Water Level Time Series Research Articles

Simulating wave setup and runup during storm conditions on a complex barred beach

The purpose of this study is to assess the ability of the SWASH model to reproduce wave setup and runup in highly dissipative stormy conditions. To proceed we use data collected during the ECORS Truc Vert’08 Experiment, especially during the Johanna storm in the winter of 2007-008 (wave setup under Hs= 8.2m and Tp= 18.3s and runup under 6.4m and peak period up to 16.4s). We test different model settings (1D and 2D mode) and model forcing (spectral and parametric) to reproduce sensor measured wave setup at several locations in the nearshore area and video measured runup on two beach profiles. For the whole tested configurations, the wave setup is reproduced accurately. Results considering all the sensor locations in the near shore area in 1D and 2D are significantly correlated to the observations with respectively ρ²=0.66 and 0.81; RMSE=0.13m and 0.08m without any significant bias. Observations and simulations of runup are investigated in terms of spectra and statistic component. 1D simulations produces an overall overestimation and no significant improvement is obtained by modifying the breaking parameters. The results for 2D simulations are fairly satisfactory reproducing significant swash height (S), but are significantly improved with spectral forcing than parametric with respectively ρ²=0.73 and 0.71, RMSE=0.19m and 0.43m. Generally, the model reproduces accurately the infragravity component but tends to overestimate the incident component, leading to an overestimation of the energy density for moderate wave conditions and more accurate results for higher-energy wave conditions. Results in 2D with spectral forcing show a saturation of the infragravity component with a threshold around Hs=4 to 5m, which is comparable to the observations collected at Truc Vert Beach. As regards the conventional statistical parameter for runup estimation (R2%) three methods are applied to derive the 2% exceedence value for runup from observed and simulated shoreline vertical elevation time series. When R2% is based on the sum of wave setup and half of the significant swash height, results provided by the model are close or even better than estimations provided by empirical formulas from the bibliography. Defining R2% as the exceeded 2% values of the time, derived considering the cumulative distribution function of the entire water-level time series also provide fairly good results. Results using only runup maxima time series are less satisfactory. In the two last cases, R2% is slightly underestimated for moderate wave conditions (Hs<4m; Tp ≈ 14s) and overestimated for higher-energy wave conditions. Generally results shows that where extreme wave conditions are concerned, the model setting must be considered carefully because the simplification of 1D (rather than 2D), or the use of parametric wave description (rather than spectral), can be a source of significant inaccuracy or overestimation in simulated run-up values.

Investigation of the safety threshold of eco-environmental water demands for the Bosten Lake wetlands, western China

Bosten Lake is the largest inland freshwater lake. It has very important ecological significance to protect Bosten Lake wetlands. In this study, the ecological water level method was applied to the Bosten Lake wetlands. A frequency analysis on water level time series data was performed to investigate the relationship between the water level variation and the changes in ecological environment. The minimum, medium and ideal ecological water level coefficients were estimated to further determine the corresponding minimum, medium and ideal ecological environment water demands. The results show that the monthly minimum, medium and ideal ecological water levels were 1045.7 m, 1047 m and 1048 m, and their coefficients were 0.9992, 1.000046 and 1.0014, respectively. The water demand threshold that sustains the eco-environmental safety in the Bosten Lake wetlands is 6.175–8.633 billion m3 per month. This study could work for the department of water resources management as a scientific basis for the rational allocation of water resources and the study of wetland ecological water rights, and thus contribute to the wetland protection.

