Articles | Volume 25, issue 5
https://doi.org/10.5194/hess-25-2373-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/hess-25-2373-2021
© Author(s) 2021. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
06 May 2021
Research article |
| 06 May 2021
| 06 May 2021
A simple cloud-filling approach for remote sensing water cover assessments
Connor Mullen
Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, IN 46556, USA
Gopal Penny
Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, IN 46556, USA
Department of Civil and Environmental Engineering and Earth Sciences, University of Notre Dame, Notre Dame, IN 46556, USA
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Gopal Penny, Diogo Bolster, and Marc F. Müller
Hydrol. Earth Syst. Sci., 26, 1187–1202, https://doi.org/10.5194/hess-26-1187-2022, https://doi.org/10.5194/hess-26-1187-2022, 2022
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In residential areas with a high housing density, septic contamination of private wells raises multiple health concerns. Often, few regulations exist to ensure good water quality in such systems, and water quality is often left to the homeowner. To address the potential obstacles to effective management, we identify situations where misplaced economic incentives hinder effective policy to support water quality in such systems.
Gopal Penny, Zubair A. Dar, and Marc F. Müller
Hydrol. Earth Syst. Sci., 26, 375–395, https://doi.org/10.5194/hess-26-375-2022, https://doi.org/10.5194/hess-26-375-2022, 2022
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We develop an empirical approach to attribute declining streamflow in the Upper Jhelum watershed, a key subwatershed of the transboundary Indus basin. We find that a loss of streamflow since the year 2000 resulted primarily due to interactions among vegetation and groundwater in response to climate rather than local changes in land use, revealing the climate sensitivity of this Himalayan watershed.
Nicolas Avisse, Amaury Tilmant, Marc François Müller, and Hua Zhang
Hydrol. Earth Syst. Sci., 21, 6445–6459, https://doi.org/10.5194/hess-21-6445-2017, https://doi.org/10.5194/hess-21-6445-2017, 2017
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Information on small reservoir storage is crucial for water management in a river basin. However, it is most of the time not freely available in remote, ungauged, or conflict-torn areas. We propose a novel approach using satellite imagery information only to quantitatively estimate storage variations in such inaccessible areas. We apply the method to southern Syria, where ground monitoring is impeded by the ongoing civil war, and validate it against in situ measurements in neighbouring Jordan.
M. F. Müller and S. E. Thompson
Hydrol. Earth Syst. Sci., 20, 669–683, https://doi.org/10.5194/hess-20-669-2016, https://doi.org/10.5194/hess-20-669-2016, 2016
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We compare a stochastic (process-based) and statistical (data-based) method to predict flow duration curves in ungauged basins, under stationary and non-stationary conditions, and using Nepal as a case study. Both methods worked well in stationary conditions, with performances driven by the main source of runoff heterogeneity (climate vs. recession). The stochastic model worked better under change, and the performance of the statistical model was determined by the resilience of the flow regime.
M. F. Müller and S. E. Thompson
Hydrol. Earth Syst. Sci., 19, 2925–2942, https://doi.org/10.5194/hess-19-2925-2015, https://doi.org/10.5194/hess-19-2925-2015, 2015
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We introduce TopREML as a method to predict runoff signatures in ungauged basins using linear mixed models with spatially correlated random effects. The nested nature of streamflow networks is accounted for by allowing for stronger correlations between flow-connected basins. The restricted maximum likelihood framework provides best linear unbiased predictions of both the predicted flow variable and its uncertainty as shown in Monte Carlo and cross-validation analyses in Nepal and Austria.
