Water Extent Research Articles

Dynamic Change Analysis of Surface Water in the Yangtze River Basin Based on MODIS Products

The use of remote sensing to monitor surface water bodies has gradually matured. Long-term serial water change analysis and floods monitoring are currently research hotspots of remote sensing hydrology. However, these studies are also faced with some problems, such as coarse temporal or spatial resolution of some remote sensing data. In general, flood monitoring requires high temporal resolution, and small-scale surface water extraction requires high spatial resolution. The machine learning method has been proven to be effective against long-term serial surface water extraction, such as random forests (RFs). MODIS data are well suited for large-scale surface water dynamic analysis and flood monitoring because of its short return cycle and medium spatial resolution. In this paper, the Yangtze River Basin (YRB) in China was selected as the study area, and two MODIS products (MOD09A1 and MOD13Q1) and RF method were used to extract the surface water from 2000 to 2016. Considering the disadvantages of temporal or spatial resolution of these two MODIS products, this study also presents a data fusion method to combine them and get higher spatiotemporal resolution water results. Finally, 762 surface water maps from 2000 to 2016 are obtained, whose temporal and spatial resolution is every eight days and 250 m, respectively. In addition, water extent variation is analyzed and compared to observed precipitation data. The main conclusions are as follows: (1) this constructed approach for long-term serial surface water extraction based on the RF classifier is feasible, and a good fusion method is used to obtain the surface water body with higher spatiotemporal resolution; (2) the maximum area of the surface water extent is 48.53 × 103 km2, and seasonal and permanent water areas are 20.51 × 103 km2 and 28.01 × 103 km2, respectively; (3) surface water area is increasing in the YRB, such that seasonal water area decreased by 3450 km2, and the permanent water area increased by 3565 km2 in 2001–2015; (4) precipitation is the main factor causing variation in the surface water bodies, and they both show an increasing trend in 2000–2016. As such, the approach is worth referring to other remote sensing applications, and these products are very both valuable for water resource management and flood monitoring in the study area.

Effects of landscape structure and temporal habitat dynamics on wintering mallard abundance

Management of wintering waterfowl in North America requires adaptability because constant landscape and environmental change challenges existing management strategies regarding waterfowl habitat use at large spatial scales. Migratory waterfowl including mallards (Anas platyrhynchos) use the lower Mississippi Alluvial Valley (MAV) for wintering habitat, making this an important area of emphasis for improving wetland conservation strategies, while enhancing the understanding of landscape-use patterns. We used aerial survey data collected in the Arkansas portion of the MAV (ARMAV) to explain the abundance and distribution of mallards in relation to variable landscape conditions. We used two-stage, hierarchical spatio-temporal models with a random spatial effect to identify covariates related to changes in mallard abundance and distribution within and among years. We found distinct spatio-temporal patterns existed for mallard distributions across the ARMAV and these distributions are dependent on the surrounding landscape structure and changing environmental conditions. Models performing best indicated seasonal surface water extent, rice field, wetland and fallow (uncultivated) fields positively influenced mallard presence. Rice fields, surface water and weather were found to influence mallard abundance. Additionally, the results suggest weather and changing surface water affects mallard presence and abundance throughout the winter. Using novel datasets to identify which environmental factors drive changes in regional wildlife distribution and abundance can improve management by providing managers additional information to manage land over landscapes spanning private and public lands. We suggest our analytical approach may be informative in other areas and for other wildlife species.

Assessing Single-Polarization and Dual-Polarization TerraSAR-X Data for Surface Water Monitoring

