Using multi-source satellite data for lake level modelling in ungauged basins: a case study for Lake Turkana, East Africa

Abstract. Managing limited surface water resources is a great challenge in areas where ground-based data are either limited or unavailable. Direct or indirect measurements of surface water resources through remote sensing offer several advantages of monitoring in ungauged basins. A physical based hydrologic technique to monitor lake water levels in ungauged basins using multi-source satellite data such as satellite-based rainfall estimates, modelled runoff, evapotranspiration, a digital elevation model, and other data is presented. This approach is applied to model Lake Turkana water levels from 1998 to 2009. Modelling results showed that the model can reasonably capture all the patterns and seasonal variations of the lake water level fluctuations. A composite lake level product of TOPEX/Poseidon, Jason-1, and ENVISAT satellite altimetry data is used for model calibration (1998–2000) and model validation (2001–2009). Validation results showed that model-based lake levels are in good agreement with observed satellite altimetry data. Compared to satellite altimetry data, the Pearson's correlation coefficient was found to be 0.81 during the validation period. The model efficiency estimated using NSCE is found to be 0.93, 0.55 and 0.66 for calibration, validation and combined periods, respectively. Further, the model-based estimates showed a root mean square error of 0.62 m and mean absolute error of 0.46 m with a positive mean bias error of 0.36 m for the validation period (2001–2009). These error estimates were found to be less than 15 % of the natural variability of the lake, thus giving high confidence on the modelled lake level estimates. The approach presented in this paper can be used to (a) simulate patterns of lake water level variations in data scarce regions, (b) operationally monitor lake water levels in ungauged basins, (c) derive historical lake level information using satellite rainfall and evapotranspiration data, and (d) augment the information provided by the satellite altimetry systems on changes in lake water levels.

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

Hydrology and Earth System Sciences ◽

10.5194/hess-16-1-2012 ◽

2012 ◽

Vol 16 (1) ◽

pp. 1-18 ◽

Cited By ~ 47

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.

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Densified multi-mission observations by developed optical water levels show marked increases in lake water storage and overflow floods on the Tibetan Plateau

10.5194/essd-2019-34 ◽

2019 ◽

Author(s):

Xingdong Li ◽

Di Long ◽

Qi Huang ◽

Pengfei Han ◽

Fanyu Zhao ◽

...

Keyword(s):

Tibetan Plateau ◽

Water Level ◽

Lake Water ◽

Water Storage ◽

Water Levels ◽

The Tibetan Plateau ◽

Altimetry Data ◽

Data Set ◽

Lake Water Level ◽

And Storage

Abstract. The Tibetan Plateau (TP) known as Asia's water towers is quite sensitive to climate change, reflected by changes in hydrological state variables such as lake water storage. Given the extremely limited ground observations on the TP due to the harsh environment and complex terrain, we exploited multisource remote sensing, i.e., multiple altimetric missions and Landsat archives to create dense time series (monthly and even higher such as 10 days on average) of lake water level and storage changes across 52 large lakes (> 100 km2) on the TP during 2000–2017 (the data set is available online with a DOI: https://doi.org/10.1594/PANGAEA.898411). Field experiments were carried out in two typical lakes to validate the remotely sensed results. With Landsat archives and partial altimetry data, we developed optical water levels that cover most of TP lakes and serve as an ideal reference for merging multisource lake water levels. The optical water levels show an uncertainty of ~ 0.1 m that is comparable with most altimetry data and largely reduce the lack of dense altimetric observations with systematic errors well removed for most of lakes. The densified lake water levels provided critical and accurate information on the long-term and short-term monitoring of lake water level and storage changes on the TP. We found that the total storage of the 52 lakes increased by 97.3 km3 at two stages, i.e., 6.68 km3/yr during 2000–2012 and 2.85 km3/yr during 2012–2017. The total overflow from Lake Kusai to Lake Haidingnuoer and Lake Salt during Nov 9–Dec 31 in 2011 was estimated to be 0.22 km3, providing critical information on lake overflow flood monitoring and prediction as the expansion of some TP lakes becomes a serious threat to surrounding residents and infrastructure.

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Relationships between pacific and atlantic ocean sea surface temperatures and water levels from satellite altimetry data in the Amazon rivers

RBRH ◽

10.1590/2318-0331.231820170148 ◽

2018 ◽

Vol 23 (0) ◽

Author(s):

Mylena Vieira Silva ◽

Adrien Paris ◽

Stéphane Calmant ◽

Luiz Antonio Cândido ◽

Joecila Santos da Silva

Keyword(s):

Water Level ◽

Satellite Altimetry ◽

Amazon Basin ◽

Strong Relationship ◽

Water Levels ◽

Sea Surface ◽

Altimetry Data ◽

Negro River ◽

Hydrological Extremes ◽

Satellite Altimetry Data

ABSTRACT The influence of SST (Sea Surface Temperature) of adjacent oceans on the variability of water levels in the Amazon basin was investigated by using radar altimetry from the ENVISAT and Jason-2 missions. Data from the in situ network was used to compare the correlations of water level and SST anomalies in the sub-basins of the Amazonas-Peru, Solimões, Negro and Madeira Rivers. The analysis was made on the monthly and annual scales between 2003 and 2015. The correlations with anomalies of levels from altimetry presented higher accuracy indices than those from the conventional network. In general, ATN and PAC are better correlated with the entire basin. During the flood months, most of the sub-basins presented negative associations with ATN. In the months of ebb, the response to the indexes varies according to the region. The satellite altimetry data permitted to reach regions non-monitored by the conventional network. We also analyzed the impacts of hydrological extremes in all these sub-regions in the last 13 years. In Western Amazon, the drought of 2010 stands out, associated with the warming of the Tropical Atlantic and the El Niño. In the Negro River, the water level anomalies were the lowest in the basin during the 2005 drought. In the Purus River, the effects of the 2010 drought that affected the entire Amazon, were higher in 2011 due to its strong relationship with the Atlântic and Pacific oceans. In general, hydrological extremes are stronger or highlighted when SST increases simultaneously in both oceans.

