Estimating continental river basin discharges using multiple remote sensing data sets

Sichangi, Arthur Wafula; Wang, Lei; Yang, Kun; Chen, Deliang; Wang, Zhongjing; Li, Xiuping; Zhou, Jing; Liu, Wenbin; Kuria, David Ndegwa

doi:10.1016/j.rse.2016.03.019

Cited by 125 publications

(91 citation statements)

References 52 publications

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“…Besides, optical sensors usually suffer from cloud cover, especially during the flood event, which hampers the correct estimation of some critical discharge records. Therefore, multisatellite techniques (Papa et al, ; Sichangi et al, ) were suggested to avoid this problem.…”

Section: Progresses and Challengesmentioning

confidence: 99%

Detecting, Extracting, and Monitoring Surface Water From Space Using Optical Sensors: A Review

Huang

Chen

Zhang

et al. 2018

Reviews of Geophysics

465

267

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Observation of surface water is a functional requirement for studying ecological and hydrological processes. Recent advances in satellite-based optical remote sensors have promoted the field of sensing surface water to a new era. This paper reviews the current status of detecting, extracting, and monitoring surface water using optical remote sensing, especially progress in the last decade. It also discusses the current status and challenges in this field, including spatio-temporal scale issues, integration with in situ hydrological data and elevation data, obscuration caused by clouds and vegetation, and the growing need to map surface water at a global scale. Historically, sensors have exhibited a contradiction in resolutions. Techniques including pixel unmixing and reconstruction, and spatio-temporal fusion have been developed to alleviate this contradiction. Spatio-temporal dynamics of surface water have been modeled by combining remote sensing data with in situ river flow. Recent studies have also demonstrated that the river discharge can be estimated using only optical remote sensing imagery, providing valuable information for hydrological studies in ungauged areas. Another historical issue for optical sensors has been obscuration by clouds and vegetation. An effective approach of reducing this limitation is to combine with synthetic aperture radar data. Digital elevation model data have also been employed to eliminate cloud/terrain shadows. The development of big data and cloud computation techniques makes the increasing demand of monitoring global water dynamics at high resolutions easier to achieve. An integrated use of multisource data is the future direction for improved global and regional water monitoring.Plain Language Summary Observing surface water is essential for ecological and hydrological studies. This paper reviews the current status of detecting, extracting, and monitoring surface water using optical remote sensing, especially progress in the last decade. It also discusses the current status and challenges in this field. For example, it was found that pixel unmixing and reconstruction, and spatio-temporal fusion are two common and low-cost approaches to enhance surface water monitoring. Remote sensing data have been integrated with in situ river flow to model spatio-temporal dynamics of surface water. Recent studies have also proved that the river discharge can be estimated using only optical remote sensing imagery. This will be a breakthrough for hydrological studies in ungauged areas. Optical sensors are also easily obscured by clouds and vegetation. This limitation can be reduced by integrating optical data with synthetic aperture radar data and digital elevation model data. There is increasing demand of monitoring global water dynamics at high resolutions. It is now easy to achieve with the development of big data and cloud computation techniques. Enhanced global or regional water monitoring in the future requires integrated use of multiple sources of remote sensing data.

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Section: Progresses and Challengesmentioning

confidence: 99%

Detecting, Extracting, and Monitoring Surface Water From Space Using Optical Sensors: A Review

Huang

Chen

Zhang

et al. 2018

Reviews of Geophysics

465

267

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“…Therefore, we only discussed the influence of coefficient a on the estimation results. Sichangi [73] research shows that for the trapezoidal section, coefficient a is shown in Equation (9). When river width >> depth, coefficient a can be approximately equal to S 1/2 /n, as shown in Equation (10).…”

Section: Parametric Sensitivity Analysismentioning

confidence: 99%

Low Altitude Unmanned Aerial Vehicles (UAVs) and Satellite Remote Sensing Are Used to Calculated River Discharge Attenuation Coefficients of Ungauged Catchments in Arid Desert