Three synthetic aperture radar (SAR) data classification methodologies were used to assess the ability of single-polarization and dual-polarization TerraSAR-X (TSX) data to classify surface water, including open water, ice, and flooded vegetation. Multi-polarization SAR observations contain more information than single-polarization SAR, but the availability of multi-polarization data is much lower, which limits the temporal monitoring capabilities. The study area is a principally natural landscape centered on a seasonally flooding river, in which four TSX dual-co-polarized images were acquired between the months of April and June 2016. Previous studies have shown that single-polarization SAR is useful for analyzing surface water extent and change using grey-level thresholding. The H-Alpha–Wishart decomposition, adapted to dual-polarization data, and the Kennaugh Element Framework were used to classify areas of water and flooded vegetation. Although grey-level thresholding was able to identify areas of water and non-water, the percentage of seasonal change was limited, indicating an increase in water area from 8% to 10%, which is in disagreement with seasonal trends. The dual-polarization methods show a decrease in water over the season and indicate a decrease in flooded vegetation, which agrees with expected seasonal variations. When comparing the two dual-polarization methods, a clear benefit of the Kennaugh Elements Framework is the ability to classify change in the transition zones of ice to open water, open water to marsh, and flooded vegetation to land, using the differential Kennaugh technique. The H-Alpha–Wishart classifier was not able to classify ice, and misclassified fields and ice as water. Although single-polarization SAR was effective in classifying open water, the findings of this study confirm the advantages of dual-polarization observations, with the Kennaugh Element Framework being the best performing classification framework.

A Hydraulic MultiModel Ensemble Framework for Visualizing Flood Inundation Uncertainty

AbstractWhile deterministic forecasts provide a single realization of potential inundation, the inherent uncertainty associated with forecasts also needs to be conveyed for improved decision support. The objective of this study was to develop an ensemble framework for the quantification and visualization of uncertainty associated with flood inundation forecast maps. An 11‐member ensemble streamflow forecast at lead times from 0 to 48 hr was used to force two hydraulic models to produce a multimodel ensemble. The hydraulic models used are (1) the International River Interface Cooperative along with Flow and Sediment Transport with Morphological Evolution of Channels solver and (2) the two‐dimensional Hydrologic Engineering Center‐River Analysis System. Uncertainty was quantified and augmented onto flood inundation maps by calculating statistical spread among the ensemble members. For visualization, a series of probability flood maps conveying the uncertainty in forecasted water extent, water depth, and flow velocity was disseminated through a web‐based decision support tool. The results from this study offer a framework for quantifying and visualizing model uncertainty in forecasted flood inundation maps.

Carbonation resistance of cements containing supplementary cementitious materials and its relation to various parameters of concrete

In this study, the carbonation resistance of cements containing supplementary cementitious materials (SCMs) exposed to carbon dioxide concentrations of 1% and 3%, relative humidity of 40%, 60% and 80% and temperature of 27 °C and 45 °C at two different water to cement ratio is investigated. The carbonation performance of concrete samples placed in accelerated conditions is compared to that of concrete samples exposed to natural conditions. The comparison of carbonation coefficients of concrete exposed to different environmental conditions indicates that the rate of carbonation is primarily governed by the extent of clinker replacement, relative humidity and water to cement ratio. Concrete mixes with slag showed better carbonation resistance as compared to mixes containing other SCMs. No specific correlation can be observed between the carbonation coefficients and physical parameters of concrete (compressive strength and porosity), however, a reasonable correlation is observed between carbonation coefficients and chemical parameters (Total alkali content, reserve alkalinity and pH). An empirical equation is developed to estimate the carbonation depth for different cements for wide range of exposure conditions.

Assessment of Surface Water Storage trends for increasing groundwater areas in India

Recent studies based on Gravity Recovery and Climate Experiment (GRACE) satellite mission suggested that groundwater has increased in central and southern parts of India. However, surface water, which is an equally important source of water in these semi-arid areas has not been studied yet. In the present study, the study areas were outlined based on trends in GRACE data followed by trend identification in surface water storages and checking the hypothesis of causality. Surface Water Extent (SWE) and Surface Soil Moisture (SSM) derived from Moderate-resolution Imaging Spectroradiometer (MODIS) and Advanced Microwave Scanning Radiometer - Earth Observing System (AMSR-E) respectively, are selected as proxies of surface water storage (SWS). Besides SWE and SSM, trend test was performed for GRACE derived terrestrial water storage (TWS) for the study areas named as R1, R2, GOR1 and KOR1. Granger-causality test is used to test the hypothesis that rainfall is a causal factor of the inter-annual variability of SWE, SSM and TWS. Positive trends were observed in TWS for R1, R2 and GOR1 whereas SWE and SSM show increasing trends for all the study regions. Results suggest that rainfall is the granger-causal of all the storage variables for R1 and R2, the regions exhibiting the most significant positive trends in TWS.

