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Special Issue "Applications of Remote Sensing and GIS in Hydrology"

A special issue of Water (ISSN 2073-4441). This special issue belongs to the section "Hydrology".

Deadline for manuscript submissions: closed (1 October 2018)

Special Issue Editors

Guest Editor
Dr. Frédéric Frappart

Laboratoire d'Etudes en Géophysique et Océanographie Spatiales, UMR 5566, CNES/CNRS/IRD/UPS, Observatoire Midi-Pyrénées, 14 Avenue Edouard Belin, 31400 Toulouse, France
Website | E-Mail
Interests: earth observation; regional/global water cycle; land hydrology; surface water storage; terrestrial water storage
Guest Editor
Dr. Nicolas Baghdadi

IRSTEA, University of Montpellier, TETIS, 34090 Montpellier, France
Website | E-Mail
Interests: remote sensing; soil moisture; soil roughness
Guest Editor
Dr. Mehrez Zribi

CESBIO (CNRS/UPS/CNES/IRD)18, Avenue Edouard Belin, 31401 Toulouse Cedex 9, France
Website | E-Mail
Interests: microwave remote sensing; airborne instrumentation; land hydrology
Guest Editor
Dr. Vincent Hanquiez

UMR5805-EPOC / OASU, Bât. B18N, allée Geoffroy St Hilaire, CS 50023, 33615 Pessac Cedex, France
Website | E-Mail
Interests: geographic information system; marine geology; acoustic data processing

Special Issue Information

Dear Colleagues,

In recent years, remote sensing has become increasingly important in Earth system science, and, especially, for the monitoring of the terrestrial water cycle with the launch of a great numbers of satellites, covering various applications (rainfall, soil moisture, flood extent, surface water level, terrestrial water storage, snow and ice, floods). This has paved the way for an explosion in the use of remote sensing data, especially through the use of Geographic Information System (GIS). This Special Issue aims to present reviews and recent advances of general interest in the use of remote sensing and GIS for hydrology. Manuscripts can be related to any use of remote sensing and/or GIS for any hydrological application. They can be focused on the monitoring of water reservoir (e.g., surface storage, soil moisture, soil roughness, groundwater, snow and ice, etc.) or flux (e.g., rainfall, evapotranspiration, discharge, etc.) at any scale, as well as on the management of water resources. Observations taking into account the spatial and temporal variability are needed to calibrate the models and control their forecasts. Remote sensing now provides access to useful factors in land surface monitoring. The assimilation of satellite measurements and products in the function models of hydrological processes and water management procedures allows an improvement in the understanding of the continental water cycle.

Dr. Frédéric Frappart
Dr. Nicolas Baghdadi
Dr. Mehrez Zribi
Dr. Vincent Hanquiez
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Water is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1600 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • hydrological cycle
  • satellite
  • Remote Sensing
  • GIS

Published Papers (28 papers)