Relations between vegetation and water level in groundwater dependent terrestrial ecosystems (GWDTEs)

Alkaline wetlands and fens are groundwater dependent, terrestrial ecosystems (GWDTEs) existing throughout the temperate zone. They contain a large number of protected and endangered plant species and their ecological status is threatened by insufficient groundwater quality and quantity. However, management and conservation of fens are constrained by limited knowledge on the relations between vegetation and measurable hydrological conditions. This study investigates the relations between vegetation and water level dynamics in groundwater dependent wetlands in Denmark.A total of 35 wetland sites across Denmark were included in the study. The sites represent a continuum of wetlands with respect to vegetation and hydrological conditions. Water level was measured continuously using pressure transducers at each site. Metrics expressing different hydrological characteristics, such as mean water level and low and high water level periods, were calculated based on the water level time series. A complete plant species list was recorded in plots covering 78.5m2 at each site. Community metrics such as total number of species and the number of bryophytes were generated from the species lists and Ellenberg Indicator scores of moisture, pH and nutrients were calculated for each site.The water level correlates with the number of typical fen species of vascular plants, whereas bryophytes are closer connected to the stable water level conditions provided by groundwater seepage. The water level variability is proved to be a significant limiting factor for species diversity in wetlands, which should be considered along with the fertility in order to access the habitat quality. The study provides new insight in the water level preferences for GWDTEs which is highly needed in the management and assessment of anthropogenic damage to these ecosystems.

Application of CryoSat-2 altimetry data for river analysis and modelling

Abstract. Availability of in situ river monitoring data, especially of data shared across boundaries, is decreasing, despite growing challenges for water resource management across the entire globe. This is especially valid for the case study of this work, the Brahmaputra Basin in South Asia. Commonly, satellite altimeters are used in various ways to provide information about such river basins. Most missions provide virtual station time series of water levels at locations where their repeat orbits cross rivers. CryoSat-2 is equipped with a new type of altimeter, providing estimates of the actual ground location seen in the reflected signal. It also uses a drifting orbit, challenging conventional ways of processing altimetry data to river water levels and their incorporation in hydrologic–hydrodynamic models. However, CryoSat-2 altimetry data provides an unprecedentedly high spatial resolution. This paper suggests a procedure to (i) filter CryoSat-2 observations over rivers to extract water-level profiles along the river, and (ii) use this information in combination with a hydrologic–hydrodynamic model to fit the simulated water levels with an accuracy that cannot be reached using information from globally available digital elevation models (DEMs) such as from the Shuttle Radar Topography Mission (SRTM) only. The filtering was done based on dynamic river masks extracted from Landsat imagery, providing spatial and temporal resolutions high enough to map the braided river channels and their dynamic morphology. This allowed extraction of river water levels over previously unmonitored narrow stretches of the river. In the Assam Valley section of the Brahmaputra River, CryoSat-2 data and Envisat virtual station data were combined to calibrate cross sections in a 1-D hydrodynamic model of the river. The hydrologic–hydrodynamic model setup and calibration are almost exclusively based on openly available remote sensing data and other global data sources, ensuring transferability of the developed methods. They provide an opportunity to achieve forecasts of both discharge and water levels in a poorly gauged river system.

River discharge estimation at daily resolution from satellite altimetry over an entire river basin

One of the main challenges of hydrological modeling is the poor spatiotemporal coverage of in situ discharge databases which have steadily been declining over the past few decades. It has been demonstrated that water heights over rivers from satellite altimetry can sensibly be used to deal with the growing lack of in situ discharge data. However, the altimetric discharge is often estimated from a single virtual station suffering from coarse temporal resolution, sometimes with data outages, poor modeling and inconsistent sampling. In this study, we propose a method to estimate daily river discharge using altimetric time series of an entire river basin including its tributaries. Here, we implement a linear dynamic model to (1) provide a scheme for data assimilation of multiple altimetric discharge along a river; (2) estimate daily discharge; (3) deal with data outages, and (4) smooth the estimated discharge. The model consists of a stochastic process model that benefits from the cyclostationary behavior of discharge. Our process model comprises the covariance and cross-covariance information of river discharge at different gauges. Combined with altimetric discharge time series, we solve the linear dynamic system using the Kalman filter and smoother providing unbiased discharge with minimum variance. We evaluate our method over the Niger basin, where we generate altimetric discharge using water level time series derived from missions ENVISAT, SARAL/AltiKa, and Jason-2. Validation against in situ discharge shows that our method provides daily river discharge with an average correlation of 0.95, relative RMS error of 12%, relative bias of 10% and NSE coefficient of 0.7. Using a modified NSE-metric, that assesses the non-cyclostationary behavior, we show that our estimated discharge outperforms available legacy mean daily discharge.

