Monitoring monthly surface water dynamics of Dongting Lake using Sentinal-1 data at 10 m

High temporal resolution water distribution maps are essential for surface water monitoring because surface water exhibits significant inner-annual variation. Therefore, high-frequency remote sensing data are needed for surface water mapping. Dongting Lake, the second-largest freshwater lake in China, is famous for the seasonal fluctuations of its inundation extents in the middle reaches of the Yangtze River. It is also greatly affected by the Three Gorges Project. In this study, we used Sentinel-1 data to generate surface water maps of Dongting Lake at 10 m resolution. First, we generated the Sentinal-1 time series backscattering coefficient for VH and VV polarizations at 10 m resolution by using a monthly composition method. Second, we generated the thresholds for mapping surface water at 10 m resolution with monthly frequencies using Sentinel-1 data. Then, we derived the monthly surface water distribution product of Dongting Lake in 2016, and finally, we analyzed the inner-annual surface water dynamics. The results showed that: (1) The thresholds were −21.56 and −15.82 dB for the backscattering coefficients for VH and VV, respectively, and the overall accuracy and Kappa coefficients were above 95.50% and 0.90, respectively, for the VH backscattering coefficient, and above 94.50% and 0.88, respectively, for the VV backscattering coefficient. The VV backscattering coefficient achieved lower accuracy due to the effect of the wind causing roughness on the surface of the water. (2) The maximum and minimum areas of surface water were 2040.33 km2in July, and 738.89 km2in December. The surface water area of Dongting Lake varied most significantly in April and August. The permanent water acreage in 2016 was 556.35 km2, accounting for 19.65% of the total area of Dongting Lake, and the acreage of seasonal water was 1525.21 km2. This study proposed a method to automatically generate monthly surface water at 10 m resolution, which may contribute to monitoring surface water in a timely manner.

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Remote Sensing of Surface Water Dynamics Between 2015 and 2020 in the Prairie Pothole Region

10.5194/egusphere-egu21-8737 ◽

2021 ◽

Author(s):

Stefan Schlaffer ◽

Marco Chini ◽

Wouter Dorigo

Keyword(s):

Surface Water ◽

Prairie Pothole Region ◽

Water Area ◽

Water Bodies ◽

Water Dynamics ◽

Drought Indices ◽

Prairie Pothole ◽

Small Water ◽

Wide Range ◽

Small Water Bodies

The North American Prairie Pothole Region (PPR) consists of millions of wetlands and holds great importance for biodiversity, water storage and flood management. The wetlands cover a wide range of sizes from a few square metres to several square kilometres. Prairie hydrology is greatly influenced by the threshold behaviour of potholes leading to spilling as well as merging of adjacent wetlands. The knowledge of seasonal and inter-annual surface water dynamics in the PPR is critical for understanding this behaviour of connected and isolated wetlands. Synthetic aperture radar (SAR) sensors, e.g. used by the Copernicus Sentinel-1 mission, have great potential to provide high-accuracy wetland extent maps even when cloud cover is present. We derived water extent during the ice-free months May to October from 2015 to 2020 by fusing dual-polarised Sentinel-1 backscatter data with topographical information. The approach was applied to a prairie catchment in North Dakota. Total water area, number of water bodies and median area per water body were computed from the time series of water extent maps. Surface water dynamics showed strong seasonal dynamics especially in the case of small water bodies (<&#160;1&#160;ha) with a decrease in water area and number of small water bodies from spring throughout summer when evaporation rates in the PPR are typically high. Larger water bodies showed a more stable behaviour during most years. Inter-annual dynamics were strongly related to drought indices based on climate data, such as the Palmer Drought Severity Index. During the extremely wet period of late 2019 to 2020, the dynamics of both small and large water bodies changed markedly. While a larger number of small water bodies was encountered, which remained stable throughout the wet period, also the area of larger water bodies increased, partly due to merging of smaller adjacent water bodies. The results demonstrate the potential of Sentinel-1 data for long-term monitoring of prairie wetlands while limitations exist due to the rather low temporal resolution of 12 days over the PPR.

