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Advances in Hydro-Meteorological Monitoring

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ISBN: 9783038429777 9783038429784 Year: Pages: 200 DOI: 10.3390/books978-3-03842-978-4 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Environmental Sciences
Added to DOAB on : 2018-10-09 08:55:30
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Basin hydrology is related to the soil–atmosphere interaction driven by several blended processes constrained by the space–time variability of precipitation and soil moisture, along with overland flow and flood routing in natural channels. The emerging technologies for the monitoring and prediction of the spatial and temporal distribution of rainfall and soil moisture over a catchment, as well as the hillslope and river runoff, are of considerable interest to predict the hydrological responses of a catchment. In this context, this Special Issue, with its eleven theoretical and applied contributions, aims to shed light on the more recent advances in ground observations and remote sensing products, as well as on the benefits resulting from the integration of technological innovation and the development of new ideas in hydrology science. To this purpose, the accepted articles, written by leading researchers in their field, are intended to present and discuss experimental analyses at the catchment scale in terms of: a) intensive measurement campaigns of soil moisture by in situ sensors, remote sensing and modelling approaches; b) discharge monitoring also for high floods, by leveraging advanced technology for ground surface velocity measurements and spaceborne observations of water surface elevation, river width and slope; c) solid precipitation-measuring methods and the selection of snow gauge stations by merging meteorological, hydrological and remote sensing datasets; d) changes in daily precipitation of different intensities over large river basins along with the identification of the space–time rainfall field for different climatic regions ; and finally e) spatial evaporation patterns in different climate regions and assessment of the dominant climate factors affecting the evaporative demand of the atmosphere. Hopefully this Special Issue provides different useful insights into advancements in emerging technologies for the monitoring of key hydrological variables and will support the design of a scalable system of operational tools leading to suitable flood mitigation measures and reliable real-time warning systems.

Applications of Remote Sensing/ GIS in Water Resources and Flooding Risk Managements

Authors: ---
ISBN: 9783038429821 9783038429814 Year: Pages: VIII, 222 Language: englisch
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Environmental Sciences
Added to DOAB on : 2018-08-21 16:57:04
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Remote sensing and GIS play critical roles in water resource and flood inundation mapping and risk management. Remote sensing provides data sources for mapping water resources (snow and glaciers, water bodies, soil moisture and groundwater), measuring hydrological fluxes (ET, precipitation and river discharge), and monitoring drought and flooding inundation, while GIS provides the best tools for water resources, drought and flooding risk management and for setting up hydrologic models, inputting data processing and output analyses and visualizations. This Special Issue Book presents the best practices, cutting-edge technologies and applications of remote sensing, GIS and hydrologic models for water resources mapping, satellite rainfall measurements, runoff simulation, water body and flood inundation mapping and risk management. The latest technologies applied include 3D model analysis and visualization of glaciers, UAV video image classification for turf grass mapping and irrigation planning, ground penetration radar for soil moisture estimates, TRMM and GPM satellite rainfall measurements, storm hyetograph analysis, rainfall runoff and urban flooding simulation, satellite radar and optical image classification for urban water bodies and flooding inundation. The application of these technologies is expected to greatly relieve the pressures on water resources and assist in better mitigating and adapting to the impact of drought and flooding.

Vorhersagbarkeit konvektiver Niederschläge: Hochauflösende Ensemblesimulationen für Westafrika

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Book Series: Wissenschaftliche Berichte des Instituts für Meteorologie und Klimaforschung des Karlsruher Instituts für Technologie ISSN: 01795619 ISBN: 9783731501893 Year: Volume: 63 Pages: 319 p. DOI: 10.5445/KSP/1000039449 Language: GERMAN
Publisher: KIT Scientific Publishing
Subject: Science (General)
Added to DOAB on : 2019-07-30 20:01:58
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During the West African Monsoon, convective systems generate the largest part of annual precipitation. We investigate their predictability by conducting high-resolution ensemble simulations with the COSMO model, focusing on the impact of the land surface. Are land-surface &#8211; atmosphere interactions in West Africa as important for precipitation forecasts as larger-scale conditions? What are the main physical processes?