Acceleration in European Mean Sea Level? A New Insight Using Improved Tools

Watson, P.J., 2017. Acceleration in European mean sea-level? A new insight using improved tools.Research into sea-level rise has taken on particular prominence in more recent times owing to the global threat posed by climate change and the fact that mean sea level and temperature remain the key proxies by which we can measure changes to the climate system. Under various climate change scenarios, it has been estimated that the threat posed by the effects of sea-level rise might lead to annual damage costs across Europe on the order of €25 billion by the 2080s. European mean sea-level records are among the best time series data available globally by which to detect the presence of necessary accelerations forecast by physics-based projection models to elevate current rates of global sea-level rise (≈3 mm/y) to anywhere in the vicinity of 10–20 mm/y by 2100. The analysis in this paper is based on a recently developed analytical package titled “msltrend,” specifically designed to enhance estimates of trend, real-time velocity, and acceleration in the relative mean sea-level signal derived from long annual average ocean water level time series. Key findings are that at the 95% confidence level, no consistent or compelling evidence (yet) exists that recent rates of rise are higher or abnormal in the context of the historical records available across Europe, nor is there any evidence that geocentric rates of rise are above the global average. It is likely a further 20 years of data will distinguish whether recent increases are evidence of the onset of climate change–induced acceleration.

Combination of multi-mission altimetry data along the Mekong River with spatio-temporal kriging

River water-level time series at fixed geographical locations, so-called virtual stations, have been computed from single altimeter crossings for many years. Their temporal resolution is limited by the repeat cycle of the individual altimetry missions. The combination of all altimetry measurements along a river enables computing a water-level time series with improved temporal and spatial resolutions. This study uses the geostatistical method of spatio-temporal ordinary kriging to link multi-mission altimetry data along the Mekong River. The required covariance models reflecting the water flow are estimated based on empirical covariance values between altimetry observations at various locations. In this study, two covariance models are developed and tested in the case of the Mekong River: a stationary and a non-stationary covariance model. The proposed approach predicts water-level time series at different locations along the Mekong River with a temporal resolution of 5 days. Validation is performed against in situ data from four gauging stations, yielding RMS differences between 0.82 and 1.29 m and squared correlation coefficients between 0.89 and 0.94. Both models produce comparable results when used for combining data from Envisat, Jason-1, and SARAL for the time period between 2002 and 2015. The quality of the predicted time series turns out to be robust against a possibly decreasing availability of altimetry mission data. This demonstrates that our method is able to close the data gap between the end of the Envisat and the launch of the SARAL mission with interpolated time series.

Investigating changes in lake systems in the south-central Tibetan Plateau with multi-source remote sensing

Lakes in the Tibetan Plateau are considered sensitive responders to global warming. Variations in physical features of lake systems such as surface area and water level are very helpful in understanding regional responses to global warming in recent decades. In this study, multi-source remote sensing data were used to retrieve the surface area and water level time series of five inland lakes in the south-central part of the Tibetan Plateau over the past decades. Changes in water level and surface area of the lakes were investigated. The results showed that the water level of three lakes (Puma Yumco, Taro Co, Zhari Namco) increased, with expanding surface area, while the water levels of the other two lakes (Paiku Co, Mapam Yumco) fell, with shrinking area. The water levels of the lakes experienced remarkable changes in 2000–2012 as compared with 1976–1999. Spatially, lakes located at the southern fringe of the Tibetan Plateau showed consistency in water level changes, which was different from lakes in the central Tibetan Plateau.

