Water Storage of the Central Amazon Floodplain Measured with GIS and Remote Sensing Imagery

Inferring floodplain bathymetry using inundation frequency

This study proposes a new method to retrieve the bathymetry of turbid-water floodplains from the inundation frequency (IF) data derived from over 32 years of composite optical remote sensing data. The new method was tested and validated over the Curuai floodplain in the lower Amazon River, where the entire bathymetry was surveyed in 2004, and water level gauge data has been available since 1960. The depth was estimated based on the relationship derived from IF and surveyed depth data, and the results were compared to those retrieved from bare-Earth DEM. We further assessed the sensitivity of the approach by analyzing the deepest part of the lake (i.e., permanent water body ~ 8m) with high IF, as well as the effect of gradual sedimentation in the lake over time. The results showed that the model is highly accurate and sensitive to IF changes even in the permanent water body areas, suggesting that this model can be used in other seasonal lakes worldwide with turbid-waters, where large-scale bathymetry surveys are not feasible due to high operation costs.

Remote Sensing of River Discharge: A Review and a Framing for the Discipline

Remote sensing of river discharge (RSQ) is a burgeoning field rife with innovation. This innovation has resulted in a highly non-cohesive subfield of hydrology advancing at a rapid pace, and as a result misconceptions, mis-citations, and confusion are apparent among authors, readers, editors, and reviewers. While the intellectually diverse subfield of RSQ practitioners can parse this confusion, the broader hydrology community views RSQ as a monolith and such confusion can be damaging. RSQ has not been comprehensively summarized over the past decade, and we believe that a summary of the recent literature has a potential to provide clarity to practitioners and general hydrologists alike. Therefore, we here summarize a broad swath of the literature, and find after our reading that the most appropriate way to summarize this literature is first by application area (into methods appropriate for gauged, semi-gauged, regionally gauged, politically ungauged, and totally ungauged basins) and next by methodology. We do not find categorizing by sensor useful, and everything from un-crewed aerial vehicles (UAVs) to satellites are considered here. Perhaps the most cogent theme to emerge from our reading is the need for context. All RSQ is employed in the service of furthering hydrologic understanding, and we argue that nearly all RSQ is useful in this pursuit provided it is properly contextualized. We argue that if authors place each new work into the correct application context, much confusion can be avoided, and we suggest a framework for such context here. Specifically, we define which RSQ techniques are and are not appropriate for ungauged basins, and further define what it means to be ‘ungauged’ in the context of RSQ. We also include political and economic realities of RSQ, as the objective of the field is sometimes to provide data purposefully cloistered by specific political decisions. This framing can enable RSQ to respond to hydrology at large with confidence and cohesion even in the face of methodological and application diversity evident within the literature. Finally, we embrace the intellectual diversity of RSQ and suggest the field is best served by a continuation of methodological proliferation rather than by a move toward orthodoxy and standardization.

Application of Remote Sensing Methods to Study the Relief of Lowland River Valleys with a Complex Geological Structure—A Case Study of the Bug River

River valleys of the Central European Lowlands are the zones of the highest dynamics of morphogenic processes. In the case of areas affected by glacial processes, despite their lowland nature, often they also have a complex geological structure. Sub-alluvial bedrock, composed of erosion-resistant deposits, commonly forms morphological protrusions within them. Their presence significantly affects both the course of flood flows and the valley floor relief. Effective forecasting of fluvial processes in such valley reaches requires conducting research within the entire geomorphologically active zone, both in the channel and the floodplain. The effectiveness of such research should be enhanced by simultaneous use of several different remote sensing methods, including short-range remote sensing. The verification of this hypothesis was the aim of the presented works. Such methods were used in the study of morphodynamics of a Bug valley reach. This area is characterized by a complex geological structure. High-resolution multispectral satellite images (VHRs) and a digital elevation model (DEM) based on aerial laser scanning (ALS) were used to examine the terrain relief. The morphology of the river channel itself was determined based on a series of bathymetric measurements made by a research team. Due to induced climate change and increasing maximum flow values, it can be assumed that the effect of a geological structure in the Central European Lowlands will play an increasing role. The threat and losses associated with floods will also increase. Rational flood prevention requires improvement of remote sensing research methods in lowland river valleys, especially those with complex geological structures. The valley reach presented in this article is an example of such a landform.

Long-Term Surface Water Dynamics Analysis Based on Landsat Imagery and the Google Earth Engine Platform: A Case Study in the Middle Yangtze River Basin

Dynamics of surface water is of great significance to understand the impacts of global changes and human activities on water resources. Remote sensing provides many advantages in monitoring surface water; however, in large scale, the efficiency of traditional remote sensing methods is extremely low because these methods consume a high amount of manpower, storage, and computing resources. In this paper, we propose a new method for quickly determining what the annual maximal and minimal surface water extent is. The maximal and minimal water extent in the year of 1990, 2000, 2010 and 2017 in the Middle Yangtze River Basin in China were calculated on the Google Earth Engine platform. This approach takes full advantage of the data and computing advantages of the Google Earth Engine’s cloud platform, processed 2343 scenes of Landsat images. Firstly, based on the estimated value of cloud cover for each pixel, the high cloud covered pixels were removed to eliminate the cloud interference and improve the calculation efficiency. Secondly, the annual greenest and wettest images were mosaiced based on vegetation index and surface water index, then the minimum and maximum surface water extents were obtained by the Random Forest Classification. Results showed that (1) the yearly minimal surface water extents were 14,751.23 km2, 14,403.48 km2, 13,601.48 km2, and 15,697.42 km2, in the year of 1990, 2000, 2010, and 2017, respectively. (2) The yearly maximal surface water extents were 18,174.76 km2, 20,671.83 km2, 19,097.73 km2, and 18,235.95 km2, in the year of 1990, 2000, 2010, and 2017, respectively. (3) The accuracies of surface water classification ranged from 86% to 93%. Additionally, the causes of these changes were analyzed. The accuracy evaluation and comparison with other research results show that this method is reliable, novel, and fast in terms of calculating the maximal and minimal surface water extent. In addition, the proposed method can easily be implemented in other regions worldwide.

Measuring water storage fluctuations in lake Dongting, China, by Topex/Poseidon satellite altimetry

Although satellite radar altimetry was developed and optimized for open oceans, it has been used to monitor variations in the level of inland water-bodies such as lakes and rivers. Here, for the first time, we have further used the altimetry-derived variation of water level for estimating the fluctuation of water storage as an addition to the present in situ water storage estimation systems to be used in remote areas and in emergency situation such as in the events flooding monitoring and for studying the effect of climate change. Lake Dongting, the second largest lake in China, influenced frequently by flooding, was, therefore, chosen to demonstrate the potential of the technique. By using the concept of an "assumed reference point", we converted Topex/Poseidon satellite altimetry data on water level variations in Lake Dongting to "water level" data. The "water level" time-series data and in situ water storage were used to establish a rating curve. From the rating curve, we converted data on "water level" derived from seven years (1993-1999) of Topex/Poseidon data to actual water storage in Lake Dongting. The result reveals that the seasonal and annual fluctuations of water storage occurred during the 1990s with a more frequent flooding at the late 1990s' especially the flooding in whole catchment level in 1998 and 1999. The study supports the usefulness of satellite altimetry for dense and continuous monitoring of the temporal variations in water dynamic in moderate to large lakes.