scholarly journals Validation of Sentinel-3A Based Lake Level over US and Canada

2020 ◽  
Vol 12 (17) ◽  
pp. 2835
Author(s):  
Karina Nielsen ◽  
Ole Baltazar Andersen ◽  
Heidi Ranndal
Keyword(s):  
Water Level ◽  
Satellite Altimetry ◽  
Lake Level ◽  
Mean Squared Error ◽  
Pearson Correlation ◽  
The United States ◽  
Water Levels ◽  
Winter Period ◽  
Large Lakes ◽  
In Situ Data

Satellite altimetry is an important contributor for measuring the water level of continental water bodies. The technique has been applied for almost three decades. In this period the data quality has increased and the applications have evolved from the study of a few large lakes and rivers, to near global applications at various scales. Products from current satellite altimetry missions should be validated to continuously improve the measurements. Sentinel-3A has been operating since 2016 and is the first mission operating in synthetic aperture radar (SAR) mode globally. Here we evaluate its performance in capturing lake level variations based on a physical and an empirical retracker provided in the official level 2 product. The validation is performed for more than 100 lakes in the United States and Canada where the altimetry based water levels are compared with in situ data. As validation measures we consider the root mean squared error, the Pearson correlation, and the percentage of outliers. For the US sites the median of the RMSE value is 25 cm and 19 cm and the median of the Pearson correlations are 0.86 and 0.93 for the physical and empirical retracker, respectively. The percentage of outliers (median) is 11% for both retrackers. The validations measures are slightly poorer for the Canadian sites; the median RMSE is approximately 5 cm larger, the Pearson correlation 0.1 lower, and the percentage of outliers 5% larger. The poorer performance for the Canadian sites is mainly related to the presence of lake ice in the winter period where the surface elevations are not able to map the surface correctly. The validation measures improve considerably when evaluated for summer data only. For both areas we show that the reconstruction of the water level variations based on the empirical retracker is significantly better compared to that of the physical retracker in terms of the RMSE and the Pearson correlation.

scholarly journals Monitoring Long-Term Lake Level Variations in Middle and Lower Yangtze Basin over 2002–2017 through Integration of Multiple Satellite Altimetry Datasets

2020 ◽  
Vol 12 (9) ◽  
pp. 1448 ◽  
Author(s):  
Peng Li ◽  
Hui Li ◽  
Fang Chen ◽  
Xiaobin Cai
Keyword(s):  
Water Level ◽  
Satellite Altimetry ◽  
Lake Level ◽  
Yangtze River Basin ◽  
Water Levels ◽  
Lake Level Changes ◽  
Lower Yangtze ◽  
Increasing Trends ◽  
The Impact

Satellite altimetry has been effectively used for monitoring lake level changes in recent years. This work focused on the integration of multiple satellite altimetry datasets from ICESat-1, Envisat and Cryosat-2 for the long-term (2002–2017) observation of lake level changes in the middle and lower Yangtze River Basin (MLYB). Inter-altimeter biases were estimated by using the gauged daily water level data. It showed that the average biases of ICESat-1 and Cryosat-2 with respect to Envisat were 6.7 cm and 3.1 cm, respectively. The satellite-derived water levels were evaluated against the gauged data. It indicated significantly high correlations between the two datasets, and the combination of three altimetry data produced precise water level time series with high temporal and spatial resolutions. A liner regression model was used to estimate the rates of lake level changes over the study period after the inter-altimeter bias adjustment was performed. The results indicated that ~79% of observed lakes (41/52) showed increasing trends in water levels with rates up to 0.203 m/y during 2002–2017. The temporal analysis of lake level variations suggested that ~60% of measured lakes (32/53) showed decreasing trends during 2002–2009 while ~66% of measured lakes (79/119) exhibited increasing trends during 2010–2017. Most of measured reservoirs displayed rapidly rising trends during the study period. The driving force analysis indicated that the temporal heterogeneity of precipitation can be mainly used to explain the observed pattern of lake level changes. The operation of reservoirs and human water consumption were also responsible for the lake level variations. This work demonstrated the potential of integrating multiple satellite altimeters for the long-term monitoring of lake levels, which can help to evaluate the impact of climate change and anthropogenic activities on regional water resources.

