Measured Water Surface Elevation Research Articles

Stage‐Slope‐Discharge Relationships Upstream of River Confluences Revealed by Satellite Altimetry

AbstractWith increasing coverage, density, and accuracy of the global inland water altimetry record, remote sensing observations of water surface elevation (WSE) and water surface slope (WSS) are becoming available for the world's rivers. In steady, uniform flows, WSS is invariable, while there is a unique one‐to‐one relationship between WSE and discharge, the rating curve. While the assumptions of steady uniform flow are appropriate for many rivers, they are violated upstream of river confluences. We present a simple analytical hydraulic model of river confluences using the theory of steady, gradually varied flow. We apply the model to four river confluences in the Mississippi‐Missouri river system. We determine the spatial extent of the backwater‐affected zones and map WSE‐discharge and WSS‐discharge relationships. We show that coincident measurements of WSE and WSS from new satellite altimetry missions effectively constrain discharge estimates from space in the backwater‐affected zones upstream of river confluences.

Satellite remote sensing of river discharge: a framework for assessing the accuracy of discharge estimates made from satellite remote sensing observations

This research presents an evaluation of the accuracy and uncertainty of estimates of river discharge made using satellite observed data sources as input to a modified form of Manning’s equation. Conventional U.S. Geological Survey (USGS) streamflow gaging station data and in-situ measurements of width, depth, height, slope, discharge, and velocity from 30 USGS gage sites were used as ground-truth to assess accuracy. This study explores accuracy in relation to the amount of ground truth information available, the number of calibration points available, and the accuracy of the input data. This research indicates that remotely sensed discharge estimates associated with the modified Manning equation may be expected to have an uncertainty in range of 10% overall given a sufficient number of calibration points. The uncertainty associated with the modified Manning algorithm increased markedly for depths <3 meters (m) and for discharges <1000 cubic meters per second (m3 / s) for many rivers after calibration. Rivers that exhibit (1) a wide range of flow conditions, (2) a significant number of dams in the watershed and along the channel, and (3) a high baseflow index are more likely to have relatively large errors overall and particularly at the low end of the streamflow range. Uncertainty in remotely sensed measurements of water-surface elevation (WSE) and width in the expected range (WSE, + / − 10 cm; Width, + / − 15 m) introduces uncertainty in the discharge estimates on the order of 10% and is greatest at the low end of discharge as rivers get shallower and narrower. As WSE and width measurement uncertainty increases, discharge uncertainty increases accordingly. In general, the observation errors are greater than the errors associated with the algorithm for a well-calibrated model (e.g., 20 calibration points).

River hydraulic modeling with ICESat-2 land and water surface elevation

Abstract. Advances in geodetic altimetry instruments are providing more accurate measurements, thus enabling satellite missions to produce useful data for narrow rivers and streams. Altimetry missions produce spatially dense land and water surface elevation (WSE) measurements in remote areas where in situ data are scarce that can be combined with hydraulic and/or hydrodynamic models to simulate WSE and estimate discharge. In this study, we combine ICESat-2 (Ice, Cloud and land Elevation Satellite) land and water surface elevation measurements with a low-parameterized hydraulic calibration to simulate WSE and discharge without the need for surveyed cross-sectional geometry and a rainfall–runoff model. ICESat-2 provides an opportunity to map river cross-sectional geometry very accurately, with an along-track resolution of 0.7 m, using the ATL03 product. These measurements are combined with the inland water product ATL13 to calibrate a steady-state hydraulic model to retrieve unobserved hydraulic parameters such as river depth or the roughness coefficient. The low-parameterized model, together with the assumption of steady-state hydraulics, enables the application of a global search algorithm for a spatially uniform parameter calibration at a manageable computational cost. The model performance is similar to that reported for highly parameterized models, with a root mean square error (RMSE) of around 0.41 m. With the calibrated model, we can calculate the WSE time series at any chainage point at any time for an available satellite pass within the river reach and estimate discharge from WSE. The discharge estimates are validated with in situ measurements at two available gauging stations. In addition, we use the calibrated parameters in a full hydrodynamic model simulation, resulting in a RMSE of 0.59 m for the entire observation period.

