Search results for "Statistics"

Budyko’s Based Method for Annual Runoff Characterization across Different Climatic Areas: an Application to United States

2018

Runoff data knowledge is of fundamental importance for a wide range of hydrological, ecological, and socioeconomic applications. The reconstruction of annual runoff is a fundamental task for several activities related to water resources management, especially for ungauged basins. At catchment scales, the Budyko's framework provides an extremely useful and, in some cases, accurate estimation of the long-term partitioning of precipitation into evapotranspiration and runoff as a function of the prevailing climatic conditions. Recently the same long-term partitioning rules have been successfully used to describe water partitioning also at the annual scale and calculate the annual runoff distrib…

Assessment of the Potential Evapotranspiration MODIS Product Using Ground Measurements in the Pampas

2018

Evapotranspiration is the hydrological variable of greatest relevance in the Argentina Pampas Region (APR). The estimation of potential evapotranspiration (PET) in this area becomes essential since primary productivity is directly linked to water availability. In order to evaluate the MOD16_A2 product of evapotranspiration (ET), a comparison with in situ measurements was conducted. We used ET data provided by the Oficina de Riesgo Agropecuario, corresponding to 24 stations placed in the region covering all seasons for the years 2012 to 2014. Results show an overestimation of 86% and 52% in Autumn-Winter and Spring-Summer, respectively. Mean Absolut Error (MAE) range between ±0.9 and ±2.1 mm…

A Global Sensitivity Analysis Toolbox to Quantify Drivers of Vegetation Radiative Transfer Models

2017

Abstract Global sensitivity analysis (GSA) enables to gain insight into the functioning of radiative transfer models (RTMs) by identifying the driving input variables of RTM spectral outputs such as reflectance, fluorescence, or radiance. This contribution introduces automated radiative transfer models operator's (ARTMO’s) new GSA toolbox. With the GSA toolbox the majority of ARTMO’s available RTMs can be decomposed into its driving variables. For a selected RTM output, a GSA identifies the most influential and noninfluential input variables according to Sobol' first-order and total-order indices. The toolbox can process RTM spectral outputs for any kind of optical sensor setting within the…

Derivation of global vegetation biophysical parameters from EUMETSAT Polar System

2020

Abstract This paper presents the algorithm developed in LSA-SAF (Satellite Application Facility for Land Surface Analysis) for the derivation of global vegetation parameters from the AVHRR (Advanced Very High Resolution Radiometer) sensor on board MetOp (Meteorological–Operational) satellites forming the EUMETSAT (European Organization for the Exploitation of Meteorological Satellites) Polar System (EPS). The suite of LSA-SAF EPS vegetation products includes the leaf area index (LAI), the fractional vegetation cover (FVC), and the fraction of absorbed photosynthetically active radiation (FAPAR). LAI, FAPAR, and FVC characterize the structure and the functioning of vegetation and are key par…

Analytical Process

2016

Application of entropic approach to estimate the mean flow velocity and Manning roughness coefficient in a high-curvature flume

2016

The entropy-based approach allows the estimation of the mean flow velocity in open channel flow by using the maximum flow velocity. The linear relationship between the mean velocity, umax, and the mean flow velocity, um, through the dimensionless parameter Φ(M), has been verified both in natural rivers and in laboratory channels. Recently, the authors of this study investigated the reliability of the entropy-based formula in a straight channel and under different bed and side-walls' roughness conditions. The present study aims to further validate the entropy-based approach and to explore the effectiveness of entropy-based formula in high curvature channels. Results show that as the effect o…

Joint Gaussian processes for inverse modeling

2017

Solving inverse problems is central in geosciences and remote sensing. Very often a mechanistic physical model of the system exists that solves the forward problem. Inverting the implied radiative transfer model (RTM) equations numerically implies, however, challenging and computationally demanding problems. Statistical models tackle the inverse problem and predict the biophysical parameter of interest from radiance data, exploiting either in situ data or simulated data from an RTM. We introduce a novel nonlinear and nonparametric statistical inversion model which incorporates both real observations and RTM-simulated data. The proposed Joint Gaussian Process (JGP) provides a solid framework…

Edge-Based Missing Data Imputation in Large-Scale Environments

2021

Smart cities leverage large amounts of data acquired in the urban environment in the context of decision support tools. These tools enable monitoring the environment to improve the quality of services offered to citizens. The increasing diffusion of personal Internet of things devices capable of sensing the physical environment allows for low-cost solutions to acquire a large amount of information within the urban environment. On the one hand, the use of mobile and intermittent sensors implies new scenarios of large-scale data analysis

Automatic emulator and optimized look-up table generation for radiative transfer models

2017

This paper introduces an automatic methodology to construct emulators for costly radiative transfer models (RTMs). The proposed method is sequential and adaptive, and it is based on the notion of the acquisition function by which instead of optimizing the unknown RTM underlying function we propose to achieve accurate approximations. The Automatic Gaussian Process Emulator (AGAPE) methodology combines the interpolation capabilities of Gaussian processes (GPs) with the accurate design of an acquisition function that favors sampling in low density regions and flatness of the interpolation function. We illustrate the good capabilities of the method in toy examples and for the construction of an…

Multioutput Automatic Emulator for Radiative Transfer Models

2018

This paper introduces a methodology to construct emulators of costly radiative transfer models (RTMs). The proposed methodology is sequential and adaptive, and it is based on the notion of acquisition functions in Bayesian optimization. Here, instead of optimizing the unknown underlying RTM function, one aims to achieve accurate approximations. The Automatic Multi-Output Gaussian Process Emulator (AMO-GAPE) methodology combines the interpolation capabilities of Gaussian processes (GPs) with the accurate design of an acquisition function that favors sampling in low density regions and flatness of the interpolation function. We illustrate the promising capabilities of the method for the const…