Dynamic River Masks from Multi-Temporal Satellite Imagery: An Automatic Algorithm Using Graph Cuts Optimization

Our knowledge of the spatio-temporal variation of river hydrological parameters is surprisingly poor. In situ gauge stations are limited in spatial and temporal coverage, and their number has been decreasing during the past decades. On the other hand, remote sensing techniques have proven their ability to measure different parameters within the Earth system. Satellite imagery, for instance, can provide variations in river area with appropriate temporal sampling. In this study, we develop an automatic algorithm for water body area monitoring based on maximum a posteriori estimation of Markov random fields. The algorithm considers pixel intensity, spatial correlation between neighboring pixels, and temporal behavior of the water body to extract accurate water masks. We solve this optimization problem using the graph cuts technique. We also measure the uncertainty associated with the determined water masks. Our method is applied over three different river reaches of Niger and Congo rivers with different hydrological characteristics. We validate the obtained river area time series by comparing with in situ river discharge and satellite altimetric water level time series. Along the Niger River, we obtain correlation coefficients of 0.85–0.96 for river reaches and 0.65 for the Congo River, which is demonstrably an improvement over other river mask retrieval algorithms.

Subtidal variability of sea level in a macrotidal and convergent estuary

Time series (2011 through 2013) of water level elevations measured at nine locations along the Gironde Estuary, on the southwest coast of France, were analyzed to investigate both propagation and forcing mechanisms of tidal and subtidal pulses. A Lanczos low pass filter (35h) was applied to the three-year time series of water level from each tide gage station and the seasonal signal was removed. Both Regular (REOF) and Complex Empirical Orthogonal Function (CEOF) analyses were applied to the detrended water level to provide information on the spatial and temporal structure of the subtidal pulses. The explained variance of the first two dominant modes from both the REOF and CEOF analyses together explained 98% of the variance, with the first mode explaining ∼90% and the second, ∼8%. The spatial structure of the first two modes both showed amplitude amplification (0.2cm/km for the first mode and 1cm/km for the second) over the entire length of the estuary. A local phase minimum, derived from the CEOF analysis, was found at the mouth of the estuary for mode 1 and at the head of the estuary for mode 2. This indicated that the first mode was forced by coastal processes and the second mode by upstream (riverine) mechanisms. A numerical model of the Gironde estuary was used to help understand the forcing mechanism behind REOF and CEOF mode 1. The results of a numerical model simulation forced only with tides was compared to the spatial structure of the dominant REOF and CEOF mode, and verified that mode 1 was a product of tidal processes. The second mode resulted from variations in river flow linked to synoptic weather patterns.

Lake Level Estimation Based on CryoSat-2 SAR Altimetry and Multi-Looked Waveform Classification

In this study, reliable water levels for four lakes are estimated based on an innovative processing strategy using a semi-automatic CryoSat-2 Synthetic Aperture Radar (SAR) multi-looked waveform classification. The selection of valid water returns is an essential step in inland altimetry applications. In order to identify reliable observations allowing for an accurate retracking, an unsupervised classification method for CryoSat-2 SAR multi-looked waveforms has been developed based on the k-mean algorithm. With this approach, changes in the water surface extent or surrounding inundation areas can be taken into account. In addition, a modified version of the Improved Threshold Retracker is developed in order to obtain optimal results for the lake heights. The used method is based on the identification of the optimal sub-waveform by employing height thresholds. The validation of the derived CryoSat-2 SAR time series with in-situ gauging data yields root mean square (RMS) differences between 3 and 90 cm for the different lakes. Compared to modeled CryoSat-2 water heights derived according to the approach used in the AltWater database our water level time series are slightly improved in terms of RMS accuracy but they contain more gaps due to the lack of reliable observations. In comparison with classical radar altimeter missions such as Envisat or Jason-2, the SAR-based time series show smaller RMS differences for the small lakes but larger RMS differences for the large lakes covered by multiple repeat missions. The presented innovative processing strategy can be easily adopted to other satellite altimetry SAR data such as from the new Sentinel-3 mission.

