Hahn Chul Jung

Characterization of surface water storage changes in Arctic lakes using simulated SWOT measurements

The planned Surface Water and Ocean Topography (SWOT) satellite mission will measure freshwater storage changes in global lakes. Herein, the anticipated SWOT storage change accuracy is evaluated for the lakes in the Peace-Athabasca Delta, Northern Alaska and Western Siberia. Because of the significant lack of Arctic lake measurements, we simulated realistic daily to seasonal changes in water elevations in the study region using a combination of data from lake gauges, satellite radar altimeter, and satellite imagery. This ‘truth’ dataset is sampled with several candidate SWOT orbits and then corrupted with expected instrument errors to simulate SWOT observed storage changes. The number of revisits increases with increasing or decreasing latitude for a given repeat cycle (e.g. four to eight revisits for a 22-day cycle), allowing us to investigate storage change errors at monthly sampling. SWOT storage change accuracy is primarily controlled by lake size. Lakes larger than 1 km2 have relative errors generally less than 5% whereas one-hectare size lakes are about 20%. We concluded that the storage change accuracy is insensitive to the orbital inclination or repeat periods, but is sensitive to lake shapes.

Repeat-pass multi-temporal interferometric SAR coherence variations with Amazon floodplain and lake habitats

We have analysed interferometric coherence variations in Japanese Earth Resources Satellite (JERS-1) L-band synthetic aperture radar (SAR) data at three central Amazon sites: Lake Balbina, Cabaliana and Solimões-Purús. Because radar pulse interactions with inundated vegetation typically follow a double-bounce travel path that returns energy to the antenna, coherence will vary with vegetation type as well as with physical and temporal baselines. Lake Balbina consists mostly of upland forests and inundated trunks of dead, leafless trees whereas Cabaliana and Solimões-Purús are dominated by flooded forests. Balbina has higher coherence values than either Cabaliana or Solimões-Purús probably because the dead, leafless trees support strong double-bounce returns. The mean coherences of flooded woodland are 0.28 in Balbina and 0.11 in both Cabaliana and Solimões-Purús. With increasing temporal baselines, flooded and nonflooded wetland habitats show a steadily decreasing trend in coherence values whereas terra-firme and especially open-water habitats have little variation and remain lower in value. Flooded and nonflooded wetland coherence varies with the season whereas terra-firme and open water do not have similarly evident seasonal variations. For example, flooded habitats in all three study regions show annual peaks in coherence values that are typically 0.02 greater than coherence values from temporal baselines 180 days later, yet open water shows no variation with time. Our findings suggest that, despite overall low coherence values, repeat-pass interferometric coherence of flooded habitats is capable of showing the annual periodicity of the Amazon flood wave.

Toward Estimating Wetland Water Level Changes Based on Hydrological Sensitivity Analysis of PALSAR Backscattering Coefficients over Different Vegetation Fields

Synthetic Aperture Radar (SAR) has been successfully used to map wetland’s inundation extents and types of vegetation based on the fact that the SAR backscatter signal from the wetland is mainly controlled by the wetland vegetation type and water level changes. This study describes the relation between L-band PALSAR and seasonal water level changes obtained from Envisat altimetry over the island of Ile Mbamou in the Congo Basin where two distinctly different vegetation types are found. We found positive correlations between and water level changes over the forested southern Ile Mbamou whereas both positive and negative correlations were observed over the non-forested northern Ile Mbamou depending on the amount of water level increase. Based on the analysis of sensitivity, we found that denser vegetation canopy leads to less sensitive variation with respect to the water level changes regardless of forested or non-forested canopy. Furthermore, we attempted to estimate water level changes which were then compared with the Envisat altimetry and InSAR results. Our results demonstrated a potential to generate two-dimensional maps of water level changes over the wetlands, and thus may have substantial synergy with the planned Surface Water and Ocean Topography (SWOT) mission.