Automated Extraction of Surface Water Extent from Sentinel-1 Data

Accurately quantifying surface water extent in wetlands is critical to understanding their role in ecosystem processes. However, current regional- to global-scale surface water products lack the spatial or temporal resolution necessary to characterize heterogeneous or variable wetlands. Here, we proposed a fully automatic classification tree approach to classify surface water extent using Sentinel-1 synthetic aperture radar (SAR) data and training datasets derived from prior class masks. Prior classes of water and non-water were generated from the Shuttle Radar Topography Mission (SRTM) water body dataset (SWBD) or composited dynamic surface water extent (cDSWE) class probabilities. Classification maps of water and non-water were derived over two distinct wetlandscapes: the Delmarva Peninsula and the Prairie Pothole Region. Overall classification accuracy ranged from 79% to 93% when compared to high-resolution images in the Prairie Pothole Region site. Using cDSWE class probabilities reduced omission errors among water bodies by 10% and commission errors among non-water class by 4% when compared with results generated by using the SWBD water mask. These findings indicate that including prior water masks that reflect the dynamics in surface water extent (i.e., cDSWE) is important for the accurate mapping of water bodies using SAR data.

The Total Drainable Water Storage of the Amazon River Basin: A First Estimate Using GRACE

AbstractIn the Amazon River basin, water stored for months to years in the soils and subsurface provide a persistent resource that regulates local and global climate via teleconnections and provides water to plants in times of little rain. While Gravity Recovery and Climate Experiment (GRACE) satellites have provided the hydrological community with large advances in the understanding of large river basin dynamics and for water resources monitoring applications, the relative storage measurements from GRACE satellites have not yet been utilized for the quantification of total available freshwater on landmasses. In this study, we quantify the total drainable water storage (TDWS) in the Amazon basin by characterizing the relationship between the water storage anomaly of a large catchment and its base flow. Previous studies have shown that these two hydrological parameters behave like a linear time‐independent system over a catchment like the Amazon dominated by fully humid tropical climate. This linear relationship allows us to determine a zero water storage level, at which the storage‐driven discharge becomes zero. We quantify the TDWS of the Amazon basin as 1,766 km3 and estimate an average 2 month residence time for stored waters. An independent analysis over nine major subbasins confirms our estimate for the entire basin. We show that our estimated TDWS values for individual subbasins, varying between 15 and 654 km3, follow two different linear relationships with their mean annual input. Through these relationships we also quantify the storage‐driven portion of the streamflow and the total streamflow for Amazon and its subbasins. Furthermore, we estimate surface water storage variation of the Amazon River system by combining the water level time series from satellite altimetry and surface water extent time series from satellite imagery. Our results show that 61% of total basin water storage variation occurs in the surface water compartment. In addition, we find that 65% of the TDWS is available in its surface water system.

WETLAND CLASSIFICATION FOR BLACK DUCK HABITAT MANAGEMENT USING COMBINED POLARIMETRIC RADARSAT 2 AND SPOT IMAGERY

Abstract. The black duck population has decreased significantly due to loss of its breeding habitat. Wetlands are an important feature that relates to habitat management and requires monitoring. Synthetic Aperture Radar (SAR) systems are helpful to map the wetland as the microwave signals are sensitive to water content and can be used to map surface water extent, saturated soils, and flooded vegetation. In this study, RadarSat 2 Polarimetric data is employed to map surface water and track changes in extent over the years through image thresholding and reviewed different approaches of Polarimetric decompositions for detecting flooded vegetation. Also, object-based analysis associated with beaver activity is conducted with combined multispectral SPOT satellite imagery. Results show SAR data has proven ability to improve mapping open water areas and locate flooded vegetation areas.