Likely effects of climate change on groundwater availability in a Mediterranean region of Southeastern Spain

AbstractGroundwater resources are typically the main fresh water source in arid and semi‐arid regions. Natural recharge of aquifers is mainly based on precipitation; however, only heavy precipitation events (HPEs) are expected to produce appreciable aquifer recharge in these environments. In this work, we used daily precipitation and monthly water level time series from different locations over a Mediterranean region of Southeastern Spain to identify the critical threshold value to define HPEs that lead to appreciable aquifer recharge in this region. Wavelet and trend analyses were used to study the changes in the temporal distribution of the chosen HPEs (≥20 mm day−1) over the observed period 1953–2012 and its projected evolution by using 18 downscaled climate projections over the projected period 2040–2099. The used precipitation time series were grouped in 10 clusters according to similarities between them assessed by using Pearson correlations. Results showed that the critical HPE threshold for the study area is 20 mm day−1. Wavelet analysis showed that observed significant seasonal and annual peaks in global wavelet spectrum in the first sub‐period (1953–1982) are no longer significant in the second sub‐period (1983–2012) in the major part of the ten clusters. This change is because of the reduction of the mean HPEs number, which showed a negative trend over the observed period in nine clusters and was significant in five of them. However, the mean size of HPEs showed a positive trend in six clusters. A similar tendency of change is expected over the projected period. The expected reduction of the mean HPEs number is two times higher under the high climate scenario (RCP8.5) than under the moderate scenario (RCP4.5). The mean size of these events is expected to increase under the two scenarios. The groundwater availability will be affected by the reduction of HPE number which will increase the length of no aquifer recharge periods (NARP) accentuating the groundwater drought in the region. Copyright © 2016 John Wiley &amp; Sons, Ltd.

Modification of closure depths by synchronisation of severe seas and high water levels

The closure depth indicates the depth down to which storm waves maintain a universal shape of the coastal profile. It is thus a key parameter of the coastal zones for a variety of engineering and ecosystem applications. Its values are commonly estimated with respect to the long-term mean water level. The present study re-evaluates closure depths for microtidal water bodies where the wave loads are highly correlated with the course of the water level. The test area is the eastern Baltic Sea. The closure depth is calculated for the eastern Baltic Sea coast with a resolution of 5.5 km and the vicinity of Tallinn Bay with a resolution of 0.5 km. While the classic values of closure depth are extracted from statistics of the roughest seas, the present analysis is based on single values of a proxy of the instantaneous closure depth. These values are evaluated from numerically simulated time series of wave properties and water levels. The water level-adjusted closure depths are almost equal to the classic values at the coasts of Lithuania but are up to 10% smaller at the Baltic Proper coasts of Latvia and Estonia. The difference is up to 20% in bayheads of the Gulf of Finland.

Tide- and wind-driven variability of water level in Sansha Bay, Fujian, China

This study analyzes water-level variability in Sansha Bay and its adjacent waters near Fujian, China, using water-level data observed from seven stations along the coast and wind data observed from a moored buoy near Mazu Island. At super- to near-inertial frequencies, tides dominated the water-level variations, mainly characterized by semi-diurnal (primarily M2, S2, and N2) and diurnal tides (primarily K1, O1). The correlation coefficients between residual (non-tidal) water-level time series and the observed wind-stress time series exceeded 0.78 at all stations, hinting that the wind acting on the study region was another factor modulating the water-level variability. A cross-wavelet and wavelet-coherence analysis further indicated that (i) the residual water level at each station was more coherent and out-of-phase with the alongshore winds mostly at sub-inertial time scales associated with synoptic weather changes; and (ii) the residual water-level difference between the outer and inner bay was more coherent with the cross-shore winds at discrete narrow frequency bands, with the wind leading by a certain phase. The analysis also implied that the monsoon relaxation period was more favorable for the formation of the land-sea breeze, modulating the residual water-level difference.