Implementation of heuristic search algorithms in the calibration of a river hydraulic model

In this contribution, two heuristic search algorithms, (1) particle swarm optimization (PSO) and (2) genetic algorithm (GA) are used to calibrate the iRIC, a two-dimensional hydraulic model for a test case on the Green River in Utah. The goal of the search algorithms was to find the combination of roughness values that minimized model error compared to the measured water surface elevation. An artificial neural network (ANN), which was trained based on the simulated water surface profiles obtained from iRIC, was used to measure the fitness of each solution. Implementation of PSO and GA both improved the accuracy of the calibration by 34 and 30 percent respectively relative to the trial and error. This research demonstrates that the implementation of heuristic search models provides an objective methodology for the calibration of hydraulic models with improved performance when compared to models calibrated via trial and error.

Automated analysis of lateral river connectivity and fish stranding risks. Part 2: Juvenile Chinook salmon stranding at a river rehabilitation site

AbstractThe dynamics of fish stranding have not been academically investigated within the context of physical adjustments to rivers for habitat enhancement purposes. River projects may aim to help fish populations but instead may function as attractive nuisances reducing populations because of unaccounted‐for stranding risk. This study applies a novel algorithm to predict spatially explicit, meter‐resolution fish stranding risk at a river rehabilitation site in California to address three scientific questions. Postproject disconnected wetted area predictions were validated against water surface elevation measurements and time lapse photography of flow reductions and stranding events. A comparison of preproject, final design, and postproject topographies revealed that the occurrence and severity of stranding events is highly sensitive to side‐channel topographic structure and postproject morphodynamic change. Even with moderate flows, side‐channel exits tend to close off by bars built across them via bedload transport. Implications for river management practices and river rehabilitation project design are discussed.

Discharge Estimation From Dense Arrays of Pressure Transducers

AbstractIn situ river discharge estimation is a critical component of studying rivers. A dominant method for establishing discharge monitoring in situ is a temporary gauge, which uses a rating curve to relate stage to discharge. However, this approach is constrained by cost and the time to develop the stage‐discharge rating curve, as rating curves rely on numerous flow measurements at high and low stages. Here, we offer a novel alternative approach to traditional temporary gauges: estimating Discharge via Arrays of Pressure Transducers (DAPT). DAPT uses a Bayesian discharge algorithm developed for the upcoming Surface Water Ocean Topography satellite (SWOT) to estimate in situ discharge from automated water surface elevation measurements. We conducted sensitivity tests over 4,954 model runs on five gauged rivers and conclude that the DAPT method can robustly reproduce discharge with an average Nash‐Sutcliffe Efficiency (NSE) of 0.79 and Kling‐Gupta Efficiency of 0.78. Further, we find that the DAPT method estimates discharge similarly to an idealized temporary gauge created from the same input data (NSE differences of less than 0.1), and that results improve significantly with accurate priors. Finally, we test the DAPT method in nine poorly gauged rivers in a realistic and complex field setting in the Peace‐Athabasca Delta, and show that the DAPT method largely outperforms a temporary gauge in this time and budget constrained setting. We therefore recommend DAPT as an effective tool for in situ discharge estimation in cases where there is not enough time or resources to develop a temporary gauge.

Advancing Field-Based GNSS Surveying for Validation of Remotely Sensed Water Surface Elevation Products

To advance monitoring of surface water resources, new remote sensing technologies including the forthcoming Surface Water and Ocean Topography (SWOT) satellite (expected launch 2022) and its experimental airborne prototype AirSWOT are being developed to repeatedly map water surface elevation (WSE) and slope (WSS) of the world’s rivers, lakes, and reservoirs. However, the vertical accuracies of these novel technologies are largely unverified; thus, standard and repeatable field procedures to validate remotely sensed WSE and WSS are needed. To that end, we designed, engineered, and operationalized a Water Surface Profiler (WaSP) system that efficiently and accurately surveys WSE and WSS in a variety of surface water environments using Global Navigation Satellite Systems (GNSS) time-averaged measurements with Precise Point Positioning corrections. Here, we present WaSP construction, deployment, and a data processing workflow. We demonstrate WaSP data collections from repeat field deployments in the North Saskatchewan River and three prairie pothole lakes near Saskatoon, Saskatchewan, Canada. We find that WaSP reproducibly measures WSE and WSS with vertical accuracies similar to standard field survey methods [WSE root mean squared difference (RMSD) ∼8 cm, WSS RMSD ∼1.3 cm/km] and that repeat WaSP deployments accurately quantify water level changes (RMSD ∼3 cm). Collectively, these results suggest that WaSP is an easily deployed, self-contained system with sufficient accuracy for validating the decimeter-level expected accuracies of SWOT and AirSWOT. We conclude by discussing the utility of WaSP for validating airborne and spaceborne WSE mappings, present 63 WaSP in situ lake WSE measurements collected in support of NASA’s Arctic-Boreal and Vulnerability Experiment, highlight routine deployment in support of the Lake Observation by Citizen Scientists and Satellites project, and explore WaSP utility for validating a novel GNSS interferometric reflectometry LArge Wave Warning System.