scholarly journals A multi-source satellite data approach for modelling Lake Turkana water level: calibration and validation using satellite altimetry data

2012 ◽  
Vol 16 (1) ◽  
pp. 1-18 ◽  
Author(s):  
N. M. Velpuri ◽  
G. B. Senay ◽  
K. O. Asante
Keyword(s):  
Water Balance ◽  
Satellite Altimetry ◽  
Lake Level ◽  
Water Balance Model ◽  
Water Levels ◽  
Balance Model ◽  
Altimetry Data ◽  
Lake Turkana ◽  
In Situ Data ◽  
Satellite Altimetry Data

Abstract. Lake Turkana is one of the largest desert lakes in the world and is characterized by high degrees of inter- and intra-annual fluctuations. The hydrology and water balance of this lake have not been well understood due to its remote location and unavailability of reliable ground truth datasets. Managing surface water resources is a great challenge in areas where in-situ data are either limited or unavailable. In this study, multi-source satellite-driven data such as satellite-based rainfall estimates, modelled runoff, evapotranspiration, and a digital elevation dataset were used to model Lake Turkana water levels from 1998 to 2009. Due to the unavailability of reliable lake level data, an approach is presented to calibrate and validate the water balance model of Lake Turkana using a composite lake level product of TOPEX/Poseidon, Jason-1, and ENVISAT satellite altimetry data. Model validation results showed that the satellite-driven water balance model can satisfactorily capture the patterns and seasonal variations of the Lake Turkana water level fluctuations with a Pearson's correlation coefficient of 0.90 and a Nash-Sutcliffe Coefficient of Efficiency (NSCE) of 0.80 during the validation period (2004–2009). Model error estimates were within 10% of the natural variability of the lake. Our analysis indicated that fluctuations in Lake Turkana water levels are mainly driven by lake inflows and over-the-lake evaporation. Over-the-lake rainfall contributes only up to 30% of lake evaporative demand. During the modelling time period, Lake Turkana showed seasonal variations of 1–2 m. The lake level fluctuated in the range up to 4 m between the years 1998–2009. This study demonstrated the usefulness of satellite altimetry data to calibrate and validate the satellite-driven hydrological model for Lake Turkana without using any in-situ data. Furthermore, for Lake Turkana, we identified and outlined opportunities and challenges of using a calibrated satellite-driven water balance model for (i) quantitative assessment of the impact of basin developmental activities on lake levels and for (ii) forecasting lake level changes and their impact on fisheries. From this study, we suggest that globally available satellite altimetry data provide a unique opportunity for calibration and validation of hydrologic models in ungauged basins.

Sedimentary Cladocera as indicators of past water-level changes in shallow northern lakes

2011 ◽  
Vol 75 (3) ◽  
pp. 430-437 ◽  
Author(s):  
Liisa Nevalainen ◽  
Kaarina Sarmaja-Korjonen ◽  
Tomi P. Luoto
Keyword(s):  
Water Level ◽  
Lake Level ◽  
Water Levels ◽  
Sediment Record ◽  
Inference Model ◽  
Water Level Changes ◽  
Long Term Changes ◽  
Lower Water Level ◽  
The Relationship

AbstractThe usability of subfossil Cladocera assemblages in reconstructing long-term changes in lake level was examined by testing the relationship between Cladocera-based planktonic/littoral (P/L) ratio and water-level inference model in a surface-sediment dataset and in a 2000-yr sediment record in Finland. The relationships between measured and inferred water levels and P/L ratios were significant in the dataset, implying that littoral taxa are primarily deposited in shallow littoral areas, while planktonic cladocerans accumulate abundantly mainly in deepwater locations. The 2000-yr water-level reconstructions based on the water-level inference model and P/L ratio corresponded closely with each other and with a previously available midge-inferred water-level reconstruction from the same core, showing a period of lower water level around AD 300–1000 and suggesting that the methods are valid for paleolimnological and -climatological use.

