Special Issue "South American Hydrology and Remote Sensing (South America Water from Space)"

A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".

Deadline for manuscript submissions: 10 September 2021.

Special Issue Editors

Dr. Rodrigo Abarca Del Rio
E-Mail Website
Guest Editor
Departamento de Geofísica (DGEO), Universidad de Concepción (UDEC), Casilla: 160-C, Barrió Universitario S/N, Concepción, Chile
Interests: satellite remote sensing for hydrology; data analysis; lakes; hydroclimate
Special Issues and Collections in MDPI journals
Dr. Daniel Moreira
E-Mail Website
Guest Editor
Companhia De Pesquisa de Recursos Minerais (CPRM) - Geological Survey of Brazil, Department of Hydrology (DEHID), Avenida Pasteur, 404, UrcA, Rio de Janeiro (RJ), 22290-040, Brazil
Interests: geodesy; remote sensing and hydrology
Dr. Fabrice Papa
E-Mail Website
Guest Editor
Institut de Recherche pour le Développement (IRD), LEGOS (Laboratoire d’Etudes en Géophysique et Océanographie Spatiales), Observatoire Midi-Pyrénées (OMP), 14, Avenue Edouard Belin, 31400, Toulouse, France
Interests: remote sensing; hydrology; water cycle; tropical climate variability
Special Issues and Collections in MDPI journals
Dr. Rodrigo Paiva
E-Mail Website
Guest Editor
Grupo Hidrologia de Grande Escala (HGE), Instituto de Pesquisas Hidráulicas –Universidade Federal do Rio Grande do Sul (IPH –UFRGS), Av. Bento Gonçalves, 9500 –Caixa Postal 15029CEP 91501-970 –Porto Alegre –RS, Brazil
Interests: hydrology; hydrodynamics; remote sensing; continental scale hydrology; modeling water systems
Dr. Marielle Gosset
E-Mail Website
Guest Editor
Geoscience Environnement Toulouse (GET), OMP, 14 avenue Edouard Belin, 31400, Toulouse, France
Interests: hydrometeorology; remote sensing; weather radar; hydrology; innovative sensors
Dr. Waldo Lavado
E-Mail Website
Guest Editor
Peruvian National Service of Meteorology and Hydrology (SENAHMI), Jr. Cahuide 785 Lima 13, Peru
Interests: hydrological models; hydroclimatological data; remote sensing; landslides; water security; hydroclimatology
Dr. Jean-Francois Cretaux
E-Mail Website
Guest Editor
CNES (Centre National d’Etudes Spatiales), CNES, 18 avenue Edouard Belin, 31400, TOULOUSE, France
Interests: satellite remote sensing for hydrology; geodesy
Dr. Oliver Saavedra
E-Mail Website
Guest Editor
Centro de Investigaciones en Ingeniería Civil y Ambiental (CIICA), Universidad Privada Boliviana (UPB), Av. Víctor Ustariz Km 6.5, Campus UPB, Cochabamba, Bolivia
Interests: applied hydrology; water resource management; satellite-based precipitation; optimal dam operation; groundwater flow
Dr. Philippe Maillard
E-Mail Website
Guest Editor
Department of Geography, Universidade federal de Minas Gerais (UFMG), Av. Antonio Carlos, 6627, Belo Horizonte, MG 31270-901, Brasil
Interests: SAR image processing; satellite radar altimetry; waveform processing; water extraction from images; dry bathymetry
Dr. Daniel Vila
E-Mail Website
Guest Editor
Divisão de Satélites e Sistemas Ambientais, Centro de Previsão de Tempo e Estudos Climáticos, Instituto Nacional de Pesquisas Espaciais (CPTEC/INPE), Rod Pres. Dutra km 40, Cachoeira Paulista, SP, Brasil
Interests: satellite rainfall estimation; severe weather nowcasting
Dr. Juan Leon
E-Mail Website
Guest Editor
Universidad Nacional de Colombia (UNAL), Carrera 32 No 12 00, Vía Candelaria, Palmira, Valle del Cauca, Colombia
Interests: spatial hydrology
Dr. Vanessa Yael Bohn
E-Mail Website
Guest Editor
Departamento de Geografía y Turismo (DGyT)- Universidad Nacional del Sur (UNS) – Consejo Nacional de Investigaciones Científicas y Técnicas (CONICET), DGyT – UNS, 12 de octubre y San Juan – Bahía Blanca (8000), Pcia. Buenos Aires, Argentina
Interests: hydrological vulnerability; remote sensing; climate variability; shallow lakes
Dr. Stéphane Calmant
E-Mail Website
Guest Editor
IRD (Institut de Recherche pour le Développement), IRD center, 275 route de Montabo, Cayenne, 97300, French Guiana
Interests: Earth observation from space (geophysics, hydrology)
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Earth has a limited amount of water that recycles itself in what is called the 'water cycle'. Climate, weather, and human life and activities are profoundly affected by the variability and changes in this continuous, interconnected cycle. Therefore, observing, monitoring, and predicting the key variables governing the global and regional water cycle is essential to our understanding of the Earth’s climate, forecasting our weather, predicting floods and droughts, and improving water resource management.