Yang

Wang

et al. 2019

Water

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The arid desert ecosystem is very fragile, and the change of its river discharge has a direct impact on irrigation and natural environment. River discharge attenuation coefficients is a key index to reveal the stability of desert river ecosystem. However, due to the harsh conditions in desert areas, it is difficult to establish a hydrological station to obtain data and calculate the attenuation coefficients, so it is urgent to develop new methods to master the attenuation coefficients of rivers. In this study, Taklamakan desert river was selected as the research area, and the river discharge of the desert river were estimated by combining low-altitude UAV and satellite remote sensing technology, so as to calculate the attenuation status of the river in its natural state. Combined with satellite remote sensing, the surface runoff in the desert reaches of the Hotan River from 1993 to 2017 were estimated. The results showed that the base of runoff attenuation in the lower reaches of the Hotan River is 40%. Coupled UAV and satellite remote sensing technology can provide technical support for the study of surface runoff in desert rivers within ungauged basins. Using UAV and satellite remote sensing can monitor surface runoff effectively providing important reference for river discharge monitoring in ungauged catchments.The attenuation coefficients of river discharge is the key index for maintaining fluvial ecosystems and arises through evaporation and infiltration during transport, which is usually calculated from the flow rate during the dry season [9,10]. The process of driving river attenuation depends on a series of physicochemical and biological parameters such as river velocity, temperature, vertical hydrological exchange of surface runoff and groundwater [11,12]. In the past 30 years, some relatively mature computational methods have been developed [13][14][15][16], which can be mainly divided into hydrological methods, hydraulic methods, habitat simulation methods and holistic analysis methods. These methods require a lot of information and require a long time of investigation, which tends to be carried out in areas with abundant hydrological data. However, large portions of total River Basins across the globe are either poorly gauged or completely ungauged [17][18][19], and hydrological observation networks are continuously deteriorating [20]. Therefore, there is a lack of research on surface runoff in ungauged catchments of arid desert [21][22][23], and the study on river attenuation is basically blank, resulting in high variability of attenuation rate in rivers, which complicates the prediction of environmental flows [24,25].Calculating the streamflow in ungauged catchments is surrounded by uncertainty, and is thus a challenging, yet vital task for water management. New and easily accessible satellite data have been increasingly steadily in recent years. Many studies have been conducted using satellite data to estimate river discharge [26][27][28]. Traditional methods for estimating river discharge mainly a...

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“…The most prevalent technique for using satellites to estimate discharge is to couple satellite observations directly with field measurements. A common algorithm for doing so involves building an empirical relationship between field measurements of discharge and satellite observations of stage, width, or some other fluvial observable (e.g., Ashmore & Sauks, ; Bjerklie et al, ; Bjerklie, ; Brakenridge et al, ; Gilvear et al, ; Nathanson et al, ; Pan et al, ; Pavelsky, ; Sichangi et al, ; Smith & Pavelsky, ; Smith et al, ; Tarpanelli et al, ; Tourian et al, ). In addition to these field calibrated approaches, the forthcoming NASA/CNES Surface Water and Ocean Topography (SWOT) satellite scheduled for launch in 2021 holds promise for estimating discharge without in situ information as demonstrated by using hydraulic model output as a proxy for future simultaneous SWOT observations of water surface elevation and width using a McFLI (Mass conserved Flow Law Inversion) paradigm (Biancamaria et al, ; Bonnema et al, ; Durand et al, ; Garambois & Monnier, ; Yoon et al, ; Gleason et al, ).…”

Section: Introductionmentioning

confidence: 99%

A Hybrid of Optical Remote Sensing and Hydrological Modeling Improves Water Balance Estimation

Gleason

Wada

Wang

2018

J Adv Model Earth Syst

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Declining gauging infrastructure and fractious water politics have decreased available information about river flows globally. Remote sensing and water balance modeling are frequently cited as potential solutions, but these techniques largely rely on these same in‐decline gauge data to make accurate discharge estimates. A different approach is therefore needed, and we here combine remotely sensed discharge estimates made via at‐many‐stations hydraulic geometry (AMHG) and the PCR‐GLOBWB hydrological model to estimate discharge over the Lower Nile. Specifically, we first estimate initial discharges from 87 Landsat images and AMHG (1984–2015), and then use these flow estimates to tune the model, all without using gauge data. The resulting tuned modeled hydrograph shows a large improvement in flow magnitude: validation of the tuned monthly hydrograph against a historical gauge (1978–1984) yields an RMSE of 439 m3/s (40.8%). By contrast, the original simulation had an order‐of‐magnitude flow error. This improvement is substantial but not perfect: tuned flows have a 1–2 month wet season lag and a negative base flow bias. Accounting for this 2 month lag yields a hydrograph RMSE of 270 m3/s (25.7%). Thus, our results coupling physical models and remote sensing is a promising first step and proof of concept toward future modeling of ungauged flows, especially as developments in cloud computing for remote sensing make our method easily applicable to any basin. Finally, we purposefully do not offer prescriptive solutions for Nile management, and rather hope that the methods demonstrated herein can prove useful to river stakeholders in managing their own water.

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Estimating continental river basin discharges using multiple remote sensing data sets

Cited by 125 publications

References 52 publications

Detecting, Extracting, and Monitoring Surface Water From Space Using Optical Sensors: A Review

Detecting, Extracting, and Monitoring Surface Water From Space Using Optical Sensors: A Review

Low Altitude Unmanned Aerial Vehicles (UAVs) and Satellite Remote Sensing Are Used to Calculated River Discharge Attenuation Coefficients of Ungauged Catchments in Arid Desert

A Hybrid of Optical Remote Sensing and Hydrological Modeling Improves Water Balance Estimation

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