Long-Term and Annual Influence of Aswan Reservoir (Egypt) on the Local Seismicity: A Spatio-Temporal Statistical Analysis

Earthquakes continue to occur in the Kalabsha embayment region near the Aswan reservoir for more than three decades. These earthquakes, including the 1981 mainshock (M 5.3), have been considered to be reservoir triggered and pore pressure appears to be the main factor for their occurrence. However, influence of reservoir water levels on the earthquakes of the region, which is significant in the initial period, is reported to be weakening with time. We statistically analyse the influence of the reservoir water levels on spatio-temporal distribution of the earthquakes for the period 1982–2013. We divided the seismicity of various zones in different time windows, depending upon their clustering, and employed the power spectrum and singular spectrum analysis (SSA). The influence of long-term and annual variations in the water level on the seismicity is very much apparent in SSA. In the 45 years of reservoir filling history, episodes of water levels more than 170 m, which lead to filling of the embayment region, appear to be correlated with the increase in seismicity of the Aswan region. In the power spectrum analysis, a strong annual peak is found for water level time series. However, in the earthquake time series, on an average, a moderate and weak annual period cycle is present in the initial (1982–1988) and in the later (2001–2013) period, respectively. In the intermediate period (1989–2000) when the water level was the least in the embayment area, a very weak annual cycle is present. Non-consideration of spatio-temporal variation in the seismicity leads to erroneous and misleading results of no or weaker reservoir influence in the later period. This also highlights that the time and space dependent pore pressure diffusion process is likely responsible for earthquake triggering in the Aswan region.

Comparative analysis of Lake Urmia and Lake Van water level time series

Recent decline in Lake Urmia water level makes it crucial to consider this issue more seriously. For this purpose, comparison of water level in Lake Urmia with Lake Van in Turkey, which is in relatively similar geographic and climate conditions, can be an effective approach. To follow this objective, trend analysis, regime shift, and coherency analyses are implemented. The results showed negative trend in Lake Urmia water level for the past 20 years, while in Lake Van, the trend is positive. Moreover, correlation of the lake level variations versus the basin rainfall during three common periods, identified by the regime shifts analysis, illustrated a decreasing trend in the correlation. These changes can be attributed to non-climatic factors such as different allocation disciplines in two lake’s catchments. Finally, the coherency analysis showed significant annual and inter-annual frequencies common between the two lake levels. Herein, the short-term period relations are associated with lags, while in long term, they act simultaneously.

An ERS-2 altimetry reprocessing compatible with ENVISAT for long-term land and ice sheets studies

Abstract Satellite altimetry has demonstrated a strong potential for the continuous monitoring of ocean, ice sheets and land surfaces over the last 25 years. While instrument processing and retracking techniques of the radar echoes improved over the years for ocean applications to produce homogeneous products for all satellite altimetry missions, less effort has been devoted to applications over land. European Space Agency (ESA) continues improving the quality of ENVISAT data over all type of surfaces through frequent reprocessing of altimeter corrections. No similar effort was performed for the ERS missions until recently with the release of the ESA ERS REAPER product mostly devoted to ocean applications. In parallel, Centre de Topographie des Oceans et de l'Hydrosphere (CTOH) processed the ERS-2 waveforms (WAP data) with a new implementation of the Ice-2 retracker algorithm, adding improvements and corrections to make ERS-2 data compatible and homogenous with the ENVISAT mission for continuity and long-term altimetry data analysis over land and ice sheets. The resulting product is evaluated against ENVISAT data during the tandem phase when they flew 30 min apart on the same orbit during 10 cycles of the two missions from June 2002 to July 2003. Maps of along-track differences averaged over the 10 cycles of the tandem phase and associated RMSE are presented over ocean, both Antarctica and Greenland ice sheets and land along with time series of altimetry backscattering coefficients and altimetry-based water levels. Similar comparisons were performed between ENVISAT and ERS-2 REAPER data. Low bias and RMSE values for altimeter heights and backscattering were found between ENVISAT and ERS-2 over ocean and flat areas over land and ice sheets with generally better results obtained using CTOH data. Comparisons with in situ water stages also show good agreement for Ice-2 and especially Ice-1 retrackers derived water levels (R > 0.95).