A Phase-Decomposition-Based PSInSAR Processing Method

A phase-decomposition-based persistent scatterer (PS) InSAR (PD-PSInSAR) method is developed in this paper to improve coherence and spatial density of measurement points (MPs). In order to improve PS network density, a distributed scatterer (DS) has been utilized in some advanced PSInSAR process, such as SqueeSAR. In addition to the conventional DS that consists of independent small scatterers with a uniform scattering mechanism, processing the DSs dominated by two or more scattering mechanisms is a promising way to improve MP density. Estimating phases from DS with multiple scattering mechanisms is difficult for many DS algorithms because of the interference between different scattering mechanisms. Recently, a covariance-matrix-decomposition-based method, which is named Component extrAction and sElection SAR (CAESAR), is proposed to extract different scattering components from the analysis of the covariance matrix. Instead of using a covariance matrix, the PD-PSInSAR in this study is developed to perform eigendecomposition on a coherence matrix, in order to estimate the phases corresponding to the different scattering mechanisms, and then to implement these estimated phases in a conventional PSInSAR process. The major benefit of using a coherence matrix rather than a covariance matrix is to compensate the amplitude unbalances among SAR images. A detailed study of comparison among SqueeSAR, CAESAR, and PD-PSInSAR is also performed in this study. It has been found that these three methods share very similar mathematic forms with different weight values. The PD-PSInSAR method is implemented to estimate land deformation over the greater Houston area using Envisat ASAR images, which verifies that the proposed method can detect more MPs and provide better coherences.

Sensitivity of a Floodplain Hydrodynamic Model to Satellite-Based DEM Scale and Accuracy: Case Study—The Atchafalaya Basin

The hydrodynamics of low-lying riverine floodplains and wetlands play a critical role in hydrology and ecosystem processes. Because small topographic features affect floodplain storage and flow velocity, a hydrodynamic model setup of these regions imposes more stringent requirements on the input Digital Elevation Model (DEM) compared to upland regions with comparatively high slopes. This current study provides a systematic approach to evaluate the required relative vertical accuracy and spatial resolution of current and future satellite-based altimeters within the context of DEM requirements for 2-D floodplain hydrodynamic models. A case study is presented for the Atchafalaya Basin with a model domain of 1190 km2. The approach analyzes the sensitivity of modeled floodplain water elevation and velocity to typical satellite-based DEM grid-box scale and vertical error, using a previously calibrated version of the physically-based flood inundation model (LISFLOOD-ACC). Results indicate a trade-off relationship between DEM relative vertical error and grid-box size. Higher resolution models are the most sensitive to vertical accuracy, but the impact diminishes at coarser resolutions because of spatial averaging. The results provide guidance to engineers and scientists when defining the observation scales of future altimetry missions such as the Surface Water and Ocean Topography (SWOT) mission from the perspective of numerical modeling requirements for large floodplains of O[103] km2 and greater.

Understanding the impact of droughts in the Yarmouk Basin, Jordan: monitoring droughts through meteorological and hydrological drought indices

This article assesses drought status in the Yarmouk Basin (YB), in northern Jordan, using the Standardized Precipitation Index (SPI), the Standardized Water-Level Index (SWI), and the Percent Departure from Normal rainfall (PDNimd) during the years 1993–2014. The results showed that the YB suffers from frequent and irregular periods of drought as variations in drought intensity and frequency have been observed. The SPI results revealed that the highest drought magnitude of − 2.34 appeared at Nuaimeh rainfall station in 1991. This station has also experienced severe drought particularly in years 1995, 1999, 2005, and 2012 with SPI values ranging from − 1.51 to − 1.59. Some other rainfall stations such as Baqura, Ibbin, Khanasiri, Kharja, Mafraq police, Ramtha, Turra, and Umm Qais have also suffered several periods of drought mostly in 1993. The SWI results show the highest extreme drought events in 2001 in Souf well while other extreme drought periods were observed at Wadi Elyabis well in 1994 and at Mafraq well in 1995. As compared to SPI maps, our SWI maps reflect severe and extreme drought events in most years, negatively impacting the groundwater levels in the study area.