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CAWRES: A Waveform Retracking Fuzzy Expert System for Optimizing Coastal Sea Levels from Jason-1 and Jason-2 Satellite Altimetry Data

Remote Sensing ◽

10.3390/rs9060603 ◽

2017 ◽

Vol 9 (6) ◽

pp. 603 ◽

Cited By ~ 7

Author(s):

Nurul Idris ◽

Xiaoli Deng ◽

Ami Md Din ◽

Nurul Idris

Keyword(s):

Expert System ◽

Satellite Altimetry ◽

Fuzzy Expert System ◽

Altimetry Data ◽

Sea Levels ◽

Waveform Retracking ◽

Coastal Sea ◽

Satellite Altimetry Data

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The Evaluation of the Result of Post-Processing Envisat Satellite Altimetry Data Used for Coastal Area Potential Flood Mapping (Case Study: Coastal Area of Buleleng Regency, Bali, Indonesia)

Procedia Environmental Sciences ◽

10.1016/j.proenv.2014.03.078 ◽

2014 ◽

Vol 20 ◽

pp. 651-657

Author(s):

Leni. S. Heliani ◽

I Wayan Krisna Eka Putra ◽

Subaryono

Keyword(s):

Coastal Area ◽

Satellite Altimetry ◽

Flood Mapping ◽

Altimetry Data ◽

Post Processing ◽

Satellite Altimetry Data

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Eddy properties in the Pacific sector of the Southern Ocean from satellite altimetry data

Acta Oceanologica Sinica ◽

10.1007/s13131-016-0946-2 ◽

2016 ◽

Vol 35 (11) ◽

pp. 28-34 ◽

Cited By ~ 1

Author(s):

Yongliang Duan ◽

Hongwei Liu ◽

Weidong Yu ◽

Yijun Hou

Keyword(s):

Southern Ocean ◽

Satellite Altimetry ◽

Altimetry Data ◽

The Pacific ◽

Satellite Altimetry Data

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Kuroshio variations in the upstream region as seen by HF radar and satellite altimetry data

International Journal of Remote Sensing ◽

10.1080/01431160802175454 ◽

2008 ◽

Vol 29 (21) ◽

pp. 6417-6426 ◽

Cited By ~ 33

Author(s):

K. Ichikawa ◽

R. Tokeshi ◽

M. Kashima ◽

K. Sato ◽

T. Matsuoka ◽

...

Keyword(s):

Satellite Altimetry ◽

Hf Radar ◽

Upstream Region ◽

Altimetry Data ◽

Satellite Altimetry Data

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Evaluation of Marine Gravity Anomaly Calculation Accuracy by Multi-Source Satellite Altimetry Data

Frontiers in Earth Science ◽

10.3389/feart.2021.730777 ◽

2021 ◽

Vol 9 ◽

Author(s):

Shanwei Liu ◽

Yinlong Li ◽

Qinting Sun ◽

Jianhua Wan ◽

Yue Jiao ◽

...

Keyword(s):

Root Mean Square Error ◽

Gravity Anomaly ◽

Mean Square Error ◽

Spatial Resolution ◽

Satellite Altimetry ◽

Gravity Anomalies ◽

Mean Square ◽

Altimetry Data ◽

Marine Gravity ◽

Satellite Altimetry Data

The purpose of this paper is to analyze the influence of satellite altimetry data accuracy on the marine gravity anomaly accuracy. The data of 12 altimetry satellites in the research area (5°N–23°N, 105°E–118°E) were selected. These data were classified into three groups: A, B, and C, according to the track density, the accuracy of the altimetry satellites, and the differences of self-crossover. Group A contains CryoSat-2, group B includes Geosat, ERS-1, ERS-2, and Envisat, and group C comprises T/P, Jason-1/2/3, HY-2A, SARAL, and Sentinel-3A. In Experiment I, the 5′×5′ marine gravity anomalies were obtained based on the data of groups A, B, and C, respectively. Compared with the shipborne gravity data, the root mean square error (RMSE) of groups A, B, and C was 4.59 mGal, 4.61 mGal, and 4.51 mGal, respectively. The results show that high-precision satellite altimetry data can improve the calculation accuracy of gravity anomaly, and the single satellite CryoSat-2 enables achieving the same effect of multi-satellite joint processing. In Experiment II, the 2′×2′ marine gravity anomalies were acquired based on the data of groups A, A + B, and A + C, respectively. The root mean square error of the above three groups was, respectively, 4.29 mGal, 4.30 mGal, and 4.21 mGal, and the outcomes show that when the spatial resolution is satisfied, adding redundant low-precision altimetry data will add pressure to the calculation of marine gravity anomalies and will not improve the accuracy. An effective combination of multi-satellite data can improve the accuracy and spatial resolution of the marine gravity anomaly inversion.

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