Wetland hydroperiod classification in the western prairies using multitemporal synthetic aperture radar

AbstractWetlands represent one of the world's most biodiverse and threatened ecosystem types and were diminished globally by about two‐thirds in the 20th century. There is continuing decline in wetland quantity and function due to infilling and other human activities. In addition, with climate change, warmer temperatures and changes in precipitation and evapotranspiration are reducing wetland surface and groundwater supplies, further altering wetland hydrology and vegetation. There is a need to automate inventory and monitoring of wetlands, and as a study system, we investigated the Shepard Slough wetlands complex, which includes numerous wetlands in urban, suburban, and agricultural zones in the prairie pothole region of southern Alberta, Canada. Here, wetlands are generally confined to depressions in the undulating terrain, challenging wetlands inventory and monitoring. This study applied threshold and frequency analysis routines for high‐resolution, single‐polarization (HH) RADARSAT‐2, synthetic aperture radar mapping. This enabled a growing season surface water extent hyroperiod‐based wetland classification, which can support water and wetland resource monitoring. This 3‐year study demonstrated synthetic aperture radar‐derived multitemporal open‐water masks provided an effective index of wetland permanence class, with overall accuracies of 89% to 95% compared with optical validation data, and RMSE between 0.2 and 0.7 m between model and field validation data. This allowed for characterizing the distribution and dynamics of 4 marsh wetlands hydroperiod classes, temporary, seasonal, semipermanent, and permanent, and mapping of the sequential vegetation bands that included emergent, obligate wetland, facultative wetland, and upland plant communities. Hydroperiod variation and surface water extent were found to be influenced by short‐term rainfall events in both wet and dry years. Seasonal hydroperiods in wetlands were particularly variable if there was a decrease in the temporary or semipermanent hydroperiod classes. In years with extreme rain events, the temporary wetlands especially increased relative to longer lasting wetlands (84% in 2015 with significant rainfall events, compared with 42% otherwise).

The Use of Sentinel-1 Time-Series Data to Improve Flood Monitoring in Arid Areas

Due to the similarity of the radar backscatter over open water and over sand surfaces a reliable near real-time flood mapping based on satellite radar sensors is usually not possible in arid areas. Within this study, an approach is presented to enhance the results of an automatic Sentinel-1 flood processing chain by removing overestimations of the water extent related to low-backscattering sand surfaces using a Sand Exclusion Layer (SEL) derived from time-series statistics of Sentinel-1 data sets. The methodology was tested and validated on a flood event in May 2016 at Webi Shabelle River, Somalia and Ethiopia, which has been covered by a time-series of 202 Sentinel-1 scenes within the period June 2014 to May 2017. The approach proved capable of significantly improving the classification accuracy of the Sentinel-1 flood service within this study site. The Overall Accuracy increased by ~5% to a value of 98.5% and the User’s Accuracy increased by 25.2% to a value of 96.0%. Experimental results have shown that the classification accuracy is influenced by several parameters such as the lengths of the time-series used for generating the SEL.

Satellite remote sensing estimation of river discharge: Application to the Yukon River Alaska

A methodology based on general hydraulic relations for rivers has been developed to estimate the discharge (flow rate) of rivers using satellite remote sensing observations. The estimates of discharge, flow depth, and flow velocity are derived from remotely observed water surface area, water surface slope, and water surface height, and demonstrated for two reaches of the Yukon River in Alaska, at Eagle (reach length 34.7 km) and near Stevens Village (reach length 38.3 km). The method is based on fundamental equations of hydraulic flow resistance in rivers, including the Manning equation and the Prandtl-von Karman universal velocity distribution equation. The method employs some new hydraulic relations to help define flow resistance and height of the zero flow boundary in the channel. Estimates are made both with and without calibration. The water surface area of the river reach is measured by using a provisional version of the U.S. Geological Survey (USGS) Landsat based product named Dynamic Surface Water Extent (DSWE). The water surface height and slope measurements require a self-consistent datum, and are derived from observations from the Jason-2 satellite altimeter mission. At both reach locations, the Jason-2 radar altimeter non-winter heights consistently tracked the stage recorded at USGS streamgages with a standard deviation of differences (error) during the non-winter periods of less than 7%. Part of the error may be due to differences in the gage and altimeter crossing locations with respect to the range of stage change and the response to changes in discharge at the upstream and downstream locations. For the non-winter periods, the radar derived slope estimates (mean = 0.0003) were constant over the mission lifetime, and in agreement with previously measured USGS water surface slopes and slopes determined from USGS topographic maps. The accuracy of the mean of the uncalibrated daily estimates of discharge varied between reaches, ranging from 13% near Stevens Village (N = 90) to −21% at Eagle (N = 246) based on the absolute error, and 5% to −6% based on the error of the log of the estimates. Calibrating to the mean of USGS daily discharge estimates from the streamflow rating for the same period of record at each streamgage resulted in mean absolute errors ranging from 1% to 2%, and log errors ranging from 1% or less. The error pattern of the estimates shows that without calibration, even though the mean is well simulated, the high and low end values over the range of estimates may have significant bias.

