Global Inland Water Research Articles

Global inland water greenhouse gas (GHG) geographical patterns and escape mechanisms under different water level

Global inland water greenhouse gas (GHG) geographical patterns and escape mechanisms under different water level

Metabolic processes drive spatio-temporal variations of carbon sink/source in a karst river

Riverine carbon dioxide (CO2) exchange is a crucial component of the global carbon cycle. However, the changes in the CO2 sink/source in karst rivers caused by differences in lithological features and climate, hindered the resolution of the spatio-temporal heterogeneity of global inland water carbon emissions. Here, we use hydrochemical data and CO2 gas isotopic data to reveal the spatio-temporal variations of CO2 sink/source in karst rivers and their controlling mechanisms. Fifty-two monitoring transects were set up in the subtropical Lijiang River in southwest China in June and December 2019. Our results indicated that the CO2 flux across the water-air interface (FCO2) in the Lijiang River basin ranged from −43.77 to 519.67 mmol/(m2·d). In June, the Lijiang River acted as an atmospheric carbon source due to higher water temperatures (Twater). However, driven by hydrodynamic conditions and the metabolism of aquatic photosynthesis, the river shifts from being an atmospheric carbon source in June to an atmospheric carbon sink in December. The stable isotopes of CO2 (δ13C-CO2) show significant differences in the spatio-temporal variations of CO2 sink/source. In December, the transects of the Lijiang River basin with a negative CO2 flux are significantly negatively correlated with dissolved oxygen (DO) and chlorophyll-a (Chl-a) concentration (p < 0.05). This confirms that the enhancement of aquatic photosynthesis efficiency increased water DO concentrations, which resulted in the positive movement of water δ13C-CO2 and a decrease in the partial pressure of CO2 (pCO2) and FCO2. Comparative analysis with global river FCO2 indicates that under the combined driving forces of metabolic processes of aquatic photosynthetic organisms and hydrodynamic conditions, rivers tend to act more frequently as CO2 sinks, particularly in subtropical and temperate rivers. In conclusion, this study represents a new example focusing on CO2 dynamics to address the spatio-temporal heterogeneity of carbon emissions in inland waters on a global scale.

Exploring the topographical pattern beneath the water surface: Global bathymetric volume-area-height curves (BVAH) of inland surface water bodies

Global inland surface water bodies such as lakes and reservoirs, important components of the hydrosphere and ecosphere, are increasingly affected by climate change. Generating bathymetric volume-area-height (BVAH) curves for global inland surface water bodies can enhance our understanding of their topography and climate impacts. However, accurately quantifying the topographic patterns of these water bodies remains challenging due to the difficulties in collecting comprehensive bathymetric data. Therefore, we collected and processed over 2000 bathymetric maps of global water bodies from over 50 different data sources and then developed the BVAH model. Finally, the BVAH hydrological curves of 16671 global inland surface water bodies (larger than 10 km2) were generated. The results include but are not limited to (1) For most targeted water bodies, area (A) and volume (V) exhibit significant power function relationships with surface heights (H), with optimal power values quantified as 1.42 for A and 2.42 for V. (2) The BVAH model outperforms GLOBathy in estimating area and volume changes, achieving higher correlation coefficients (CC) of approximately 0.962 for the area and 0.991 for volume, and demonstrating lower percentages of root mean squared errors (PRMSE) around 10.9% for the area and 4.8% for volume. (3) In the case study of the Tibetan Plateau and various large global reservoirs, the BVAH curve database can capture dynamic volume changes. As a unified simulation of the bathymetric topographical patterns, our bathymetric dataset and corresponding BVAH curve database have great potential to contribute to effective water resource management and ecological conservation efforts worldwide.

Stage‐Slope‐Discharge Relationships Upstream of River Confluences Revealed by Satellite Altimetry

AbstractWith increasing coverage, density, and accuracy of the global inland water altimetry record, remote sensing observations of water surface elevation (WSE) and water surface slope (WSS) are becoming available for the world's rivers. In steady, uniform flows, WSS is invariable, while there is a unique one‐to‐one relationship between WSE and discharge, the rating curve. While the assumptions of steady uniform flow are appropriate for many rivers, they are violated upstream of river confluences. We present a simple analytical hydraulic model of river confluences using the theory of steady, gradually varied flow. We apply the model to four river confluences in the Mississippi‐Missouri river system. We determine the spatial extent of the backwater‐affected zones and map WSE‐discharge and WSS‐discharge relationships. We show that coincident measurements of WSE and WSS from new satellite altimetry missions effectively constrain discharge estimates from space in the backwater‐affected zones upstream of river confluences.