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Research

Open AccessArticle Identification of Water Body Extent Based on Remote Sensing Data Collected with Unmanned Aerial Vehicle
Water 2019, 11(2), 338; https://doi.org/10.3390/w11020338
Received: 27 November 2018 / Revised: 12 January 2019 / Accepted: 13 February 2019 / Published: 16 February 2019
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Abstract
The paper presents an efficient methodology of water body extent estimation based on remotely sensed data collected with UAV (Unmanned Aerial Vehicle). The methodology includes the data collection with selected sensors and processing of remotely sensed data to obtain accurate geospatial products that [...] Read more.
The paper presents an efficient methodology of water body extent estimation based on remotely sensed data collected with UAV (Unmanned Aerial Vehicle). The methodology includes the data collection with selected sensors and processing of remotely sensed data to obtain accurate geospatial products that are finally used to estimate water body extent. Three sensors were investigated: RGB (Red Green Blue) camera, thermal infrared camera, and laser scanner. The platform used to carry each of these sensors was an Aibot X6—a multirotor type of UAV. Test data was collected at 6 sites containing different types of water bodies, including 4 river sections, an old river bed, and a part of a lake shore. The processing of collected data resulted in 2.5-D and 2-D geospatial products that were used subsequently for water body extent estimation. Depending on the type of used sensor, the created geospatial product, and the type of the water body and the land cover, three strategies employing image processing tools were developed to estimate water body range. The obtained results were assessed in terms of classification accuracy (distinguishing the water body from the land) and geometrical planar accuracy of the water body extent. The product identified as the most suitable in water body detection was four bands RGB+TIR (Thermal InfraRed) ortho mosaic. It allowed to achieve the average kappa coefficient of the water body identification above 0.9. The planar accuracy of water body extent varied depending on the type of the sensor, the geospatial product, and the test site conditions, but it was comparable with results obtained in similar studies. Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessArticle Evaluation of Hydrological Application of CMADS in Jinhua River Basin, China
Water 2019, 11(1), 138; https://doi.org/10.3390/w11010138
Received: 16 October 2018 / Revised: 26 December 2018 / Accepted: 8 January 2019 / Published: 14 January 2019
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Abstract
Evaluating the hydrological application of reanalysis datasets is of practical importance for the design of water resources management and flood controlling facilities in regions with sparse meteorological data. This paper compared a new reanalysis dataset named CMADS with gauge observations and investigated the [...] Read more.
Evaluating the hydrological application of reanalysis datasets is of practical importance for the design of water resources management and flood controlling facilities in regions with sparse meteorological data. This paper compared a new reanalysis dataset named CMADS with gauge observations and investigated the performance of the hydrological application of CMADS on daily streamflow, evapotranspiration, and soil moisture content simulations. The results show that: CMADS can represent meteorological elements including precipitation, temperature, relative humidity, and wind speed reasonably for both daily and monthly temporal scales while underestimates precipitation compared with gauge observations slightly (<15%). The hydrological model using CMADS dataset as meteorological inputs can capture the daily streamflow chracteristics well overall (with a NS value of 0.56 during calibration period and 0.61 during validation period) but underestimates streamflow obviously (with a BIAS of 42.42 % during calibration period and a BIAS of 33.29 % during validation period). The underestimation of streamflow simulated with CMADS dataset is more seriously in dry seasons ( 48.40 %) than that in wet seasons ( 39.41 %) for calibration period. The model driven by CMADS estimates evapotranspiration and soil moisture content well compared with the model driven by gauge observations. Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessArticle Variations of Surface and Subsurface Water Storage in the Lower Mekong Basin (Vietnam and Cambodia) from Multisatellite Observations
Water 2019, 11(1), 75; https://doi.org/10.3390/w11010075
Received: 31 October 2018 / Revised: 17 December 2018 / Accepted: 30 December 2018 / Published: 4 January 2019
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Abstract
In this study, we estimate monthly variations of surface-water storage (SWS) and subsurface water storage (SSWS, including groundwater and soil moisture) within the Lower Mekong Basin located in Vietnam and Cambodia during the 2003–2009 period. The approach is based on the combination of [...] Read more.
In this study, we estimate monthly variations of surface-water storage (SWS) and subsurface water storage (SSWS, including groundwater and soil moisture) within the Lower Mekong Basin located in Vietnam and Cambodia during the 2003–2009 period. The approach is based on the combination of multisatellite observations using surface-water extent from MODIS atmospherically corrected land-surface imagery, and water-level variations from 45 virtual stations (VS) derived from ENVISAT altimetry measurements. Surface-water extent ranges from ∼6500 to ∼40,000 km 2 during low and high water stages, respectively. Across the study area, seasonal variations of water stages range from 8 m in the upstream parts to 1 m in the downstream regions. Annual variation of SWS is ∼40 km 3 for the 2003–2009 period that contributes to 40–45% of total water-storage (TWS) variations derived from Gravity Recovery And Climate Experiment (GRACE) data. By removing the variations of SWS from GRACE-derived TWS, we can isolate the monthly variations of SSWS, and estimate its mean annual variations of ∼50 km 3 (55–60% of the TWS). This study highlights the ability to combine multisatellite observations to monitor land-water storage and the variations of its different components at regional scale. The results of this study represent important information to improve the overall quality of regional hydrological models and to assess the impacts of human activities on the hydrological cycles. Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessArticle Integration of Remote Sensing Evapotranspiration into Multi-Objective Calibration of Distributed Hydrology–Soil–Vegetation Model (DHSVM) in a Humid Region of China
Water 2018, 10(12), 1841; https://doi.org/10.3390/w10121841
Received: 5 November 2018 / Revised: 4 December 2018 / Accepted: 10 December 2018 / Published: 12 December 2018
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Abstract
This study presents an approach that integrates remote sensing evapotranspiration into multi-objective calibration (i.e., runoff and evapotranspiration) of a fully distributed hydrological model, namely a distributed hydrology–soil–vegetation model (DHSVM). Because of the lack of a calibration module in the DHSVM, a multi-objective calibration [...] Read more.
This study presents an approach that integrates remote sensing evapotranspiration into multi-objective calibration (i.e., runoff and evapotranspiration) of a fully distributed hydrological model, namely a distributed hydrology–soil–vegetation model (DHSVM). Because of the lack of a calibration module in the DHSVM, a multi-objective calibration module using ε-dominance non-dominated sorted genetic algorithm II (ε-NSGAII) and based on parallel computing of a Linux cluster for the DHSVM (εP-DHSVM) is developed. The module with DHSVM is applied to a humid river basin located in the mid-west of Zhejiang Province, east China. The results show that runoff is simulated well in single objective calibration, whereas evapotranspiration is not. By considering more variables in multi-objective calibration, DHSVM provides more reasonable simulation for both runoff (NS: 0.74% and PBIAS: 10.5%) and evapotranspiration (NS: 0.76% and PBIAS: 8.6%) and great reduction of equifinality, which illustrates the effect of remote sensing evapotranspiration integration in the calibration of hydrological models. Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessArticle Evaluation and Hydrological Validation of GPM Precipitation Products over the Nanliu River Basin, Beibu Gulf
Water 2018, 10(12), 1777; https://doi.org/10.3390/w10121777
Received: 17 November 2018 / Revised: 30 November 2018 / Accepted: 30 November 2018 / Published: 3 December 2018
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Abstract
