Soil moisture is widely recognized as a key parameter in the mass and energy balance between the land surface and the atmosphere and, hence, the potential societal benefits of an accurate estimation ...of soil moisture are immense. Recently, scientific community is making great effort for addressing the estimation of soil moisture over large areas through in situ sensors, remote sensing and modelling approaches. The different techniques used for addressing the monitoring of soil moisture for hydrological applications are briefly reviewed here. Moreover, some examples in which in situ and satellite soil moisture data are successfully employed for improving hydrological monitoring and predictions (e.g., floods, landslides, precipitation and irrigation) are presented. Finally, the emerging applications, the open issues and the future opportunities given by the increased availability of soil moisture measurements are outlined.
Data assimilation (DA) of satellite soil moisture (SM) observations represents a great opportunity for improving the ability of rainfall-runoff models in predicting river discharges. Many studies ...have been carried out so far demonstrating the possibility to reduce model prediction uncertainty by incorporating satellite SM observations. However, large discrepancies can be perceived between these studies with the result that successful DA is not only related to the quality of the satellite observations but can be significantly controlled by many methodological and morphoclimatic factors. In this article, through an experimental study carried out on the Tiber River basin in Central Italy, we explore how the catchment area, soil type, climatology, rescaling technique, observation and model error selection may affect the results of the assimilation and can be the causes of the apparent discrepancies obtained in the literature. The results show that: (i) DA of SM generally improves discharge predictions (with a mean efficiency of about 30%); (ii) unlike catchment area, the soil type and the catchment specific characteristics might have a remarkable influence on the results; (iii) simple rescaling techniques may perform equally well to more complex ones; (iv) an accurate quantification of the model error is paramount for a correct choice of the observation error and, (v) SM temporal variability has a stronger influence than the season itself. On this basis, we advise that DA of SM may be not a simple task and one should carefully test the optimality of the assimilation experiment prior to drawing any general conclusions.
A methodology to estimate the discharge along rivers, even poorly gauged ones, taking advantage of water level measurements derived from satellite altimetry is proposed. The procedure is based on the ...application of the Rating Curve Model (RCM), a simple method allowing for the estimation of the flow conditions in a river section using only water levels recorded at that site and the discharges observed at another upstream section. The European Remote-Sensing Satellite 2, ERS-2, and the Environmental Satellite, ENVISAT, altimetry data are used to provide time series of water levels needed for the application of RCM. In order to evaluate the usefulness of the approach, the results are compared with the ones obtained by applying an empirical formula that allows discharge estimation from remotely sensed hydraulic information. To test the proposed procedure, the 236 km-reach of the Po River is investigated, for which five in situ stations and four satellite tracks are available. Results show that RCM is able to appropriately represent the discharge, and its performance is better than the empirical formula, although this latter does not require upstream hydrometric data. Given its simple formal structure, the proposed approach can be conveniently utilized in ungauged sites where only the survey of the cross-section is needed.
The NASA Surface Water Ocean Topography (SWOT) mission and ESA Sentinel‐1, inter‐alia, propose to monitor inland waters from satellites. The radar altimeter and the microwave radiometer can be used ...to monitor water surface level and assess the cross‐sectional mean flow velocity, respectively. However, for most river sites bathymetric data are lacking, preventing the direct computation of discharge. In this context, a new methodology for simulating the bathymetry and estimating the discharge is proposed. The approach is based on entropy theory and can be applied using ground and satellite observations. Four parameters are needed and include channel roughness, water surface slope, channel bottom elevation, and an entropy parameter of flow depth. These parameters are estimated using a genetic algorithm by minimizing the error in the observed maximum surface velocity. Parameter uncertainty is considered through 1,000 random realizations based on different initial values. Eighteen streamflow measurements recorded from three different gauged river sites are used to benchmark the ground observations. The method included ENVISAT altimetry and Moderate Resolution Imaging Spectroradiometer (MODIS) data (2002‐2010) at one river site. Relative to ground measurements, the method provides good results with an error in channel area and discharge that, on average, does not exceed 10% on the 50th percentile. Relative to satellite measurements, channel area is well simulated with an error, on average, lower than 9%; discharge is less well simulated and represented by an error greater than 30% on the 50th percentile.
Key Points
The paper brings together important hydraulic and remote sensing information that combine to build a methodology to be applied to any river
The paper can lay the groundwork for numerous remote sensing applications to estimating bathymetry, flow velocity, and discharge in rivers
A new perspective for noncontact streamflow measurements during high floods is addressed also at ungauged river sites
To promote the advancement of novel observation techniques that may lead to new sources of information to help better understand the hydrological cycle, the International Association of Hydrological ...Sciences (IAHS) established the Measurements and Observations in the XXI century (MOXXI) Working Group in July 2013. The group comprises a growing community of tech-enthusiastic hydrologists that design and develop their own sensing systems, adopt a multi-disciplinary perspective in tackling complex observations, often use low-cost equipment intended for other applications to build innovative sensors, or perform opportunistic measurements. This paper states the objectives of the group and reviews major advances carried out by MOXXI members toward the advancement of hydrological sciences. Challenges and opportunities are outlined to provide strategic guidance for advancement of measurement, and thus discovery.