scholarly journals Causes of the Transboundary Lake Khanka Extreme High Water Level

2016 ◽  
pp. 62
Author(s):  
Keyword(s):  
Water Level ◽  
Lake Level ◽  
High Water ◽  
Water Levels ◽  
Anthropogenic Factors ◽  
Economic Activities ◽  
Republic Of China ◽  
High Water Level ◽  
Level Regime ◽  
Lake Khanka

Reasons of the extremely high water level in Lake Khanka (it was 0.5 m higher the historical maximum over the past years) have been revealed within the frameworks of the carried out exploration. The lake capacity characteristics alteration due to the natural and anthropogenic factors’ impact has been assessed. We have considered the factors that form the Lake Khanka level regime, i.e. natural: atmosphere circulation, atmospheric perspiration, river inflow to the lake, evaporation from the lake surface, and outflow; anthropogenic: economic activities on the catchment on Russian and Chinese territories (hydro/melioration and the runoff transfer). The passage capacity of the Sungachi River, the only outflow from the lake, has been analyzed in details at different water levels in Lake Khanka. The paper is based on summing up and analysis of information on the lake hydro/meteorological regime and economic activities on its catchment, as well as reference literature. As a result of the study the authors for the first time has identified the main reason of the abnormal rise of the Kanka level. It was found that the significant transformation of the lake level regime occurred due to the Mulinkhe Rivers runoff transfer to Lake Malaya Khanka from the People’s Republic of China. A forecast of the lake level for 2016 taking into consideration different scenarios of the basin moistening has been given. In connection with the forecasted rise of the water level in Lake Khanka in the nearest future we propose a number of measures aimed to minimize inevitable damage to the Russian party.

scholarly journals Interannual variability of the lake levels in northwest Russia based on satellite altimetry

2015 ◽  
Vol 365 ◽  
pp. 91-97
Author(s):  
S. A. Lebedev ◽  
Y. I. Troitskaya ◽  
G. V. Rybushkina ◽  
M. N. Dobrovolsky
Keyword(s):  
Water Level ◽  
Interannual Variability ◽  
Temporal Variability ◽  
Satellite Altimetry ◽  
Lake Level ◽  
Lake Ladoga ◽  
Lake Levels ◽  
Lake Onega ◽  
Lake Ilmen ◽  
Altimetric Measurements

Abstract. Variability of the largest lakes levels in northwest Russia, a climatic change parameter, is characterized by alternating periods of rise and fall according to altimetric measurements of the TOPEX/Poseidon and Jason-1/2 satellites. Water level was calculated with the use of a regional adaptive retracking algorithm for the lakes Il’men, Ladoga, Onega and Peipus. Applications of this algorithm considerably increase the quantity of actual data records and significantly improve the accuracy of water level evaluation. According to the results, temporal variability of Lake Ilmen, Lake Ladoga and Lake Piepus levels is characterized by a wave with a period of 4–5 years, and that of Lake Onega level is characterized by a wave with a period of 15 years. During the period from 1993 to 2011, lake level rose at a rate of 1.17±0.95 cm/year for Lake Il’men, 0.24 ± 0.10 cm/year for Lake Ladoga, 1.39 ± 0.18 cm/year for Lake Piepus and 0.18 ± 0.09 cm/year for Lake Onega.

scholarly journals Seasonal and Annual Probabilistic Forecasting of Water Levels in Large Lakes (Case Study of the Ladoga Lake)