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Spatial and Temporal Changes in Surface Water Area of Sri Lanka over a 30-Year Period

Remote Sensing ◽

10.3390/rs12223701 ◽

2020 ◽

Vol 12 (22) ◽

pp. 3701

Author(s):

Deepakrishna Somasundaram ◽

Fangfang Zhang ◽

Sisira Ediriweera ◽

Shenglei Wang ◽

Junsheng Li ◽

...

Keyword(s):

Climate Change ◽

Surface Water ◽

Sri Lanka ◽

Anthropogenic Activities ◽

Water Area ◽

Temporal Changes ◽

Water Bodies ◽

Water Dynamics ◽

Annual Growth Rate ◽

Spatial And Temporal Changes

Sri Lanka contains a large number of natural and man-made water bodies, which play an essential role in irrigation and domestic use. The island has recently been identified as a global hotspot of climate change extremes. However, the extent, spatial distribution, and the impact of climate and anthropogenic activities on these water bodies have remained unknown. We investigated the distribution, spatial and temporal changes, and the impacts of climatic and anthropogenic drivers on water dynamics in Dry, Intermediate, and Wet zones of the island. We used Landsat 5 and Landsat 8 images to generate per-pixel seasonal and annual water occurrence frequency maps for the period of 1988–2019. The results of the study demonstrated high inter- and intra-annual variations in water with a rapid increase. Further, results showed strong zonal differences in water dynamics, with most dramatic variations in the Dry zone. Our results revealed that 1607.73 km2 of the land area of the island is covered by water bodies, among this 882.01 km2 (54.86%) is permanent and 725.72 km2 (45.14%) is seasonal water area. Total inland seasonal water increased with a dramatic annual growth rate of 7.06 ± 1.97 km2 compared to that of permanent water (4.47 ± 2.08 km2/year). Sri Lanka has the highest permanent water area during December–February (1045.97 km2), and drops to the lowest in May–September (761.92 km2) when the seasonal water (846.46 km2) is higher than permanent water. The surface water area was positively related to both precipitation and Gross Domestic Product, while negatively related to the temperature. Findings of our study provide important insights into possible spatiotemporal changes in surface water availability in Sri Lanka under certain climate change and anthropogenic activities.

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Constructing Mediterranean wetland open water dynamics using a new 18-year MODIS-derived surface water fraction dataset

10.5194/egusphere-egu2020-19945 ◽

2020 ◽

Author(s):

Linlin Li ◽

Anton Vrieling ◽

Andrew Skidmore ◽

Tiejun Wang

Keyword(s):

Time Series ◽

Surface Water ◽

Temporal Dynamics ◽

Open Water ◽

Water Area ◽

Water Bodies ◽

Water Dynamics ◽

Water Fraction ◽

Wide Range

Wetlands are among the most biodiverse ecosystems in the world, due largely to their dynamic hydrology. Frequent observations by satellite sensors such as the Moderate Resolution Imaging Spectrometer (MODIS) allow for monitoring the seasonal, inter-annual and long-term dynamics of surface water extent. However, existing MODIS-based studies have only demonstrated this for large water bodies despite the ecological importance of smaller-sized wetland systems. In this paper, we constructed the temporal dynamics of surface water extent for 340 individual water bodies in the Mediterranean region between 2000 and 2017, using a previously developed 8-day 500 m MODIS surface water fraction (SWF) dataset. These water bodies has a wide range of size, specifically 0.01 km2 and larger. We then compared the water extent time series derived from MODIS SWF with those derived from a Landsat-based dataset. Results showed that MODIS- and Landsat-derived water extent time series showed a high correlation (r = 0.81) for more dynamic water bodies. Our MODIS SWF dataset can also effectively monitor the variability of very small water bodies (<1 km2) when comparing with Landsat data as long as the temporal variability in their surface water area was high. We conclude that MODIS SWF is a useful product to help understand hydrological dynamics for both small and larger-sized water bodies, and to monitor their seasonal, intermittent, inter-annual and long-term changes.