Increased Terrestrial Carbon Export and CO2 Evasion From Global Inland Waters Since the Preindustrial Era

AbstractGlobal carbon dioxide (CO2) evasion from inland waters (rivers, lakes, and reservoirs) and carbon (C) export from land to oceans constitute critical terms in the global C budget. However, the magnitudes, spatiotemporal patterns, and underlying mechanisms of these fluxes are poorly constrained. Here, we used a coupled terrestrial–aquatic model to assess how multiple changes in climate, land use, atmospheric CO2 concentration, nitrogen (N) deposition, N fertilizer and manure applications have affected global CO2 evasion and riverine C export along the terrestrial‐aquatic continuum. We estimate that terrestrial C loadings, riverine C export, and CO2 evasion in the preindustrial period (1800s) were 1,820 ± 507 (mean ± standard deviation), 765 ± 132, and 841 ± 190 Tg C yr−1, respectively. During 1800–2019, multifactorial global changes caused an increase of 25% (461 Tg C yr−1) in terrestrial C loadings, reaching 2,281 Tg C yr−1 in the 2010s, with 23% (104 Tg C yr−1) of this increase exported to the ocean and 59% (273 Tg C yr−1) being emitted to the atmosphere. Our results showed that global inland water recycles and exports nearly half of the net land C sink into the atmosphere and oceans, highlighting the important role of inland waters in the global C balance, an amount that should be taken into account in future C budgets. Our analysis supports the view that a major feature of the global C cycle–the transfer from land to ocean–has undergone a dramatic change over the last two centuries as a result of human activities.

A dataset of carbon and water flux observed in aquaculture ponds in Quanjiao, Anhui Province from 2016 to 2020

Aquaculture ponds are inland small water bodies subject to human activities. They are not only carbon sources, but important sources of regional water evaporation. Accurate observation of carbon and water fluxes in aquaculture ponds is the basis for quantifying carbon emission and evaporation contribution of inland water. Nanjing University of Information Science and Technology set up an atmospheric environment experiment site to observe the carbon and water flux over aquaculture water bodies in Guandu Village of Quanjiao County, Anhui Province. This dataset includes the CO2 flux data (measured by the multi-channel closed dynamic floating chamber method), CH4 flux data (measured by the eddy covariance method, multi-channel closed dynamic floating chamber method, and inverted funnel method), latent heat and sensible heat fluxes data (measured by the eddy covariance method), as well as key environmental factors data, such as air temperature, water temperature, and radiation. All data were processed by standardized procedures. Moreover, data quality controls were performed. This dataset can provide important data for accurately estimating carbon emission and evaporation contribution in regional and global inland small water bodies.

Retrieving time series of river water extent from global inland water data sets

The accurate monitoring of the surface water storage as an essential component of the global water cycle requires a realistic representation of river networks and channel characteristics. Since such a representation has not been available for many rivers and is becoming less available even for many gauged rivers, crucial questions about the spatio-temporal dynamics of freshwater in river networks cannot be answered properly.The global coverage and fine temporal resolution of satellite imagery provide the opportunity to obtain time series of surface water extent at the global scale for almost all rivers. However, despite recent advances in satellite imaging sensors, water extraction algorithms, and big data processing capabilities, none of the available global water extent data sets can meet the necessary requirements in terms of accuracy and spatio-temporal resolutions. Due to the inherent complexity of monitoring the river surface extent, efforts have been limited to the development of global river extent data sets with a limited number of temporal layers usually obtained from long-term averaged satellite imagery.In this study, we propose a region-based image restoration algorithm to obtain the river surface extent from a pre-existing global inland water data set by incorporating temporal and spatial constraints between pixel labels. We employ our algorithm on the Monthly Water History maps of the Global Surface Water data set (Pekel et al., 2016). We validate the proposed method on 98 river reaches that their average width ranges from approximately 36m to 3400m with in situ discharge measurements in the Mississippi, Amazon, Niger and Po river basins. The obtained river width time series exhibit a strong monotonic relationship with discharge measurements as the Spearman correlation coefficients are predominantly larger than 0.70 (on average 0.74 for Mississippi, 0.84 for Amazon, 0.86 for Niger and 0.77 for Po rivers). Such a performance confirms that the proposed method can facilitate the acquisition of a global dynamic river extent data set, which plays a key role in better understanding the distribution and availability of freshwater across continents.

