation ranges from 400 to 600 mm, with the majority occurring between November and March. The observed rainfall pattern plays a vital role in the replenishment of local water sources; however, the variability in precipitation may result in instances of drought.

The management of water resources is significantly impacted by the numerous environmental challenges that the basin faces. The increasing demands of agriculture, industry, and population expansion have resulted in water scarcity, which is a substantial challenge. The overexploitation of groundwater resources has led to a reduction in water tables, which in turn has exacerbated shortages. The region faces a substantial issue of soil erosion, intensified by deforestation, overgrazing, and unsustainable agricultural practices. Erosion significantly affects soil health and leads to heightened sedimentation in rivers and reservoirs, adversely impacting water quality and diminishing their capacity. Climate change presents a significant challenge, as increasing temperatures and changing precipitation patterns may result in a higher incidence of severe droughts. Climate change have the potential to disturb the intricate equilibrium of local ecosystems in the region, influencing both plant and animal life. Comprehending these climatic conditions and environmental challenges is essential for the monitoring and management of water bodies within the basin. The study seeks to address these factors in order to contribute to the development of more effective water resource management strategies, thereby enhancing sustainability in this vulnerable region.

Datasets

Landsat 8 and Landsat 9 Level 2 surface reflectance data were employed to observe water bodies in the Qattinah Lake basin. The Level 2 products provide substantial benefits for environmental monitoring, especially by delivering atmospherically corrected surface reflectance data that more accurately reflects ground conditions. Both satellites deliver imagery with a 30-meter spatial resolution for multispectral bands, achieving an ideal equilibrium between detail and coverage for regional-scale water body identification. Their collective 8-day revisit interval allows for frequent observations, thereby facilitating comprehensive temporal analyses of alterations in water bodies. The Operational Land Imager (OLI) sensors on both satellites provide 11 spectral bands, encompassing Near-Infrared (NIR) and Shortwave Infrared (SWIR), which are especially effective for water detection [24]. The congruity between Landsat 8 and 9 data guarantees uninterrupted integration and analysis throughout study period from 2013 to 2024 [25].  The unrestricted access to Landsat data via platforms such as Google Earth Engine has transformed extensive and prolonged environmental research, rendering thorough analyses more attainable than ever. This study employs Level 2 surface reflectance products, negating the necessity for further atmospheric correction, thus optimizing the analysis and improving the precision of water body detection and monitoring. The amalgamation of high-quality, consistent, and freely accessible data renders Landsat 8 and 9 optimal for examining temporal variations in the water bodies of the Qattinah Lake Basin.

The study area boundaries were derived from the global HydroSHEDS database accessible via Google Earth Engine (GEE) [26], which utilizes elevation data collected in 2000 by NASA’s Shuttle Radar Topography Mission (SRTM). This database offers polygon maps of nested and hierarchically organized watersheds, encompassing watershed levels from level 1 to level 12. In this research, the basin of the study area was delineated at level 9.

Monitoring water bodies

The Normalized Difference Water Index (NDWI) is an effective and dependable instrument for detecting and observing water bodies utilizing Landsat 8 and 9 data. This index was created to improve the differentiation of water from adjacent land and vegetation, rendering it beneficial for multiple applications, such as water resource management, flood monitoring, and drought evaluation.

The integration of this index with the Google Earth Engine (GEE) platform enables extensive spatial and temporal analyses with enhanced precision and efficiency, bolstering research and management initiatives in water resources. The NDWI can be computed using the subsequent formula:

Where:

P₃: Surface reflectance at the green visible wavelength.

Ρ_s: Surface reflectance at the near-infrared (NIR) wavelength.

The NDWI values span from -1 to +1 [27]. This index increases water reflectivity while diminishing the effects of vegetation and soil. Water exhibits substantial absorption in the Near-Infrared (NIR) spectrum and considerable reflection in the green spectrum, leading to elevated positive NDWI values for aquatic environments and negative or nearly zero values for terrestrial regions [28][29].

A specific threshold value is applied to the NDWI to classify pixels as water or non-water. In this study, a threshold value of zero was used, designating values exceeding zero as water and values below zero as non-water [29]. Google Earth Engine (GEE) streamlines the computation of NDWI on an extensive scale with remarkable efficiency. Concise scripts can be developed in GEE to access an extensive repository of Landsat images, execute computations, and process data swiftly [30].