Microwave Indices from Active and Passive Sensors for Remote Sensing Applications

Authors: ---
ISBN: 9783038978206 9783038978213 Year: Pages: 224 DOI: 10.3390/books978-3-03897-821-3 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Geography --- Science (General)
Added to DOAB on : 2019-12-09 11:49:16
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Past research has comprehensively assessed the capabilities of satellite sensors operating at microwave frequencies, both active (SAR, scatterometers) and passive (radiometers), for the remote sensing of Earth’s surface. Besides brightness temperature and backscattering coefficient, microwave indices, defined as a combination of data collected at different frequencies and polarizations, revealed a good sensitivity to hydrological cycle parameters such as surface soil moisture, vegetation water content, and snow depth and its water equivalent. The differences between microwave backscattering and emission at more frequencies and polarizations have been well established in relation to these parameters, enabling operational retrieval algorithms based on microwave indices to be developed. This Special Issue aims at providing an overview of microwave signal capabilities in estimating the main land parameters of the hydrological cycle, e.g., soil moisture, vegetation water content, and snow water equivalent, on both local and global scales, with a particular focus on the applications of microwave indices.

Earth Observation for Water Resource Management in Africa

Authors: --- --- ---
ISBN: 9783038421535 9783038421542 Year: Pages: XVIII, 538 DOI: 10.3390/books978-3-03842-154-2 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Added to DOAB on : 2016-05-20 14:55:31
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Reliable access to water, managing the spatial and temporal variability of water availability, ensuring the quality of freshwater and responding to climatological changes in the hydrological cycle are prerequisites for the development of countries in Africa. Water being an essential input for biomass growth and for renewable energy production (e.g. biofuels and hydropower schemes) plays an integral part in ensuring food and energy security for any nation. Water, as a source of safe drinking water, is furthermore the basis for ensuring the health of citizens and plays an important role in urban sanitation.The concept of Integrated Water Resource Management (IWRM) is seen as an opportunity to help manage water variability and the wide spread water scarcity in Africa. One key component missing from IWRM in Africa is the limited knowledge of the available extent and quality of water resources at basin level. Earth Observation (EO) technology can help fill this information gap by assessing and monitoring water resources at adequate temporal and spatial scales. The goal of this Special Issue is to understand and demonstrate the contribution which satellite observations, consistent over space and time, can bring to improve water resource management in Africa. Possible EO products and applications range from catchment characterization, water quality monitoring, soil moisture assessment, water extent and level monitoring, irrigation services, urban and agricultural water demand modeling, evapotranspiration estimation, ground water management, to hydrological modeling and flood mapping/forecasting. Some of these EO applications have already been developed by African scientists within the 10 year lifetime of the TIGER initiative: Looking after Water in Africa (http://www.tiger.esa.int), whose contributions are intended to be the starting point of this Special Issue and is only one example of the wide range of activities in the field. Contributions from the entire African and international scientific community dealing with the challenges of water resource management in Africa are the target of the special issue.

Advancing Earth Surface Representation via Enhanced Use of Earth Observations in Monitoring and Forecasting Applications

Authors: --- --- --- --- et al.
ISBN: 9783039210640 9783039210657 Year: Pages: 262 DOI: 10.3390/books978-3-03921-065-7 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General)
Added to DOAB on : 2019-12-09 11:49:15
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The representation of the Earth's surface in global monitoring and forecasting applications is moving towards capturing more of the relevant processes, while maintaining elevated computational efficiency and therefore a moderate complexity. These schemes are developed and continuously improved thanks to well instrumented field-sites that can observe coupled processes occurring at the surface–atmosphere interface (e.g., forest, grassland, cropland areas and diverse climate zones). Approaching global kilometer-scale resolutions, in situ observations alone cannot fulfil the modelling needs, and the use of satellite observation becomes essential to guide modelling innovation and to calibrate and validate new parameterization schemes that can support data assimilation applications. In this book, we review some of the recent contributions, highlighting how satellite data are used to inform Earth surface model development (vegetation state and seasonality, soil moisture conditions, surface temperature and turbulent fluxes, land-use change detection, agricultural indicators and irrigation) when moving towards global km-scale resolutions.

Assimilation of Remote Sensing Data into Earth System Models

Authors: --- ---
ISBN: 9783039216406 9783039216413 Year: Pages: 236 DOI: 10.3390/books978-3-03921-641-3 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General)
Added to DOAB on : 2019-12-09 11:49:16
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In the Earth sciences, a transition is currently occurring in multiple fields towards an integrated Earth system approach, with applications including numerical weather prediction, hydrological forecasting, climate impact studies, ocean dynamics estimation and monitoring, and carbon cycle monitoring. These approaches rely on coupled modeling techniques using Earth system models that account for an increased level of complexity of the processes and interactions between atmosphere, ocean, sea ice, and terrestrial surfaces. A crucial component of Earth system approaches is the development of coupled data assimilation of satellite observations to ensure consistent initialization at the interface between the different subsystems. Going towards strongly coupled data assimilation involving all Earth system components is a subject of active research. A lot of progress is being made in the ocean–atmosphere domain, but also over land. As atmospheric models now tend to address subkilometric scales, assimilating high spatial resolution satellite data in the land surface models used in atmospheric models is critical. This evolution is also challenging for hydrological modeling. This book gathers papers reporting research on various aspects of coupled data assimilation in Earth system models. It includes contributions presenting recent progress in ocean–atmosphere, land–atmosphere, and soil–vegetation data assimilation.

