Water Surface Width Research Articles

Quantifying the Effect of Xiluodu Reservoir on the Temperature of the Surrounding Mountains.

To quantitatively determine the effect of Xiluodu Reservoir on the temperature of the surrounding mountains, the temperature differences between various locations and the reservoir were calculated based on Landsat 8 thermal infrared sensor (TIRS) data. Elevation, slope, aspect, normalized difference vegetation index (NDVI), and visual field were selected as the impact factors, and the most significant grid size used to explore the effect of reservoir on the surrounding mountains was determined by spatial analysis and partial correlation analysis. The effect of the Xiluodu Reservoir on the surrounding mountains' temperature was then quantitatively studied while accounting for the effect of water surface width on temperature. The results are summarized as follows. The most significant grid size for determining the influence of Xiluodu Reservoir on the surrounding mountains' temperature is 90 m. The effect range threshold of the entire reservoir on the temperature of the surrounding mountains is approximately 600 m, and the partial correlation coefficient in each buffer area decreases gradually with increasing distance from the reservoir. The effect threshold of the reservoir on the temperature of the surrounding mountains is approximately 1,500 m in the head area with a water surface width approximately 1,000 m, but it is negligible in the tributary area where the width is approximately 60 m.

Constraining the Assimilation of SWOT Observations With Hydraulic Geometry Relations

AbstractThe Surface Water Ocean Topography (SWOT) satellite mission expected to launch in 2021 will offer a unique opportunity to map river discharge at an unprecedented spatial resolution globally from observations of water surface elevation, width, and slope. Because river discharge will not be directly observed from SWOT, a number of algorithms of varying complexity have been developed to estimate discharge from SWOT observables. Outstanding issues include the lack of accurate prior information and parameter equifinality. We developed a new data assimilation discharge algorithm that aimed to overcome these limitations by integrating a data‐driven approach to estimate priors with a model informed by hydraulic geometry relations. A comprehensive simulated dataset of 18 rivers was used to evaluate the algorithm and four different configurations (rectangular channel, generic channel, and geomorphologically classified channel with and without regularization) to assess the impact of progressively adding hydraulic geometry constraints to the estimation problem. The algorithm with the full set of constraints outperformed the other configurations with median Nash‐Sutcliffe coefficients of 0.77, compared with −0.46, 0.31 and 0.66, while other error metrics showed similar improvement. Results from this study show the promise of this hybrid data‐driven approach to estimating river discharge from SWOT observations, although a number of enhancements need to be tested to improve the operational applicability of the algorithm.

Classification of instream ecological water demand and crucial values in a semi-arid river basin

Analyzing the instream environmental flow demand by coupling the hydrological cycle and the hydrodynamic process with aquatic ecological processes at watershed scale remains one of the most important yet most difficult issues. One or two of the above processes have been the focus in the evaluation of intra-annual ecological water demand in recent studies. In this study, a hydrology–hydrodynamic–habitat model was developed and applied to the Huangshui River basin. A new classification method for instream ecological water demand (IEWD), which considered sensitive species was proposed. The suitable level of IEWD and crucial values with different flow frequencies were analysed, including runoff, water level, water surface width and weighted usable areas (WUA). The results of the study indicated that monthly IEWD had an increasing trend during the flood season and a decreasing trend during the non-flood season in three sections at different suitable levels. With the increase of suitable levels, the range of IEWD in three sections also increased. The IEWD and crucial values were the lowest in March with the smallest range and were the highest from July to October because the amount of precipitation during that period accounted for nearly 84.3% of that of the entire year. Furthermore, the lower the flow frequency in three sections, the higher the suitable levels of IEWD, as well as water level and water surface width every month. When the flow frequency of 90% decreased to 75%, the value of IEWD increased by at least 55% during the wet season and doubled during the dry season. The WUA with the lowest or highest flow frequencies were relatively poor, especially reproduction period. The IEWD and crucial values at different suitable levels agreed with the actual situations. Thus, this study provided a new method for implementing river ecosystem restoration and aquatic ecosystem management.