Adequate and high-quality precipitation estimates, from spaceborne precipitation radars, are necessary for a variety of applications in hydrology. In this study, we investigated the performance of two Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG) products, against gauge observations over [...] Read more.
Adequate and high-quality precipitation estimates, from spaceborne precipitation radars, are necessary for a variety of applications in hydrology. In this study, we investigated the performance of two Integrated Multi-satellitE Retrievals for the Global Precipitation Measurement (GPM) mission (IMERG) products, against gauge observations over a small river basin, the Beibu Gulf—the Nanliu River basin, and evaluated their capability of streamflow simulation, based on a conceptual watershed model from April 2014 to December 2016. The results showed that both IMERG_Cal and IMERG_Uncal could roughly capture the spatial patterns of precipitation with slight over/underestimation (Relative Bias (RB) values of 6.5% and −5.5%, respectively) at a basin scale. At grid-cell scales, two IMERG products got an RB of −23.3% to 18.9%, Correlation Coefficient (CC) of 0.521 to 0.744, and Root Mean Square Error (RMSE) of 11.3 to 17.5 mm. There were some considerable errors in heavy precipitation events, and the IMERG significantly overestimated the amounts of these extreme events. The two IMERG products showed a higher accuracy and lower error rate, when detecting the light precipitation. IMERG-driven simulation had a better quality when the model was calibrated with satellite data rather than with rain gauge data. This analysis implied that IMERG products have potential in hydrological applications, in this region, and need further improvement in algorithms. Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessArticle Quantifying the Effects of Dramatic Changes in Runoff and Sediment on the Channel Morphology of a Large, Wandering River Using Remote Sensing Images
Water 2018, 10(12), 1767; https://doi.org/10.3390/w10121767
Received: 17 October 2018 / Revised: 16 November 2018 / Accepted: 27 November 2018 / Published: 1 December 2018
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Abstract
The Yellow River (Huanghe River), which is the second largest river in China, has experienced dramatic changes in both runoff and sediment over the last 60 years. To quantify the effects on the channel morphology of the wandering reach on the Lower Yellow [...] Read more.
The Yellow River (Huanghe River), which is the second largest river in China, has experienced dramatic changes in both runoff and sediment over the last 60 years. To quantify the effects on the channel morphology of the wandering reach on the Lower Yellow River (LYR), this study extracts morphological indices from Landsat imageries taken between 1979 and 2015. Over the dynamically adjusting complex channel-floodplain system, the spatial distribution of NDVI (Normalized Difference Vegetation Index) is found helpful for identifying the wandering belt created by the frequent migrations of the pathways of the main flow, which are determined from the reflection of the sediment-laded water body in remote sensing images taken at low flows. The extracted results show clearly that the average width and area of the wandering belt over the entire study reach declined in a dramatic fashion between 1979 and 2000 and yet both varied respectively within very narrow ranges from 2000 to 2015. Although the number of bends increased significantly since the 1990s, the sinuosity of the pathways of the main flow remained almost unchanged. By combining the morphological indices extracted from the remote sensing images with field hydrological and geomorphological measurements, our regression analysis identifies that the width of the wandering belt changes at the highest degree of correspondence with the width/depth ratio of the main channel and the variations of both are related most closely to the average flow discharge and then to sediment concentration during the flood seasons. These implicate that a significant reduction of the magnitude of floods and sediment concentration is beneficial not only for making the main channel transit from a wider and shallower cross-section into a narrower and deeper profile but also for narrowing the wandering range of the LYR. Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessArticle Evaluating Glacier Volume Changes since the Little Ice Age Maximum and Consequences for Stream Flow by Integrating Models of Glacier Flow and Hydrology in the Cordillera Blanca, Peruvian Andes
Water 2018, 10(12), 1732; https://doi.org/10.3390/w10121732
Received: 25 September 2018 / Revised: 21 November 2018 / Accepted: 23 November 2018 / Published: 26 November 2018
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Abstract
Evaluating the historical contribution of the volume loss of ice to stream flow based on reconstructed volume changes through the Little Ice Age (LIA) can be directly related to the understanding of glacier-hydrology in the current epoch of rapid glacier loss that has [...] Read more.
Evaluating the historical contribution of the volume loss of ice to stream flow based on reconstructed volume changes through the Little Ice Age (LIA) can be directly related to the understanding of glacier-hydrology in the current epoch of rapid glacier loss that has disquieting implications for a water resource in the Cordillera Blanca in the Peruvian Andes. However, the accurate prediction of the future glacial meltwater availability for the developing regional Andean society needs more extensive quantitative estimation from long-term glacial meltwater of reconstructed glacial volume. Modeling the LIA paleoglaciers through the mid-19th century (with the most extensive recent period of mountain glacier expansion having occurred around 1850 AD) in different catchments of the Cordillera Blanca allows us to reconstruct glacier volume and its change from likely combinations of climatic control variables and time. We computed the rate and magnitude of centennial-scale glacier volume changes for glacier surfaces between the LIA and the modern era, as defined by 2011 Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global Digital Elevation Model Version 2 (GDEM V2) and 2008 Light Detection and Range (LiDAR) data. The model simulation showed good agreement with the observed geomorphic data and the volume and surface area (V-S) scaling remained within the 25% error range in the reconstructed simulation. Also, we employed a recently demonstrated approach (Baraër, M. et al.) to calculate meltwater contribution to glacierized catchment runoff. The results revealed multiple peaks of both mean annual and dry season discharge that have never been shown in previous research on the same mountain range. Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessArticle Barrier-based Longitudinal Connectivity Index for Managing Urban Rivers
Water 2018, 10(11), 1701; https://doi.org/10.3390/w10111701
Received: 12 October 2018 / Revised: 14 November 2018 / Accepted: 16 November 2018 / Published: 21 November 2018
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Abstract
A large variety of barriers can affect longitudinal connectivity, which leads to shipping blocking and even flood hazard. However, few existing methods can quantify physically the river channel connectivity from the barrier’s details perspective in a watershed. This paper establishes a new model [...] Read more.
A large variety of barriers can affect longitudinal connectivity, which leads to shipping blocking and even flood hazard. However, few existing methods can quantify physically the river channel connectivity from the barrier’s details perspective in a watershed. This paper establishes a new model of the River Channel Connectivity Index (RCCI) to quantify the unobstructed degree of river flow in river channels within geographic information system (GIS ) platforms based on the modified concept of time accessibility. A comprehensive classification system of barriers is setup before these barriers are identified by the remote sensing technology. The model is applied to Dashi Watershed in suburban Beijing, China. Results show that submersible bridges and sediment siltation are the main barriers in the watershed. RCCI values in the mountainous areas are generally higher than that of the plains. The assessment results verified by two historical flood events show that the RCCI can reveal where the river channel connectivity is impaired, how serious it is, and what the reason is for managers. Through scenarios’ results, the best restoration measure for each tributary is obtained from the perspective of reducing flood hazards. The new RCCI method not only has methodological significance, but also helps policymakers to enhance river flooding reduction and determine restoration priorities of the river channel. Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessArticle Automated Geospatial Models of Varying Complexities for Pine Forest Evapotranspiration Estimation with Advanced Data Mining
Water 2018, 10(11), 1687; https://doi.org/10.3390/w10111687
