Snowmelt runoff models

1999 ◽  
Vol 23 (2) ◽  
pp. 205-227 ◽  
Author(s):  
R. I. Ferguson
Keyword(s):  
Snow Cover ◽  
Water Resource Management ◽  
Flood Hazard ◽  
Observation Data ◽  
Internal Validation ◽  
Distributed Models ◽  
Current Trends ◽  
Meltwater Runoff ◽  
Basin Scale ◽  
Earth Observation Data

Models that predict meltwater runoff at a daily timescale are important in water resource management, flood hazard assessment and climate-change impact studies. This article identifies four basic components of such models: meteorological extrapolation, snowmelt estimation at a point, snow-cover depletion and runoff routing. Alternative ways of handling these are discussed, with emphasis on the contrasting treatments in two widely used models: HBV and SRM. Many of the issues in meltwater modelling reflect wider debates in hydrological and environmental modelling, including problems of complexity vs. simplicity, the appropriate level of spatial disaggregation, parameter identification and calibration, and internal validation. In reviewing current trends emphasis is placed on the potential and limitations of fully distributed models, problems in using energy-balance rather than temperature-index melt models at basin scale, ways to deal with spatial variability in snow cover, and the value and limitations of earth observation data.

scholarly journals Snow Cover Evolution in the Gran Paradiso National Park, Italian Alps, Using the Earth Observation Data Cube

Data ◽  
2019 ◽  
Vol 4 (4) ◽  
pp. 138 ◽  
Author(s):  
Charlotte Poussin ◽  
Yaniss Guigoz ◽  
Elisa Palazzi ◽  
Silvia Terzago ◽  
Bruno Chatenoux ◽  
...  
Keyword(s):  
Snow Cover ◽  
National Park ◽  
Data Cube ◽  
Observation Data ◽  
Italian Alps ◽  
Temporal Filtering ◽  
Time Series Analyses ◽  
Earth Observation Data ◽  
Gran Paradiso ◽  
Gran Paradiso National Park

Mountainous regions are particularly vulnerable to climate change, and the impacts are already extensive and observable, the implications of which go far beyond mountain boundaries and the environmental sectors. Monitoring and understanding climate and environmental changes in mountain regions is, therefore, needed. One of the key variables to study is snow cover, since it represents an essential driver of many ecological, hydrological and socioeconomic processes in mountains. As remotely sensed data can contribute to filling the gap of sparse in-situ stations in high-altitude environments, a methodology for snow cover detection through time series analyses using Landsat satellite observations stored in an Open Data Cube is described in this paper, and applied to a case study on the Gran Paradiso National Park, in the western Italian Alps. In particular, this study presents a proof of concept of the preliminary version of the snow observation from space algorithm applied to Landsat data stored in the Swiss Data Cube. Implemented in an Earth Observation Data Cube environment, the algorithm can process a large amount of remote sensing data ready for analysis and can compile all Landsat series since 1984 into one single multi-sensor dataset. Temporal filtering methodology and multi-sensors analysis allows one to considerably reduce the uncertainty in the estimation of snow cover area using high-resolution sensors. The study highlights that, despite this methodology, the lack of available cloud-free images still represents a big issue for snow cover mapping from satellite data. Though accurate mapping of snow extent below cloud cover with optical sensors still represents a challenge, spatial and temporal filtering techniques and radar imagery for future time series analyses will likely allow one to reduce the current cloud cover issue.

scholarly journals National Open Data Cubes and Their Contribution to Country-Level Development Policies and Practices

Data ◽  
2019 ◽  
Vol 4 (4) ◽  
pp. 144 ◽  
Author(s):  
Trevor Dhu ◽  
Gregory Giuliani ◽  
Jimena Juárez ◽  
Argyro Kavvada ◽  
Brian Killough ◽  
...  
Keyword(s):  
International Development ◽  
Water Resource Management ◽  
Open Data ◽  
Data Cube ◽  
Observation Data ◽  
Country Level ◽  
Global Trend ◽  
Development Policies ◽  
Earth Observation Data ◽  
Development Agendas

The emerging global trend of satellite operators producing analysis-ready data combined with open source tools for managing and exploiting these data are leading to more and more countries using Earth observation data to drive progress against key national and international development agendas. This paper provides examples from Australia, Mexico, Switzerland, and Tanzania on how the Open Data Cube technology has been combined with analysis-ready data to provide new insights and support better policy making across issues as diverse as water resource management through to urbanization and environmental–economic accounting.

scholarly journals Cutting the costs of coastal protection by integrating vegetation in flood defences

2021 ◽  
Vol 12 (1) ◽  
Author(s):  
Vincent T. M. van Zelst ◽  
Jasper T. Dijkstra ◽  
Bregje K. van Wesenbeeck ◽  
Dirk Eilander ◽  
Edward P. Morris ◽  
...  
Keyword(s):  
Urban Areas ◽  
Flood Hazard ◽  
Coastal Flooding ◽  
Global Scale ◽  
Coastal Vegetation ◽  
Coastal Protection ◽  
Observation Data ◽  
Protection Strategies ◽  
Earth Observation Data