A Constant Potential Molecular Dynamics Simulation Study of the Atomic‐Scale Structure of Water Surfaces Near Electrodes

Summary of main observation and conclusionNovel and technologically important processes and phenomena arise at water surfaces in the presence of electric fields. However, experimental measurements on water surfaces are challenging, and the results are scarce and inconclusive. In this work, the constant potential molecular dynamics method, in which the electrode charges are allowed to fluctuate to keep the electric potential fixed, was implemented in the study of a near‐electrode water surface systems. This simulation system was set up with a vapor/liquid‐water/vapor slab and two electrodes under different sets of applied electrostatic potential, yielding i) a detailed characterization of the external E‐field dependent electrostatic potential/density/dipole moment density profiles, and ii) the relationship between the water surface width and the applied electrode voltage differences which has been rarely reported. The adjustments in the number density profiles in the vicinity of water surfaces due to external E‐fields were observed, while the capillary interfacial widths for the surfaces near both cathode and anode were found with different increment rates under increasing E‐fields. By examining dipole density profiles across the water surfaces, we found that external E‐field induced polarization occurs in both bulk and surface regimes, yet the surface polarization densities vary asymmetrically with respect to the increasing E‐fields. Detailed discussions were carried out to explain the correlation between water surface tension and surface widths, as well as the interplay between the surface polarization densities and the hydrogen bond network structure. We conclude that the mechanical and structural properties of the water surfaces could be tuned by both magnitude and direction of the strong external E‐fields. We also recognize that more surface properties with application value, such as dielectric permittivity tensor or surface potential, could also be regulated by the external E‐fields.

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.

A Curve‐Fitting Method for Estimating Bathymetry From Water Surface Height and Width

AbstractRiver discharge estimation requires knowledge of bathymetry. However, aside from a few locations where surveys have been conducted, bathymetric data are unavailable, even for major rivers. It has been suggested that water surface elevation and flow width measurements from the upcoming Surface Water and Ocean Topography (SWOT) satellite mission (planned launch 2021) may be used to infer the submerged channel geometry; however, the full potential of these measurements for inferring bathymetry has yet to be explored. We apply four different techniques, with varying assumptions about height‐width relationships, to predict unknown bathymetry. We call these “curve‐fitting methods” the linear, slope break, nonlinear, and nonlinear slope break (NLSB) methods. The linear and slope break methods are based on a linear height‐width relationship, while the nonlinear and NLSB methods are based on a height‐width relationship derived from hydraulic geometry equations. We generate SWOT‐like observations of height and width based on 5‐m gridded Upper Mississippi River data and evaluate the performance of each curve‐fitting method given the SWOT‐like observations. The NLSB method predicts bed elevation and low flow area with the least error, although the nonlinear method may be preferred in low data conditions. Additionally, we show that our method outperforms previously suggested methods, and we propose an NLSB‐based bathymetry prior for Bayesian discharge estimation algorithms.

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

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

Predicting the geometry of regime rivers using M5 model tree, multivariate adaptive regression splines and least square support vector regression methods

ABSTRACTThe complex dynamic equilibrium state of rivers, in which the amount of deposition and erosion are in balance, has been a fundamental research topic in river engineering. In this research, three advanced machine learning approaches, including M5 Model Tree (M5Tree), Multivariate Adaptive Regression Splines (MARS) and Least Square Support Vector Regression (LSSVR), are employed to gain new insights and develop more accurate methods for assessment of the longitudinal slope (S), water-surface width (W) and mean water depth (D) of rivers in regime state. Geometric and hydraulic characteristic of 85 cross-sections of Gamasiab River (located in western of Iran), Kaaj River (located in southwestern of Iran) and Behesht-Abad River (located in southwestern of Iran) are used to train and evaluate the employed methods (M5Tree, MARS, and LSSVR). Seven different models comprising various combinations of effective parameters influencing regime river geometry (the flow discharge (Q), median bed grain size (d50) and Shields parameter (τ )), are developed to evaluate the effect of each of these variables on the prediction of the geometry of regime rivers (S, W and D). The M5Tree method outperformed the other approaches with respect to correlation coefficient (R) values of 0.872, 0.951, and 0.770 and Mean Absolute Relative Error (MARE) values of 0.484, 0.102, and 0.126 for slope, width, and depth prediction, respectively. Furthermore, the flow discharge Q was the key variable governing regime channel width and depth while the regime channel slope was found to be mainly controlled by the Shields parameter.