Received: 25 April 2018 / Revised: 31 August 2018 / Accepted: 12 September 2018 / Published: 19 November 2018
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Abstract
The study goal was to develop automated user-friendly remote-sensing based evapotranspiration (ET) estimation tools: (i) artificial neural network (ANN) based models, (ii) ArcGIS-based automated geospatial model, and (iii) executable software to predict pine forest daily ET flux on a pixel- or plot average-scale. [...] Read more.
The study goal was to develop automated user-friendly remote-sensing based evapotranspiration (ET) estimation tools: (i) artificial neural network (ANN) based models, (ii) ArcGIS-based automated geospatial model, and (iii) executable software to predict pine forest daily ET flux on a pixel- or plot average-scale. Study site has had long-term eddy-flux towers for ET measurements since 2006. Cloud-free Landsat images of 2006−2014 were processed using advanced data mining to obtain Principal Component bands to correlate with ET data. The regression model’s r2 was 0.58. The backpropagation neural network (BPNN) and radial basis function network (RBFN) models provided a testing/validation average absolute error of 0.18 and 0.15 Wm−2 and average accuracy of 81% and 85%, respectively. ANN models though robust, require special ANN software and skill to operate; therefore, automated geospatial model (toolbox) was developed on ArcGIS ModelBuilder as user-friendly alternative. ET flux map developed with model tool provided consistent ET patterns for landuses. The software was developed for lay-users for ET estimation. Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessArticle Detecting Snowfall Events over Mountainous Areas Using Optical Imagery
Water 2018, 10(11), 1514; https://doi.org/10.3390/w10111514
Received: 16 August 2018 / Revised: 16 October 2018 / Accepted: 21 October 2018 / Published: 25 October 2018
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Abstract
Snowfall over mountainous areas not only has important implications on the water cycle and the Earth’s radiation balance, but also causes potentially hazardous weather. However, snowfall detection remains one of the most difficult problems in modern hydrometeorology. We present a method for detecting [...] Read more.
Snowfall over mountainous areas not only has important implications on the water cycle and the Earth’s radiation balance, but also causes potentially hazardous weather. However, snowfall detection remains one of the most difficult problems in modern hydrometeorology. We present a method for detecting snowfall events from optical satellite data for seasonal snow in mountainous areas. The proposed methodology is based on identifying expanded snow cover or suddenly declined snow grain size using time series images, from which it is possible to detect the location and time of snowfall events. The methodology was tested with Moderate Resolution Imaging Spectroradiometer (MODIS) daily radiance data for an entire hydrologic year from July 2014 to June 2015 in the mountainous area of the Manas River Basin, Northwest China. The study evaluated the recordings of precipitation events at eighteen meteorological stations in the study area prove the effectiveness of the proposed method, showing that there was more liquid precipitation in the second and third quarter, and more solid precipitation in the first and fourth quarter. Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessArticle Characterizing Hydrological Connectivity of Artificial Ditches in Zoige Peatlands of Qinghai-Tibet Plateau
Water 2018, 10(10), 1364; https://doi.org/10.3390/w10101364
Received: 6 September 2018 / Revised: 26 September 2018 / Accepted: 28 September 2018 / Published: 30 September 2018
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Abstract
Peats have the unique ability of effectively storing water and carbon. Unfortunately, this ability has been undermined by worldwide peatland degradation. In the Zoige Basin, located in the northeastern Qinghai-Tibet Plateau, China, peatland degradation is particularly severe. Although climate change and (natural and [...] Read more.
Peats have the unique ability of effectively storing water and carbon. Unfortunately, this ability has been undermined by worldwide peatland degradation. In the Zoige Basin, located in the northeastern Qinghai-Tibet Plateau, China, peatland degradation is particularly severe. Although climate change and (natural and artificial) drainage systems have been well-recognized as the main factors catalyzing this problem, little is known about the impact of the latter on peatland hydrology at larger spatial scales. To fill this gap, we examined the hydrological connectivity of artificial ditch networks using Google Earth imagery and recorded hydrological data in the Zoige Basin. After delineating from the images of 1392 ditches and 160 peatland patches in which these ditches were clustered, we calculated their lengths, widths, areas, and slopes, as well as two morphological parameters, ditch density (Dd) and drainage ability (Pa). The subsequent statistical analysis and examination of an index defined as the product Dd and Pa showed that structural hydrological connectivity, which was quantitatively represented by the value of this index, decreased when peatland patch areas increased, suggesting that ditches in small patches have higher degrees of hydrological connectivity. Using daily discharge data from three local gauging stations and Manning’s equation, we back-calculated the mean ditch water depths (Dm) during raining days of a year and estimated based on Dm the total water volume drained from ditches in each patch (V) during annual raining days. We then demonstrated that functional hydrological connectivity, which may be represented by V, generally decreased when patch areas increased, more sensitive to changes of ditch number and length in larger peatland patches. Furthermore, we found that the total water volume drained from all ditches during annual raining days only took a very small proportion of the total volume of stream flow out of the entire watershed (0.0012%) and this nature remained similar for the past 30 years, suggesting that during annual rainfall events, water drained from connected ditches is negligible. This revealed that the role of connected artificial ditches in draining peatland water mainly takes effect during the prolonged dry season of a year in the Zoige Basin. Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessArticle Modelling Groundwater Flow with MIKE SHE Using Conventional Climate Data and Satellite Data as Model Forcing in Haihe Plain, China
Water 2018, 10(10), 1295; https://doi.org/10.3390/w10101295
Received: 3 July 2018 / Revised: 28 August 2018 / Accepted: 17 September 2018 / Published: 20 September 2018
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Abstract
In North China Plain, accurate spatial and temporal ET and precipitation pattern is very important in the groundwater resource assessment. This study demonstrated the potential for modelling ET and groundwater processes using remote sensing data for distributed hydrological modelling with MIKE SHE codes [...] Read more.
In North China Plain, accurate spatial and temporal ET and precipitation pattern is very important in the groundwater resource assessment. This study demonstrated the potential for modelling ET and groundwater processes using remote sensing data for distributed hydrological modelling with MIKE SHE codes in the Haihe Plain, China. The model was successfully validated against independent groundwater level measurements following the calibration period and the model also provided a reasonable match of the lysimeter measurements of ET. The remote sensing data included ET derived from global radiation products of Fengyun-2C geostationary meteorological satellite (FY-2C) and FY-2C precipitation products. The comparisons show that precipitation is a critical factor for the hydrological response and for the spatial distribution of ET and groundwater flow. FY-2C precipitation products has a spatial resolution of about 11 km, which thus adds more spatial variability to the most important driving variable. The ET map based on FY-2C data has a higher spatial variability than that map based on conventional data, which are caused by higher resolution of ground information. The groundwater level changes in the aquifer system are shown in the quite different spatial patterns under two models, which is affected by the significant difference between two types of precipitation. In the Haihe Plain, accurate spatial and temporal ET pattern is very important in the groundwater resource assessment that determines the recharge to the saturated zone. Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessArticle Development of RiverBox—An ArcGIS Toolbox for River Bathymetry Reconstruction
Water 2018, 10(9), 1266; https://doi.org/10.3390/w10091266
Received: 29 August 2018 / Revised: 13 September 2018 / Accepted: 13 September 2018 / Published: 17 September 2018