Related subject area
Subject: Rivers and Lakes | Techniques and Approaches: Remote Sensing and GIS
High-resolution automated detection of headwater streambeds for large watersheds
Remote quantification of the trophic status of Chinese lakes
Hydrological regime of Sahelian small waterbodies from combined Sentinel-2 MSI and Sentinel-3 Synthetic Aperture Radar Altimeter data
Deriving transmission losses in ephemeral rivers using satellite imagery and machine learning
Long-term water clarity patterns of lakes across China using Landsat series imagery from 1985 to 2020
Changes in glacial lakes in the Poiqu River basin in the central Himalayas
Assimilation of probabilistic flood maps from SAR data into a coupled hydrologic–hydraulic forecasting model: a proof of concept
Evaluation of historic and operational satellite radar altimetry missions for constructing consistent long-term lake water level records
Sentinel-3 radar altimetry for river monitoring – a catchment-scale evaluation of satellite water surface elevation from Sentinel-3A and Sentinel-3B
Assessing the capabilities of the Surface Water and Ocean Topography (SWOT) mission for large lake water surface elevation monitoring under different wind conditions
Assimilation of wide-swath altimetry water elevation anomalies to correct large-scale river routing model parameters
Technical Note: Flow velocity and discharge measurement in rivers using terrestrial and unmanned-aerial-vehicle imagery
River-ice and water velocities using the Planet optical cubesat constellation
Exposure of tourism development to salt karst hazards along the Jordanian Dead Sea shore
A global lake and reservoir volume analysis using a surface water dataset and satellite altimetry
Surface water monitoring in small water bodies: potential and limits of multi-sensor Landsat time series
Technical note: Bathymetry observations of inland water bodies using a tethered single-beam sonar controlled by an unmanned aerial vehicle
Satellite-derived light extinction coefficient and its impact on thermal structure simulations in a 1-D lake model
Observing river stages using unmanned aerial vehicles
Quantification of the contribution of the Beauce groundwater aquifer to the discharge of the Loire River using thermal infrared satellite imaging
Swath-altimetry measurements of the main stem Amazon River: measurement errors and hydraulic implications
Satellite radar altimetry for monitoring small rivers and lakes in Indonesia
Quantifying river form variations in the Mississippi Basin using remotely sensed imagery
River ice flux and water velocities along a 600 km-long reach of Lena River, Siberia, from satellite stereo
Geometric dependency of Tibetan lakes on glacial runoff
Assessing the potential hydrological impact of the Gibe III Dam on Lake Turkana water level using multi-source satellite data
River monitoring from satellite radar altimetry in the Zambezi River basin
Flood occurrence mapping of the middle Mahakam lowland area using satellite radar
Satellite remote sensing of water turbidity in Alqueva reservoir and implications on lake modelling
Hydro-physical processes at the plunge point: an analysis using satellite and in situ data
Regional scale analysis of landform configuration with base-level (isobase) maps
Reconstructing the Tropical Storm Ketsana flood event in Marikina River, Philippines
Reading the bed morphology of a mountain stream: a geomorphometric study on high-resolution topographic data
Francis Lessard, Naïm Perreault, and Sylvain Jutras
Hydrol. Earth Syst. Sci., 28, 1027–1040, https://doi.org/10.5194/hess-28-1027-2024, https://doi.org/10.5194/hess-28-1027-2024, 2024
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Headwaters streams, which are small streams at the top of a watershed, represent two-thirds of the total length of streams, yet their exact locations are still unknown. This article compares different techniques in order to remotely detect the position of these streams. Thus, a database of more than 464 km of headwaters was used to explain what drives their presence. A technique developed in this article makes it possible to detect headwater streams with more accuracy, despite the land uses.
Sijia Li, Shiqi Xu, Kaishan Song, Tiit Kutser, Zhidan Wen, Ge Liu, Yingxin Shang, Lili Lyu, Hui Tao, Xiang Wang, Lele Zhang, and Fangfang Chen
Hydrol. Earth Syst. Sci., 27, 3581–3599, https://doi.org/10.5194/hess-27-3581-2023, https://doi.org/10.5194/hess-27-3581-2023, 2023
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1. Blue/red and green/red Rrs(λ) are sensitive to lake TSI. 2. Machine learning algorithms reveal optimum performance of TSI retrieval. 3. An accurate TSI model was achieved by MSI imagery data and XGBoost. 4. Trophic status in five limnetic regions was qualified. 5. The 10m TSI products were first produced in 555 typical lakes in China.
Mathilde de Fleury, Laurent Kergoat, and Manuela Grippa
Hydrol. Earth Syst. Sci., 27, 2189–2204, https://doi.org/10.5194/hess-27-2189-2023, https://doi.org/10.5194/hess-27-2189-2023, 2023
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This study surveys small lakes and reservoirs, which are vital resources in the Sahel, through a multi-sensor satellite approach. Water height changes compared to evaporation losses in dry seasons highlight anthropogenic withdrawals and water supplies due to river and groundwater connections. Some reservoirs display weak withdrawals, suggesting low usage may be due to security issues. The
satellite-derived water balance thus proved effective in estimating water resources in semi-arid areas.