The sign, magnitude and potential drivers of change in surface water extent in Canadian tundra

The accelerated rate of warming in the Arctic has considerable implications for all components of ecosystem functioning in the High Northern Latitudes. Changes to hydrological cycle in the Arctic are particularly complex as the observed and projected warming directly impacts permafrost and leads to variable responses in surface water extent which is currently poorly characterized at the regional scale. In this study we take advantage of the 30 plus years of medium resolution (30 m) Landsat data to quantify the spatial patterns of change in the extent of water bodies in the Arctic tundra in Nunavut, Canada. Our results show a divergent pattern of change—growing surface water extent in the north-west and shrinking in the south-east—which is not a function of the overall distribution of surface water in the region. The observed changes cannot be explained by latitudinal stratification, nor is it explained by available temperature and precipitation records. However, the sign of change appears to be consistent within the boundaries of individual watersheds defined by the Canada National Hydro Network based on the random forest analysis. Using land cover maps as a proxy for ecological function we were able to link shrinking tundra water bodies to substrates with shallow soil layers (i.e. bedrock and barren landscapes) with a moderate correlation (R2 = 0.46, p < 0.001). It has previously been reported that rising temperatures are driving a deepening of the active layer and shrinking water bodies can be associated with coarse textured soils beneath the lakes. Unlike water bodies with soil, or gravel, beneath them the water bodies that are situated on bedrock are likely cut off from ground water. Drying water bodies clustered in areas of bedrock and thin soils points to evaporation as an important driver of surface water decrease in these cases.

Wetlands inform how climate extremes influence surface water expansion and contraction

Effective monitoring and prediction of flood and drought events requires an improved understanding of how and why surface-water expansion and contraction in response to climate varies across space. This paper sought to (1) quantify how interannual patterns of surface-water expansion and contraction vary spatially across the Prairie Pothole Region (PPR) and adjacent Northern Prairie (NP) in the United States, and (2) explore how landscape characteristics influence the relationship between climate inputs and surface-water dynamics. Due to differences in glacial history, the PPR and NP show distinct patterns in regards to drainage development and wetland density, together providing a diversity of conditions to examine surface-water dynamics. We mapped surface-water extent across eleven Landsat path/rows representing the PPR and NP (images spanning 1985-2015). The PPR not only experienced a 2.6-fold increase of surface-water extent under median conditions relative to the NP, but also showed a 3.4-fold greater difference in surface-water extent between drought and deluge conditions. The relationship between surface-water extent and accumulated water availability (precipitation minus potential evapotranspiration) was quantified per watershed and statistically related to variables representing hydrology-related landscape characteristics (e.g., infiltration capacity, surface storage capacity, stream density). To investigate the influence stream-connectivity has on the rate at which surface water leaves a given location, we modeled stream-connected and stream-disconnected surface water separately. Stream-connected surface water showed a greater expansion with wetter climatic conditions in landscapes with greater total wetland area. Disconnected surface water showed a greater expansion with wetter climatic conditions in landscapes with higher wetland density, lower infiltration and less anthropogenic drainage. From these findings, we can expect that shifts in precipitation and evaporative demand will have uneven effects on surface-water quantity. Accurate predictions regarding the effect of climate change on surface-water quantity will require consideration of hydrology-related landscape characteristics including wetlands.

Correlated Increase of High Ocean Waves and Winds in the Ice-Free Waters of the Arctic Ocean

The long-term trend of extreme ocean waves in the emerging ice-free waters of the summer Arctic is studied using ERA-Interim wave reanalysis, with validation by two drifting wave buoys deployed in summer 2016. The 38-year-long reanalysis dataset reveals an increase in the expected largest significant wave height from 2.3 m to 3.1 m in the ice-free water from the Laptev to the Beaufort Seas during October. The trend is highly correlated with the expected increase in highest wind speed from 12.0 m/s to 14.2 m/s over the ice-free ocean, and less so with the extent of the ice-free water. Since the storms in this area did not strengthen throughout the analysis period, the increase in the expected largest significant wave height follows from the enhanced probability of storms in ice-free waters, which is pertinent to the estimation of extreme sea conditions along the Northern Sea Route.