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The main purpose of the present research is to develop software for reconstruction of the river bed on the basis of sparse cross-section measurements. The tools prepared should support the process of hydrodynamic model preparation for simulation of river flow. Considering the formats [...] Read more.
The main purpose of the present research is to develop software for reconstruction of the river bed on the basis of sparse cross-section measurements. The tools prepared should support the process of hydrodynamic model preparation for simulation of river flow. Considering the formats of available data and the requirements of modern modeling techniques, the prepared software is fully integrated with the GIS environment. The scripting language Python 2.7 implemented in ArcGIS 10.5.1 was chosen for this purpose. Two study cases were selected to validate and test the prepared procedures. These are stream reaches in Poland. The first is located on the Warta river, and the second on the Ner river. The data necessary for the whole procedure are: a digital elevation model, measurements of the cross-sections in the form of points, and two polyline layers representing an arbitrary river centerline and river banks. In the presented research the concept of a channel-oriented coordinate system is applied. The elevations are linearly interpolated along the longitudinal and transversal directions. The interpolation along the channel is implemented in three computational schemes linking different tools available in ArcGIS and ArcToolbox. A simplified comparison of memory usage and computational time is presented. The scheme linking longitudinal and spatial interpolation algorithms seems to be the most advantageous. Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessArticle Land Use and Land Cover Changes and Their Effect on the Flow Regime in the Upstream Dong Nai River Basin, Vietnam
Water 2018, 10(9), 1206; https://doi.org/10.3390/w10091206
Received: 19 June 2018 / Revised: 26 August 2018 / Accepted: 5 September 2018 / Published: 7 September 2018
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Abstract
The upstream Dong Nai River Basin is located in the country’s key economic development region and its water resources are a key component of sustainable regional development. The objective of this study was to assess the impact of land use and land cover [...] Read more.
The upstream Dong Nai River Basin is located in the country’s key economic development region and its water resources are a key component of sustainable regional development. The objective of this study was to assess the impact of land use and land cover changes (LULCC) on the flow regime in this tropical forest basin using a flow–duration curve analysis that has been widely used in Japan. This study combined two different temporal and spatial scales of satellite data, Landsat and Global Inventory Modeling, and Mapping Studies (GIMMS) normalized difference vegetation index (NDVI) to analyze LUCC. Results from the land cover classification of five Landsat images between 1973 and 2014 indicated that the forest area decreased significantly in the period of 1994 to 2005 due to population growth, leading to land conversion for agriculture. Furthermore, secular changes in the annual GIMMS-NDVI data revealed that land cover changes occurred from 1996 and a large amount of forest was lost in 1999; however, due to the rapid regrowth of secondary forest of tropical forests and the development of the crop, the vegetation recovered shortly afterwards in 2000 before decreasing again after 2004. Following large-scale deforestation, the total discharge, maximum flow, and the plentiful, ordinary, low, and small-scale runoff increased sharply and decreased thereafter because of vegetation regrowth. Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessArticle Variations of the Snow Water Equivalent in the Ourika Catchment (Morocco) over 2000–2018 Using Downscaled MERRA-2 Data
Water 2018, 10(9), 1120; https://doi.org/10.3390/w10091120
Received: 29 June 2018 / Revised: 2 August 2018 / Accepted: 3 August 2018 / Published: 23 August 2018
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Abstract
The Ourika River is an important tributary of the Tensift River in the water-stressed region of Marrakesh (Morocco). The Ourika river flow is dominated by the snow melt contribution from the High Atlas mountains. Despite its importance in terms of water resources, the [...] Read more.
The Ourika River is an important tributary of the Tensift River in the water-stressed region of Marrakesh (Morocco). The Ourika river flow is dominated by the snow melt contribution from the High Atlas mountains. Despite its importance in terms of water resources, the snow water equivalent (SWE) is poorly monitored in the Ourika catchment. Here, we used MERRA-2 data to run a distributed energy-balance snowpack model (SnowModel) over 2000–2018. MERRA-2 data were downscaled to 250-m spatial resolution using a digital elevation model. The model outputs were compared to in situ measurements of snow depth, precipitation, river flow and remote sensing observations of the snow cover area from MODIS. The results indicate that the model provides an overall acceptable representation of the snow cover dynamics given the coarse resolution of the MERRA-2 forcing. Then, we used the model output to analyze the spatio-temporal variations of the SWE in the Ourika catchment for the first time. We suggest that MERRA-2 data, which are routinely available with a delay of a few weeks, can provide valuable information to monitor the snow resource in high mountain areas without in situ measurements. Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessArticle Integration of DSM and SPH to Model Tailings Dam Failure Run-Out Slurry Routing Across 3D Real Terrain
Water 2018, 10(8), 1087; https://doi.org/10.3390/w10081087
Received: 6 July 2018 / Revised: 3 August 2018 / Accepted: 9 August 2018 / Published: 16 August 2018
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Abstract
Tailings dam failure accidents occur frequently, causing substantial damage and loss of human and animal life. The prediction of run-out tailings slurry routing following dam failures is of great significance for disaster prevention and mitigation. Using satellite remote sensing digital surface model (DSM) [...] Read more.
Tailings dam failure accidents occur frequently, causing substantial damage and loss of human and animal life. The prediction of run-out tailings slurry routing following dam failures is of great significance for disaster prevention and mitigation. Using satellite remote sensing digital surface model (DSM) data, tailings pond parameters and the advanced meshless smoothed particle hydrodynamics (SPH) method, a 3D real-scale numerical modelling method was adopted to study the run-out tailings slurry routing across real downstream terrains that have and have not been affected by dam failures. Three case studies, including a physical modelling experiment, the 2015 Brazil Fundão tailings dam failure accident and an operating high-risk tailings pond in China, were carried out. The physical modelling experiment and the known consequences were successfully modeled and validated using the SPH method. This and the other experiments showed that the run-out tailings slurry would be tremendously destructive in the early stages of dam failure, and emergency response time would be extremely short if the dam collapses at its full designed capacity. The results could provide evidence for disaster prevention and mitigation engineering, emergency management plan optimization, and the development of more responsible site plans and sustainable site designs. However, improvements such as rheological model selection, terrain data quality, computing efficiency and land surface roughness need to be made for future studies. SPH numerical modelling is a powerful and advanced technique that is recommended for hazard assessment and the sustainable design of tailings dam facilities globally. Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessArticle Radar Data Analyses for a Single Rainfall Event and Their Application for Flow Simulation in an Urban Catchment Using the SWMM Model
Water 2018, 10(8), 1007; https://doi.org/10.3390/w10081007
Received: 31 May 2018 / Revised: 20 July 2018 / Accepted: 30 July 2018 / Published: 30 July 2018
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Abstract
The disadvantage of radar measurements is that the obtained rainfall data is imprecise. Therefore, the use of radar data in hydrological applications usually requires correction. The main aim of the study was to verify and optimize various methods of estimating the rainfall depths [...] Read more.