Antoine Di Ciacca, Scott Wilson, Jasmine Kang, and Thomas Wöhling
Hydrol. Earth Syst. Sci., 27, 703–722, https://doi.org/10.5194/hess-27-703-2023, https://doi.org/10.5194/hess-27-703-2023, 2023
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We present a novel framework to estimate how much water is lost by ephemeral rivers using satellite imagery and machine learning. This framework proved to be an efficient approach, requiring less fieldwork and generating more data than traditional methods, at a similar accuracy. Furthermore, applying this framework improved our understanding of the water transfer at our study site. Our framework is easily transferable to other ephemeral rivers and could be applied to long time series.
Xidong Chen, Liangyun Liu, Xiao Zhang, Junsheng Li, Shenglei Wang, Yuan Gao, and Jun Mi
Hydrol. Earth Syst. Sci., 26, 3517–3536, https://doi.org/10.5194/hess-26-3517-2022, https://doi.org/10.5194/hess-26-3517-2022, 2022
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A 30 m LAke Water Secchi Depth (LAWSD30) dataset of China was first developed for 1985–2020, and national-scale water clarity estimations of lakes in China over the past 35 years were analyzed. Lake clarity in China exhibited a significant downward trend before the 21st century, but improved after 2000. The developed LAWSD30 dataset and the evaluation results can provide effective guidance for water preservation and restoration.
Pengcheng Su, Jingjing Liu, Yong Li, Wei Liu, Yang Wang, Chun Ma, and Qimin Li
Hydrol. Earth Syst. Sci., 25, 5879–5903, https://doi.org/10.5194/hess-25-5879-2021, https://doi.org/10.5194/hess-25-5879-2021, 2021
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We identified ± 150 glacial lakes in the Poiqu River basin (central Himalayas), and we explore the changes in five lakes over the last few decades based on remote sensing images, field surveys, and satellite photos. We reconstruct the lake basin topography, calculate the water capacity, and propose a water balance equation (WBE) to explain glacial lake evolution in response to local weather conditions. The WBE also provides a framework for the water balance in rivers from glacierized sources.
Concetta Di Mauro, Renaud Hostache, Patrick Matgen, Ramona Pelich, Marco Chini, Peter Jan van Leeuwen, Nancy K. Nichols, and Günter Blöschl
Hydrol. Earth Syst. Sci., 25, 4081–4097, https://doi.org/10.5194/hess-25-4081-2021, https://doi.org/10.5194/hess-25-4081-2021, 2021
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This study evaluates how the sequential assimilation of flood extent derived from synthetic aperture radar data can help improve flood forecasting. In particular, we carried out twin experiments based on a synthetically generated dataset with controlled uncertainty. Our empirical results demonstrate the efficiency of the proposed data assimilation framework, as forecasting errors are substantially reduced as a result of the assimilation.
Song Shu, Hongxing Liu, Richard A. Beck, Frédéric Frappart, Johanna Korhonen, Minxuan Lan, Min Xu, Bo Yang, and Yan Huang
Hydrol. Earth Syst. Sci., 25, 1643–1670, https://doi.org/10.5194/hess-25-1643-2021, https://doi.org/10.5194/hess-25-1643-2021, 2021
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This study comprehensively evaluated 11 satellite radar altimetry missions (including their official retrackers) for lake water level retrieval and developed a strategy for constructing consistent long-term water level records for inland lakes. It is a two-step bias correction and normalization procedure. First, we use Jason-2 as the initial reference to form a consistent TOPEX/Poseidon–Jason series. Then, we use this as the reference to remove the biases with other radar altimetry missions.
Cecile M. M. Kittel, Liguang Jiang, Christian Tøttrup, and Peter Bauer-Gottwein
Hydrol. Earth Syst. Sci., 25, 333–357, https://doi.org/10.5194/hess-25-333-2021, https://doi.org/10.5194/hess-25-333-2021, 2021
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In poorly instrumented catchments, satellite altimetry offers a unique possibility to obtain water level observations. Improvements in instrument design have increased the capabilities of altimeters to observe inland water bodies, including rivers. In this study, we demonstrate how a dense Sentinel-3 water surface elevation monitoring network can be established at catchment scale using publicly accessible processing platforms. The network can serve as a useful supplement to ground observations.
