Operational applications of remote sensing in hydrology: success,prospects and problems

Abstract

The use of remote sensing information in operational hydrology is relatively limited, but specific examples can be cited for determining precipitation, soil moisture, groundwater, snow, surface water and basin characteristics. The application of remote sensing in hydrology can be termed operational if at least one of two conditions are met: (a) the application produces an output on a regular basis, or (b) the remote sensing data are used regularly on a continuing basis as part of a procedure to solve a problem or make decisions. When surveying the various operational applications, simple approaches and simple remote sensing data sets are the most successful. In the data-sparse developing countries, many operational remote sensing approaches exist (out of necessity) that may not be needed in developed countries because of existing data networks. To increase the use of remote sensing in operational hydrology in developed countries, pilot projects need to be increased and information services must be improved. Increased utilization of GIS to combine remote sensing with other information will promote new products and applications. End user training must be improved by focusing on satellite data processing and manipulation. In developing countries the same improvements are needed plus some more basic ones. There is a need for international monetary assistance to establish long-term remote sensing data, improved database systems and image processing capabilities. There is also the need to set up innovative regional training centres throughout the developing world.     

Groundwater potential zones using a combination of geospatial technology and geophysical approach: case study in Dehradun,India

ABSTRACT

A combination of geospatial, geophysical and statistical models using satellite data, the weighted index overlay (WIO) method and two-dimensional electrical resistivity tomography (2D-ERT) is applied to generate the highest potential groundwater area and to further explore the groundwater in Dehradun, India. The results show that of 19.7 km² total basin area, 0.26% falls under the “poor” category as a prospect zone for groundwater, 4.3% is “moderate”, 10.10% “moderately good”, 4.9% “good” and 0.17% “very good”. In addition, the demonstration of the geophysical survey is presented, in which Purkal Youth Society Division (PYSD) site is categorized as a shallow aquifer zone and the Guru Nanak Fifth Centenary School (GNFCS) site is a deeper aquifer zone. Our study emphasizes remote sensing and geographic information system integrated with a geophysical survey to support prospecting the most probable area and confirm the existence of groundwater.     

Climate variability,hydrology and water resources: do we communicate in the field? (HAPEX,FIFE, GEWEX,GCIP and what next?)

Abstract

All the field “experiments” indicated in the sub-title above include the hydrological cycle in some or all of its aspects and thus require the use of “hydrological sciences”. Is hydrology actually included in them? This depends on the definition of hydrology used. The paper briefly describes the different definitions of “hydrology” in the context of the scientific objectives and concepts of these experiments and related scientific activities. It further evaluates the role actually assigned to hydrologists in past cross-disciplinary endeavours to conduct “field experiments” and goes on to propose adjustments to this role in the GEWEX Continental-scale International Project (GCIP). Related activities are analysed in some detail in this framework and proposals are presented for increased inter-disciplinary communication.     

Potential for satellite remote sensing of ground water

Predicting hydrologic behavior at regional scales requires heterogeneous data that are often prohibitively expensive to acquire on the ground. As a result, satellite-based remote sensing has become a powerful tool for surface hydrology. Subsurface hydrology has yet to realize the benefits of remote sensing, even though surface expressions of ground water can be monitored from space. Remotely sensed indicators of ground water may provide important data where practical alternatives are not available. The potential for remote sensing of ground water is explored here in the context of active and planned satellite-based sensors. Satellite technology is reviewed with respect to its ability to measure ground water potential, storage, and fluxes. It is argued here that satellite data can be used if ancillary analysis is used to infer ground water behavior from surface expressions. Remotely sensed data are most useful where they are combined with numerical modeling, geographic information systems, and ground-based information.     