The disadvantage of radar measurements is that the obtained rainfall data is imprecise. Therefore, the use of radar data in hydrological applications usually requires correction. The main aim of the study was to verify and optimize various methods of estimating the rainfall depths for single events based on radar data, as well as determining their influence on the values of peak flow and outflow volume of hydrographs simulated using the SWMM (Storm Water Management Model) hydrodynamic model. Regression analyses were used to find a relationship between the rain gauge rainfall rate R and radar reflectivity Z for the urban catchment of the Służewiecki Stream in Warsaw, Poland. Five methods for determining calculational values of radar reflectivity in reference to specific rainfall cells with 1 km resolution within an event duration were applied. Moreover, the correction coefficient for data from the SRI (Surface Rainfall Intensity) product was established. The Z-R relationships determined in this study offer much better rainfall rate estimation as compared to Marshall-Palmer’s relationship. Different scenarios were applied to investigate the stream response to changes in rainfall depths estimated on the basis of radar data, in which the data both for 2 existing, as well as 64 virtual, rain gauges assigned to appropriate rainfall cells in the catchment were included. Relatively good agreement was achieved between the measured parameters of the hydrograph of flows and those simulated in response to rainfall depths which had been calculated for single events using the correction coefficient and the determined Z-R relationships. Radar estimates of rainfall depths based on the tested methods can be used as input data to the SWMM model for the purpose of simulating flows in the investigated urban catchment. Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessArticle Assessing Vegetation Response to Soil Moisture Fluctuation under Extreme Drought Using Sentinel-2
Water 2018, 10(7), 838; https://doi.org/10.3390/w10070838
Received: 31 May 2018 / Revised: 12 June 2018 / Accepted: 21 June 2018 / Published: 24 June 2018
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Abstract
The aim of this study was to determine the extent to which Sentinel-2 Normalised Difference Vegetation Index (NDVI) reflects soil moisture conditions, and whether this product offers an improvement over Landsat-8. Based on drought exposure, cloud-free imagery availability, and measured soil moisture, five [...] Read more.
The aim of this study was to determine the extent to which Sentinel-2 Normalised Difference Vegetation Index (NDVI) reflects soil moisture conditions, and whether this product offers an improvement over Landsat-8. Based on drought exposure, cloud-free imagery availability, and measured soil moisture, five sites in the Southwestern United States were selected. These sites, normally dry to arid, were in various states of drought. A secondary focus was therefore the performance of the NDVI under extreme conditions. Following supervised classification, the NDVI values for one-kilometre radius areas were calculated. Sentinel-2 NDVI variants using Spectral Bands 8 (10 m spatial resolution), 5, 6, 7, and 8A (20 m spatial resolution) were calculated. Landsat-8 NDVI was calculated at 30 m spatial resolution. Pearson correlation analysis was undertaken for NDVI against moisture at various depths. To assess the difference in correlation strength, a principal component analysis was performed on the combination of all bands and the combination of the new red-edge bands. Performance of the red-edge NDVI against the standard near infrared (NIR) was then evaluated using a Steiger comparison. No significant correlations between Landsat-8 NDVI and soil moisture were found. Significant correlations at depths of less than 30 cm were present between Sentinel-2 NDVI and soil moisture at three sites. The remaining two sites were characterised by low vegetation cover, suggesting a cover threshold of approximately 30–40% is required for a correlation to be present. At all sites of significant positive moisture to NDVI correlation, the linear combination of the red-edge bands produced stronger correlations than the poorer spectral but higher spatial resolution band. NDVI calculated using the higher spectral resolution bands may therefore be of greater use in this context than the higher spatial resolution option. Results suggest potential for the application of Sentinel-2 NDVI in soil moisture monitoring, even in extreme environments. To the best of our knowledge, this paper represents the first study of this kind using Sentinel-2. Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessArticle Satellite-Based, Multi-Indices for Evaluation of Agricultural Droughts in a Highly Dynamic Tropical Catchment, Central Vietnam
Water 2018, 10(5), 659; https://doi.org/10.3390/w10050659
Received: 23 January 2018 / Revised: 13 May 2018 / Accepted: 15 May 2018 / Published: 18 May 2018
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Abstract
Characterization of droughts using satellite-based data and indices in a steep, highly dynamic tropical catchment, like Vu Gia Thu Bon, which is the most important basin in central Vietnam, has remained a challenge for many years. This study examined the six widely used [...] Read more.
Characterization of droughts using satellite-based data and indices in a steep, highly dynamic tropical catchment, like Vu Gia Thu Bon, which is the most important basin in central Vietnam, has remained a challenge for many years. This study examined the six widely used vegetation indices (VIs) to effectively monitor droughts that are based on their sensitivity with precipitation, soil moisture, and their linkage with the impacts on agricultural crop production and forest fires. Six VIs representing the four main groups, including greenness-based VIs (Vegetation Condition Index), water-based VIs (Normalized Difference Water Index, Land Surface Water Index), temperature-based VIs (Temperature Condition Index), and combined VIs (Vegetation Health Index, Normalized Difference Drought Index) were tested using MODIS data from January 2001 to December 2016 with the support of cloud-based Google Earth Engine computational platform. Results showed that droughts happened almost every year, but with different intensity. Vegetation stress was found to be mainly attributed to precipitation in the rice paddy fields and to temperature in the forest areas. Findings revealed that combined vegetation indices were more sensitive drought indicators in the basin, whereas their performance was different by vegetation type. In the rice paddy fields, NDDI was more sensitive to precipitation than other indices; it better captured droughts and their impacts on crop yield. In the forest areas, VHI was more sensitive to temperature, and thus had better performance than other VIs. Accordingly, NDDI and VHI were recommended for monitoring droughts in the agricultural and forest lands, respectively. The findings from this study are crucial to map drought risks and prepare an effective mitigation plan for the basin. Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessArticle Daily Evapotranspiration Estimation at the Field Scale: Using the Modified SEBS Model and HJ-1 Data in a Desert-Oasis Area, Northwestern China
Water 2018, 10(5), 640; https://doi.org/10.3390/w10050640
Received: 11 April 2018 / Revised: 8 May 2018 / Accepted: 9 May 2018 / Published: 15 May 2018
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Abstract
Accurate continuous daily evapotranspiration (ET) at the field scale is crucial for allocating and managing water resources in irrigation areas, particularly in arid and semi-arid regions. The authors integrated the modified perpendicular drought index (MPDI) as an indicator of water stress into surface [...] Read more.
Accurate continuous daily evapotranspiration (ET) at the field scale is crucial for allocating and managing water resources in irrigation areas, particularly in arid and semi-arid regions. The authors integrated the modified perpendicular drought index (MPDI) as an indicator of water stress into surface energy balance system (SEBS) to improve ET estimation under water-limited conditions. The new approach fed with Chinese satellite HJ-1 (environmental and disaster monitoring and forecasting with a small satellite constellation) images was used to map daily ET on the desert-oasis irrigation fields in the middle of the Heihe River Basin. The outputs, including instantaneous sensible heat flux (H) and daily ET from the MPDI-integrated SEBS and the original SEBS model, were compared with the eddy covariance observations. The results indicate that the MPDI-integrated SEBS significantly improved the surface turbulent fluxes in water-limited regions, especially for sparsely vegetated areas. The new approach only uses one optical satellite data and meteorological data as inputs, providing a considerable operational improvement for ET mapping. Moreover, HJ-1 high-resolution data promised continuous daily ET at the field scale, which helps in understanding the corresponding relationships among field, crop, and water consumption. Such detailed ET information can greatly serve water resources management in the study area as well as other arid and semi-arid regions. Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessArticle Topography-Related Glacier Area Changes in Central Tianshan from 1989 to 2015 Derived from Landsat Images and ASTER GDEM Data