How will radar layover impact SWOT measurements of water surface elevation and slope, and estimates of river discharge?

Water surface elevation (WSE), slope and width measurements from the forthcoming Surface Water and Ocean Topography (SWOT) mission will enable spaceborne estimates of global river discharge. WSE will be measured by interferometric synthetic aperture radar (InSAR). InSAR measurements are vulnerable to contamination from layover, a phenomenon wherein radar returns from multiple locations arrive at the sensor simultaneously, rendering them indistinguishable. This study assesses whether layover will significantly impact the precision of SWOT estimates of global river discharge. We present a theoretical river layover uncertainty model at the scale of nodes and reaches, which constitute nominal 200 m and 10 km averages, respectively, along river centerlines. The model is calibrated using high-resolution simulations of SWOT radar interaction with topography covering a total of 41,233 node observations, across a wide range of near-river topographic features. We find that height uncertainty increases to a maximum value at relatively low values of topographic standard deviation and varies strongly with position in the swath. When applied at global scale, the calibrated model shows that layover causes expected height uncertainty to increase by only a modest amount (from 9.4 to 10.4 cm at the 68th percentile). The 68th percentile of the slope uncertainty increases more significantly, from 10 to 17 mm/km. Nonetheless, the 68th percentile discharge uncertainty increases only marginally. We find that the impact of layover on SWOT river discharge is expected to be small in most environments.

Detecting Ship Wakes for the Study of Coastal Processes

Rätsep, M.; Parnell, K.E., and Soomere, T., 2020. Detecting ship wakes for the study of coastal processes. In: Malvárez, G. and Navas, F. (eds.), Global Coastal Issues of 2020. Journal of Coastal Research, Special Issue No. 95, pp. 1258–1262. Coconut Creek (Florida), ISSN 0749-0208.Wakes from contemporary vessels may affect, and in some places dominate, coastal processes in the vicinity of major shipping lanes. The analysis of the properties and impact of wakes has generally been restricted to wakes that can be visually observed in raw data. In this work, spectral analysis of the time series of single-point measurements of water surface elevation from Tallinn Bay is used to highlight the structure of ship wakes using a Short Time Fourier Transform. This method makes it possible to determine the speed and distance of a vessel from the measurement site. Wakes are detected using an algorithm based on Gabor multipliers. The results are compared with vessel passages retrieved from the Automatic Identification System (AIS) data. The algorithm detects the majority of ship wakes that can be visually recognized in spectrograms and misses only those with low signal to noise ratio or those in close proximity to another vessel wake. The calculated speed and distance are consistent with the AIS data except for high-speed vessels sailing at ≥30 knots. The results indicate that by using these techniques the detection of vessel wakes from a single-point wave record is achievable under favorable weather conditions. The methods provide an option for mitigation of the impact of ship wakes in semi-enclosed water bodies.

A Framework for Modeling Flood Depth Using a Hybrid of Hydraulics and Machine Learning

Solving river engineering problems typically requires river flow characterization, including the prediction of flow depth, flow velocity, and flood extent. Hydraulic models use governing equations of the flow in motion (conservation of mass and momentum principles) to predict the flow characteristics. However, solving such equations can be substantially expensive, depending upon their spatial extension. Moreover, modeling two- or three-dimensional river flows with high-resolution topographic data for large-scale regions (national or continental scale) is next to impossible. Such simulations are required for comprehensive river modeling, where a system of connected rivers is to be simulated simultaneously. Machine Learning (ML) approaches have shown promise for different water resources problems, and they have demonstrated an ability to learn from current data to predict new scenarios, which can enhance the understanding of the systems. The aim of this paper is to present an efficient flood simulation framework that can be applied to large-scale simulations. The framework outlines a novel, quick, efficient and versatile model to identify flooded areas and the flood depth, using a hybrid of hydraulic model and ML measures. To accomplish that, a two-dimensional hydraulic model (iRIC), calibrated by measured water surface elevation data, was used to train two ML models to predict river depth over the domain for an arbitrary discharge. The first ML model included a random forest (RF) classification model, which was used to identify wet or dry nodes over the domain. The second was a multilayer perceptron (MLP) model that was developed and trained by the iRIC simulation results, in order to estimate river depth in wet nodes. For the test data the overall accuracy of 98.5 percent was achieved for the RF classification. The regression coefficient for the MLP model for depth was 0.88. The framework outlined in this paper can be used to couple hydraulics and ML models to reduce the computation time, resources and expenses of large-scale, real-time simulations, specifically for two- or three-dimensional hydraulic modeling, where traditional hydraulic models are infeasible or prohibitively expensive.