Jean Bergeron, Gabriela Siles, Robert Leconte, Mélanie Trudel, Damien Desroches, and Daniel L. Peters
Hydrol. Earth Syst. Sci., 24, 5985–6000, https://doi.org/10.5194/hess-24-5985-2020, https://doi.org/10.5194/hess-24-5985-2020, 2020
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We want to assess how well the Surface Water and Ocean Topography (SWOT) satellite mission will be able to provide information on lake surface water elevation and how much of an impact wind conditions (speed and direction) can have on these retrievals.
Charlotte Marie Emery, Sylvain Biancamaria, Aaron Boone, Sophie Ricci, Mélanie C. Rochoux, Vanessa Pedinotti, and Cédric H. David
Hydrol. Earth Syst. Sci., 24, 2207–2233, https://doi.org/10.5194/hess-24-2207-2020, https://doi.org/10.5194/hess-24-2207-2020, 2020
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The flow of freshwater in rivers is commonly studied with computer programs known as hydrological models. An important component of those programs lies in the description of the river environment, such as the channel resistance to the flow, that is critical to accurately predict the river flow but is still not well known. Satellite data can be combined with models to enrich our knowledge of these features. Here, we show that the coming SWOT mission can help better know this channel resistance.
Anette Eltner, Hannes Sardemann, and Jens Grundmann
Hydrol. Earth Syst. Sci., 24, 1429–1445, https://doi.org/10.5194/hess-24-1429-2020, https://doi.org/10.5194/hess-24-1429-2020, 2020
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An automatic workflow is introduced to measure surface flow velocities in rivers. The provided tool enables the measurement of spatially distributed surface flow velocities independently of the image acquisition perspective. Furthermore, the study illustrates how river discharge in previously ungauged and unmeasured regions can be retrieved, considering the image-based flow velocities and digital elevation models of the studied river reach reconstructed with UAV photogrammetry.
Andreas Kääb, Bas Altena, and Joseph Mascaro
Hydrol. Earth Syst. Sci., 23, 4233–4247, https://doi.org/10.5194/hess-23-4233-2019, https://doi.org/10.5194/hess-23-4233-2019, 2019
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Knowledge of water surface velocities in rivers is useful for understanding a wide range of processes and systems, but is difficult to measure over large reaches. Here, we present a novel method to exploit near-simultaneous imagery produced by the Planet cubesat constellation to track river ice floes and estimate water surface velocities. We demonstrate the method for a 60 km long reach of the Amur River and a 200 km long reach of the Yukon River.
Najib Abou Karaki, Simone Fiaschi, Killian Paenen, Mohammad Al-Awabdeh, and Damien Closson
Hydrol. Earth Syst. Sci., 23, 2111–2127, https://doi.org/10.5194/hess-23-2111-2019, https://doi.org/10.5194/hess-23-2111-2019, 2019
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The Dead Sea shore is a unique salt karst system. Development began in the 1960s, when the water resources that used to feed the Dead Sea were diverted. The water level is falling at more than 1 m yr−1, causing a hydrostatic disequilibrium between the underground fresh water and the base level. Despite these conditions, tourism development projects have flourished. Here, we show that a 10 km long strip of coast that encompasses several resorts is exposed to subsidence, sinkholes and landslides.
Tim Busker, Ad de Roo, Emiliano Gelati, Christian Schwatke, Marko Adamovic, Berny Bisselink, Jean-Francois Pekel, and Andrew Cottam
Hydrol. Earth Syst. Sci., 23, 669–690, https://doi.org/10.5194/hess-23-669-2019, https://doi.org/10.5194/hess-23-669-2019, 2019
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This paper estimates lake and reservoir volume variations over all continents from 1984 to 2015 using remote sensing alone. This study improves on previous methodologies by using the Global Surface Water dataset developed by the Joint Research Centre, which allowed for volume calculations on a global scale, a high resolution (30 m) and back to 1984 using very detailed lake area dynamics. Using 18 in situ volume time series as validation, our volume estimates showed a high accuracy.