Climate and landscape changes enhance the global spread of a bloom-forming dinoflagellate related to fish kills and water quality deterioration

Global inland water biodiversity is under mounting stress facing future scenarios of climate change, biological invasions, pollution, diversion, damming of rivers, and increase of water abstractions. Apart from having isolated effects, all these stressors threats act synergistically and thus pose additional emerging threats to biodiversity and ecosystem services. Native to Northern Europe, the nuisance and potential toxic dinoflagellate Ceratium furcoides (Levander) Langhans 1925 is a silent invader that blooms in freshwater systems; it has one of the most rapid spread rates globally. We propose a framework to determine the worldwide most vulnerable areas for the invasion by C. furcoides shortly (2041–2060) by combining future scenarios of climate change (a proxy for invasiveness) derived from ecological niche models with future dam construction data (a proxy for invasibility). The nine models applied in four future scenarios of greenhouse gas emission from Coupled Model Intercomparison Project Phase 6 showed a general increase in areas suitable for the invasion success of C. furcoides. High susceptibility overlapped with areas densely occupied by large and medium-size dams and future dam construction projects. Considering that C. furcoides can reproduce from a single cell, produces resistant stages, and has several strategies to cope with local environmental constraints, early detection protocols, and mitigation actions are urgently needed to avoid biodiversity declines related to this invader.

Determining Temporal Uncertainty of a Global Inland Surface Water Time Series

Earth observation time series are well suited to monitor global surface dynamics. However, data products that are aimed at assessing large-area dynamics with a high temporal resolution often face various error sources (e.g., retrieval errors, sampling errors) in their acquisition chain. Addressing uncertainties in a spatiotemporal consistent manner is challenging, as extensive high-quality validation data is typically scarce. Here we propose a new method that utilizes time series inherent information to assess the temporal interpolation uncertainty of time series datasets. For this, we utilized data from the DLR-DFD Global WaterPack (GWP), which provides daily information on global inland surface water. As the time series is primarily based on optical MODIS (Moderate Resolution Imaging Spectroradiometer) images, the requirement of data gap interpolation due to clouds constitutes the main uncertainty source of the product. With a focus on different temporal and spatial characteristics of surface water dynamics, seven auxiliary layers were derived. Each layer provides probability and reliability estimates regarding water observations at pixel-level. This enables the quantification of uncertainty corresponding to the full spatiotemporal range of the product. Furthermore, the ability of temporal layers to approximate unknown pixel states was evaluated for stratified artificial gaps, which were introduced into the original time series of four climatologic diverse test regions. Results show that uncertainty is quantified accurately (&gt;90%), consequently enhancing the product’s quality with respect to its use for modeling and the geoscientific community.

Mapping and sampling to characterize global inland water dynamics from 1999 to 2018 with full Landsat time-series

Global surface water extent is changing due to natural processes as well as anthropogenic drivers such as reservoir construction and conversion of wetlands to agriculture. However, the extent and change of global inland surface water are not well quantified. To address this, we classified land and water in all 3.4 million Landsat 5, 7, and 8 scenes from 1999 to 2018 and performed a time-series analysis to produce maps that characterize inter-annual and intra-annual open surface water dynamics. We also used a probability sample and reference time-series classification of land and water for 1999–2018 to provide unbiased estimators of area of stable and dynamic surface water extent and to assess the accuracy of the surface water maps. From the reference sample data, we estimate that permanent surface water covers 2.93 (standard error ±0.09) million km2, and during this time period an estimated 138,011 (±28,163) km2 underwent only gain of surface water, over double the estimated 53,154 (±10,883) km2 that underwent only loss of surface water. The estimated area of 950,719 (±104,034) km2 that experienced recurring change between land and water states is far greater than the area undergoing these unidirectional trends. From a probability sample of high resolution imagery, an estimated 10.9% (±1.9%) of global inland surface water is within mixed pixels at Landsat resolution indicating that monitoring of surface water changes requires improved spatial detail. We provide the first unbiased area estimators of open surface water extent and its changes with associated uncertainties and illustrate the challenges of tracking changes in surface water area using medium spatial and temporal resolution data.