Exact solution of optimum hydraulic horizontal-bottomed power-law section with general exponent parameter

Horizontal-bottomed power-law sections (HBP sections) are new composite channel sections, which provide more adaptability and flexibility for optimal section design than power-law sections (PL sections). Analytical solutions for wetted perimeters with general exponent parameter m are difficult to obtain, except for several definite sections, such as a horizontal-bottomed parabolic section and a horizontal-bottomed half-cubic parabola section. Therefore, there has been no detailed investigation of the general form of the HBP section. This paper present a group of general exact solutions (ratio of water surface width of PL section to water depth, and ratio of channel bed width to water depth) of the optimum hydraulic HBP section with exponent m as a parameter based on Gauss Hyper geometric mathematics and Lagrange multiplier. Many explicit exact formulas for various hydraulic parameters (flow discharge or water depth) under the condition of optimum hydraulic HBP section are also given. Error analysis shows the proposed explicit exact formulas are accurate. Next, by comparing several sections, the results indicate the cross area and wetted perimeter of horizontal-bottomed cubic sections are smaller than those of other sections for a given flow discharge. This finding means that the least amount of excavation and lining is required for construction. Therefore, the horizontal-bottomed cubic parabola section is the most economical section among the typical sections (PL sections, Rectangular, Triangular, Trapezoid, semi-cubic section and other HBP sections). This study sheds new light on a general and concise hydraulic calculation method for any HBP section with general exponent parameter m.

Stable alluvial channel design using evolutionary neural networks

Accurate prediction of the long-term average dimensions of alluvial stable channels is a significant problem in river engineering. The goal of this research is to investigate the effect of flow discharge (Q), mean sediment size (d50) and Shields parameter (τ∗) on the stable channel dimensions by employing non-linear regression (NLR) and two Artificial Intelligence (AI) methods, including: Generalized Structure of Group Method of Data Handling (GS-GMDH) neural network and Gene Expression Programming (GEP). Discharge, grain size and Shields parameter from 85 gaging stations situated in three stable Iranian rivers were used as input data for the three methods to estimate the water-surface width (W), average flow depth (D) and longitudinal slope (S) of the rivers. Based on the results, it was found that the GS-GMDH produced more accurate results for simulating the channel width with a Mean Absolute Relative Error (MARE) value of 0.055; and GEP produced better estimations for channel depth and slope with MARE values of 0.035 and 0.03, respectively. Furthermore, by employing Artificial Intelligence (AI) methods (GS-GMDH and GEP), the RMSE values decreased by 22%, 25% and 75% in predicting width, depth, and slope, respectively, compared to NLR method. The overall results showed that the AI methods generally produced better estimations than the non-linear regression method. To determine the effect of each input variable (Q, d50, τ∗) on the target variables (W, D, S), a sensitivity analysis comprising various combinations of input variables was conducted. Based on the results, the flow discharge had a dominant role on depth and width estimation of stable channels. In slope estimation, the most important parameter was τ∗ and then d50, while the discharge had a weak effect on slope prediction. In general, the Shields parameter was the most effective parameter in depth and specially slope estimation of stable channels.

Immediately downstream effects of Three Gorges Dam on channel sandbars morphodynamics between Yichang-Chenglingji Reach of the Changjiang River, China