Google Earth Engine Applications

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ISBN: 9783038978848 9783038978855 Year: Pages: 420 DOI: 10.3390/books978-3-03897-885-5 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Technology (General) --- Environmental Technology
Added to DOAB on : 2019-04-25 16:37:17
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In a rapidly changing world, there is an ever-increasing need to monitor the Earth&rsquo;s resources and manage it sustainably for future generations. Earth observation from satellites is critical to provide information required for informed and timely decision making in this regard. Satellite-based earth observation has advanced rapidly over the last 50 years, and there is a plethora of satellite sensors imaging the Earth at finer spatial and spectral resolutions as well as high temporal resolutions. The amount of data available for any single location on the Earth is now at the petabyte-scale. An ever-increasing capacity and computing power is needed to handle such large datasets. The Google Earth Engine (GEE) is a cloud-based computing platform that was established by Google to support such data processing. This facility allows for the storage, processing and analysis of spatial data using centralized high-power computing resources, allowing scientists, researchers, hobbyists and anyone else interested in such fields to mine this data and understand the changes occurring on the Earth&rsquo;s surface. This book presents research that applies the Google Earth Engine in mining, storing, retrieving and processing spatial data for a variety of applications that include vegetation monitoring, cropland mapping, ecosystem assessment, and gross primary productivity, among others. Datasets used range from coarse spatial resolution data, such as MODIS, to medium resolution datasets (Worldview -2), and the studies cover the entire globe at varying spatial and temporal scales.

Keywords

Google Earth Engine --- NDVI --- vegetation index --- Landsat --- remote sensing --- phenology --- surface reflectance --- cropland mapping --- cropland areas --- 30-m --- Landsat-8 --- Sentinel-2 --- Random Forest --- Support Vector Machines --- segmentation --- RHSeg --- Google Earth Engine --- Africa --- remote sensing --- semi-arid --- ecosystem assessment --- land use change --- image classification --- seasonal vegetation --- carbon cycle --- Google Earth Engine --- crop yield --- gross primary productivity (GPP) --- data fusion --- Landsat --- MODIS --- MODIS --- Random Forest --- pasture mapping --- Brazilian pasturelands dynamics --- Google Earth Engine --- crop classification --- multi-classifier --- cloud computing --- time series --- high spatial resolution --- BACI --- Enhanced Vegetation Index --- Google Earth Engine --- cloud-based geo-processing --- satellite-derived bathymetry --- image composition --- pseudo-invariant features --- sun glint correction --- empirical --- spatial error --- Google Earth Engine --- low cost in situ --- Sentinel-2 --- Mediterranean --- burn severity --- change detection --- Landsat --- dNBR --- RdNBR --- RBR --- composite burn index (CBI) --- MTBS --- lower mekong basin --- landsat collection --- suspended sediment concentration --- online application --- google earth engine --- Landsat --- Google Earth Engine --- protected area --- forest and land use mapping --- machine learning classification --- China --- temporal compositing --- image time series --- multitemporal analysis --- change detection --- cloud masking --- Landsat-8 --- Google Earth Engine (GEE) --- Google Earth Engine --- LAI --- FVC --- FAPAR --- CWC --- plant traits --- random forests --- PROSAIL --- small-scale mining --- industrial mining --- google engine --- image classification --- land-use cover change --- seagrass --- habitat mapping --- image composition --- machine learning --- support vector machines --- Google Earth Engine --- Sentinel-2 --- Aegean --- Ionian --- global scale --- soil moisture --- Soil Moisture Ocean Salinity --- Soil Moisture Active Passive --- Google Earth Engine --- drought --- cloud computing --- remote sensing --- snow hydrology --- water resources --- Google Earth Engine --- user assessment --- MODIS --- snow cover --- flood --- disaster prevention --- emergency response --- decision making --- Google Earth Engine --- land cover --- deforestation --- Brazilian Amazon --- Bayesian statistics --- BULC-U --- Mato Grosso --- spatial resolution --- Landsat --- GlobCover --- SDG --- surface urban heat island --- Geo Big Data --- Google Earth Engine --- global monitoring service --- Google Earth Engine --- web portal --- satellite imagery --- trends --- earth observation --- wetland --- Google Earth Engine --- Sentinel-1 --- Sentinel-2 --- random forest --- cloud computing --- geo-big data --- cloud computing --- big data analytics --- long term monitoring --- data archival --- early warning systems