Estimation of the temporal autocorrelation structure by the collocation technique with an emphasis on soil moisture studies

Abstract

The collocation technique has become a popular tool in oceanography and hydrology for estimating the error variances of different data sources such as in situ sensors, models and remote sensing products. It is also possible to determine calibration constants, for example to account for an off-set between the data sources. So far, the temporal autocorrelation structure of the errors has not been studied, although it is known that it has detrimental effects on the results of the collocation technique, in particular when calibration constants are also determined. This paper shows how the (triple) collocation estimators can be adapted to retrieve the autocovariance functions; the statistical properties as well as the structural deficencies are described. The coupling between the autocorrelation of the error and the estimation of calibration constants is studied in detail, due to its importance for analysing temporal changes. In soil moisture applications, such time variations can be induced, for example, by seasonal changes in the vegetation cover, which affect both models and remote sensing products. The limitations of the proposed technique associated with these considerations are analysed using remote sensing and in situ soil moisture data. The variability of the inter-sensor calibration and the autocovariance are shown to be closely related to temporal patterns of the data.

Editor D. Koutsoyiannis

Citation Zwieback, S., Dorigo, W., and Wagner, W., 2013. Estimation of the temporal autocorrelation structure by the collocation technique with an emphasis on soil moisture studies. Hydrological Sciences Journal, 58 (8), 1729–1747.     

Remote sensing applications to hydrology: future impact

Abstract

The case is made that the hydrological sciences are data limited and that future progress in understanding hydrological processes is hampered by the lack of adequate data. The future applications of remote sensing to hydrology should provide new types of data that enable hydrologists to address the previously unsolved questions.     

Publications received by the Editor

Abstract

Remote sensing is the use of electromagnetic energy to measure the physical properties of distant objects. It includes photography and geophysical surveying as well as newer techniques that use other parts of the electromagnetic spectrum. The history of remote sensing begins with photography. The origin of other types of remote sensing can be traced to World War II, with the development of radar, sonar, and thermal infrared detection systems. Since the 1960s, sensors have been designed to operate in virtually all of the electromagnetic spectrum. Today a wide variety of remote sensing instruments are available for use in hydrological studies; satellite data, such as Skylab photographs and Landsat images are particularly suitable for regional problems and studies. Planned future satellites will provide a ground resolution of 10–80 m.

Remote sensing is currently used for hydrological applications in most countries of the world. The range of applications includes groundwater exploration determination of physical water quality, snowfield mapping, flood-inundation delineation, and making inventories of irrigated land. The use of remote sensing commonly results in considerable hydrological information at minimal cost. This information can be used to speed-up the development of water resources, to improve management practices, and to monitor environmental problems.     

II. Snow hydrology processes and remote sensing

In the last 20 years remote sensing research has led to significant progress in monitoring and measuring certain snow hydrology processes. Snow distribution in a drainage basin can be adequately assessed by visible sensors. Although there are still some interpretation problems, the NOAA-AVHRR sensor can provide frequent views of the areal snow cover in a basin, and snow cover maps are produced operationally by the National Weather Service on about 3000 drainage basins in North America. Measurement of snow accumulation or snow water equivalent with microwave remote sensing has great potential because of the capabilities for depth penetration, all-weather observation and night-time viewing. Several critical areas of research remain, namely, the acquisition of snow grain size information for input to microwave models and improvement in passive microwave resolution from space. Methods that combine both airborne gamma ray and visible satellite remote sensing of the snowpack with field measurements also hold promise for determining areal snow water equivalent. Some remote sensing techniques can also be used to detect different stages of snow metamorphism. Various aspects of snowpack ripening can be detected using microwave and thermal infra-red capabilities. The capabilities for measurement of snow albedo and surface temperature have direct application in both snow metamorphism and snowpack energy balance studies. The potentially most profitable research area here is the study of the bidirectional reflectance distribution function to improve snow albedo measurements. Most of the remote sensing capabilities in snow hydrology have been developed for improving snowmelt-run-off forecasting. Most applications have used the input of snow cover extent to deterministic models, both of the degree day and energy balance types. Snowmelt-run-off forecasts using satellite derived snow cover depletion curves and the models have been successfully made. As the extraction of additional snow cover characteristics becomes possible, remote sensing will have an even greater impact on snow hydrology. Important remote sensing capabilities will become available in the next 20 years through space platform observing systems that will improve our capability to observe the snowpack on an operational basis.     

