Viviana Maggioni

Viviana Maggioni
George Mason University | GMU · Department of Civil, Environmental and Infrastructure Engineering

Ph.D.

About

102
Publications
25,794
Reads
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1,747
Citations
Introduction
Viviana Maggioni currently works at the Department of Civil, Environmental and Infrastructure Engineering, George Mason University. Viviana does research in Environmental Engineering, Remote Sensing and Hydrology.
Additional affiliations
January 2016 - present
University of Maryland, College Park
Position
  • Visiting Assistant Research Scientist
January 2014 - January 2016
University of Maryland, College Park
Position
  • Visiting Research Associate
January 2014 - present
George Mason University
Position
  • Professor (Assistant)
Education
September 2007 - May 2012
University of Connecticut
Field of study
  • Environmental Engineering
September 2003 - March 2006
Politecnico di Milano
Field of study
  • Environmental Engineering
September 2000 - September 2003
Politecnico di Milano
Field of study
  • Environmental Engineering

Publications

Publications (102)
Article
Full-text available
The usefulness of satellite multi‐sensor precipitation (SMP) and other satellite‐informed precipitation products in water resources modeling can be hindered by substantial errors which vary considerably with spatiotemporal scale. One approach to cope with these errors is to combine SMPs with ensemble generation methods, such that each ensemble memb...
Article
Full-text available
This second paper of the two‐part series focuses on demonstrating the impact of assimilating satellite‐based snow cover and freeze/thaw observations into the hyper‐resolution, offline terrestrial modeling system used for the High Mountain Asia (HMA) region from 2003 to 2016. To this end, this study systematically evaluates a total of six sets of 0....
Article
Full-text available
In the spring of 2020, many countries enacted strict lockdowns to contain the spread of the 2019 coronavirus disease (COVID-19), resulting in a sharp observed decrease in regional atmospheric pollutant concentrations, such as NO x and aerosols in early 2020. Atmospheric composition can influence cloud properties and might have a significant effect...
Article
Full-text available
This work tests the hypothesis that jointly assimilating satellite observations of leaf area index and surface soil moisture into a land surface model improves the estimation of land vegetation and water variables. An Ensemble Kalman Filter is used to test this hypothesis across the Contiguous United States from April 2015 to December 2018. The per...
Article
Full-text available
The investigation of regional vulnerability to extreme hydroclimatic events (e.g., floods and hurricanes) is quite challenging due to its dependence on reliable precipitation estimates. Better understanding of past precipitation trends is crucial to examine changing precipitation extremes, optimize future water demands, stormwater infrastructure, e...
Article
Full-text available
As vegetation regulates water, carbon, and energy cycles from the local to the global scale, its accurate representation in land surface models is crucial. The assimilation of satellite-based vegetation observations in a land surface model has the potential to improve the estimation of global carbon and energy cycles, which in turn can enhance our...
Chapter
Measuring precipitation on a global scale is only possible from satellite platforms. Satellite precipitation estimates are based on geosynchronous infrared sensors on geostationary satellites, characterized by high sampling frequency, and polar-orbiting microwave sensors on low-Earth-orbiting satellites with less-frequent sampling. Assessing satell...
Article
This article focuses on developing a data assimilation system that combines the modeled surface moisture estimates and satellite observations. Specifically, model states simulated by the Noah-MP land surface model are updated using an Ensemble Kalman Filter with products from the NASA SMAP (Soil Moisture Active Passive) satellite mission. The land...
Article
Full-text available
The coronavirus disease 2019 (COVID-19) has been first reported in December 2019 and rapidly spread worldwide. As other severe acute respiratory syndromes, it is a widely discussed topic whether seasonality affects the COVID-19 infection spreading. This study presents two different approaches to analyse the impact of social activity factors and wea...
Article
Full-text available
Freeze/thaw (FT) processes at the earth's surface can have a considerable effect on global carbon, energy, and hydrologic cycles. Therefore, an accurate representation of FT is valuable to adequately monitor and model these processes. In this study, we assess the relationship between satellite-based FT products and modeled surface and soil temperat...