The progress of Earth observation satellite technologies (EO) over the past few decades has made it possible to survey several of these variables from space. In the coming years, an increasing number of satellite missions will offer an unprecedented capacity to observe the Earth’s surface, its interior, and the atmosphere, ushering in a new era in the science of the Earth Environment and the water cycle.

It is within this perspective that we are pleased to invite you to participate in this issue. Our goal is for this issue to be the first of many, an issue regularly carried out in which all those using remote sensing technologies for monitoring waters (in all its forms) in Latin America find a receptacle.

We will welcome studies focusing on applications of remote sensing techniques to investigate water cycle studies, water management issues, liquid and solid discharge in rivers, hydrometeorological risks, precipitation, the cryosphere, soil moisture, water levels and surface waters, lakes, wetlands, rivers (including calibration/validation of current satellite missions), turbulent energy fluxes and evapotranspiration, irrigation, floods, and droughts, among others. Contributions dealing with modeling of the regional water cycle in synergy with the use of remote sensing observations will also be considered. Special contributions dealing with South American regional thematic (rivers such as the Amazon, the Orinoco, La Plata, Nordeste, Sao Francisco, Biobío, arid areas like the TPDS, etc.) are a plus, but contributions dealing with tropical large river basins, in general, are also welcome.

Studies devoted to the possibilities provided by the current South America CBERS, SAOCOM, and SABIA-MAR and results from other south American satellite missions (such as SSOT-FASAT CHARLIE), PERU-SAR1, VRSS1-2 etc ) and the European COPERNICUS space program, or to the advent of the new capabilities of the Surface Water Ocean Topography (SWOT) Mission (NASA, CNES, CSA, and UKSA) are most appreciated.

Dr. Rodrigo Abarca Del Rio
Dr. Daniel Moreira
Dr. Fabrice Papa
Dr. Rodrigo Paiva
Dr. Marielle Gosset
Dr. Waldo Lavado
Dr. Jean-Francois Cretaux
Dr. Oliver Saavedra
Dr. Philippe Maillard
Dr. Daniel Vila
Dr. Juan Leon
Dr. Vanessa Yael Bohn
Dr. Stephane Calmant
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. Remote Sensing is an international peer-reviewed open access semimonthly 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 2400 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

  • South America
  • Earth observation satellite technologies
  • Continental waters
  • Water cycle
  • Discharge
  • Hydrological models
  • Hydrometeorology
  • Climate change
  • Anthropic impact
  • Geodesy