Andrew Ogilvie, Gilles Belaud, Sylvain Massuel, Mark Mulligan, Patrick Le Goulven, and Roger Calvez
Hydrol. Earth Syst. Sci., 22, 4349–4380, https://doi.org/10.5194/hess-22-4349-2018, https://doi.org/10.5194/hess-22-4349-2018, 2018
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Accurate monitoring of surface water extent is essential for hydrological investigation of small lakes (1–10 ha), which supports millions of smallholder farmers. Landsat monitoring of long-term surface water dynamics is shown to be suited to lakes over 3 ha based on extensive hydrometric data from seven field sites over 15 years. MNDWI water classification optimized here for the specificities of small water bodies reduced mean surface area errors by 57 % compared to published global datasets.
Filippo Bandini, Daniel Olesen, Jakob Jakobsen, Cecile Marie Margaretha Kittel, Sheng Wang, Monica Garcia, and Peter Bauer-Gottwein
Hydrol. Earth Syst. Sci., 22, 4165–4181, https://doi.org/10.5194/hess-22-4165-2018, https://doi.org/10.5194/hess-22-4165-2018, 2018
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Water depth observations are essential data to forecast flood hazard, predict sediment transport, or monitor in-stream habitats. We retrieved bathymetry with a sonar wired to a drone. This system can improve the speed and spatial scale at which water depth observations are retrieved. Observations can be retrieved also in unnavigable or inaccessible rivers. Water depth observations showed an accuracy of ca. 2.1 % of actual depth, without being affected by water turbidity or bed material.
Kiana Zolfaghari, Claude R. Duguay, and Homa Kheyrollah Pour
Hydrol. Earth Syst. Sci., 21, 377–391, https://doi.org/10.5194/hess-21-377-2017, https://doi.org/10.5194/hess-21-377-2017, 2017
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A remotely-sensed water clarity value (Kd) was applied to improve FLake model simulations of Lake Erie thermal structure using a time-invariant (constant) annual value as well as monthly values of Kd. The sensitivity of FLake model to Kd values was studied. It was shown that the model is very sensitive to variations in Kd when the value is less than 0.5 m-1.
Tomasz Niedzielski, Matylda Witek, and Waldemar Spallek
Hydrol. Earth Syst. Sci., 20, 3193–3205, https://doi.org/10.5194/hess-20-3193-2016, https://doi.org/10.5194/hess-20-3193-2016, 2016
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We study detectability of changes in water surface areas on orthophotomaps. We use unmanned aerial vehicles to acquire visible light photographs. We offer a new method for detecting changes in water surface areas and river stages. The approach is based on the application of the Student's t test, in asymptotic and bootstrapped versions. We test our approach on aerial photos taken during 3-year observational campaign. We detect transitions between all characteristic river stages using drone data.
E. Lalot, F. Curie, V. Wawrzyniak, F. Baratelli, S. Schomburgk, N. Flipo, H. Piegay, and F. Moatar
Hydrol. Earth Syst. Sci., 19, 4479–4492, https://doi.org/10.5194/hess-19-4479-2015, https://doi.org/10.5194/hess-19-4479-2015, 2015
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This work shows that satellite thermal infrared images (LANDSAT) can be used to locate and quantify groundwater discharge into a large river (Loire River, France - 100 to 300 m wide). Groundwater discharge rate is found to be highly variable with time and space and maximum during flow recession periods and in winter. The main identified groundwater discharge area into the Loire River corresponds to a known discharge area of the Beauce aquifer.
M. D. Wilson, M. Durand, H. C. Jung, and D. Alsdorf
Hydrol. Earth Syst. Sci., 19, 1943–1959, https://doi.org/10.5194/hess-19-1943-2015, https://doi.org/10.5194/hess-19-1943-2015, 2015
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We use a virtual mission analysis on a ca. 260km reach of the central Amazon River to assess the hydraulic implications of potential measurement errors in swath-altimetry imagery from the forthcoming Surface Water and Ocean Topography (SWOT) satellite mission. We estimated water surface slope from imagery of water heights and then derived channel discharge. Errors in estimated discharge were lowest when using longer reach lengths and channel cross-sectional averaging to estimate water slopes.