Article
Full-text available
This study characterizes precipitation error propagation through a distributed hydrological model based on the river basins across the Contiguous United States (CONUS), to better understand the relationship between errors in precipitation inputs and simulated discharge (i.e., P-Q error relationship). The NLDAS-2 precipitation and its simulated disc...
Technical Report
Full-text available
This report reviews the current state of precipitation products, and includes assessments of sub-daily global satellite precipitation products, discussions of various climate applications of precipitation products, and deliberations on emerging directions and the future of precipitation products.
Article
To address the need to map precipitation on a global scale a collection of satellites carrying passive microwave (PMW) radiometers has grown over the last 20 years to form a constellation of about 10-12 sensors at any one time. Over the same period, a broad range of science and user communities has become increasingly dependent on the precipitation...
Article
Full-text available
This first paper of the two‐part series focuses on demonstrating the accuracy of a hyper‐resolution, offline terrestrial modeling system used for the High Mountain Asia (HMA) region. To this end, this study systematically evaluates four sets of model simulations at point scale, basin scale, and domain scale obtained from different spatial resolutio...
Article
This work investigates the use of a stochastic error model (the 2-Dimensional Satellite Rainfall Error Model-SREM2D) to generate an ensemble of rainfall fields, based on the forecasts from the Eta regional weather forecast model. To evaluate the usefulness of this approach against traditional techniques, streamflow probabilistic forecasts from a di...
Article
Full-text available
The Gravity Recovery and Climate Experiment (GRACE) mission and its Follow-On (GRACE-FO) mission provide unprecedented observations of terrestrial water storage (TWS) dynamics at basin to continental scales. Established GRACE data assimilation techniques directly adjust the simulated water storage components to improve the estimation of groundwater...
Article
Full-text available
This work investigates the inter-relationships among stream water quality indicators, hydroclimatic variables (e.g., precipitation, river discharge), and land characteristics (e.g., soil type, land use), which is crucial to developing effective methods for water quality protection. The potential of using statistical tools, such as Principal Compone...
Article
The goal of this work is to estimate surface and root zone soil moisture at resolutions that are useful for decision making and water resources management. A 500-m atmospheric forcing dataset is developed from the 12.5-km NLDAS-2 (North America Land Data Assimilation System) products across Oklahoma, where high-quality observations are available fo...
Article
Full-text available
This study provides a comprehensive evaluation of streamflow and water quality simulated by a hydrological model using three different Satellite Precipitation Products (SPPs) with respect to observations from a dense rain gauge network over the Occoquan Watershed, located in Northern Virginia, suburbs to Washington, D.C., U.S. Eight extreme hydromet...
Article
Full-text available
This study investigated the propagation of errors in input satellite-based precipitation products (SPPs) on streamflow and water quality indicators simulated by a hydrological model in the Occoquan Watershed, located in the suburban Washington, D.C. area. A dense rain gauge network was used as reference to evaluate three SPPs which are based on dif...
Article
Full-text available
The accurate representation of the local-scale variability of precipitation plays an important role in understanding the hydrological cycle and land-atmosphere interactions in the High Mountain Asia region. Therefore, the development of hyper-resolution precipitation data is of urgent need. In this study, we propose a statistical framework to downs...
Article
Full-text available
This article presents an online teaching tool that introduces students to basic concepts of remote sensing and its applications in hydrology. The learning module is intended for junior/senior undergraduate students or junior graduate students with no (or little) prior experience in remote sensing, but with some basic background of environmental sci...
Article
Full-text available
This study evaluates the potential of assimilating phenology observations using a direct insertion (DI) method by constraining the modeled terrestrial carbon dynamics with synthetic observations of vegetation condition. Specifically, observations of leaf area index (LAI) are assimilated in the Noah-Multi Parameterization (Noah-MP) land surface mode...