Characteristics of low-frequency oscillations in the Hambantota Port during the southwest monsoon

The low-frequency (1/400- 1/30 Hz) oscillations within the Hambantota Port, Sri Lanka, are investigated based on the in-situ measured water surface elevations in and outside the harbor. By combining analyses of spectra derived from the in-situ measurement and modal analyses solving the extended mild-slope equation, four natural frequencies of the port are identified and their modal structures are obtained. It is found that the low-frequency oscillations within the port were dominated by its natural frequencies (i.e., the eigen oscillations) instead of the frequencies of external waves. Subsequently, the correlation analysis is carried out to determine the generation of the low-frequency oscillations. Although both the offshore low-frequency and short waves contributed to the low-frequency oscillations, the low-frequency energy spectrum within the port is found to be more significantly correlated with the offshore total low-frequency wave energy than with the offshore total short-wave energy. Moreover, the empirical formula and artificial neural network models are presented to efficiently estimate the low-frequency waves inside the harbor in terms of the offshore wave parameters. Although both methods give excellent results, the artificial neural network performs slightly better.

How will radar layover impact SWOT measurements of water surface elevation and slope, and estimates of river discharge?

How will radar layover impact SWOT measurements of water surface elevation and slope, and estimates of river discharge?

Unmanned Aerial System (UAS) observations of water surface elevation in a small stream: Comparison of radar altimetry, LIDAR and photogrammetry techniques

Water Surface Elevation (WSE) is an important hydrometric observation, useful to calibrate hydrological models, predict floods, and assess climate change. However, the number of in-situ gauging stations is in decline worldwide. Satellite altimetry, including the recently launched satellite missions (e.g. the radar altimetry missions Cryosat 2, Jason 3, Sentinel 3A/B and the LIDAR mission ICESat-2), can determine WSE only in rivers which are more than ca. 100 m wide. WSE measurements in small streams currently remain limited to the few existing in-situ stations or to time-consuming in-situ surveys. Unmanned Aerial Systems (UAS) can acquire real-time WSE observations during periods of hydrological interest (but with flight limitations in extreme weather conditions), within short survey times and with automatic or semi-automatic flight operations. UAS-borne photogrammetry is a well-known technique that can estimate land elevation with an accuracy as high as a few cm, similarly UAS-borne LIDAR can estimate land elevation but without requiring Ground Control Points (GCPs). However, both techniques face limitations in estimating WSE: water transparency and lack of stable visual key points on the Water Surface (WS) complicate the UAS-borne photogrammetric estimates of WSE, while the LIDAR reflection from the water surface is generally not strong enough to be captured by most of the UAS-borne LIDAR systems currently available on the market. Thus, LIDAR and photogrammetry generally require extraction of the elevation of the “water-edge” points, i.e. points at the interface between land and water, for identifying the WSE. We demonstrate highly accurate WSE observations with a new radar altimetry solution, which comprises a 77 GHz radar chip with full waveform analysis and an accurate dual frequency differential Global Navigation Satellite System (GNSS) system. The radar altimetry solution shows the lowest standard deviation (σ) and RMSE on WSE estimates, ca. 1.5 cm and ca. 3 cm respectively, whilst photogrammetry and LIDAR show a σ and an RMSE at decimetre level. Radar altimetry also requires a significantly shorter survey and processing time compared to LIDAR and especially to photogrammetry.

Mapping Water Surface Elevation and Slope in the Mississippi River Delta Using the AirSWOT Ka-Band Interferometric Synthetic Aperture Radar