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STUDY OF THE TEMPERATURE CONDITION OF SURFACE WATERS OF NOVOTROITSKY RESERVOIR BASED ON REMOTE SENSING DATA AND EVALUATION OF ITS IMPACT ON FISH GROWTH AND DEVELOPMENT

South of Russia ecology development ◽

10.18470/1992-1098-2018-3-150-158 ◽

2018 ◽

Vol 13 (3) ◽

pp. 150-158

Author(s):

Evgeniy G. Mishvelov ◽

Ivan A. Bakumenko ◽

Anatoliy F. Shevkhuzhev ◽

Vladimir A. Pogodaev

Keyword(s):

Remote Sensing ◽

Surface Water ◽

Surface Waters ◽

Growth And Development ◽

Water Surface ◽

Water Reservoir ◽

Remote Sensing Data ◽

Water Area ◽

Temperature Fields ◽

Summer Period

Aim. The aim of the study is to analyze and reveal the features of the temperature regime of the Novotroitsky water reservoir surface based on remote sensing data; to determine the influence of the temperature regime of the surface waters of Novotroitsky reservoir on the ecological state of the reservoir, as well as to determine the areas of the surface water zones of the Novotroitsky reservoir with optimal and unfavorable temperature conditions for fish. Methods. The temperature values of the earth's surface (water area) were calculated according to the generally accepted methodology. Its essence lies in the fact that the calculation of the earth's surface temperature is performed after radiometric calibration of the images and compensation of the effect of the optical density of the atmosphere taking into account the emissivity of various objects on the earth's surface. The calculations were performed separately for the 10 and 11 channels of images from the Landsat 8 satellite, and then averaged. Results. Were established the quantitative characteristics of the inhomogeneity of the temperature fields of the water surface of Novotroitsky reservoir during the summer period due to discharges of the heated waters of the Stavropol GRES power plant. The peculiarities of the spatial variability of the temperature fields of the Novotroitsky water reservoir surface in summer season were revealed. It is shown that the use of the Novotroitsky water reservoir as a reservoir-cooler is potentially accompanied by the development of eutrophication processes and creation of risks for drinking purposes, as well as cultural, household and fishery use. The table shows the data demonstrating the temperature condition of the Novotroitsky reservoir water surface. The figure shows the temperature fields of the surface of the Novotroitsky water reservoir. Conclusions. In summer period, half of the water area of the Novotroitsky water reservoir can be attributed to the zones of optimum temperatures for the juvenile pikeperch. Were revealed the periods when the reservoir becomes practically unsuitable for growth and development of juveniles of oxyphilic fish. Excessive rise of water temperature in summer was established in accordance with SanPiN (Sanitary Rules and Regulations) 2.1.5.980-00.2.1.5. Such an increase in temperature is observed in 13-16% of the whole water area.

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Evaluation of surface water dynamics for water-food security in seasonal wetlands, north-central Namibia

Proceedings of the International Association of Hydrological Sciences ◽

10.5194/piahs-364-380-2014 ◽

2014 ◽

Vol 364 ◽

pp. 380-385 ◽

Cited By ~ 2

Author(s):

T. Hiyama ◽

T. Suzuki ◽

M. Hanamura ◽

H. Mizuochi ◽

J. R. Kambatuku ◽

...

Keyword(s):

Remote Sensing ◽

Food Security ◽

Surface Water ◽

Satellite Remote Sensing ◽

Cropping Systems ◽

Remote Sensing Data ◽

Water Dynamics ◽

Mixed Cropping ◽

North Central ◽

Seasonal Wetlands

Abstract. Agricultural use of wetlands is important for food security in various regions. However, land-use changes in wetland areas could alter the water cycle and the ecosystem. To conserve the water environments of wetlands, care is needed when introducing new cropping systems. This study is the first attempt to evaluate the water dynamics in the case of the introduction of rice-millet mixed-cropping systems to the Cuvelai system seasonal wetlands (CSSWs) in north-central Namibia. We first investigated seasonal changes in surface water coverage by using satellite remote sensing data. We also assessed the effect of the introduction of rice-millet mixed-cropping systems on evapotranspiration in the CSSWs region. For the former investigation, we used MODIS and AMSR-E satellite remote sensing data. These data showed that at the beginning of the wet season, surface water appears from the southern (lower) part and then expands to the northern (higher) part of the CSSWs. For the latter investigation, we used data obtained by the classical Bowen ratio-energy balance (BREB) method at an experimental field site established in September 2012 on the Ogongo campus, University of Namibia. This analysis showed the importance of water and vegetation conditions when introducing mixed-cropping to the region.