Potential of ENVISAT Radar Altimetry for Water Level Monitoring in the Pantanal Wetland

Wetlands are important ecosystems playing an essential role for continental water regulation and the hydrologic cycle. Moreover, they are sensitive to climate changes as well as anthropogenic influences, such as land-use or dams. However, the monitoring of these regions is challenging as they are normally located in remote areas without in situ measurement stations. Radar altimetry provides important measurements for monitoring and analyzing water level variations in wetlands and flooded areas. Using the example of the Pantanal region in South America, this study demonstrates the capability and limitations of ENVISAT radar altimeter for monitoring water levels in inundation areas. By applying an innovative processing method consisting of a rigorous data screening by means of radar echo classification as well as an optimized waveform retracking, water level time series with respect to a global reference and with a temporal resolution of about one month are derived. A comparison between altimetry-derived height variations and six in situ time series reveals accuracies of 30 to 50 cm RMS. The derived water level time series document seasonal height variations of up to 1.5 m amplitude with maximum water levels between January and June. Large scale geographical pattern of water heights are visible within the wetland. However, some regions of the Pantanal show water level variations less than a few decimeter, which is below the accuracies of the method. These areas cannot be reliably monitored by ENVISAT.

Shoreline Change Analysis and Insight into the Sediment Transport Path along Santa Catarina Island North Shore, Brazil

ABSTRACT Vieira da Silva, G.; Muler, M.; Prado, M.F.V.; Short, A.D.; Klein, A.H.F., and Toldo, E.E., Jr., 2016. Shoreline change analysis and insight into the sediment transport path along Santa Catarina Island north shore, Brazil. This paper presents a shoreline change analysis applied to identify the sediment transport path involving nine adjoining beaches, including dunes and spits, located along the microtidal eastern and northern shores of Santa Catarina Island (Brazil) and extending 50 km from Barra-Mocambique to Daniela. A data set was comprised of aerial images from 1957, 1978, 1998, 2002, 2007, and 2010, and the 2012 shoreline position measured with real-time kinematic GPS, topobathymetric data set, and a 60-year water-level time series. The images were rectified and the shoreline position for each year was extracted. The average errors (ranging from 1 to 9.8 m) of the rectification process as well as the horizontal tide-related errors (varying from 8.3 ± 2.6 m to 14.9 ± 0.6 m) were calculated wi...

AN ORIGINAL PROCESSING METHOD OF SATELLITE ALTIMETRY FOR ESTIMATING WATER LEVELS AND VOLUME FLUCTUATIONS IN A SERIES OF SMALL LAKES OF THE PANTANAL WETLAND COMPLEX IN BRAZIL

Abstract. Satellite altimetry is becoming a major tool for measuring water levels in rivers and lakes offering accuracies compatible with many hydrological applications, especially in uninhabited regions of difficult access. The Pantanal is considered the largest tropical wetland in the world and the sparsity of in situ gauging station make remote methods of water level measurements an attractive alternative. This article describes how satellites altimetry data from Envisat and Saral was used to determine water level in two small lakes in the Pantanal. By combining the water level with the water surface area extracted from satellite imagery, water volume fluctuations were also estimated for a few periods. The available algorithms (retrackers) that compute a range solution from the raw waveforms do not always produce reliable measurements in small lakes. This is because the return signal gets often “contaminated” by the surrounding land. To try to solve this, we created a “lake” retracker that rejects waveforms that cannot be attributed to “calm water” and convert them to altitude. Elevation data are stored in a database along with the water surface area to compute the volume fluctuations. Satellite water level time series were also produced and compared with the only nearby in situ gauging station. Although the “lake” retracker worked well with calm water, the presence of waves and other factors was such that the standard “ice1” retracker performed better on the overall. We estimate our water level accuracy to be around 75 cm. Although the return time of both satellites is only 35 days, the next few years promise to bring new altimetry satellite missions that will significantly increase this frequency.