AirSWOT is an airborne Ka-band synthetic aperture radar, capable of mapping water surface elevation (WSE) and water surface slope (WSS) using single-pass interferometry. AirSWOT was designed as a calibration and validation instrument for the forthcoming Surface Water and Ocean Topography (SWOT) mission, an international spaceborne synthetic aperture radar mission planned for launch in 2022 which will enable global mapping of WSE and WSS. As an airborne instrument, capable of quickly repeating overflights, AirSWOT enables measurement of high frequency and fine scale hydrological processes encountered in coastal regions. In this paper, we use data collected by AirSWOT in the Mississippi River Delta and surrounding wetlands of coastal Louisiana, USA, to investigate the capabilities of Ka-band interferometry for mapping WSE and WSS in coastal marsh environments. We introduce a data-driven method to estimate the time-varying interferometric phase drift resulting from radar hardware response to environmental conditions. A system of linear equations based on AirSWOT measurements is solved for elevation bias and time-varying phase calibration parameters using weighted least squares. We observed AirSWOT WSE uncertainty of 12 cm RMS compared to in situ water level measurements when averaged over an area of 0.5 km 2 at incidence angles below 15 ∘ . At higher incidence angles, the observed AirSWOT elevation bias is possibly due to residual phase calibration errors or radar backscatter from vegetation. Elevation profiles along the Wax Lake Outlet river channel indicate AirSWOT can measure WSS over a 24 km distance with uncertainty below 0.3 cm/km, 8% of the true water surface slope as measured by in situ data. The data analysis and results presented in this paper demonstrate the potential of AirSWOT to measure water surface elevation and slope within highly dynamic and spatially complex coastal environments.

How Does the Unique Space‐Time Sampling of the SWOT Mission Influence River Discharge Series Characteristics?

AbstractThe Surface Water and Ocean Topography (SWOT) satellite mission will, for the first time, provide simultaneous, high‐resolution measurements of water surface elevation and extent. Here we explore the applicability of SWOT's unique sampling to capture discharge frequency behavior throughout the Mississippi River Basin. Our findings suggest the mission may capture key variability in river discharge series. SWOT orbit specifications, US Geological Survey (USGS) discharge measurements, and potential uncertainty estimates are used to generate SWOT‐like river discharges. Frequency distributions and specific quantiles derived from synthetic SWOT discharge series are compared to those derived from daily USGS discharge series. Based on the Kolmogorov‐Smirnov test, SWOT temporal sampling has essentially no impact on derived frequency distributions. When including potential uncertainty, 78% of derived distributions are statistically identical. The combined effects of temporal sampling and discharge uncertainty mitigates the negative bias used for SWOT discharge uncertainty at larger discharge quantiles (i.e., ≥75% quantiles).

Greater Water Surface Variability Revealed by New Congo River Field Data: Implications for Satellite Altimetry Measurements of Large Rivers

AbstractLarge river hydrodynamics studies inform global and regional issues pertaining to biogeochemical cycling, ecology, water availability, and flood risk. Such studies rely increasingly on satellite measurements, but these are limited by resolution, coverage, and uncertainty and their inability to directly measure bathymetry or discharge. We obtain new in situ data covering 650 km of the Congo's main stem, including elusive bathymetry and discharge measurements that complement space‐borne data sets. Our key findings relate to our water surface elevation measurements, which show that spatial coverage of existing satellite altimetry for deriving river water surface profiles may be adequate through the globally important Cuvette Centrale but is not at its outlet where our field data reveal significant spatial variability in water surface slope. The findings have implications for altimetry‐based hydrodynamics studies of other large rivers, such as those that involve estimating discharge or modeling multichannel river hydraulics.

The impact of reach averaging Manning’s equation for an in-situ dataset of water surface elevation, width, and slope

The Surface Water and Ocean Topography Mission (SWOT) will generate global, spatially continuous maps of water surface elevation and extent for large inland water bodies when it launches in 2021. We present an analysis of water surface elevation, width, and bathymetry timeseries data from a medium-sized (average annual discharge 14 m3/s) river to explore Manning’s equation, an empirical open channel flow equation, in the context of SWOT discharge algorithms. While this equation is in theory inapplicable to natural channels due to the non-uniform and spatially heterogeneous nature of river systems, we explored approaches to adapt it to this context using reach-averaged variables. At twenty sites along a 6.5 km stretch of the Olentangy River in Ohio, USA, we collected automated and manual measurements of water surface elevation and river width, undertook a full bathymetric survey of the study area, and built a hydraulic model. The stretch of river was divided into five reaches, and hydraulic variables were reach-averaged. Using these variables, we used a modified form of Manning’s equation to compute a reach-averaged roughness coefficient. Reach-averaged roughness coefficients varied nonlinearly with discharge and were 2–10 times larger at low flow than at high flow in the in-situ data, ranging from 0.06 to 0.61 in one of the study reaches. These results were compared with the output of an unsteady flow simulation using a calibrated 1-D hydraulic model which was run with constant roughness coefficients at each cross section. When reach-averaged data was used, model-derived roughness coefficient also varied by more than an order of magnitude, with a range of 0.02–0.82 for one reach. For both in-situ and model-derived datasets, using a two-parameter roughness coefficient which scaled with a power law on either discharge or stage reduced discharge estimation error, with error for one reach dropping from 81% to 8% relative root-mean square error (rRMSE) in the in-situ data and 58% to 8% nRMSE in the modeled data. These results imply that spatial averaging of hydraulic variables leads to large variations in reach averaged Manning’s n, which we term the reach’s “effective resistance”, and suggest that this variability can be accounted for with a simple parameterization in estimates of discharge that use spatially averaged data.