Published Papers (6 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Article
Analysing the Impact of Climate Change on Hydrological Ecosystem Services in Laguna del Sauce (Uruguay) Using the SWAT Model and Remote Sensing Data
Remote Sens. 2021, 13(10), 2014; https://doi.org/10.3390/rs13102014 - 20 May 2021
Viewed by 739
Abstract
Assessing how climate change will affect hydrological ecosystem services (HES) provision is necessary for long-term planning and requires local comprehensive climate information. In this study, we used SWAT to evaluate the impacts on four HES, natural hazard protection, erosion control regulation and water [...] Read more.
Assessing how climate change will affect hydrological ecosystem services (HES) provision is necessary for long-term planning and requires local comprehensive climate information. In this study, we used SWAT to evaluate the impacts on four HES, natural hazard protection, erosion control regulation and water supply and flow regulation for the Laguna del Sauce catchment in Uruguay. We used downscaled CMIP-5 global climate models for Representative Concentration Pathways (RCP) 2.6, 4.5 and 8.5 projections. We calibrated and validated our SWAT model for the periods 2005–2009 and 2010–2013 based on remote sensed ET data. Monthly NSE and R2 values for calibration and validation were 0.74, 0.64 and 0.79, 0.84, respectively. Our results suggest that climate change will likely negatively affect the water resources of the Laguna del Sauce catchment, especially in the RCP 8.5 scenario. In all RCP scenarios, the catchment is likely to experience a wetting trend, higher temperatures, seasonality shifts and an increase in extreme precipitation events, particularly in frequency and magnitude. This will likely affect water quality provision through runoff and sediment yield inputs, reducing the erosion control HES and likely aggravating eutrophication. Although the amount of water will increase, changes to the hydrological cycle might jeopardize the stability of freshwater supplies and HES on which many people in the south-eastern region of Uruguay depend. Despite streamflow monitoring capacities need to be enhanced to reduce the uncertainty of model results, our findings provide valuable insights for water resources planning in the study area. Hence, water management and monitoring capacities need to be enhanced to reduce the potential negative climate change impacts on HES. The methodological approach presented here, based on satellite ET data can be replicated and adapted to any other place in the world since we employed open-access software and remote sensing data for all the phases of hydrological modelling and HES provision assessment. Full article
Show Figures

Graphical abstract

Article
Assessing Near Real-Time Satellite Precipitation Products for Flood Simulations at Sub-Daily Scales in a Sparsely Gauged Watershed in Peruvian Andes
Remote Sens. 2021, 13(4), 826; https://doi.org/10.3390/rs13040826 - 23 Feb 2021
Cited by 1 | Viewed by 1411
Abstract
This study investigates the applicability of Satellite Precipitation Products (SPPs) in near real-time for the simulation of sub-daily runoff in the Vilcanota River basin, located in the southeastern Andes of Peru. The data from rain gauge stations are used to evaluate the quality [...] Read more.
This study investigates the applicability of Satellite Precipitation Products (SPPs) in near real-time for the simulation of sub-daily runoff in the Vilcanota River basin, located in the southeastern Andes of Peru. The data from rain gauge stations are used to evaluate the quality of Integrated Multi-satellite Retrievals for GPM–Early (IMERG-E), Global Satellite Mapping of Precipitation–Near Real-Time (GSMaP-NRT), Climate Prediction Center Morphing Method (CMORPH), and HydroEstimator (HE) at the pixel-station level; and these SPPs are used as meteorological inputs for the hourly hydrological modeling. The GR4H model is calibrated with the hydrometric station of the longest record, and model simulations are also verified at one station upstream and two stations downstream of the calibration point. Comparing the sub-daily precipitation data observed, the results show that the IMERG-E product generally presents higher quality, followed by GSMaP-NRT, CMORPH, and HE. Although the SPPs present positive and negative biases, ranging from mild to moderate, they do represent the diurnal and seasonal variability of the hourly precipitation in the study area. In terms of the average of Kling-Gupta metric (KGE), the GR4H_GSMaP-NRT’ yielded the best representation of hourly discharges (0.686), followed by GR4H_IMERG-E’ (0.623), GR4H_Ensemble-Mean (0.617) and GR4H_CMORPH’ (0.606), and GR4H_HE’ (0.516). Finally, the SPPs showed a high potential for monitoring floods in the Vilcanota basin in near real-time at the operational level. The results obtained in this research are very useful for implementing flood early warning systems in the Vilcanota basin and will allow the monitoring and short-term hydrological forecasting of floods by the Peruvian National Weather and Hydrological Service. Full article
Show Figures