Intermittent inland waters as important carbon sources

A large part of the world’s inland waters, including streams, rivers, ponds, lakes, and reservoirs is subject to occasional, seasonal, or even permanent drying. Moreover, the intermittent inland waters are increasing in many areas of the world because of climate change, anthropogenic influence, and land-use change. However, information on the carbon dioxide (CO2) fluxes from intermittent inland waters is scarce. Thus, a comprehensive assessment of CO2 emissions in intermittent inland waters is necessary and is a research gap in China. Here, we review the current knowledge on CO2 fluxes from lotic (streams and rivers) and lentic (ponds, lakes, and reservoirs) inland waters during dry and rewetting phases, considering controls and sources as well as implications of the two phases for local and global scale estimates. In exposed sediments of dry riverbeds, it can be a long time between wet and dry conditions. At the onset of drying, the increased oxygen availability can stimulate enzymatic activities and overall microbial growth, leading to an increased breakdown of organic matter and the subsequent release of CO2. As in any ecosystem, carbon emissions derive from a set of abiotic and biotic sources, the relative importance of which is tied to intrinsic features, such as geology, microbial communities and available organic substrates, and environmental controls, such as moisture and nutrient availability. Besides microbial respiration, geologic carbon can be a relevant source of CO2 emissions. Particularly in carbonate-rich regions, photodegradation of organic matter on dry light-exposed sediments can also lead to increased CO2 losses. In addition, covered vegetation metabolism, including photosynthesis and respiration, can be a relevant part of dry riverbed sediment CO2 emissions. Short rewetting episodes can trigger microbial respiration and CO2 release from the exposed sediments, and marked increases in the CO2 flux from dry sediments are to be expected during rewetting after a dry period, similar to soils, and it is known as the Birch effect. Immediately after rewetting, gases in pore spaces are displaced by water, potentially causing a significant efflux of CO2, impacting the overall annual CO2 flux. Rewetting events can also cause the remobilization of organic matter and nutrients. At the micro-scale, pore-filling will increase the dissemination of water-soluble substrates and mobilize labile substances from dead biomass. Aggregate disruption and the destabilization of organic-mineral complexes will also liberate carbon otherwise protected from microbial action. Other major drivers of CO2 fluxes from dry riverbeds include the presence or absence of vegetation or micro-phyto benthos in the exposed sediments, sediment texture, sediment temperature, and sediment organic matter. The organic matter quantity may be more important than the quality in controlling the magnitude of CO2 fluxes from the exposed sediments. Our conservative estimates indicate that adding emissions from intermittent inland waters to current global estimates of CO2 emissions from inland waters could result in an increase of 0.51 Pg C a−1 or ~1/4 of total fluxes. Therefore, intermittent internal waters should be considered when estimating the CO2 emissions of global inland water. Future investigations should focus on the in-depth study of the main sources of uncertainty involved in carbon emissions from intermittent internal waters to understand the physical and biological mechanisms behind this flux, and the impact on the global carbon cycle. Important study topics include: (1) Accurate estimation of the area of intermittent inland waters, in particular, the area of small-flow rivers, scattered ponds, and the area of headwaters; (2) CO2 efflux measurement of dry riverbeds, including the determination of CO2 efflux directly and indirectly, and combining the two methods; (3) the mechanism of CO2 release from dry riverbeds and factors driving CO2 fluxes from intermittent inland waters, such as the ratio of autochthonous and allochthonous carbon in sediments during dry and rewetting episodes; and (4) deep understanding of the changes in extension and seasonality of intermittent internal waters, particularly those in response to climate oscillations, land-use changes, and potential feedback related to climate at decadal time-scales. The results from these additional studies will help explain completely the inland water carbon emissions and identify potential implications for regional and global carbon cycles.

Assessment of Water Storage Changes Using GRACE and GLDAS

Water crisis is one of the main global risks that has different impacts on the society. This work uses available data and tools to track water storage changes in Iran, where lack of observations limits hydroclimatological studies and thus causes disasters. Data from Global Land Data Assimilation System (GLDAS) and Gravity Recovery and Climate Experiment (GRACE) are combined to analyze water storage changes (LWE) in Iran. GRACE signals indicate a large reduction of the water storage in North of Iran along the coast of the Caspian Sea (the largest global inland water body), where the water level has been oscillating significantly. In addition, results show the largest reduction of the water storage that occurred in the karstic and alluvial aquifers in Zagros, where groundwater is overused and many dams are constructed across the rivers. In addition to anthropogenic forcing, climate change has short- and long-term impact on the water storage. The highest correlation between LWE and climatological variables including temperature and precipitation is at 3- and 2-month lags, respectively. Natural and anthropogenic forcing caused the maximum rate of LWE reduction (maximum average reduction) in Kermanshah province, where a sequence of earthquakes occurred (in 2017, 2018, and 2019). Results highlight the main role of water storage monitoring in management plans and decision-making processes to conserve natural resources and reduce hazards.