Results and Discussion

This study involved the development of a JavaScript script to monitor the surface area of water bodies within the designated study area. The script consolidates Landsat 8 and 9 Level 2 images, choosing data with cloud cover below 2% over a seasonal timeframe. The year is segmented into four seasons (summer, spring, fall, and winter), facilitating user transitions among them. All Landsat 8 and 9 data within the designated timeframe and cloud cover criteria are consolidated. The necessary bands are subsequently merged, and the numerical values of these bands are transformed into surface reflectance to compute the NDWI. Subsequently, the threshold value (NDWI ≥ 0) is utilized to delineate the water bodies and quantify the water area within the study area. Users can access the developed Water Source Monitoring Application through the following link: (Application Link).

The examination of alterations in the water area of the Qattinah Lake Basin from 2013 to 2024 uncovers multiple notable trends. From 2013 to 2018, there was a significant reduction in water area, decreasing from 30.89 km² in 2013 to 21.65 km² in 2018, amounting to a total decline of 9.24 km² (approximately 30.4%) (Fig. 2) (Fig. 3 A and B). This period experienced fluctuations, with minor recoveries in 2015 and 2016, yet ultimately followed a downward trajectory. In 2019, a significant recovery transpired, with the water area expanding to 34.77 km², representing an

increase of 13.12 km² (approximately 60.7%) compared to 2018 (Fig. 2). The recovery persisted into 2021, culminating in a peak water area of 36.73 km² (Fig. 3 C). From 2022 to 2024, the data exhibited fluctuations, culminating in a decrease to 27.51 km² in 2023, followed by a modest recovery to 28.98 km² in 2024 (Fig. 3 D). Recent declines signify persistent difficulties in sustaining water levels, likely attributable to factors such as evaporation, diminished precipitation, or heightened water extraction for agricultural and industrial purposes. The dataset highlights the necessity of ongoing monitoring and adaptive management strategies to tackle water resource challenges in the Qattinah Lake Basin, as comprehending these trends is essential for formulating effective policies to improve water sustainability in the region.

The significant reduction in water body area indicates the possible influence of various factors, including drought, diminished precipitation, and anthropogenic activities such as excessive irrigation and unsustainable water consumption. This trend corresponds with other reports [31], indicating that severe drought events resulted in significant decreases in surface water area. The congruence of results highlights the worldwide influence of climate change on water resources and underscores the necessity of ongoing monitoring in drought-affected areas. The recent recovery of lake surface area post-2019 can be ascribed to favorable climatic conditions, including augmented rainfall in prior months, and potentially the implementation of new policies aimed at improving water resource management in the region. The upward trend persisted until 2021, marking the largest recorded area throughout the study period. The study’s results affirm the strong correlation between alterations in land cover, encompassing the expansion and reduction of water bodies, and wider environmental and climatic variables.

The utilization of NDWI and GEE for the detection and analysis of water bodies is consistent with contemporary trends in remote sensing. A recent study [32] illustrated the efficacy of employing various spectral indices, including NDWI, for water monitoring. This paper emphasizes the efficacy of integrating spectral indices with cloud computing platforms like GEE for effective large-scale water resource monitoring. The persistent variations in the examined basin highlight the necessity for ongoing surveillance and a more profound comprehension of climatic and managerial alterations impacting water resources. In this context, it is essential to adopt flexible management strategies that can adjust to these fluctuations to ensure the long-term sustainability of water resources.

This study’s utilization of Landsat 8 and 9 data corresponds with the global trend of employing remote sensing methodologies for the monitoring of natural resources. Landsat data provides superior spatial precision and extensive coverage for the classification of diverse land cover types, including aquatic environments [33]. This highlights the necessity of persistently employing and advancing these techniques to improve our comprehension of water resource dynamics.  Moreover, the utilization of the GEE platform in this research exemplifies the increasing trend of employing cloud-based platforms for environmental monitoring [14]. The efficiency and scalability of GEE have facilitated extensive analyses of water resources across vast regions and prolonged durations, enhancing decision-making in water resource management.

Conclusion

This assessment of Qattinah Lake Basin offers significant understanding of the dynamics of aquatic systems in a region affected by climatic fluctuations and anthropogenic influences. The analysis indicated substantial variations in water body area, peaking at 36.73 km² in 2021, after a marked recovery from a low of 21.65 km² in 2018. The observed changes highlight the need for ongoing monitoring and flexible management strategies. Utilizing advanced remote sensing methods and cloud computing platforms can improve the comprehension of water resource dynamics and aid in the development of more sustainable water management practices in response to global environmental changes.

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Cite this article:

Ayek, A. A., Zerouali, B. Monitoring temporal changes of the Qattinah Lake surface area using Landsat data and Google Earth Engine. DYSONA – Applied Science, 2025;6(1): 126-133. doi: 10.30493/das.2024.476854