Figure 1

Article
The Performance of the Diurnal Cycle of Precipitation from Blended Satellite Techniques over Brazil
Remote Sens. 2021, 13(4), 734; https://doi.org/10.3390/rs13040734 - 17 Feb 2021
Viewed by 483
Abstract
The knowledge of the diurnal cycle of precipitation is of extreme relevance to understanding the physical/dynamic processes associated with the spatial and temporal distribution of precipitation. The main difficulty of this task is the lack of surface precipitation information over certain regions on [...] Read more.
The knowledge of the diurnal cycle of precipitation is of extreme relevance to understanding the physical/dynamic processes associated with the spatial and temporal distribution of precipitation. The main difficulty of this task is the lack of surface precipitation information over certain regions on an hourly time scale and the low spatial representativeness of these data (normally surface gauges). In order to overcome these difficulties, the main objective of this study is to create a 3-h precipitation accumulation database from the gauge-adjusted daily regional precipitation products to resolve the diurnal cycle properly. This study also proposes to evaluate different methodologies for partitioning gauge-adjusted daily precipitation products, i.e., a product made by the combination of satellite estimates and surface gauge observations, into 3-h precipitation accumulation. Two methodologies based on the calculation of a conversion factor F between a daily gauge-adjusted product, combined scheme (CoSch, hereafter), and a non-gauge-adjusted one, the integrated multi-satellite retrievals for GPM (IMERG)-Early (IMERG, hereafter) were tested for this research. Hourly rain gauge stations for the period of 2015–2018 over Brazil were used to assess the performance of the proposed methodologies over the whole region and five sub-regions with homogeneous precipitation regimes. Standard statistical metrics and categorical indices related with the capability to detect rainfall events were used to compare the ability of each product to represent the diurnal cycle. The results show that the new 3-h CoSch products show better agreement with rainfall gauge stations when compared with IMERG, better capturing the diurnal cycle of precipitation. The biggest improvement was over northeastern region close to the coast, where IMERG was not able to capture the diurnal cycle properly. One of the proposed methodologies (CoSchB) performed better on the critical success index and equitable threat score metrics, suggesting that this is the best product over the two. The downside, when compared with the other methodology (CoSchA), was a slight increase in the values of bias and mean absolute error, but still at acceptable levels. Full article
Show Figures

Graphical abstract

Article
Exploring the Fingerprints of Past Rain-on-Snow Events in a Central Andean Mountain Range Basin Using Satellite Imagery
Remote Sens. 2020, 12(24), 4173; https://doi.org/10.3390/rs12244173 - 20 Dec 2020
Viewed by 824
Abstract
Rain-on-snow (ROS) events can alter nival regimes and increase snowmelt, peak river flow, and reduce water storage. However, detection of ROS events is challenging and only the most intense and obvious cases are identified. Rain is known to reduce snow cover and decrease [...] Read more.
Rain-on-snow (ROS) events can alter nival regimes and increase snowmelt, peak river flow, and reduce water storage. However, detection of ROS events is challenging and only the most intense and obvious cases are identified. Rain is known to reduce snow cover and decrease near-infrared reflectance due to increased grain size. This study explored the fingerprints of ROS events on mountain snowpack with a simple typology that classifies changes in snow reflectance using fifteen years of MODIS imagery, reanalysis, and surface hydrometeorological data. The Maipo River Basin, with strong nival regime and a steep topography, in the western Andean mountain range was selected as a case study. Statistical analysis showed two distinct and opposite responses in the near infrared reflectance distribution of snow-covered pixels after precipitation, consistent with the typology for rain or snow events. For the probable ROS events, the daily maximum and minimum temperature increased in the days preceding the event and subsequently decreased, in some cases followed by a less consistent response in river flow. Although much remains to be studied, this approach can be used to expand historical records and improve modelling and detection schemes. Full article
Show Figures