Sandbars are of vital ecological and environmental significance, which however, have been intensively influenced by human activities. Morphodynamic processes of sandbars along the Yichang-Chenglingji Reach of the Changjiang River, the channel immediately downstream of the Three Gorges Dam (TGD), are assessed based on remote sensing images between 2000 and 2016. It can be found that the entire area of sandbars reduces drastically by 19.23% from 149.04 km2 in 2003 to 120.38 km2 in 2016, accompanied with an increase in water surface width. Owing to differences in sediment grain size and anti-erosion capacity, sandbar area in the upstream sandy gravel reach (Yichang-Dabujie) and downstream sandy reach (Dabujie-Chenglingji) respectively decreases by 45.94% (from 20.79 km2 to 11.24 km2) and 14.93% (from 128.30 km2 to 109.14 km2). Furtherly, morphological evolutions of sandbars are affected by channel type: in straight-microbend channel, mid-channel sandbars exhibit downstream moving while maintaining the basic profile; in meandering channel, point sandbars show erosion and deposition in convex and concave bank respectively, with mid-channel sandbars distributing sporadically; in bending-branching channel, point sandbars experience erosion and move downstream while mid-channel sandbars show erosion in the head part along with retreating outline. We document that the primary mechanism of sandbars shrinkages along the Yichang-Chenglingji Reach can be attributed to TGD induced suspended sediment concentration decreasing and increasing in unsaturation of sediment carrying capacity. Additionally, channel type can affect the morphological evolution of sandbars. Along the Yichang-Chenglingji Reach, sandbars in straight-microbend channel are more affected by water flow than that in bending-branching channel.

Discharge Estimation in Ungauged Basins Through Variational Data Assimilation: The Potential of the SWOT Mission

AbstractSpace‐borne instruments can measure river water surface elevation, slope, and width. Remote sensing of river discharge in ungauged basins is far more challenging, however. This work investigates the estimation of river discharge from simulated observations of the forthcoming Surface Water and Ocean Topography (SWOT) satellite mission using a variant of the classical variational data assimilation method “4D‐Var.” The variational assimilation scheme simultaneously estimates discharge, river bathymetry, and bed roughness in the context of a 1.5 D full Saint‐Venant hydraulic model. Algorithms and procedures are developed to apply the method to fully ungauged basins. The method was tested on the Po and Sacramento Rivers. The SWOT hydrology simulator was used to produce synthetic SWOT observations at each overpass time by simulating the interaction of SWOT radar measurements with the river water surface and nearby land surface topography at a scale of approximately 1 m, thus accounting for layover, thermal noise, and other effects. SWOT data products were synthesized by vectorizing the simulated radar returns, leading to height and width estimates at 200 m increments along the river centerlines. The ingestion of simulated SWOT data generally led to local improvements on prior bathymetry and roughness estimates which allowed the prediction of river discharge at the overpass times with relative root mean squared errors of 12.1% and 11.2% for the Po and Sacramento Rivers, respectively. Nevertheless, equifinality issues that arise from the simultaneous estimation of bed elevation and roughness may prevent their use for different applications, other than discharge estimation through the presented framework.

Uncertainty analysis of intelligent model of hybrid genetic algorithm and particle swarm optimization with ANFIS to predict threshold bank profile shape based on digital laser approach sensing

Measuring the bank profile shape when bank sediment particles are undergoing incipient motion (threshold) is notable for researchers. In the present study, an advanced laser gauge sensor instrument is utilized to measure the coordinates of points located in a stable channel bank cross section. A robust Particle Swarm Optimization (PSO) algorithm combined with a Genetic Algorithm (GA) is developed in an Adaptive Neuro-Fuzzy Inference System (ANFIS) model to predict and compare the bank profile with measured data. The results show that the proposed ANFIS-PSO/GA optimization method had a determination coefficient (R2) and Mean Absolute Relative Error (MARE) of 0.9951 and 0.1575, respectively, and was thus highly accurate in stable bank shape prediction. With increasing flow discharge, the ANFIS-PSO/GA model accuracy augmented, and the model could simulate the widening of the water surface width quite well with an appropriate bank profile function that can be used in the design and implementation of stable channel geometry. Moreover, an uncertainty analysis was carried out to calculate the reliability of the proposed model based on the Monte-Carlo method. The results show that the ANFIS-PSO/GA model has less uncertainty in different hydraulic conditions of channels for predicting the vertical level of threshold bank profile and can predict satisfactorily the channel bank profiles.