Estimation of river discharge from non-trapezoidal open channel using QuickBird-2 satellite imagery/Utilisation des images satellites de Quickbird-2 pour le calcul des débits fluviaux en chenaux ouverts non-trapézoïdaux

Abstract

Abstract River discharge is traditionally acquired by measuring water stage and then converting the water stage to discharge by using a stage–discharge rating curve. The possibility of monitoring river discharge by satellite has not been adequately studied hitherto, because of the difficulty in making sufficiently precise measurements of the water surface. Since the successful launch of commercial satellites with very-high-resolution sensors, it has become possible to derive ground information from satellite data. To determine river discharge in a non-trapezoidal open channel, an efficient approach has been developed that uses mainly satellite data. The method, which focuses on the measurement of surface water width coupled with river width–stage and ?remote? stage–discharge rating curves, was applied to the Yangtze River (Changjiang) and an accurate estimate of river discharge was obtained. The method can be regarded as ancillary to traditional field measurement methods or other remote sensing methods.     

On Creating Global Gridded Terrestrial Water Budget Estimates from Satellite Remote Sensing

The increasing availability and reliability of satellite remote sensing products [e.g., precipitation (P), evapotranspiration (ET), and the total water storage change (TWSC)] make it feasible to estimate the global terrestrial water budget at fine spatial resolution. In this study, we start from a reference water budget dataset that combines all available data sources, including satellite remote sensing, land surface model (LSM) and reanalysis, and investigate the roles of different non-satellite remote sensing products in closing the terrestrial water budget through a sensitivity analysis by removing/replacing one or more categories of products during the budget estimation. We also study the differences made by various satellite products for the same budget variable. We find that the gradual removal of non-satellite data sources will generally worsen the closure errors in the budget estimates, and remote sensing retrievals of P, ET, and TWSC together with runoff (R) from LSM give the worst closure errors. The gauge-corrected satellite precipitation helps to improve the budget closure (4.2–9 % non-closure errors of annual mean precipitation) against using the non-gauge-corrected precipitation (7.6–10.4 % non-closure errors). At last, a data assimilation technique, the constrained Kalman filter, is applied to enforce the water balance, and it is found that the satellite remote sensing products, though with worst closure, yield comparable budget estimates in the constrained system to the reference data. Overall, this study provides a first comparison between the water budget closure using the satellite remote sensing products and a full combination of remote sensing, LSM, and reanalysis products on a quasi-global basis. This study showcases the capability and potential of the satellite remote sensing in closing the terrestrial water budget at fine spatial resolution if properly constrained.     

Intercomparison across scales between remotely-sensed land surface temperature and representative equilibrium temperature from a distributed energy water balance model

Abstract

Quantifying the reliability of distributed hydrological models is an important task in hydrology to understand their ability to estimate energy and water fluxes at the agricultural district scale as well the basin scale for water resources management in drought monitoring and flood forecasting. In this context, the paper presents an intercomparison of simulated representative equilibrium temperature (RET) derived from a distributed energy water balance model and remotely-sensed land surface temperature (LST) at spatial scales from the agricultural field to the river basin. The main objective of the study is to evaluate the use of LST retrieved from operational remote sensing data at different spatial and temporal resolutions for the internal validation of a distributed hydrological model to control its mass balance accuracy as a complementary method to traditional calibration with discharge measurements at control river cross-sections. Modelled and observed LST from different radiometric sensors located on the ground surface, on an aeroplane and a satellite are compared for a maize field in Landriano (Italy), the agricultural district of Barrax (Spain) and the Upper Po River basin (Italy). A good ability of the model in reproducing the observed LST values in terms of mean bias error, root mean square error, relative error and Nash-Sutcliffe index is shown.