Application of the China Meteorological Assimilation Driving Datasets for the SWAT Model (CMADS) in East Asia

Authors: ---
ISBN: 9783039212354 9783039212361 Year: Pages: 384 DOI: 10.3390/books978-3-03921-236-1 Language: English
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Geography
Added to DOAB on : 2019-08-28 11:21:27
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To promote scientific understanding of surface processes in East Asia, we have published details of the CMADS dataset in the journal, Water, and expect that users around the world will learn about CMADS datasets while promoting the development of hydrometeorological disciplines in East Asia. We hope and firmly believe that scientific development in East Asia and our understanding of this typical region will be further advanced.

Keywords

East Asia --- CMADS --- meteorological input uncertainty --- hydrological modelling --- SWAT --- non-point source pollution models --- CMADS --- Qinghai-Tibet Plateau (TP) --- SWAT --- CFSR --- TRMM --- PERSIANN --- PERSIANN-CDR --- CMADS --- satellite-derived rainfall --- streamflow simulation --- SWAT --- Han River --- GLUE --- hydrological model --- ParaSol --- SUFI2 --- uncertainty analysis --- SWAT model --- CMADS --- Lijiang River --- runoff --- uncertainty analysis --- hydrological elements --- statistical analysis --- SWAT --- CMADS --- climate variability --- land use change --- streamflow --- potential evapotranspiration --- Penman-Monteith --- CMADS --- China --- CMADS dataset --- parameter sensitivity --- SUFI-2 --- Yellow River --- reanalysis products --- satellite-based products --- hydrological model --- bayesian model averaging --- Xiang River basin --- total nitrogen --- accumulation --- SWAT model --- CMADS --- Biliuhe reservoir --- CMADS --- SWAT --- East Asia --- meteorological --- hydrological --- precipitation --- TMPA-3B42V7 --- CMADS --- hydrologic model --- uncertainty --- reservoirs --- operation rule --- Noah LSM-HMS --- capacity distribution --- aggregated reservoir --- CMADS --- CMADS --- IMERG --- statistical analysis --- SWAT hydrological simulation --- Jinsha River Basin --- blue and green water flows --- climate variability --- sensitivity analysis --- Erhai Lake Basin --- CMADS --- SWAT --- JBR --- soil moisture --- hydrological processes --- spatio-temporal --- sloping black soil farmland --- soil moisture content --- freeze–thaw period --- soil temperature --- CMADS-ST --- reservoir parameters --- runoff --- CMADS --- SWAT --- Yalong River --- CMADS --- impact --- hydrological modeling --- SWAT --- runoff --- sediment yield --- land-use change --- SWAT --- CMADS

Managing Forests and Water for People under a Changing Environment

Authors: --- --- ---
ISBN: 9783039288236 / 9783039288243 Year: Pages: 198 DOI: 10.3390/books978-3-03928-824-3 Language: eng
Publisher: MDPI - Multidisciplinary Digital Publishing Institute
Subject: Science (General) --- Biology --- Forestry
Added to DOAB on : 2020-06-09 16:38:57
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Forests cover 30% of the Earth’s land area, or nearly four billion hectares. Enhancing the benefits and ecosystem services of forests has been increasingly recognized as an essential part of nature-based solutions for solving many emerging global environmental problems today. A core science supporting forest management is understanding the interactions of forests, water, and people. These interactions have become increasingly complex under climate change and its associated impacts, such as the increases in the intensity and frequency of drought and floods, increasing population and deforestation, and a rise in global demands for multiple ecosystem services including clean water supply and carbon sequestration. Forest watershed managers have recognized that water management is an essential component of forest management. Global environmental change is posing more challenges for managing forests and water toward sustainable development. New science on forest and water is critically needed across the globe. The International Forests and Water Conference 2018, Valdivia, Chile (http://forestsandwater2018.cl/), a joint effort of the 5th IUFRO International Conference on Forests and Water in a Changing Environment and the Second Latin American Conference on Forests and Water provided a unique forum to examine forest and water issues in Latin America under a global context. This book represents a collection of some of the peer-reviewed papers presented at the conference that were published in a Special Issue of Forests.

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