River discharge estimation from synthetic SWOT-type observations using variational data assimilation and the full Saint-Venant hydraulic model

The upcoming Surface Water and Ocean Topography satellite mission, to be launched in 2021, will measure river water surface elevation, slope and width, with an unprecedented level of accuracy for a remote sensing tool. This work investigates the river discharge estimation from synthetic SWOT observations, in the presence of strong uncertainties in the model inputs, i.e. the river bathymetry and bed roughness. The estimation problem is solved by a novel variant of the standard variational data assimilation, the ‘4D-Var’ method, involving the full Saint-Venant 1.5D-network hydraulic model SIC2. The assimilation scheme simultaneously estimates the discharge, bed elevation and bed roughness coefficient and is designed to assimilate both satellite and in situ measurements. The method is tested on a 50 km-long reach of the Garonne River during a five-month period of the year 2010, characterized by multiple flooding events. First, the impact of the sampling frequency on discharge estimation is investigated. Secondly, discharge as well as the spatially distributed bed elevation and bed roughness coefficient are determined simultaneously. Results demonstrate feasibility and efficiency of the chosen combination of the estimation method and of the hydraulic model. Assimilation of the SWOT data results into an accurate estimation of the discharge at observation times, and a local improvement in the bed level and bed roughness coefficient. However, the latter estimates are not generally usable for different independent experiments.

Technical note: Stage and water width measurement of a mountain stream using a simple time-lapse camera

Abstract. Remote sensing applied to river monitoring adds complementary information useful for understanding the system behaviour. In this paper, we present a method for visual stage gauging and water surface width measurement using a ground-based time-lapse camera and a fully automatic image analysis algorithm for flow monitoring at a river cross section of a steep, bouldery channel. The remote stage measurement was coupled with a water level logger (pressure transducer) on site and shows that the image-based method gives a reliable estimate of the water height variation and daily flow record when validated against the pressure transducer (R = 0.91). From the remotely sensed pictures, we also extracted the water width and show that it is possible to correlate water surface width and stage. The images also provide valuable ancillary information for interpreting and understanding flow hydraulics and site weather conditions. This image-based gauging method is a reliable, informative and inexpensive alternative or adjunct to conventional stage measurement especially for remote sites.

BAM: Bayesian AMHG‐Manning Inference of Discharge Using Remotely Sensed Stream Width, Slope, and Height

AbstractThe forthcoming Surface Water and Ocean Topography (SWOT) NASA satellite mission will measure water surface width, height, and slope of major rivers worldwide. The resulting data could provide an unprecedented account of river discharge at continental scales, but reliable methods need to be identified prior to launch. Here we present a novel algorithm for discharge estimation from only remotely sensed stream width, slope, and height at multiple locations along a mass‐conserved river segment. The algorithm, termed the Bayesian AMHG‐Manning (BAM) algorithm, implements a Bayesian formulation of streamflow uncertainty using a combination of Manning's equation and at‐many‐stations hydraulic geometry (AMHG). Bayesian methods provide a statistically defensible approach to generating discharge estimates in a physically underconstrained system but rely on prior distributions that quantify the a priori uncertainty of unknown quantities including discharge and hydraulic equation parameters. These were obtained from literature‐reported values and from a USGS data set of acoustic Doppler current profiler (ADCP) measurements at USGS stream gauges. A data set of simulated widths, slopes, and heights from 19 rivers was used to evaluate the algorithms using a set of performance metrics. Results across the 19 rivers indicate an improvement in performance of BAM over previously tested methods and highlight a path forward in solving discharge estimation using solely satellite remote sensing.

Air-photo based change in channel width in the Minnesota River basin: Modes of adjustment and implications for sediment budget

The Minnesota River and major tributaries have experienced large increases in discharge over the past century. Aerial photograph-based measurements of channel width were made for the 1938–2015 period at 16 multibend subreaches by digitizing the area between vegetation lines and dividing by centerline length. Results show considerable increases in width for the main stem (0.62±0.10%/y) and major tributaries (0.31±0.08%/y) but are inconclusive for smaller channels (width<25m). Width change for a 146.5-km reach of the lower Minnesota River between 1938 and 2008 is similar to that from the subreach-scale analysis. Widening was associated with lateral centerline movement and temporal change in at-a-station hydraulic geometry for water surface width, indicating that widening is associated with cross-sectional change and not simply upward movement of the vegetation line. Digital elevation model analysis and regional hydraulic geometry show that the main stem and larger tributaries account for the vast majority (~85%) of bankfull channel volume. High-order channels are thus disproportionately responsible for sediment production through cross section enlargement, although floodplains or off-channel water bodies adjacent to these channels likely represent important sediment sinks. Because channel enlargement can play an important role in sediment production, it should be considered in sediment reduction strategies in the Minnesota River basin and carefully evaluated in other watersheds undergoing long-term increases in discharge.