Congo Floodplain Hydraulics using PALSAR InSAR and Envisat Altimetry Data

Wetlands of lowland rivers and lakes are massive in size and in volumetric fluxes, which greatly limits a thorough understanding of their flow dynamics. The complexity of floodwater flows has not well been captured because floodwater moves laterally across wetlands and its movement is not bounded like that of typical channel flow. Water flow across wetlands is more complex than implied by one-dimensional, point-based measurements. Interferometric Synthetic Aperture Radar (InSAR) has been proven to be an effective tool to map wetland’s relative water level changes \( \left(\partial h/\partial t\right) \) with high spatial resolution and accuracy. In this study, we integrated relative \( \partial h/\partial t \) from ALOS PALSAR interferograms and Envisat altimetry data to estimate absolute \( \partial h/\partial t \) in the Congo floodplain near Lisala in Democratic Republic of the Congo. Three fringe patterns from PALSAR interferograms were identified due to spatiotemporal water level changes in the floodplain. We observed (1) dense fringes parallel to the Congo mainstem in high water season, (2) broad fringes across the floodplain, (3) and fringes around the floodplain boundary in low water season. The absolute water level change maps generated by integrating InSAR and Envisat altimetry data suggest that \( \partial h/\partial t \) can reach up to 1.2 m in the proximal floodplain in high water level season. During low water season, \( \partial h/\partial t \) can reach up to several decimeters. Based on the maps of absolute \( \partial h/\partial t \) and the principle of mass continuity, analysis of temporal hydraulic variations is also presented. Our hydraulic analysis suggests that \( \partial h/\partial t \) is subtle and the water flow in the floodplain is not well confined during low water season. On the other hand, the proximal floodplain has greater \( \partial h/\partial t \) than the distal floodplain during high water season, which suggests that water mostly flows from floodplain to river.

The NASA Global Flood Mapping System

Significant flooding is a common occurrence in many parts of the globe, and remote sensing from satellite platforms can provide near real-time information for response during flooding disasters. This same information is also valuable for flood mitigation, preparedness, and recovery including large-scale infrastructure planning, settling insurance claims following flood disasters, and planning community rebuilding. Here we review the basic considerations of mapping surface water and flood extent using remote sensing and describe the NASA Near Real Time Global Flood Mapping System, a fully automated, near real-time system designed to produce such products for nearly the entire globe each day. The NASA system, a collaboration between NASA and the Dartmouth Flood Observatory, processes data from the MODerate resolution Imaging Spectro-radiometer (MODIS) instruments on the NASA Aqua and Terra satellites to produce a range of products for use by both the disaster management community and the scientific research community.

Mathematical Framework for Phase-Triangulation Algorithms in Distributed-Scatterer Interferometry

To improve the spatial density of measurement points of persistent-scatterer interferometry, distributed scatterer (DS) should be considered and processed. An important procedure in DS interferometry is the phase triangulation (PT). This letter introduces two modified PT algorithms (i.e., equal-weighted PT and coherence-weighted PT) and analyzes the mathematical relations between different published PT methods (i.e., the maximum-likelihood phase estimator, least squares estimator, and eigendecomposition-based phase estimators). The analysis shows that the above five PT methods share very similar mathematical forms with different weight values in the estimation procedure.

Estimation of Water Level Changes of Large-Scale Amazon Wetlands Using ALOS2 ScanSAR Differential Interferometry

Differential synthetic aperture radar (SAR) interferometry (DInSAR) has been successfully used to estimate water level changes (∂h/∂t) over wetlands and floodplains. Specifically, amongst ALOS PALSAR datasets, the fine-beam stripmap mode has been mostly implemented to estimate ∂h/∂t due to its availability of multitemporal images. However, the fine-beam observation mode provides limited swath coverage to study large floodplains and wetlands, such as the Amazon floodplains. Therefore, for the first time, this paper demonstrates that ALOS2 ScanSAR data can be used to estimate the large-scale ∂h/∂t in Amazon floodplains. The basic procedures and challenges of DInSAR processing with ALOS2 ScanSAR data are addressed and final ∂h/∂t maps are generated based on the Satellite with ARgos and ALtiKa (SARAL) altimetry’s reference data. This study reveals that the local ∂h/∂t patterns of Amazon floodplains are spatially complex with highly interconnected floodplain channels, but the large-scale (with 350 km swath) ∂h/∂t patterns are simply characterized by river water flow directions.