Editor Z.W. Kundzewicz; Associate editor D. Gerten     

Producing time series of river water height by means of satellite radar altimetry—a comparative study

Abstract

Satellite radar altimetry is complementary to in situ limnimetric surveys as a means of estimating the water height of large rivers, lakes and flood plains. Production of water height time series by satellite radar altimetry technology requires first the selection of radar ground target locations corresponding to water body surfaces under study, i.e. the definition of “virtual limnimetric stations”. We propose to investigate qualitative and quantitative differences between three representative virtual station creation methodologies: (a) a fully manual method, (b) a semi-automatic method based on a land cover characterization that allows the water body surface under study to be located; and (c) an original fully automatic procedure that exploits a digital elevation model and an estimation of the river width. The results yielded by these three methods are comparable: maximum absolute magnitudes of water height differences being 0.46, 0.26 and 0.15 m for, respectively, 95, 90 and 80% of the water height values obtained. Moreover, more than 67% and 92% of time series jointly produced by the methods present root mean square differences lower than 20 and 50 cm, respectively. The results show that the fully automatic method developed herein provides as reliable results as the fully manual one. This opens the way to use of satellite radar altimetry for the generation of water height time series on a large scale, and considerably extends the applicability of satellite radar altimetry in hydrology.

Citation Roux, E., Santos da Silva, J., Vieira Getirana, A. C., Bonnet, M.-P., Calmant, S., Martinez, J.-M. & Seyler, F. (2010) Producing time series of river water height by means of satellite radar altimetry—comparative study. Hydrol. Sci. J. 55(1), 104–120.     

Management of Cultural Heritage Sites Using Remote Sensing Indices and Spatial Analysis Techniques

Sustainable management and exploitation policies as well as suitable conservation and mitigation strategies are mandatory to preserve cultural heritage and to reduce threats, weathering phenomena, and human actions that may produce significant deterioration and alteration of cultural heritage and “its environment”. In this context, remote sensing technologies can offer useful data to timely update information and documentation and set up reliable tools for systematic monitoring of cultural properties. In this study, multi-temporal and multi-sensor satellite data from Corona, Landsat, Spot, Quickbird, and Sentinel-2A have been exploited along with spatial analysis to investigate the area of the Theban temples at west Luxor (Egypt), severely threatened by uncontrolled urban sprawl. The results from our analyses showed that the urban expansion continuously occurred during the whole investigated period causing an increasing in urban areas around (1) 1.316 km² from 1967 to 1984, (2) 1.705 km² from 1984 to 2000, (3) 0.978 km² from 2000 to 2003, (4) 2.314 km² from 2003 to 2011, and (5) 1.377 km² from 2011 to 2017. The random urban expansion caused bad sewage networks and high groundwater depth which in turn affected the archaeological areas directly (as evident on a landscape view) and indirectly by causing changes (growing) in the level of ground water depth and increasing and accelerating weathering phenomena. The quantification and mapping of urban sprawl enabled us not only to quantify and spatially characterize urban sprawl but also to create a model to mitigate the impact and provide some operational recommendations to protect the archaeological site. Outcomes from our analysis pointed out that today the tremendous availability of advanced remote sensing data has opened new prospectives unthinkable several years ago.     

Data-driven modelling approaches for socio-hydrology: opportunities and challenges within the Panta Rhei Science Plan

ABSTRACT

“Panta Rhei – Everything Flows” is the science plan for the International Association of Hydrological Sciences scientific decade 2013–2023. It is founded on the need for improved understanding of the mutual, two-way interactions occurring at the interface of hydrology and society, and their role in influencing future hydrologic system change. It calls for strategic research effort focused on the delivery of coupled, socio-hydrologic models. In this paper we explore and synthesize opportunities and challenges that socio-hydrology presents for data-driven modelling. We highlight the potential for a new era of collaboration between data-driven and more physically-based modellers that should improve our ability to model and manage socio-hydrologic systems. Crucially, we approach data-driven, conceptual and physical modelling paradigms as being complementary rather than competing, positioning them along a continuum of modelling approaches that reflects the relative extent to which hypotheses and/or data are available to inform the model development process.

EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR not assigned     

Remote sensing of rivers: the emergence of a subdiscipline in the river sciences

This article reports on the special issue of Earth Surface Processes and Landforms dedicated to remote sensing of rivers. This emerging subdiscipline of river science has grown at a rapid rate in recent years because of: (a) the growing desire and need for data to document and explore the full range of spatial and temporal variations in river systems; (b) evolving technologies that enable lower cost data acquisition, processing and analysis at reach to catchment to continental scales; and (c) the increasing engagement of river scientists with GIScience. The convergence of these factors and the ever growing number of practitioners speaks to the need for more communication among researchers, a major reason for creating this special issue. The 12 articles in the volume cover a broad spectrum of applications that use a variety of platforms and sensors, ranging from photogrammetric mapping of riffle‐pool morphology beneath forest canopy using a camera mounted on a hand held pole to satellite‐based synthetic radar mapping of subcontinental scale hydrology of large rivers. In this overview each of the 12 articles is briefly summarized. Based on these works and other research, it is concluded that the time for more widespread application of river remote sensing techniques is now. To promote more widespread use of remote sensing techniques for river science and management, the following are advocated: (a) developing stand alone or plug‐in software products that enable non‐expert users to implement these new methods, (b) incorporating remote sensing of rivers training into classes, workshops, and on‐line tutorials; and (c) promoting more intentional and formal collaboration among members of the river remote sensing community. Copyright © 2010 John Wiley & Sons, Ltd.     

Application of remote sensing to forest hydrology

The paper reviews the application of remote sensing to forest hydrology. After discussing the general advantages and disadvantages of satellite remote sensing, the estimation of precipitation, changes in soil moisture, runoff, radiation components, sensible heat flux, latent heat flux, soil heat flux, changes in energy storage in biomass, primary production and monitoring the extent, type and density of forests are reviewed. Finally, the paper looks forward to future developments and concludes that these are likely to come from the use of multitemporal data, combined analysis of different types of remotely sensed data and of remotely sensed and ground data, improved image analysis techniques and combining satellite data with models.     

Data-driven modelling approaches for socio-hydrology: opportunities and challenges within the Panta Rhei Science Plan

ABSTRACT

“Panta Rhei – Everything Flows” is the science plan for the International Association of Hydrological Sciences scientific decade 2013–2023. It is founded on the need for improved understanding of the mutual, two-way interactions occurring at the interface of hydrology and society, and their role in influencing future hydrologic system change. It calls for strategic research effort focused on the delivery of coupled, socio-hydrologic models. In this paper we explore and synthesize opportunities and challenges that socio-hydrology presents for data-driven modelling. We highlight the potential for a new era of collaboration between data-driven and more physically-based modellers that should improve our ability to model and manage socio-hydrologic systems. Crucially, we approach data-driven, conceptual and physical modelling paradigms as being complementary rather than competing, positioning them along a continuum of modelling approaches that reflects the relative extent to which hypotheses and/or data are available to inform the model development process.

EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR not assigned     

Soil moisture estimation using ERS 2 SAR data: a case study in the Solani River catchment/Estimation de l’humidité du sol grâce à des données ERS-2 SAR: étude de cas dans le bassin de la rivière Solani