Water 2018, 10(5), 555; https://doi.org/10.3390/w10050555
Received: 13 March 2018 / Revised: 18 April 2018 / Accepted: 23 April 2018 / Published: 25 April 2018
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Abstract
Studies have investigated the glacier projected area (2D Area) on a horizontal plane, which is much smaller than the glacier topographic surface extent (3D Area) in steep terrains. This study maps the glacier outline in Central Tianshan using Landsat images from four periods, [...] Read more.
Studies have investigated the glacier projected area (2D Area) on a horizontal plane, which is much smaller than the glacier topographic surface extent (3D Area) in steep terrains. This study maps the glacier outline in Central Tianshan using Landsat images from four periods, i.e., 1989, 2002, 2007 and 2015, by an object-based classification approach, and analyzes the glacier 2D and 3D area changes related to topographic factors based on Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) Global DEM data. This approach shows an accuracy of 90.8% for clean ice mapping. The derived clean ice outlines are in good agreement with the 2nd Chinese Glacier Inventory (CGI2) and the Global Land Ice Measurements from Space (GLIMS). The fields with a northern aspect receive the least surface solar radiation, leading to dominant existing glaciers. Glaciers are near evenly distributed in slope zones of 0° to 50° and have a mean slope angle of 28.8°, resulting in a 30.3% larger 3D area than the 2D area in 2015 in Central Tianshan. The glacier 2D area decreased by 404 km2 (−8.1%) between 1989 and 2015, while the 3D area declined by 516 km2 (−7.9%). The glacier 2D area showed a reduction of −1.8% between 1989 and 2002, −3.8% between 2002 and 2007, and −2.7% between 2007 and 2015, and these retreating rates closely responded to the variations of regional mean air temperature and precipitation. Topographically, most reductions occurred in elevation bands of 3000–4000 m and in slope zones of 10–20° and 40–50°, and in the eastern aspect fields. The northern Tekes River catchment had the largest shrinking rate of −17.0% (2D area), followed by the southern Karasu River (−14.2%) and Muzart River (−7.7%) catchments. In contrast, glaciers in the Kumerik/Aksu and Tailan River catchments in the Tuomuer region showed little change (−2%). Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessArticle An Efficient Method for Mapping High-Resolution Global River Discharge Based on the Algorithms of Drainage Network Extraction
Water 2018, 10(4), 533; https://doi.org/10.3390/w10040533
Received: 25 March 2018 / Revised: 17 April 2018 / Accepted: 20 April 2018 / Published: 23 April 2018
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Abstract
River discharge, which represents the accumulation of surface water flowing into rivers and ultimately into the ocean or other water bodies, may have great impacts on water quality and the living organisms in rivers. However, the global knowledge of river discharge is still [...] Read more.
River discharge, which represents the accumulation of surface water flowing into rivers and ultimately into the ocean or other water bodies, may have great impacts on water quality and the living organisms in rivers. However, the global knowledge of river discharge is still poor and worth exploring. This study proposes an efficient method for mapping high-resolution global river discharge based on the algorithms of drainage network extraction. Using the existing global runoff map and digital elevation model (DEM) data as inputs, this method consists of three steps. First, the pixels of the runoff map and the DEM data are resampled into the same resolution (i.e., 0.01-degree). Second, the flow direction of each pixel of the DEM data (identified by the optimal flow path method used in drainage network extraction) is determined and then applied to the corresponding pixel of the runoff map. Third, the river discharge of each pixel of the runoff map is calculated by summing the runoffs of all the pixels in the upstream of this pixel, similar to the upslope area accumulation step in drainage network extraction. Finally, a 0.01-degree global map of the mean annual river discharge is obtained. Moreover, a 0.5-degree global map of the mean annual river discharge is produced to display the results with a more intuitive perception. Compared against the existing global river discharge databases, the 0.01-degree map is of a generally high accuracy for the selected river basins, especially for the Amazon River basin with the lowest relative error (RE) of 0.3% and the Yangtze River basin within the RE range of ±6.0%. However, it is noted that the results of the Congo and Zambezi River basins are not satisfactory, with RE values over 90%, and it is inferred that there may be some accuracy problems with the runoff map in these river basins. Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessArticle Inundation Analysis of Reservoir Flood Based on Computer Aided Design (CAD) and Digital Elevation Model (DEM)
Water 2018, 10(4), 530; https://doi.org/10.3390/w10040530
Received: 23 February 2018 / Revised: 2 April 2018 / Accepted: 16 April 2018 / Published: 23 April 2018
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Abstract
GIS (Geographic Information System) can be used to combine multiple hydrologic data and geographic data for FIA (Flood Impact Assessment). For a developing country like China, a lot of geographic data is in the CAD (Computer Aided Design) format. The commonly used method [...] Read more.
GIS (Geographic Information System) can be used to combine multiple hydrologic data and geographic data for FIA (Flood Impact Assessment). For a developing country like China, a lot of geographic data is in the CAD (Computer Aided Design) format. The commonly used method for converting CAD into DEM may result in data loss. This paper introduces a solution for the conversion between CAD data and DEM data. The method has been applied to the FIA based on the topographic map of CAD in Hanjiang River. When compared with the other method, the new method solves the data loss problem. Besides, the paper use GIS to simulate the inundation range, area, and the depth distribution of flood backwater. Based on the analysis, the author concludes: (1) the differences of the inundation areas between the flood of HQ100 and the flood of HQ50 are small. (2) The inundation depth shows a decreasing trend along the upstream of the river. (3) The inundation area less than 4 m in flood of HQ50 is larger than that in flood of HQ100, the result is opposite when the inundation depth is greater than 4 m. (4) The flood loss is 392.32 million RMB for flood of HQ50 and 610.02 million RMB for flood of HQ100. The method can be applied to FIA. Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessArticle Glacial Lake Detection from GaoFen-2 Multispectral Imagery Using an Integrated Nonlocal Active Contour Approach: A Case Study of the Altai Mountains, Northern Xinjiang Province
Water 2018, 10(4), 455; https://doi.org/10.3390/w10040455
Received: 15 March 2018 / Revised: 4 April 2018 / Accepted: 6 April 2018 / Published: 10 April 2018
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Abstract
Due to recent global climate change, glacial lake outburst floods (GLOFs) have become a serious problem in many high mountain areas. Accurately and rapidly mapping glacial lakes is the basis of other glacial lake studies that are associated with water resources management, flood [...] Read more.
Due to recent global climate change, glacial lake outburst floods (GLOFs) have become a serious problem in many high mountain areas. Accurately and rapidly mapping glacial lakes is the basis of other glacial lake studies that are associated with water resources management, flood hazard assessment, and climate change. Most glacial lake detection studies have mainly used medium to coarse resolution images, whose application is limited to large lakes. Because small glacial lakes are abundant and because changes in these lakes are small and occur around the lake shores, fine-resolution satellite imagery is required for adequate assessments. In addition, the existing detection methods are mainly based on simply applying a threshold on various normalized difference water indices (NDWIs); this cannot give appropriate results for glacial lakes that have a wide range of turbidity, mineral, and chlorophyll content. In the present study, we propose a region-dependent framework to overcome the spectral heterogeneity of glacial lake areas using a nonlocal active contour model that is integrated with the NDWI. As the first trial, the glacial lakes were detected using high-resolution GaoFen-2 multispectral imagery in the test site of Altai Mountains (northern Xinjiang Province). The validation of the results was carried out using the manually digitized lake boundaries. The average probabilities of false positives P F P and false negatives P F N were found to be 0.0106 and 0.0039, respectively. After taking into consideration the spectral features of the water and making slight NDWI threshold adjustments, this method can also be used for lake detection in any glaciated environment elsewhere in the world. Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessFeature PaperArticle Unstructured-Mesh Terrain Analysis and Incident Solar Radiation for Continuous Hydrologic Modeling in Mountain Watersheds