Article
Full-text available
Vegetation plays a fundamental role not only in the energy and carbon cycles but also in the global water balance by controlling surface evapotranspiration (ET). Thus, accurately estimating vegetation-related variables has the potential to improve our understanding and estimation of the dynamic interactions between the water, energy, and carbon cyc...
Article
Full-text available
The NASA L-Band Soil Moisture Active Passive (SMAP) satellite mission launched in 2015 has produced soil moisture and freeze thaw (FT) products at a global scale. While the use of L-band (1.41 GHz) passive microwave radiometry (P-MW) has proven useful in detecting changes in the surface FT state, these classifications have not been comprehensively...
Article
Full-text available
Rain gauges are unevenly spaced around the world with extremely low gauge density over developing countries. For instance, in some regions in Africa the gauge density is often less than one station per 10 000 km2. The availability of rainfall data provided by gauges is also not always guaranteed in near real time or with a timeliness suited for agr...
Chapter
Quantifying errors and uncertainties associated with satellite precipitation products (SPPs) is fundamental to guarantee their correct use in several applications, including hydrological predictions, climate studies, and water resource management. Numerous factors affect the accuracy and precision of these products, including the sensor frequencies...
Chapter
The estimation of precipitation (rainfall and snowfall) across the Earth’s surface is important for both science and user applications, ranging from understanding and improving our knowledge of the global energy and water cycle, to water resources and hydrological modelling, and to societal applications such as water availability and monitoring of...
Article
Error estimates associated with satellite precipitation retrievals are crucial to allow inferences about the reliability of such products in their operational applications. However, evaluating satellite precipitation error characteristics is challenging because of the inherent temporal and spatial variability of precipitation, measurement errors, a...
Article
Full-text available
Study Region The Washington D.C area. Study Focus This work investigates the potential of using satellite-based precipitation products in a hydrological model to estimate water quality indicators in the Occoquan Watershed, located in the suburban Washington D.C area. Three (3) satellite-based precipitation products based on different retrieval alg...
Article
Full-text available
This study proposes a physically-based downscaling approach for a set of atmospheric variables that relies on correlations with landscape information, such as topography, surface roughness, and vegetation. A proof-of-concept has been implemented over Oklahoma, where high-resolution, high-quality observations are available for validation purposes. H...
Preprint
Full-text available
Abstract. Vegetation plays a fundamental role not only in the energy and carbon cycle, but also the global water balance by controlling surface evapotranspiration. Thus, accurately estimating vegetation-related variables has the potential to improve our understanding and estimation of the dynamic interactions between the water and carbon cycles. Th...
Preprint
Full-text available
With more satellite and model precipitation data becoming available, new analytical methods are needed that can take advantage of emerging data patterns to make well informed predictions in many hydrological applications. We propose a new strategy where we extract precipitation variability patterns and use correlation map to build the resulting den...
Article
Full-text available
Rain gauges are unevenly spaced around the world with extremely low gauge density over developing countries. For instance, in some regions in Africa the gauge density is often less than one station per 10 000 km². The availability of rainfall data provided by gauges is also not always guaranteed in near real time or with a timeliness suited for agr...
Article
This paper investigates surface temperature variables as they relate to passive microwave-derived surface freeze/thaw (FT) state and assesses the accuracy of such FT products relative to surface temperature. Utilizing retrievals from the soil moisture active/passive (SMAP), advanced microwave scanning radiometer, and special sensor microwave imager...
Article
Full-text available
High‐intensity precipitation represents a threat for several regions of the world because of the related risk of natural disasters (e.g., floods and landslides). This work focuses on low‐level precipitation enhancement that occurs in the cloud warm layer and has been observed in relation to collision‐coalescence (CC) leading to flash floods and ext...
Article
Full-text available
This study explores the uncertainties in terrestrial water budget estimation over High Mountain Asia (HMA) using a suite of uncoupled land surface model (LSM) simulations. The uncertainty in the water balance components of precipitation (P), evapotranspiration (ET), runoff (R), and terrestrial water storage (TWS) is significantly impacted by the un...