Application of Sentinel 3 OLCI for chl-a retrieval over small inland water targets: Successes and challenges

Eutrophication and increasing prevalence of potentially toxic cyanobacterial blooms among global inland water bodies is becoming a major concern and requires direct attention. The European Space Agency recently launched the Ocean and Land Color Instrument (OLCI) aboard the Sentinel 3 satellite. The success of the mission will depend on extensive validation efforts for the development of accurate and robust in-water algorithms. In this study, four full atmospheric correction methods are assessed over four inland water reservoirs in South Africa, along with a suite of red/NIR based semi-analytic and band difference models for chl-a estimation which were applied to both full and partial atmospherically corrected data. In addition, we tested a novel duplicate pixel correction method to account for duplicate pixels induced by high observation zenith angles. Radiometric errors associated with OLCI Top of Atmosphere (TOA) radiances over small water targets were also investigated by modeling in situ reflectance measurements to at-sensor radiances using MODTRAN. Of the four atmospheric corrections, the 6SV1 radiative transfer code showed the most promise for producing reasonable reflectances when compared to in-situ measurements. Empirically derived band difference models outperformed all other chl-a retrieval methods on both partially and fully corrected reflectances. The Maximum Peak Height (MPH) algorithm applied to Bottom of Rayleigh Reflectance (BRR) performed best overall (R2 = 0.55, RMSE(%) = 99), while the Maximum Chlorophyll Index (MCI) performed best on atmospherically corrected data using 6SV1 (R2 = 0.35, RMSE(%) = 107). Semi-analytic chl-a retrieval methods proved very successful when applied to in situ Rrs, however, are not reliable when applied to low quality reflectance data. The SIMilarity Environment Correction (SIMEC), an adjacency correction applied in conjunction with the image correction for atmospheric effects (iCOR) processor, did not improve retrieval results for these small water targets.

Characterization of chromophoric dissolved organic matter in lakes across the Tibet-Qinghai Plateau using spectroscopic analysis

Fluorescent dissolved organic matter (FDOM) has a significant influence on global inland water carbon cycling and biogeochemical processes. The alpine lakes on Tibet-Qinghai Plateau (TQP) are exposed to high-intensity ultraviolet radiation, long retention time with less anthropogenic influences. Yet, limited studies were conducted on FDOM of lakes on the highest plateau in the world with unique aquatic environments. Spatiotemporal variations of FDOM components from 63 lakes (32 fresh lakes, N = 135; 31 brackish lakes, N = 109) were grouped according to salinity across the TQP collected during 2014–2017. FDOM were examined using excitation-emission matrix spectra (EEM) and fluorescence regional integration (FRI). CDOM absorption and FDOM fluorescence indices, average fluorescence intensities of the five fluorescent components (φi,i = I, II, III, IV, V) and total fluorescence intensities (φT) are significantly different between brackish and freshwater lakes (p < 0.05). High correlations (−0.51** < r < −0.86**, p < 0.01) were revealed between FDOM and dissolved organic carbon (DOC) concentrations with salinity > 10‰. A comparatively prolonged retention time and terrestrial allochthonous inputs caused higher DOC accumulation in brackish water. Strong UV radiation resulted in an important effect on CDOM photo-absorption characteristics, and that contributed to DOC variability and fate. Likewise, average CDOM spectroscopic indices in each basin with different land covers showed a moderate correlation between DOC and normalized humic-like φV for 20 basins (r = −0.46**, p < 0.01). The results suggest that studies on the highest alpine lakes across the TQP should focus on the impact of the evapo-concentration, ultraviolet irradiance and landscape features within different basins on FDOM characteristics. It demonstrated that the FDOM was dominated by the allochthonous sources in brackish lakes from the TQP and had a similarity to those observed in marine environments.

Nitrous oxide emissions from inland waters: Are IPCC estimates too high?