Investigation of ultrasonic sensor type JSN-SRT04 performance as flood elevation detection

To measure water surface elevation, the measurement technique with ultrasonic technology has been recently being applied to various sectors, such as automotive, robotic and industrial requirement. This research aims to create water surface elevation measurement with JSN-SR04T ultrasonic sensor, which has 0.5 cm measurement resolution. Arduino-Uno microcontroller with a microprocessor-Atmega238 type was used as a measurement data processing system. The system test was conducted in a river where the system was placed under the bridge, and then the elevation water surface levels were captured by the sensor. After that, the results were displayed on the LCD screen. The test was executed in 37 testing scenarios of the condition of the river water surface. Then, the measurement results from the system were compared to the manual measurement. The results showed that the value of measurement error was 0.75%. This finding is in line with the datasheet which indicates that WSN-SR04T sensor can provide a maximum resolution of 0.5 cm.

Airborne LiDAR Measurements and Model Simulations of Tides, Waves, and Surface Slope at the Mouth of the Columbia River

Airborne light detection and ranging (LiDAR) measurements and model simulations are used to investigate the temporal and spatial variability of the water surface elevation at the mouth of the Columbia River. A series of 15-km transects repeated in 2-3-h flights over a two week period resolve processes at a range of scales that are important to the dynamics of the river mouth region, including tides, surface slope, surface gravity waves, and wave setup. Water surface elevations agree well with a nearby tide gauge with an average difference of 0.01 m and an root mean square error of 0.39 m. Significant wave heights derived from the LiDAR measurements agree well with in situ wave drifter measurements and are observed to react to both bathymetry and spatial/temporal variations in currents, increasing up to 228 % on large ebb tides. Surface slopes varied from 2.7 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-5</sup> to -2.6 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-5</sup> over the course of a typical tide to as large as 6.3 × 10-5 to -4.8 × 10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-5</sup> during a larger tide. The magnitude of the setup and set down due to wave height amplification during ebb tide was estimated to be 4×10 <sup xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">-6</sup> . These observations demonstrate that many of the key dynamical variables at river mouths can be determined from airborne remote sensing measurements of water surface elevation and suggest that forthcoming altimetry products, such as those from the Surface Water Ocean Topography altimeter, may be able to provide new insight on monitoring in these complex regions.

Unmanned aerial vehicle observations of water surface elevation and bathymetry in the cenotes and lagoons of the Yucatan Peninsula, Mexico

Observations of water surface elevation (WSE) and bathymetry of the lagoons and cenotes of the Yucatan Peninsula (YP) in southeast Mexico are of hydrogeological interest. Observations of WSE (orthometric water height above mean sea level, amsl) are required to inform hydrological models, to estimate hydraulic gradients and groundwater flow directions. Measurements of bathymetry and water depth (elevation of the water surface above the bed of the water body) improve current knowledge on how lagoons and cenotes connect through the complicated submerged cave systems and the diffuse flow in the rock matrix. A novel approach is described that uses unmanned aerial vehicles (UAVs) to monitor WSE and bathymetry of the inland water bodies on the YP. UAV-borne WSE observations were retrieved using a radar and a global navigation satellite system on-board a multi-copter platform. Water depth was measured using a tethered floating sonar controlled by the UAV. This sonar provides depth measurements also in deep and turbid water. Bathymetry (wet-bed elevation amsl) can be computed by subtracting water depth from WSE. Accuracy of the WSE measurements is better than 5–7 cm and accuracy of the water depth measurements is estimated to be ~3.8% of the actual water depth. The technology provided accurate measurements of WSE and bathymetry in both wetlands (lagoons) and cenotes. UAV-borne technology is shown to be a more flexible and lower cost alternative to manned aircrafts. UAVs allow monitoring of remote areas located in the jungle of the YP, which are difficult to access by human operators.