Water 2018, 10(4), 398; https://doi.org/10.3390/w10040398
Received: 26 February 2018 / Revised: 20 March 2018 / Accepted: 22 March 2018 / Published: 28 March 2018
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Abstract
This article presents a methodology for estimating total incoming solar radiation from Triangular Irregular Network (TIN) topographic meshes. The algorithm also computes terrain slope degree and aspect (slope orientation) and accounts for self shading and cast shadows, sky view fractions for diffuse radiation, [...] Read more.
This article presents a methodology for estimating total incoming solar radiation from Triangular Irregular Network (TIN) topographic meshes. The algorithm also computes terrain slope degree and aspect (slope orientation) and accounts for self shading and cast shadows, sky view fractions for diffuse radiation, remote albedo and atmospheric backscattering, by using a vectorial approach within a topocentric coordinate system establishing geometric relations between groups of TIN elements and the sun position. A normal vector to the surface of each TIN element describes its slope and aspect while spherical trigonometry allows computing a unit vector defining the position of the sun at each hour and day of the year. Sky view fraction, useful to determine diffuse and backscattered radiation, is computed for each TIN element at prescribed azimuth intervals targeting the steepest elevation gradient. A comparison between the sun zenith angle and the steepest gradient allows deciding whether or not the pivot element is shaded. Finally, remote albedo is computed from the sky view fraction complementary functions for observed albedo values of the surrounding terrain. The sensitivity of the different radiative components to seasonal changes in atmospheric transmissivitties and surrounding albedo is tested in a mountainous watershed in Wyoming. This methodology represents an improvement on the current algorithms to compute terrain and radiation values on unstructured-mesh terrain models. All terrain-related features (e.g., slope, aspect, sky view fraction) can be pre-computed and stored for easy access into a subsequent, progressive-in-time, numerical simulation. Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessArticle Land Water-Storage Variability over West Africa: Inferences from Space-Borne Sensors
Water 2018, 10(4), 380; https://doi.org/10.3390/w10040380
Received: 22 December 2017 / Revised: 13 March 2018 / Accepted: 22 March 2018 / Published: 25 March 2018
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Abstract
The potential of terrestrial water storage (TWS) inverted from Gravity Recovery and Climate Experiment (GRACE) measurements to investigate water variations and their response to droughts over the Volta, Niger, and Senegal Basins of West Africa was investigated. An altimetry-imagery approach was proposed to [...] Read more.
The potential of terrestrial water storage (TWS) inverted from Gravity Recovery and Climate Experiment (GRACE) measurements to investigate water variations and their response to droughts over the Volta, Niger, and Senegal Basins of West Africa was investigated. An altimetry-imagery approach was proposed to deduce the contribution of Lake Volta to TWS as “sensed” by GRACE. The results showed that from April 2002 to July 2016, Lake Volta contributed to approximately 8.8% of the water gain within the Volta Basin. As the signal spreads out far from the lake, it impacts both the Niger and Senegal Basins with 1.7% (at a significance level of 95%). This figure of 8.8% for the Volta Basin is approximately 20% of the values reported in previous works. Drought analysis based on GRACE-TWS (after removing the lake’s contribution) depicted below-normal conditions prevailing from 2002 to 2008. Wavelet analysis revealed that TWS changes (fluxes) and rainfall as well as vegetation index depicted a highly coupled relationship at the semi-annual to biennial periods, with common power covariance prevailing in the annual frequencies. While acknowledging that validation of the drought occurrence and severity based on GRACE-TWS is needed, we believe that our findings shall contribute to the water management over West Africa. Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessArticle Water Level Measurements from Drones: A Pilot Case Study at a Dam Site
Water 2018, 10(3), 297; https://doi.org/10.3390/w10030297
Received: 10 January 2018 / Revised: 21 February 2018 / Accepted: 6 March 2018 / Published: 9 March 2018
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Abstract
Unmanned Aerial Vehicles (UAVs) are now filling in the gaps between spaceborne and ground-based observations and enhancing the spatial resolution and temporal coverage of data acquisition. In the realm of hydrological observations, UAVs play a key role in quantitatively characterizing the surface flow, [...] Read more.
Unmanned Aerial Vehicles (UAVs) are now filling in the gaps between spaceborne and ground-based observations and enhancing the spatial resolution and temporal coverage of data acquisition. In the realm of hydrological observations, UAVs play a key role in quantitatively characterizing the surface flow, allowing for remotely accessing the water body of interest. In this paper, we propose a technology that uses a sensing platform encompassing a drone and a camera to determine the water level. The images acquired by means of the sensing platform are then analyzed using the Canny method to detect the edges of water level and of Ground Control Points (GCPs) used as reference points. The water level is then retrieved from images and compared to a benchmark value obtained by a traditional device. The method is tested at four locations in an artificial lake in central Italy. Results are encouraging, as the overall mean error between estimated and true water level values is around 0.05 m. This technology is well suited to improve hydraulic modeling and thus provides reliable support to flood mitigation strategies. Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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Open AccessArticle Potential of Sentinel-1 Images for Estimating the Soil Roughness over Bare Agricultural Soils
Water 2018, 10(2), 131; https://doi.org/10.3390/w10020131
Received: 13 December 2017 / Revised: 24 January 2018 / Accepted: 29 January 2018 / Published: 31 January 2018
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Abstract
The purpose of this study is to analyze the potential of Sentinel-1 C-band SAR data in VV polarization for estimating the surface roughness (Hrms) over bare agricultural soils. An inversion technique based on Multi-Layer Perceptron neural networks is used. It involves [...] Read more.
The purpose of this study is to analyze the potential of Sentinel-1 C-band SAR data in VV polarization for estimating the surface roughness (Hrms) over bare agricultural soils. An inversion technique based on Multi-Layer Perceptron neural networks is used. It involves two steps. First, a neural network (NN) is used for estimating the soil moisture without taking into account the soil roughness. Then, a second neural network is used for retrieving the soil roughness when using as an input to the network the soil moisture that was estimated by the first network. The neural networks are trained and validated using simulated datasets generated from the radar backscattering model IEM (Integral Equation Model) with the range of soil moisture and surface roughness encountered in agricultural environments. The inversion approach is then validated using Sentinel-1 images collected over two agricultural study sites, one in France and one in Tunisia. Results show that the use of C-band in VV polarization for estimating the soil roughness does not allow a reliable estimate of the soil roughness. From the synthetic dataset, the achievable accuracy of the Hrms estimates is about 0.94 cm when using the soil moisture estimated by the NN built with a priori information on the moisture volumetric content “mv” (accuracy of mv is about 6 vol. %). In addition, an overestimation of Hrms for low Hrms-values and an underestimation of Hrms for Hrms higher than 2 cm are observed. From a real dataset, results show that the accuracy of the estimates of Hrms in using the mv estimated over a wide area (few km2) is similar to that in using the mv estimated at the plot scale (RMSE about 0.80 cm). Full article
(This article belongs to the Special Issue Applications of Remote Sensing and GIS in Hydrology)
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