2021 ◽  
Vol 82 ◽  
pp. 13-19
Author(s):  
Natalia V. Myakisheva ◽  
Ekaterina V. Gaidukova ◽  
Sergei V. Shanochkin ◽  
Anna A. Batmazova
Keyword(s):  
Water Level ◽  
Moving Average ◽  
Water Levels ◽  
Probabilistic Forecasting ◽  
Large Lakes ◽  
Annual Variations ◽  
Ladoga Lake ◽  
Moving Average Processes ◽  
Relative Errors

The production functions of water-dependent sectors of the economy can include the water level in the lake as a natural resource. This characteristic must be able to reliably predict for the effective functioning of sectors of the economy. In the article the main attention is paid to the methods of forecasting based on the extrapolation of natural variations of the large lakes water level. As an example, is considered. In this paper, it is assumed that the level varies accordingly to a stochastic multi-cycle process with principal energy-containing zones in frequency bands associated with seasonal and multi-annual variations. Hence, the multi-year monthly and yearly averaged time series are represented by the ARIMA (auto-regression integrated moving average) processes. Forecasts are generated by using of the seasonal ARIMA-models, which take into account not only the seasonal but also the evolution non-stationarity. To compare the forecasts and the actual values, the relative errors are computed. It is shown that implementation of the models mainly allows receiving good and excellent forecasts. Subject Classification Numbers: UDC 556.555.2.06(4)

scholarly journals Accuracy of Copernicus Altimeter Water Level Data in Italian Rivers Accounting for Narrow River Sections

2021 ◽  
Vol 13 (21) ◽  
pp. 4456
Author(s):  
Cristina Deidda ◽  
Carlo De Michele ◽  
Ali Nadir Arslan ◽  
Silvano Pecora ◽  
Nicolas Taburet
Keyword(s):  
Water Level ◽  
Satellite Data ◽  
Pearson Correlation ◽  
Absolute Error ◽  
Drought Risk ◽  
Satellite Measurements ◽  
Joint Measurement ◽  
Initial Water ◽  
In Situ Data

Information about water level is essential for hydrological monitoring and flood/ drought risk assessment. In a large part of Italian river network, in situ instruments for measuring water level are rare or lacking. Here we consider the satellite measurements of water level retrieved by Copernicus altimetric missions (Sentinel 3A, Sentinel 3B, Jason 2/3), and compare these with in situ data, from 19 gauging stations in Italy with a river section in the range of [50, 555] m. The results highlight the potentiality of altimetric satellite measurements for water level retrieval in a case study of Italian rivers. By comparing synchronous satellite and in situ water level difference (i.e., difference between two successive measurements in time of satellite data compared to the difference of two successive measurements in time of in situ data), we found a median value of Pearson correlation of 0.79 and 0.37 m of RMSE. Then, from water level differences, we extracted the satellite water level values with two different procedures: (1) assuming as the initial water level of the satellite measurements the first joint measurement (satellite–in situ data) and (2) calibrating the initial water level, minimizing the mean absolute error metric. The results show the feasibility of using satellite data for water level retrieval in an operative and automatic perspective.

scholarly journals STORM SURGE FORECASTING METHODS IN ENCLOSED SEAS

1978 ◽  
Vol 1 (16) ◽  
pp. 58
Author(s):  
P.F. Hamblin
Keyword(s):  
Water Level ◽  
Storm Surge ◽  
Storm Surges ◽  
High Water ◽  
Computational Effort ◽  
Water Levels ◽  
Large Lakes ◽  
Forecasting Methods ◽  
The Stability ◽  
Storm Surge Forecasting