Морфо-анатомічні показники хвої Pinus pallasiana D. Don. у різних лісорослинних умовах протиерозійного насадження

&lt;p&gt;The paper studies morpho-anatomical parameters of the needles of &lt;em&gt;Pinus pallasiana&lt;/em&gt; D. Don. in different forest growth conditions of the antierosion afforestation in the steppe Prydniprovya. The research objects are 25-27-year-old plants, which grow in cross-sectional rows on the northern slope of wooded ravine Viyskovyi. The test Plots differ in forest growth conditions especially in the extent of water supply.In spite of the relatively high drought tolerance of &lt;em&gt;P. pallasiana&lt;/em&gt;, such morphometric indices of needles as length, width and thickness are reduced in dry forest conditions. Quantitative changes in a number of indicators of the structural elements of the anatomical structure of the needles indicate adaptive changes to the lack of moisture. The formation of needles in dry forest conditions causes the formation of a thicker cuticle, an increase in the thickness of the cells of the epidermis and the hypodermis (radially in the transverse section), which reduces the loss of moisture. However, reducing the size of the conducting beams limits both the flow of water into the needle and the outflow of assimilates. In arid growing conditions, the number of resin canals in needles is reduced compared to plants of thalweg, the layer of folded parenchyma, both the adaxial and abaxial parts of the needles, is thinned.&lt;/p&gt;

Improved Chlorophyll-a Algorithm for the Satellite Ocean Color Data in the Northern Bering Sea and Southern Chukchi Sea

The Bering and Chukchi seas are an important conduit to the Arctic Ocean and are reported to be one of the most productive regions in the world’s oceans in terms of high primary productivity that sustains large numbers of fishes, marine mammals, and sea birds as well as benthic animals. Climate-induced changes in primary production and production at higher trophic levels also have been observed in the northern Bering and Chukchi seas. Satellite ocean color observations could enable the monitoring of relatively long term patterns in chlorophyll-a (Chl-a) concentrations that would serve as an indicator of phytoplankton biomass. The performance of existing global and regional Chl-a algorithms for satellite ocean color data was investigated in the northeastern Bering Sea and southern Chukchi Sea using in situ optical measurements from the Healy 2007 cruise. The model-derived Chl-a data using the previous Chl-a algorithms present striking uncertainties regarding Chl-a concentrations – for example, overestimation in lower Chl-a concentrations or systematic overestimation in the northeastern Bering Sea and southern Chukchi Sea. Accordingly, a simple two band ratio (Rrs(443)/Rrs(555)) algorithm of Chl-a for the satellite ocean color data was devised for the northeastern Bering Sea and southern Chukchi Sea. The MODIS-derived Chl-a data from July 2002 to December 2014 were produced using the new Chl-a algorithm to investigate the seasonal and interannual variations of Chl-a in the northern Bering Sea and the southern Chukchi Sea. The seasonal distribution of Chl-a shows that the highest (spring bloom) Chl-a concentrations are in May and the lowest are in July in the overall area. Chl-a concentrations relatively decreased in June, particularly in the open ocean waters of the Bering Sea. The Chl-a concentrations start to increase again in August and become quite high in September. In October, Chl-a concentrations decreased in the western area of the Study area and the Alaskan coastal waters. Strong interannual variations are shown in Chl-a concentrations in all areas. There is a slightly increasing trend in Chl-a concentrations in the northern Bering Strait (SECS). This increasing trend may be related to recent increases in the extent and duration of open waters due to the early break up of sea ice and the late formation of sea ice in the Chukchi Sea.