AbstractExposure to coastal flooding is increasing due to growing population and economic activity. These developments go hand-in-hand with a loss and deterioration of ecosystems. Ironically, these ecosystems can play a buffering role in reducing flood hazard. The ability of ecosystems to contribute to reducing coastal flooding has been emphasized in multiple studies. However, the role of ecosystems in hybrid coastal protection (i.e. a combination of ecosystems and levees) has been poorly quantified at a global scale. Here, we evaluate the use of coastal vegetation, mangroves, and marshes fronting levees to reduce global coastal protection costs, by accounting for wave-vegetation interaction.The research is carried out by combining earth observation data and hydrodynamic modelling. We show that incooperating vegetation in hybrid coastal protection results in more sustainable and financially attractive coastal protection strategies. If vegetated foreshore levee systems were established along populated coastlines susceptible to flooding, the required levee crest height could be considerably reduced. This would result in a reduction of 320 (range: 107-961) billion USD2005 Power Purchasing Parity (PPP) in investments, of which 67.5 (range: 22.5- 202) billion USD2005 PPP in urban areas for a 1 in 100-year flood protection level.

scholarly journals Heihe Watershed Allied Telemetry Experimental Research (HiWATER): Scientific Objectives and Experimental Design

2013 ◽  
Vol 94 (8) ◽  
pp. 1145-1160 ◽  
Author(s):  
Xin Li ◽  
Guodong Cheng ◽  
Shaomin Liu ◽  
Qing Xiao ◽  
Mingguo Ma ◽  
...  
Keyword(s):  
Experimental Design ◽  
Experimental Research ◽  
Water Resource Management ◽  
Model Simulation ◽  
Interdisciplinary Studies ◽  
Heihe River ◽  
Observation Data ◽  
Science Data ◽  
Basin Scale ◽  
Research Plan

A major research plan entitled “Integrated research on the ecohydrological process of the Heihe River Basin” was launched by the National Natural Science Foundation of China in 2010. One of the key aims of this research plan is to establish a research platform that integrates observation, data management, and model simulation to foster twenty-first-century watershed science in China. Based on the diverse needs of interdisciplinary studies within this research plan, a program called the Heihe Watershed Allied Telemetry Experimental Research (HiWATER) was implemented. The overall objective of HiWATER is to improve the observability of hydrological and ecological processes, to build a world-class watershed observing system, and to enhance the applicability of remote sensing in integrated ecohydrological studies and water resource management at the basin scale. This paper introduces the background, scientific objectives, and experimental design of HiWATER. The instrumental setting and airborne mission plans are also outlined. The highlights are the use of a flux observing matrix and an eco-hydrological wireless sensor network to capture multiscale heterogeneities and to address complex problems, such as heterogeneity, scaling, uncertainty, and closing water cycle at the watershed scale. HiWATER was formally initialized in May 2012 and will last four years until 2015. Data will be made available to the scientific community via the Environmental and Ecological Science Data Center for West China. International scientists are welcome to participate in the field campaign and use the data in their analyses.

scholarly journals Mapping and Monitoring the Multi-Decadal Dynamics of Australia’s Open Waterbodies Using Landsat

2021 ◽  
Vol 13 (8) ◽  
pp. 1437
Author(s):  
Claire E. Krause ◽  
Vanessa Newey ◽  
Matthew J. Alger ◽  
Leo Lymburner
Keyword(s):  
Water Resource Management ◽  
Temporal Dynamics ◽  
Observation Data ◽  
Detection Algorithms ◽  
Water Detection ◽  
History Of ◽  
Spatio Temporal ◽  
Earth Observation Data ◽  
Spatial Locations ◽  
Pixel Scale

Water detection algorithms are now being routinely applied to continental and global archives of satellite imagery. However, water resource management decisions typically take place at the waterbody rather than pixel scale. Here, we present a workflow for generating polygons of persistent waterbodies from Landsat observations, enabling improved monitoring and management of water assets across Australia. We use Digital Earth Australia’s (DEA) Water Observations from Space (WOfS) product, which provides a water classified output for every available Landsat scene, to determine the spatial locations and extents of waterbodies across Australia. We generated a polygon set of waterbodies that identified 295,906 waterbodies ranging in size from 3125 m2 to 4820 km2. Each polygon was used to generate a time series of WOfS, providing a history of the change in surface area of each waterbody every ~16 days since 1987. We demonstrate the applications of this new dataset, DEA Waterbodies, to understanding local through to national-scale surface water spatio-temporal dynamics. DEA Waterbodies provides new insights into Australia’s water availability and enables the monitoring of important landscape features such as lakes and dams, improving our ability to use earth observation data to make meaningful decisions.