Nitrous oxide (N2 O) emissions from inland waters remain a major source of uncertainty in global greenhouse gas budgets. N2 O emissions are typically estimated using emission factors (EFs), defined as the proportion of the terrestrial nitrogen (N) load to a water body that is emitted as N2 O to the atmosphere. The Intergovernmental Panel on Climate Change (IPCC) has proposed EFs of 0.25% and 0.75%, though studies have suggested that both these values are either too high or too low. In this work, we develop a mechanistic modeling approach to explicitly predict N2 O production and emissions via nitrification and denitrification in rivers, reservoirs and estuaries. In particular, we introduce a water residence time dependence, which kinetically limits the extent of denitrification and nitrification in water bodies. We revise existing spatially explicit estimates of N loads to inland waters to predict both lumped watershed and half-degree grid cell emissions and EFs worldwide, as well as the proportions of these emissions that originate from denitrification and nitrification. We estimate global inland water N2 O emissions of 10.6-19.8GmolNyear-1 (148-277GgNyear-1 ), with reservoirs producing most N2 O per unit area. Our results indicate that IPCC EFs are likely overestimated by up to an order of magnitude, and that achieving the magnitude of the IPCC's EFs is kinetically improbable in most river systems. Denitrification represents the major pathway of N2 O production in river systems, whereas nitrification dominates production in reservoirs and estuaries.

Construction of the 500‐m Resolution Daily Global Surface Water Change Database (2001–2016)

AbstractSurface water is the most dynamic land‐cover type. Transitions between water and nonwater types (such as vegetation and ice) can happen momentarily. More frequent mapping is necessary to study the changing patterns of water. However, monitoring of long‐term global water changes at high spatial resolution and in high temporal frequency is challenging. Here we report the generation of a daily global water map data set at 500‐m resolution from 2001 to 2016 based on the daily reflectance time series from Moderate Resolution Imaging Spectroradiometer. Each single‐date image is classified into three types: water, ice/snow, and land. Following temporal consistency check and spatial‐temporal interpolation for missing data, we conducted a series of validation of the water data set. The producer's accuracy and user's accuracy are 94.61% and 93.57%, respectively, when checked with classification results derived from 30‐m resolution Landsat images. Both the producer's accuracy and user's accuracy reached better than 90% when compared with manually interpreted large‐sized sample units (≥1,000 m × 1,000 m) collected in a previous global land cover mapping project. Generally, the global inland water area reaches its maximum (~3.80 × 106 km2) in September and minimum (~1.50 × 106 km2) in February during an annual cycle. Short‐duration water bodies, sea level rise effects, different types of rice field use can be detected from the daily water maps. The size distribution of global water bodies is also discussed from the perspective of the number of water bodies and the corresponding water area. In addition, the daily water maps can precisely reflect water freezing and help correct water areas with inconsistent cloud flags in the MOD09GA quality assessment layer.

Trophic state assessment of global inland waters using a MODIS-derived Forel-Ule index

Eutrophication of inland waters is considered a serious global environmental problem. Satellite remote sensing (RS) has been established as an important source of information to determine the trophic state of inland waters through the retrieval of optically active water quality parameters such as chlorophyll-a (Chl-a). However, the use of RS techniques for assessment of the trophic state of inland waters on a global scale is hindered by the performance of retrieval algorithms over highly dynamic and complex optical properties that characterize many of these systems. In this study, we developed a new RS approach to assess the trophic state of global inland water bodies based on Moderate Resolution Imaging Spectroradiometer (MODIS) imagery and the Forel-Ule index (FUI). First, the FUI was calculated from MODIS data by dividing natural water colour into 21 indices from dark blue to yellowish-brown. Then the relationship between FUI and the trophic state index (TSI) was established based on in-situ measurements and MODIS products. The water-leaving reflectance at 645 nm band was employed to distinguish coloured dissolved organic matter (CDOM)-dominated systems in the FUI-based trophic state assessment. Based on the analysis, the FUI-based trophic state assessment method was developed and applied to assess the trophic states of 2058 large inland water bodies (surface area >25 km2) distributed around the world using MODIS data from the austral and boreal summers of 2012. Our results showed that FUI can be retrieved from MODIS with a considerable accuracy (92.5%, R2 = 0.92) by comparing with concurrent in situ measurements over a wide range of lakes, and the overall accuracy of the FUI-based trophic state assessment method is 80.0% (R2 = 0.75) validated by an independent dataset. Of the global large water bodies considered, oligotrophic large lakes were found to be concentrated in plateau regions in central Asia and southern South America, while eutrophic large lakes were concentrated in central Africa, eastern Asia, and mid-northern and southeast North America.