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An Integrated Hydrological-Hydraulic Model for Simulating Surface Water Flows of a Shallow Lake Surrounded by Large Floodplains

Water ◽

10.3390/w10091213 ◽

2018 ◽

Vol 10 (9) ◽

pp. 1213 ◽

Cited By ~ 9

Author(s):

Tomohiro Tanaka ◽

Hidekazu Yoshioka ◽

Sokly Siev ◽

Hideto Fujii ◽

Yoichi Fujihara ◽

...

Keyword(s):

Surface Water ◽

Remote Sensing Data ◽

Hydraulic Model ◽

Water Dynamics ◽

Roughness Coefficient ◽

Time Step ◽

Data Set ◽

Water Flows ◽

Tonle Sap ◽

Numerical Stability Analysis

An integrated hydrological-hydraulic model employing the 2-D local inertial equation as the core is established for effective numerical simulation of surface water flows in a great lake and its floodplain. The model is a cascade of validated hydrological and hydraulic sub-models. The model was applied to simulating the surface water flows of the Tonle Sap Lake and its floodplain in Cambodia using the roughness coefficient value calibrated comparing with a remote-sensing data set. The resulting model reasonably handles backwater flows during the rainy season and simulates the propagations of wet and dry interfaces without numerical instability, owing to a proper setting of time step supported by a novel numerical stability analysis. Sensitivity analysis of the surface water dynamics focusing on the setting of roughness coefficient and the backwater effect was also carried out. Overall, utilizing the 2-D local inertial equation in the assessment of lake water dynamics is a new modelling approach, which turns out to be an efficient simulation tool.

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Lake Chad Total Surface Water Area as Derived from Land Surface Temperature and Radar Remote Sensing Data

Remote Sensing ◽

10.3390/rs10020252 ◽

2018 ◽

Vol 10 (2) ◽

pp. 252 ◽

Cited By ~ 12

Author(s):

Frederick Policelli ◽

Alfred Hubbard ◽

Hahn Jung ◽

Ben Zaitchik ◽

Charles Ichoku

Keyword(s):

Remote Sensing ◽

Surface Water ◽

Surface Temperature ◽

Land Surface Temperature ◽

Land Surface ◽

Remote Sensing Data ◽

Water Area ◽

Radar Remote Sensing ◽

Lake Chad ◽

Sensing Data

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High Spatiotemporal Resolution Mapping of Surface Water in the Southwest Poyang Lake and Its Responses to Climate Oscillations

Sensors ◽

10.3390/s20174872 ◽

2020 ◽

Vol 20 (17) ◽

pp. 4872

Author(s):

Haifeng Tian ◽

Jian Wang ◽

Jie Pei ◽

Yaochen Qin ◽

Lijun Zhang ◽

...

Keyword(s):

Surface Water ◽

Poyang Lake ◽

Water Area ◽

Water Extraction ◽

Water Dynamics ◽

Lake Area ◽

Lake Surface ◽

Spatiotemporal Resolution ◽

High Spatiotemporal Resolution ◽

Resolution Mapping

Accurately quantifying spatiotemporal changes in surface water is essential for water resources management, nevertheless, the dynamics of Poyang Lake surface water areas with high spatiotemporal resolution, as well as its responses to climate change, still face considerable uncertainties. Using the time series of Sentinel-1 images with 6- or 12-day intervals, the Sentinel-1 water index (SWI), and SWI-based water extraction model (SWIM) from 2015 to 2020 were used to document and study the short-term characteristics of southwest Poyang Lake surface water. The results showed that the overall accuracy of surface water area was satisfactory with an average of 91.92%, and the surface water area ranged from 129.06 km2 on 2 March 2017 to 1042.57 km2 on 17 July 2016, with significant intra- and inter-month variability. Within the 6-day interval, the maximum change of lake area was 233.42 km2 (i.e., increasing from 474.70 km2 up to 708.12 km2). We found that the correlation coefficient between the water area and the 45-day accumulated precipitation reached to 0.75 (p < 0.001). Moreover, a prediction model was built to predict the water area based on climate records. These results highlight the significance of high spatiotemporal resolution mapping for surface water in the erratic southwest Poyang Lake under a changing climate. The automated water extraction algorithm proposed in this study has potential applications in delineating surface water dynamics at broad geographic scales.