Y. B. Sulistioadi, K.-H. Tseng, C. K. Shum, H. Hidayat, M. Sumaryono, A. Suhardiman, F. Setiawan, and S. Sunarso
Hydrol. Earth Syst. Sci., 19, 341–359, https://doi.org/10.5194/hess-19-341-2015, https://doi.org/10.5194/hess-19-341-2015, 2015
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This paper investigates the possibility of monitoring small water bodies through Envisat altimetry observation. A novel approach is introduced to identify qualified and non-qualified altimetry measurements by assessing the waveform shapes for each returned radar signal. This research indicates that small lakes (extent < 100 km2) and medium-sized rivers (e.g., 200--800 m in width) can be successfully monitored by satellite altimetry.
Z. F. Miller, T. M. Pavelsky, and G. H. Allen
Hydrol. Earth Syst. Sci., 18, 4883–4895, https://doi.org/10.5194/hess-18-4883-2014, https://doi.org/10.5194/hess-18-4883-2014, 2014
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Many previous studies have used stream gauge data to estimate patterns of river width and depth based on variations in river discharge. However, these relationships may not capture all of the actual variability in width and depth. We have instead mapped the widths of all of the rivers wider than 100 m (and many narrower) in the Mississippi Basin and then used them to also improve estimates of depth as well. Our results show width and depth variations not captured by power-law relationships.
A. Kääb, M. Lamare, and M. Abrams
Hydrol. Earth Syst. Sci., 17, 4671–4683, https://doi.org/10.5194/hess-17-4671-2013, https://doi.org/10.5194/hess-17-4671-2013, 2013
V. H. Phan, R. C. Lindenbergh, and M. Menenti
Hydrol. Earth Syst. Sci., 17, 4061–4077, https://doi.org/10.5194/hess-17-4061-2013, https://doi.org/10.5194/hess-17-4061-2013, 2013
N. M. Velpuri and G. B. Senay
Hydrol. Earth Syst. Sci., 16, 3561–3578, https://doi.org/10.5194/hess-16-3561-2012, https://doi.org/10.5194/hess-16-3561-2012, 2012
C. I. Michailovsky, S. McEnnis, P. A. M. Berry, R. Smith, and P. Bauer-Gottwein
Hydrol. Earth Syst. Sci., 16, 2181–2192, https://doi.org/10.5194/hess-16-2181-2012, https://doi.org/10.5194/hess-16-2181-2012, 2012
H. Hidayat, D. H. Hoekman, M. A. M. Vissers, and A. J. F. Hoitink
Hydrol. Earth Syst. Sci., 16, 1805–1816, https://doi.org/10.5194/hess-16-1805-2012, https://doi.org/10.5194/hess-16-1805-2012, 2012
M. Potes, M. J. Costa, and R. Salgado
Hydrol. Earth Syst. Sci., 16, 1623–1633, https://doi.org/10.5194/hess-16-1623-2012, https://doi.org/10.5194/hess-16-1623-2012, 2012
A. T. Assireu, E. Alcântara, E. M. L. M. Novo, F. Roland, F. S. Pacheco, J. L. Stech, and J. A. Lorenzzetti
Hydrol. Earth Syst. Sci., 15, 3689–3700, https://doi.org/10.5194/hess-15-3689-2011, https://doi.org/10.5194/hess-15-3689-2011, 2011
C. H. Grohmann, C. Riccomini, and M. A. C. Chamani
Hydrol. Earth Syst. Sci., 15, 1493–1504, https://doi.org/10.5194/hess-15-1493-2011, https://doi.org/10.5194/hess-15-1493-2011, 2011
C. C. Abon, C. P. C. David, and N. E. B. Pellejera
Hydrol. Earth Syst. Sci., 15, 1283–1289, https://doi.org/10.5194/hess-15-1283-2011, https://doi.org/10.5194/hess-15-1283-2011, 2011
S. Trevisani, M. Cavalli, and L. Marchi
Hydrol. Earth Syst. Sci., 14, 393–405, https://doi.org/10.5194/hess-14-393-2010, https://doi.org/10.5194/hess-14-393-2010, 2010
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Short summary
The level of lake water is rapidly changing globally, and long-term, consistent observations of lake water extents are essential for ascertaining and attributing these changes. These data are rarely collected and challenging to obtain from satellite imagery. The proposed method addresses these challenges without any local data, and it was successfully validated against lakes with and without ground data. The algorithm is a valuable tool for the reliable historical water extent of changing lakes.
The level of lake water is rapidly changing globally, and long-term, consistent observations of...