Development of a spectral‐pattern‐analysis‐based method for automated water body extraction using Landsat image data: A case study in central Vietnam and southern Laos

AbstractWater body mapping is an important application of optical remote sensing. Methods for classifying water bodies using multispectral image data have been successfully developed for water resource monitoring and management. However, in most cases, these traditional methods provide only partial automation capabilities. In this study, we propose a new spectral‐pattern‐analysis‐based (SPAB) method for water body extraction using simplified spectral patterns (SSPs). Simplified spectral patterns are a generalized transformation of spectral patterns from analogue to digital format, realized by nonrepetitive pairwise comparison of reflectance values between two bands. Simplified spectral patterns allow for the direct incorporation of spectral patterns into the recognition process. The advantage of this method compared to traditional methods is that the SPAB method allows automation of water body classification using an SSP database. In this study, we selected a mountainous region in central Vietnam and southern Laos as a study site. Four Landsat 8 OLI scenes from 2015 and four Landsat 7 ETM+ scenes from 2001 and 2002 were used. The results of our proposed method were compared with visual interpretation, normalized differential water index (NDWI) thresholding, and the Global Inland Water (GIW) dataset provided by the Global Land Cover Facility of the University of Maryland. It is concluded that the classification results of the SPAB method agree by more than 98.0% with NDWI results for Landsat 8 OLI images, and by more than 95.0% with the GIW dataset for Landsat 7 ETM+ images.

ASTER GLOBAL DEM VERSION 3, AND NEW ASTER WATER BODY DATASET

Abstract. In 2016, the US/Japan ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) project released Version 3 of the Global DEM (GDEM). This 30 m DEM covers the earth’s surface from 82N to 82S, and improves on two earlier versions by correcting some artefacts and filling in areas of missing DEMs by the acquisition of additional data. The GDEM was produced by stereocorrelation of 2 million ASTER scenes and operation on a pixel-by-pixel basis: cloud screening; stacking data from overlapping scenes; removing outlier values, and averaging elevation values. As previously, the GDEM is packaged in ~ 23,000 1 x 1 degree tiles. Each tile has a DEM file, and a NUM file reporting the number of scenes used for each pixel, and identifying the source for fill-in data (where persistent clouds prevented computation of an elevation value). An additional data set was concurrently produced and released: the ASTER Water Body Dataset (AWBD). This is a 30 m raster product, which encodes every pixel as either lake, river, or ocean; thus providing a global inland and shore-line water body mask. Water was identified through spectral analysis algorithms and manual editing. This product was evaluated against the Shuttle Water Body Dataset (SWBD), and the Landsat-based Global Inland Water (GIW) product. The SWBD only covers the earth between about 60 degrees north and south, so it is not a global product. The GIW only delineates inland water bodies, and does not deal with ocean coastlines. All products are at 30 m postings.

ASTER GLOBAL DEM VERSION 3, AND NEW ASTER WATER BODY DATASET

In 2016, the US/Japan ASTER (Advanced Spaceborne Thermal Emission and Reflection Radiometer) project released Version 3 of the Global DEM (GDEM). This 30&amp;thinsp;m DEM covers the earth’s surface from 82N to 82S, and improves on two earlier versions by correcting some artefacts and filling in areas of missing DEMs by the acquisition of additional data. The GDEM was produced by stereocorrelation of 2 million ASTER scenes and operation on a pixel-by-pixel basis: cloud screening; stacking data from overlapping scenes; removing outlier values, and averaging elevation values. As previously, the GDEM is packaged in ~&amp;thinsp;23,000 1&amp;thinsp;x&amp;thinsp;1 degree tiles. Each tile has a DEM file, and a NUM file reporting the number of scenes used for each pixel, and identifying the source for fill-in data (where persistent clouds prevented computation of an elevation value). An additional data set was concurrently produced and released: the ASTER Water Body Dataset (AWBD). This is a 30&amp;thinsp;m raster product, which encodes every pixel as either lake, river, or ocean; thus providing a global inland and shore-line water body mask. Water was identified through spectral analysis algorithms and manual editing. This product was evaluated against the Shuttle Water Body Dataset (SWBD), and the Landsat-based Global Inland Water (GIW) product. The SWBD only covers the earth between about 60 degrees north and south, so it is not a global product. The GIW only delineates inland water bodies, and does not deal with ocean coastlines. All products are at 30&amp;thinsp;m postings.