Quantification of surface water volume changes in the Mackenzie Delta using satellite multi-mission data

Abstract. Quantification of surface water storage in extensive floodplains and their dynamics are crucial for a better understanding of global hydrological and biogeochemical cycles. In this study, we present estimates of both surface water extent and storage combining multi-mission remotely sensed observations and their temporal evolution over more than 15 years in the Mackenzie Delta. The Mackenzie Delta is located in the northwest of Canada and is the second largest delta in the Arctic Ocean. The delta is frozen from October to May and the recurrent ice break-up provokes an increase in the river's flows. Thus, this phenomenon causes intensive floods along the delta every year, with dramatic environmental impacts. In this study, the dynamics of surface water extent and volume are analysed from 2000 to 2015 by combining multi-satellite information from MODIS multispectral images at 500 m spatial resolution and river stages derived from ERS-2 (1995–2003), ENVISAT (2002–2010) and SARAL (since 2013) altimetry data. The surface water extent (permanent water and flooded area) peaked in June with an area of 9600 km2 (±200 km2) on average, representing approximately 70 % of the delta's total surface. Altimetry-based water levels exhibit annual amplitudes ranging from 4 m in the downstream part to more than 10 m in the upstream part of the Mackenzie Delta. A high overall correlation between the satellite-derived and in situ water heights (R &gt; 0.84) is found for the three altimetry missions. Finally, using altimetry-based water levels and MODIS-derived surface water extents, maps of interpolated water heights over the surface water extents are produced. Results indicate a high variability of the water height magnitude that can reach 10 m compared to the lowest water height in the upstream part of the delta during the flood peak in June. Furthermore, the total surface water volume is estimated and shows an annual variation of approximately 8.5 km3 during the whole study period, with a maximum of 14.4 km3 observed in 2006. The good agreement between the total surface water volume retrievals and in situ river discharges (R= 0.66) allows for validation of this innovative multi-mission approach and highlights the high potential to study the surface water extent dynamics.

Thermal and isotopic evidence for surface and subsurface water contributions to baseflow in a high Arctic river

AbstractSeven longitudinal water temperature tow surveys were conducted to attempt to identify the location of surface and subsurface river water exchanges along the length of the West River at the Cape Bounty Arctic Watershed Observatory, Melville Island, Nunavut, Canada (74°55′ N, 109°35′ W). Water temperature data were collected using a calibrated thermistor with an accuracy of ±0.002 °C (resolution &lt;0.00005 °C) along the river during July 2014 in conjunction with stable water isotope sampling to support the thermal data and to determine the extent of surface water mixing from different sources such as precipitation, snowmelt, and surface/subsurface water contributions to the river. Atmospheric conditions were found to be the main contributor to seasonal temperature variance in the river, whereas tributary inflows and residual channel snow also had important thermal effects to river temperatures. Residual channel snow was a sustained source of cold water during much of the 2014 summer season (June–August) and substantially offset downstream warming. The longitudinal temperature profiles indicate notable changes to the thermal state of the river, which are interpreted to be indicative of subsurface and surface water exchange through inputs of relatively cold or warm water. Broadly, surface inflows were found to provide warmer water relative to the West River, and contributed to downstream warming of the river, along with downstream enrichment of δD and δ18O. Subsurface inflows provided cooler water relative to the river, and contributed to downstream depletion of δD and δ18O and downstream cooling of river temperatures. These results demonstrate that localized changes in river temperature, in conjunction with isotopic tracers, can be used to track channel–slope water interactions in Arctic hydrological systems, work previously limited to alpine and temperate settings.

Using Sentinel-1A DInSAR interferometry and Landsat 8 data for monitoring water level changes in two lakes in Crete, Greece

Differential Interferometric Synthetic Aperture Radar (DInSAR) methodology has been successfully employed to detect water level changes and produce corresponding water level variation maps. In this study, Agia and Kournas lakes, located in Western Crete, Greece, were used as pilot areas to monitor water level change with means of SAR interferometry and auxiliary Earth Observation (EO) data. The water level variation was monitored for the period 2015–2016, using Sentinel-1A imageries and corresponding stage water level data. Landsat 8 data were additionally used to study vegetation regime and surface water extent and how these parameters affect interferograms performance. The results highlighted the fact that the combination of SAR backscattering intensity and unwrapped phase can provide additional insight into hydrological studies. The overall analysis of both interferometric characteristics and backscattering mechanism denoted their potential in enhancing the reliability of the water-level retrieval scheme and optimizing the capture of hydrological patterns spatial distribution.