This Special Issue is a collection of papers that focus on the use of remote sensing data and describe methods for flood monitoring and mapping. These articles span a wide range of topics; present ...novel processing techniques and review methods; and discuss limitations and challenges. This preface provides a brief overview of the content.
Flow duration curve (FDC) is a cumulative frequency curve that shows the percent of time a specific discharge has been equaled or exceeded during a particular period of time at a given river ...location, providing a comprehensive description of the hydrological regime of a catchment. Thus, relying on historical streamflow records, FDCs are typically constrained to gauged and updated ground stations. Earth Observations can support our monitoring capability and be considered as a valuable and additional source for the observation of the Earth’s physical parameters. Here, we investigated the potential of the surface reflectance in the Near Infrared (NIR) band of the MODIS 500 m and eight-day product, in providing reliable FDCs along the Mississippi River. Results highlight the capability of NIR bands to estimate the FDCs, enabling a realistic reconstruction of the flow regimes at different locations. Apart from a few exceptions, the relative Root Mean Square Error, rRMSE, of the discharge value in validation period ranges from 27–58% with higher error experienced for extremely high flows (low duration), mainly due to the limit of the sensor to penetrate the clouds during the flood events. Due to the spatial resolution of the satellite product higher errors are found at the stations where the river is narrow. In general, good performances are obtained for medium flows, encouraging the use of the satellite for the water resources management at ungauged river sites.
Irrigation represents one of the most impactful human interventions in the terrestrial water cycle. Knowing the distribution and extent of irrigated areas as well as the amount of water used for ...irrigation plays a central role in modeling irrigation water requirements and quantifying the impact of irrigation on regional climate, river discharge, and groundwater depletion. Obtaining high-quality global information about irrigation is challenging, especially in terms of quantification of the water actually used for irrigation. Here, we review existing Earth observation datasets, models, and algorithms used for irrigation mapping and quantification from the field to the global scale. The current observation capacities are confronted with the results of a survey on user requirements on satellite-observed irrigation for agricultural water resources’ management. Based on this information, we identify current shortcomings of irrigation monitoring capabilities from space and phrase guidelines for potential future satellite missions and observation strategies.
This study investigates the capability of the Moderate resolution Imaging Spectroradiometer (MODIS) to estimate river discharge, even for ungauged sites. Because of its frequent revisits (as little ...as every 3h) and adequate spatial resolution (250m), MODIS bands 1 and 2 have significant potential for mapping the extent of flooded areas and estimating river discharge even for medium-sized basins. Specifically, the different behaviour of water and land in the Near Infrared (NIR) portion of the electromagnetic spectrum is exploited by computing the ratio (C/M) of the MODIS channel 2 reflectance values between two pixels located within (M) and outside (C), but close to, the river. The values of C/M increase with the presence of water and, hence, with discharge. Moreover, in order to reduce the noise effects due to atmospheric contribution, an exponential smoothing filter is applied, thus obtaining C/M⁎.
Time series of hourly mean flow velocity and discharge between 2005 and 2011 measured at four gauging stations located along the Po river (Northern Italy) are employed for testing the capability of C/M⁎ to estimate discharge/flow velocity. Specifically, the meanders and urban areas are considered the best locations for the position of the pixels M and C, respectively. Considering the optimal pixels, the agreement between C/M⁎ and discharge/flow velocity is fairly good with values in the range of 0.65–0.77. Additionally, the application to ungauged sites is tested by deriving a unique regional relationship between C/M⁎ and flow velocity valid for the whole Po river and providing only a slight deterioration of the performance. Finally, the sensitivity of the results to the selection of the C and M pixels is investigated by randomly changing their location. Also in this case, the agreement with in situ observations of velocity is fairly satisfactory (r~0.6). The obtained results demonstrate the capability of MODIS to monitor discharge (and flow velocity). Therefore, its application for a larger number of sites worldwide will be the object of future studies.
•The capability of MODIS to estimate river discharge is investigated.•The procedure has been applied to four gauged stations of the Po River basin.•MODIS-derived and in situ discharge/velocity time series are in fairly good agreement.•The estimation of discharge for ungauged sites is also addressed.
The monitoring of rivers by satellite is an up-to-date subject in hydrological studies as confirmed by the interest of space agencies to finance specific missions that respond to the quantification ...of surface water flows. We address the problem by using multi-spectral sensors, in the near-infrared (NIR) band, correlating the reflectance ratio between a dry and a wet pixel extracted from a time series of images, the C/M ratio, with five river flow-related variables: water level, river discharge, flow area, mean flow velocity and surface width. The innovative aspect of this study is the use of the Ocean and Land Colour Instrument (OLCI) on board Sentinel-3 satellites, compared to the Moderate Resolution Imaging Spectroradiometer (MODIS) used in previous studies. Our results show that the C/M ratio from OLCI and MODIS is more correlated with the mean flow velocity than with other variables. To improve the number of observations, OLCI and MODIS products are combined into multi-mission time series. The integration provides good quality data at around daily resolution, appropriate for the analysis of the Po River investigated in this study. Finally, the combination of only MODIS products outperforms the other configurations with a frequency slightly lower (~1.8 days).
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