Article
Full-text available
Toward qualifying hydrologic changes in the High Mountain Asia (HMA) region, this study explores the use of a hyper-resolution (1 km) land data assimilation (DA) framework developed within the NASA Land Information System using the Noah Multi-parameterization Land Surface Model (Noah-MP) forced by the meteorological boundary conditions from Modern-...
Poster
Full-text available
This study evaluates the potential of assimilating phenology observations on water cycle in a land data assimilation system. Specifically, observations of Leaf Area Index (LAI) are assimilated in the Noah-Multi Parameterization (Noah-MP) within a Land Data Assimilation System, forced with the NASA NLDAS-2 dataset across the contiguous United States...
Poster
Full-text available
An accurate characterization of the global hydrologic cycle is essential not only to study and forecast climate variations, but also for extreme event mitigation and agricultural planning. Since precipitation is the major driving force of the hydrological cycle, current and future satellite missions with a focus on precipitation are critical to est...
Article
Precipitation is a fundamental forcing variable in land surface modeling, controlling several hydrological and biogeochemical processes (e.g., runoff, carbon cycling, evaporation, transpiration, groundwater recharge, and soil moisture). However, precipitation estimates from rain gauges, ground-based radars, satellite sensors, and numerical models a...
Article
This work investigates the potential of using the Bayesian-based Model Conditional Processor (MCP) for complementing satellite precipitation products with a rainfall dataset derived from satellite soil moisture observations. MCP – which is a Bayesian Inversion approach – was originally developed for predictive uncertainty estimates of water level a...
Article
Full-text available
The performance of Level-3 gridded Global Precipitation Mission (GPM)-based precipitation products (IMERG, Integrated Multi-satellite Retrievals for GPM) is assessed against two references over oceans: the OceanRAIN dataset, derived from oceanic shipboard disdrometers, and a satellite-based radar product (the Level-3 Dual-frequency Precipitation Ra...
Poster
Full-text available
In this work, we analyze Level-3 Global Precipitation Mission (GPM) based precipitation products against systematic long-term disdrometer-based oceanic shipboard precipitation data (OceanRAIN) over oceans. The early, late, final IMERG products, their merged microwave-only (MW) and infrared-only (IR) components, and the Level-3 Dual-frequency Precip...
Poster
Full-text available
This study evaluates the potential of assimilating phenology observations in a land data assimilation system by constraining the modeled terrestrial carbon dynamics with remotely sensed observations of vegetation condition. Specifically, observations of Leaf Area Index (LAI) are assimilated in the Noah-Multi Parameterization (Noah-MP) within a Land...
Article
Full-text available
This work proposes an approach to analyze water quality data that is based on rough set theory. Six major water quality indicators (temperature, pH, dissolved oxygen, turbidity, specific conductivity, and nitrate concentration) were collected at the outlet of the watershed that contains the George Mason University campus in Fairfax, VA during three...
Article
This study investigates the efficiency of correcting radar rainfall estimates using a stochastic error model in the upper Iguaçu river basin in Southern Brazil for improving streamflow simulations. The 2-Dimensional Satellite Rainfall Error Model (SREM2D) is adopted here and modified to account for topographic complexity, seasonality, and distance...
Article
This work investigates the viability of using the Global Precipitation Mission (GPM) Dual‐frequency Precipitation Radar (DPR) as a reference for evaluating multi‐satellite precipitation products in locations where a ground‐based reference is not available. The Integrated Multi‐Satellite Retrievals for Global Precipitation Measurement (IMERG) versio...
Chapter
Full-text available
This chapter addresses some of the mathematical challenges associated with current experimental and computational methods to analyze spatiotemporal precipitation patterns. After a brief overview of the various methods to measure precipitation from in situ observations, satellite platforms, and via model simulations, the chapter focuses on the stati...