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Determining Temporal Uncertainty of a Global Inland Surface Water Time Series

Remote Sensing ◽

10.3390/rs13173454 ◽

2021 ◽

Vol 13 (17) ◽

pp. 3454

Author(s):

Stefan Mayr ◽

Igor Klein ◽

Martin Rutzinger ◽

Claudia Kuenzer

Keyword(s):

Time Series ◽

Surface Water ◽

Observation Time ◽

Water Dynamics ◽

High Temporal Resolution ◽

Sampling Errors ◽

Large Area ◽

Validation Data ◽

Moderate Resolution Imaging Spectroradiometer ◽

Original Time

Earth observation time series are well suited to monitor global surface dynamics. However, data products that are aimed at assessing large-area dynamics with a high temporal resolution often face various error sources (e.g., retrieval errors, sampling errors) in their acquisition chain. Addressing uncertainties in a spatiotemporal consistent manner is challenging, as extensive high-quality validation data is typically scarce. Here we propose a new method that utilizes time series inherent information to assess the temporal interpolation uncertainty of time series datasets. For this, we utilized data from the DLR-DFD Global WaterPack (GWP), which provides daily information on global inland surface water. As the time series is primarily based on optical MODIS (Moderate Resolution Imaging Spectroradiometer) images, the requirement of data gap interpolation due to clouds constitutes the main uncertainty source of the product. With a focus on different temporal and spatial characteristics of surface water dynamics, seven auxiliary layers were derived. Each layer provides probability and reliability estimates regarding water observations at pixel-level. This enables the quantification of uncertainty corresponding to the full spatiotemporal range of the product. Furthermore, the ability of temporal layers to approximate unknown pixel states was evaluated for stratified artificial gaps, which were introduced into the original time series of four climatologic diverse test regions. Results show that uncertainty is quantified accurately (>90%), consequently enhancing the product’s quality with respect to its use for modeling and the geoscientific community.

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Potential and Limitations of Satellite Altimetry Constellations for Monitoring Surface Water Storage Changes—A Case Study in the Mississippi Basin

Remote Sensing ◽

10.3390/rs12203320 ◽

2020 ◽

Vol 12 (20) ◽

pp. 3320

Author(s):

Denise Dettmering ◽

Laura Ellenbeck ◽

Daniel Scherer ◽

Christian Schwatke ◽

Christoph Niemann

Keyword(s):

Surface Water ◽

Mississippi River ◽

Satellite Altimetry ◽

Remote Sensing Data ◽

Water Area ◽

Water Levels ◽

In Situ Data ◽

Ocean Topography

Remote sensing data are essential for monitoring the Earth’s surface waters, especially since the amount of publicly available in-situ data is declining. Satellite altimetry provides valuable information on the water levels and variations of lakes, reservoirs and rivers. In combination with satellite imagery, the derived time series allow the monitoring of lake storage changes and river discharge. However, satellite altimetry is limited in terms of its spatial resolution due to its measurement geometry, only providing information in the nadir direction beneath the satellite’s orbit. In a case study in the Mississippi River Basin (MRB), this study investigates the potential and limitations of past and current satellite missions for the monitoring of basin-wide storage changes. For that purpose, an automated target detection is developed and the extracted lake surfaces are merged with the satellites’ tracks. This reveals that the current altimeter configuration misses about 80% of all lakes larger than 0.1 km2 in the MRB and 20% of lakes larger than 10 km2, corresponding to 30% and 7% of the total water area, respectively. Past altimetry configurations perform even more poorly. From the larger water bodies represented by a global hydrology model, at least 91% of targets and 98% of storage changes are captured by the current altimeter configuration. This will improve significantly with the launch of the planned Surface Water and Ocean Topography (SWOT) mission.

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