Abstract

Abstract The information regarding spatial and temporal variation of soil moisture in a catchment is of utmost importance in hydrological, as well as many other studies. Point measurements from gravimetric and other methods for soil moisture determination are insufficient to understand the spatial behaviour of soil moisture in a region. Microwave remote sensing data from active sensors on board various satellites are increasingly being used to map spatial distribution of soil moisture within the 0–10 cm top surface. The northern part of India has a network of large rivers and canals and, therefore, spatial and temporal distribution of soil moisture in this region has a significant bearing on the hydrology of the region. In this paper, results on estimation of soil moisture from an ERS-2 SAR image in the catchment of the Solani River (a tributary to the River Ganga) in and around the town of Roorkee, India, have been presented. The radar backscatter coefficient for each pixel of the image has been modelled from the digital numbers of the SAR image. Gravimetric measurements have been made simultaneously during the satellite pass to determine the concurrent value of volumetric soil moisture at a large number of sample points within the satellite sweep area. The backscatter coefficient is found to vary from –30 dB to –42 dB for a variation in soil moisture from 30 to 75%. Regression analyses between volumetric soil moisture and both the digital numbers and backscatter coefficients were performed. Strong correlations between volumetric soil moisture and digital number were observed with R ² values of 0.84, 0.75 and 0.83 for bare soil, vegetative and combined surfaces, respectively. A similar trend was observed with the relationship between backscatter and volumetric soil moisture with R ² values of 0.60, 0.89 and 0.67 for bare soil, vegetative and combined surfaces, respectively. These results demonstrate the utilization of SAR data for estimation of spatial distribution of soil moisture in the region of the present study.     

An assessment of water reserve changes in Salt Lake,Turkey, through multi‐temporal Landsat imagery and real‐time ground surveys

This paper focuses mainly on the investigation of water reserve changes in Salt Lake, Turkey, using remote‐sensing data. The study is performed in two stages: (1) correlation analysis for real‐time ground and satellite data and (2) assessment of water reserve changes using multi‐temporal Landsat imagery. First, correlation analysis is conducted to investigate the relationship between digital data from Landsat‐5 TM and spectral (in situ) measurements collected using a field spectroradiometer on the same day and time. A radiometric correction procedure, including conversions from digital numbers to radiance and from radiance to at‐satellite reflectance, is executed to make satellite data comparable to in situ measurements. This procedure show that simultaneous ground and satellite remote‐sensing data are highly correlated (0·84 > R² > 97) and the near‐infrared region (for this study TM4‐Landsat‐5 TM, band 4) is the best spectral range to distinguish salt and water on the satellite data for the multi‐temporal analysis of the water reserve in Salt Lake. It also shows that the use of shortwave infrared band(s) will result in confusion for the determination of the water reserve in this water‐covered study area. In a second and last phase, the water reserve change in the lake is examined using multi‐temporal Landsat imagery collected in 1990, 2001 and 2005. The remotely sensed, sampled and treated data show that the water reserve in the lake has decreased markedly between 1990 and 2005 due to drought and uncontrolled water usage. It is suggested that the use of water supplies around Salt Lake should be controlled and that the lake should regularly be monitored by up‐to‐date remote‐sensing data (at least annually) for better management of water resources. Copyright © 2007 John Wiley & Sons, Ltd.     

The scientific legacy of Harold Edwin Hurst (1880–1978)

ABSTRACT

Emanating from his remarkable characterization of long-term variability in geophysical records in the early 1950s, Hurst’s scientific legacy to hydrology and other disciplines is explored. A statistical explanation of the so-called “Hurst Phenomenon” did not emerge until 1968 when Mandelbrot and co-authors proposed fractional Gaussian noise based on the hypothesis of infinite memory. A vibrant hydrological literature ensued where alternative modelling representations were explored and debated, e.g. ARMA models, the Broken Line model, shifting mean models with no memory, FARIMA models, and Hurst-Kolmogorov dynamics, acknowledging a link with the work of Kolmogorov in 1940. The diffusion of Hurst’s work beyond hydrology is summarized by discipline and citations, showing that he arguably has the largest scientific footprint of any hydrologist in the last century. Its particular relevance to the modelling of long-term climatic variability in the era of climate change is discussed. Links to various long-term modes of variability in the climate system, driven by fluctuations in sea surface temperatures and ocean dynamics, are explored. Several issues related to the Hurst Phenomenon in hydrology remain as a challenge for future research.

Editor M. Acreman; Associate editor A. Carsteanu