Horizontal bottomed semi-cubic parabolic channel and best hydraulic section

This paper presents a new channel section having semi-cubic parabolic sides and horizontal bottom. The formulae for calculating the area, wetted perimeter are presented. The best hydraulic section is derived using three variables (water depth, water surface width and horizontal bottom width). Results show the ratios of the water surface width to depth, bottom width to depth and water surface width to bottom are all constant for the best hydraulic section. Explicit equations of the best hydraulic section for design are also deduced. Examples show these explicit equations are convenient for design. This type of best hydraulic section is compared with the trapezoid and classic semi-cubic parabolic sections. Results indicate that the area and wetted perimeter are less than those of trapezoid and classic semi-cubic parabolic sections for a given flow discharge. It means less lining and excavation cost is required for construction.

Inference of effective river properties from remotely sensed observations of water surface

The future SWOT mission (Surface Water and Ocean Topography) will provide cartographic measurements of inland water surfaces (elevation, widths and slope) at an unprecedented spatial and temporal resolution. Given synthetic SWOT like data, forward flow models of hierarchical-complexity are revisited and few inverse formulations are derived and assessed for retrieving the river low flow bathymetry, roughness and discharge (A0,K,Q). The concept of an effective low flow bathymetry A0 (the real one being never observed) and roughness K, hence an effective river dynamics description, is introduced. The few inverse models elaborated for inferring (A0,K,Q) are analyzed in two contexts: (1) only remotely sensed observations of the water surface (surface elevation, width and slope) are available; (2) one additional water depth measurement (or estimate) is available. The inverse models elaborated are independent of data acquisition dynamics; they are assessed on 91 synthetic test cases sampling a wide range of steady-state river flows (the Froude number varying between 0.05 and 0.5 for 1km reaches) and in the case of a flood on the Garonne River (France) characterized by large spatio-temporal variabilities. It is demonstrated that the most complete shallow-water like model allowing to separate the roughness and bathymetry terms is the so-called low Froude model. In Case (1), the resulting RMSE on infered discharges are on the order of 15% for first guess errors larger than 50%. An important feature of the present inverse methods is the fairly good accuracy of the discharge Q obtained, while the identified roughness coefficient K includes the measurement errors and the misfit of physics between the real flow and the hypothesis on which the inverse models rely; the later neglecting the unobserved temporal variations of the flow and the inertia effects. A compensation phenomena between the indentifiedvalues of K and the unobserved bathymetry A0 is highlighted, while the present inverse models lead to an effective river dynamics model that is accurate in the range of the discharge variability observed. In Case (2), the effective bathymetry profile for 80km of the Garonne River is retrieved with 1% relative error only. Next, accurate effective topography-friction pairs and also discharge can be inferred. Finally, defining river reaches from the observation grid tends to average the river properties in each reach, hence tends to smooth the hydraulic variability.

Estimating daily time series of streamflow using hydrological model calibrated based on satellite observations of river water surface width: Toward real world applications

Lacking observation data for calibration constrains applications of hydrological models to estimate daily time series of streamflow. Recent improvements in remote sensing enable detection of river water-surface width from satellite observations, making possible the tracking of streamflow from space. In this study, a method calibrating hydrological models using river width derived from remote sensing is demonstrated through application to the ungauged Irrawaddy Basin in Myanmar. Generalized likelihood uncertainty estimation (GLUE) is selected as a tool for automatic calibration and uncertainty analysis. Of 50,000 randomly generated parameter sets, 997 are identified as behavioral, based on comparing model simulation with satellite observations. The uncertainty band of streamflow simulation can span most of 10-year average monthly observed streamflow for moderate and high flow conditions. Nash–Sutcliffe efficiency is 95.7% for the simulated streamflow at the 50% quantile. These results indicate that application to the target basin is generally successful. Beyond evaluating the method in a basin lacking streamflow data, difficulties and possible solutions for applications in the real world are addressed to promote future use of the proposed method in more ungauged basins.