Storm surges in enclosed seas although generally not as large in amplitude as their oceanic counterparts are nonetheless of considerable importance when low lying shoreline profiles, shallow water depth, and favourable geographical orientation to storm winds occur together. High water may result in shoreline innundation and in enhanced shoreline erosion. Conversely low water levels are hazardous to navigation. The purpose of this paper is to discuss the problem of storm surge forecasting in enclosed basins with emphasis on automated operational procedures. In general, operational forecasting methods must be based on standard forecast parameters, require a minimum of computational effort in the preparation of the forecast, must be applicable to lakes of different geometry and to any point on the shore, and to be able to resolve water level changes on an hourly basis to 10 cm in the case of high water level excursions associated with large lakes and less than that for smaller lakes. Particular physical effects arising in lakes which make these constraints difficult to fulfill are the reflections of resurgences of water levels arising from lateral boundaries, the stability of the atmospheric boundary layer and the presence of such subsynoptic disturbances as squall lines and travelling pressure jumps.

scholarly journals Visualization of Lake Mead Surface Area Changes from 1972 to 2009

2021 ◽  
Author(s):  
K. Wayne Forsythe ◽  
Barbara Schatz ◽  
Stephen J. Swales ◽  
Lisa-Jen Ferrato ◽  
David M. Atkinson
Keyword(s):  
United States ◽  
Water Level ◽  
Surface Area ◽  
Satellite Images ◽  
Strong Relationship ◽  
The United States ◽  
Water Levels ◽  
Lake Area ◽  
Lake Mead ◽  
Landsat Satellite

For most of the last decade, the south-western portion of the United States has experienced a severe and enduring drought. This has caused serious concerns about water supply and management in the region. In this research, 30 orthorectified Landsat satellite images from the United States Geological Service (USGS) Earth Explorer archive were analyzed for the 1972 to 2009 period. The images encompassed Lake Mead (a major reservoir in this region) and were examined for changes in water surface area. Decadal lake area minimums/maximums were achieved in 1972/1979, 1981/1988, 1991/1998, and 2009/2000. The minimum lake area extent occurred in 2009 (356.4 km2), while the maximum occurred in 1998 (590.6 km2). Variable trends in water level and lake area were observed throughout the analysis period, however progressively lower values were observed since 2000. The Landsat derived lake areas show a very strong relationship with actual measured water levels at the Hoover Dam. Yearly water level variations at the dam vary minimally from the satellite derived estimates. A complete (yearly) record of satellite images may have helped to reduce the slight deviations in the time series.

scholarly journals Automated Water Level Monitoring at the Continental Scale from ICESat-2 Photons

2021 ◽  
Vol 13 (18) ◽  
pp. 3631
Author(s):  
Austin Madson ◽  
Yongwei Sheng
Keyword(s):  
United States ◽  
Water Level ◽  
Cluster Computing ◽  
Mean Squared Error ◽  
The United States ◽  
United States Geological Survey ◽  
Continental Scale ◽  
Water Level Changes ◽  
Lakes And Reservoirs ◽  
The Mean

Of the approximately 6700 lakes and reservoirs larger than 1 km2 in the Contiguous United States (CONUS), only ~430 (~6%) are actively gaged by the United States Geological Survey (USGS) or their partners and are available for download through the National Water Information System database. Remote sensing analysis provides a means to fill in these data gaps in order to glean a better understanding of the spatiotemporal water level changes across the CONUS. This study takes advantage of two-plus years of NASA’s ICESat-2 (IS-2) ATLAS photon data (ATL03 products) in order to derive water level changes for ~6200 overlapping lakes and reservoirs (>1 km2) in the CONUS. Interactive visualizations of large spatial datasets are becoming more commonplace as data volumes for new Earth observing sensors have markedly increased in recent years. We present such a visualization created from an automated cluster computing workflow that utilizes tens of billions of ATLAS photons which derives water level changes for all of the overlapping lakes and reservoirs in the CONUS. Furthermore, users of this interactive website can download segmented and clustered IS-2 ATL03 photons for each individual waterbody so that they may run their own analysis. We examine ~19,000 IS-2 derived water level changes that are spatially and temporally coincident with water level changes from USGS gages and find high agreement with our results as compared to the in situ gage data. The mean squared error (MSE) and the mean absolute error (MAE) between these two products are 1 cm and 6 cm, respectively.

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