Development of basinal scale glacier mass balance model: an approach based on satellite observation and energy balance components

2020 ◽  
Author(s):  
Akansha Patel ◽  
Ajanta Goswami ◽  
Thamban Meloth ◽  
Parmanand Sharma
Keyword(s):  
Energy Balance ◽  
Mass Balance ◽  
Water Resource Management ◽  
Water Storage ◽  
Balance Model ◽  
Future Climate Change ◽  
Glacier Mass Balance ◽  
Observation Data ◽  
Basin Scale ◽  
The Impact

<p>The understanding of fresh water storage in the Himalayan region is essential for water resource management of the region. As glacier mass balance is a difference between the input and output water storage in a glacier over a period, glacier mass balance can be used as an indirect method to understand the storage. In the northwestern Himalaya, microscale meteorological stations are needed for mass balance estimation due to rugged terrain and complex topography of this region. However, there are only few meteorological stations available in that region. Therefore, in this study, we have developed a new model for glacier mass balance estimation at basinal scale. This model  includes the parameterization of energy balance components viz. albedo, longwave radiation, shortwave radiation, sensible heat, latent heat and heat flux at spatial and temporal scale using earth observation data. The modeling of air temperature is performed using the multi-regression analysis over the Chenab basin of the Indian Himalayas. Simulation is driven with the 16-days Landsat optical and thermal data from 2015 to 2018 that can be used for parameterization of the variable. This model is calibrated and validated with the field data of period 2015-2016. Further, the impact of climatic change and their influence on mass balance was also assessed to understand the future glacier health and mass changes. In contrast to previous temperature index based basin scale models, this model includes most of the energy balance components for better estimation of glacier mass balance. The model can also be used to estimate possible responses of the world’s glaciers to future climate change.</p>

Our goal is to establish the earth observation data in the business world Unser Ziel ist es, die Erdbeobachtungsdaten in der Geschäftswelt zu etablieren

GIS Business ◽  
2019 ◽  
Vol 12 (3) ◽  
pp. 12-14
Author(s):  
Eicher, A
Keyword(s):  
Earth Observation ◽  
Observation Data ◽  
Business World ◽  
The Earth ◽  
Earth Observation Data

Our goal is to establish the earth observation data in the business world Unser Ziel ist es, die Erdbeobachtungsdaten in der Geschäftswelt zu etablieren

Mapping slums and model population density using earth observation data and open source solutions

2019 ◽  
Author(s):  
Tais Grippa ◽  
Stefanos Georganos ◽  
Sabine Vanhuysse ◽  
Moritz Lennert ◽  
Nicholus Mboga ◽  
...  
Keyword(s):  
Population Density ◽  
Open Source ◽  
Earth Observation ◽  
Observation Data ◽  
Model Population ◽  
Earth Observation Data

scholarly journals Examining the Economic and Environmental Impacts of COVID-19 Using Earth Observation Data

2020 ◽  
Vol 13 (1) ◽  
pp. 5
Author(s):  
William Straka ◽  
Shobha Kondragunta ◽  
Zigang Wei ◽  
Hai Zhang ◽  
Steven D. Miller ◽  
...  
Keyword(s):  
Air Quality ◽  
Los Angeles ◽  
Environmental Impacts ◽  
Demographic Data ◽  
The United States ◽  
Earth Observation ◽  
Observation Data ◽  
Washington Dc ◽  
Mobility Data ◽  
Earth Observation Data

The COVID-19 pandemic has infected almost 73 million people and is responsible for over 1.63 million fatalities worldwide since early December 2019, when it was first reported in Wuhan, China. In the early stages of the pandemic, social distancing measures, such as lockdown restrictions, were applied in a non-uniform way across the world to reduce the spread of the virus. While such restrictions contributed to flattening the curve in places like Italy, Germany, and South Korea, it plunged the economy in the United States to a level of recession not seen since WWII, while also improving air quality due to the reduced mobility. Using daily Earth observation data (Day/Night Band (DNB) from the National Oceanic and Atmospheric Administration Suomi-NPP and NO2 measurements from the TROPOspheric Monitoring Instrument TROPOMI) along with monthly averaged cell phone derived mobility data, we examined the economic and environmental impacts of lockdowns in Los Angeles, California; Chicago, Illinois; Washington DC from February to April 2020—encompassing the most profound shutdown measures taken in the U.S. The preliminary analysis revealed that the reduction in mobility involved two major observable impacts: (i) improved air quality (a reduction in NO2 and PM2.5 concentration), but (ii) reduced economic activity (a decrease in energy consumption as measured by the radiance from the DNB data) that impacted on gross domestic product, poverty levels, and the unemployment rate. With the continuing rise of COVID-19 cases and declining economic conditions, such knowledge can be combined with unemployment and demographic data to develop policies and strategies for the safe reopening of the economy while preserving our environment and protecting vulnerable populations susceptible to COVID-19 infection.

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