Figure 1

Article
Precipitation Diurnal Cycle Assessment of Satellite-Based Estimates over Brazil
Remote Sens. 2020, 12(14), 2339; https://doi.org/10.3390/rs12142339 - 21 Jul 2020
Cited by 1 | Viewed by 802
Abstract
The main objective of this study is to assess the ability of several high-resolution satellite-based precipitation estimates to represent the Precipitation Diurnal Cycle (PDC) over Brazil during the 2014–2018 period, after the launch of the Global Precipitation Measurement satellite (GPM). The selected algorithms [...] Read more.
The main objective of this study is to assess the ability of several high-resolution satellite-based precipitation estimates to represent the Precipitation Diurnal Cycle (PDC) over Brazil during the 2014–2018 period, after the launch of the Global Precipitation Measurement satellite (GPM). The selected algorithms are the Global Satellite Mapping of Precipitation (GSMaP), The Integrated Multi-satellitE Retrievals for GPM (IMERG) and Climate Prediction Center (CPC) MORPHing technique (CMORPH). Hourly rain gauge data from different national and regional networks were used as the reference dataset after going through rigid quality control tests. All datasets were interpolated to a common 0.1° × 0.1° grid every 3 h for comparison. After a hierarchical cluster analysis, seven regions with different PDC characteristics (amplitude and phase) were selected for this study. The main results of this research could be summarized as follow: (i) Those regions where thermal heating produce deep convective clouds, the PDC is better represented by all algorithms (in term of amplitude and phase) than those regions driven by shallow convection or low-level circulation; (ii) the GSMaP suite (GSMaP-Gauge (G) and GSMaP-Motion Vector Kalman (MVK)), in general terms, outperforms the rest of the algorithms with lower bias and less dispersion. In this case, the gauge-adjusted version improves the satellite-only retrievals of the same algorithm suggesting that daily gauge-analysis is useful to reduce the bias in a sub-daily scale; (iii) IMERG suite (IMERG-Late (L) and IMERG-Final (F)) overestimates rainfall for almost all times and all the regions, while the satellite-only version provide better results than the final version; (iv) CMORPH has the better performance for a transitional regime between a coastal land-sea breeze and a continental amazonian regime. Further research should be performed to understand how shallow clouds processes and convective/stratiform classification is performed in each algorithm to improve the representativity of diurnal cycle. Full article
Show Figures

Graphical abstract

Article
Assessment of the Extreme Precipitation by Satellite Estimates over South America
Remote Sens. 2020, 12(13), 2085; https://doi.org/10.3390/rs12132085 - 29 Jun 2020
Cited by 5 | Viewed by 979
Abstract
In developing countries, accurate rainfall estimation with adequate spatial distribution is limited due to sparse rain gauge networks. One way to solve this problem is the use of satellite-based precipitation products. These satellite products have significant spatial coverage of rainfall estimates and it [...] Read more.
In developing countries, accurate rainfall estimation with adequate spatial distribution is limited due to sparse rain gauge networks. One way to solve this problem is the use of satellite-based precipitation products. These satellite products have significant spatial coverage of rainfall estimates and it is of fundamental importance to investigate their performance across space–time scales and the factors that affect their uncertainties. In the open literature, some studies have already analyzed the ability of satellite-based rain estimation products to estimate average rainfall values. These investigations have found very close agreement between the estimates and observed data. However, further evaluation of the satellite precipitation products is necessary to improve their reliability to estimate extreme values. In this scenario, the main goal of this work is to evaluate the ability of satellite-based precipitation products to capture the characteristics of extreme precipitation over the tropical region of South America. The products evaluated in this investigation were 3B42 RT v7.0, 3B42 RT v7.0 uncalibrated, CMORPH V1.0 RAW, CMORPH V1.0 CRT, GSMAP-NRT-no gauge v6.0, GSMAP-NRT- gauge v6.0, CHIRP V2.0, CHIRPS V2.0, PERSIANN CDR v1 r1, CoSch and TAPEER v1.5 from Frequent Rainfall Observations on GridS (FROGS) database. Some products considered in this investigation are adjusted with rain gauge values and others only with satellite information. In this study, these two sets of products were considered. In addition, gauge-based daily precipitation data, provided by Brazil’s National Institute for Space Research, were used as reference in the analyses. In order to compare gauge-based daily precipitation and satellite-based data for extreme values, statistical techniques were used to evaluate the performance the selected satellite products over the tropical region of South America. According to the results, the threshold for rain to be considered an extreme event in South America presented high variability, ranging from 20 to 150 mm/day, depending on the region and the percentile threshold chosen for analysis. In addition, the results showed that the ability of the satellite estimates to retrieve rainfall extremes depends on the geographical location and large-scale rainfall regimes. Full article
Show Figures

Graphical abstract

Planned Papers

The below list represents only planned manuscripts. Some of these manuscripts have not been received by the Editorial Office yet. Papers submitted to MDPI journals are subject to peer-review.

  1. Calmant S., Moreira D., Santos da Silva, J., Paris A. "Parintins : A reference site for the détermination of absolute and inter-missions biaises in Satellite Altimetry"
  2. Arsen. A; Abarca-del-Rio, R; Cretaux, J-F. "An endorheic based remote sensing model for the Perito Moreno Glacier Ice Damming water outbursts"
  3. Lavado et al. "Rainfall erosivity assessment in Peru using the GPM product"
Back to TopTop