Optimal sequential sampling design for environmental extremes

06/24/2021
by   Raphael de Fondeville, et al.
0

The Sihl river, located near the city of Zurich in Switzerland, is under continuous and tight surveillance as it flows directly under the city's main railway station. To issue early warnings and conduct accurate risk quantification, a dense network of monitoring stations is necessary inside the river basin. However, as of 2021 only three automatic stations are operated in this region, naturally raising the question: how to extend this network for optimal monitoring of extreme rainfall events? So far, existing methodologies for station network design have mostly focused on maximizing interpolation accuracy or minimizing the uncertainty of some model's parameters estimates. In this work, we propose new principles inspired from extreme value theory for optimal monitoring of extreme events. For stationary processes, we study the theoretical properties of the induced sampling design that yields non-trivial point patterns resulting from a compromise between a boundary effect and the maximization of inter-location distances. For general applications, we propose a theoretically justified functional peak-over-threshold model and provide an algorithm for sequential station selection. We then issue recommendations for possible extensions of the Sihl river monitoring network, by efficiently leveraging both station and radar measurements available in this region.

READ FULL TEXT
POST COMMENT

Comments

There are no comments yet.

Authors

page 16

08/13/2020

Towards Dynamic Urban Bike Usage Prediction for Station Network Reconfiguration

Bike sharing has become one of the major choices of transportation for r...
06/24/2013

A State-Space Approach for Optimal Traffic Monitoring via Network Flow Sampling

The robustness and integrity of IP networks require efficient tools for ...
12/09/2020

Estimating Effectiveness of Identifying Human Trafficking via Data Envelopment Analysis

Transit monitoring is a preventative approach used to identify possible ...
01/28/2022

Non-Stationary Time Series Model for Station Based Subway Ridership During Covid-19 Pandemic (Case Study: New York City)

The COVID-19 pandemic in 2020 has caused sudden shocks in transportation...
02/08/2021

Prototyping Low-Cost Automatic Weather Stations for Natural Disaster Monitoring

Weather events put human lives at risk mostly when people might reside i...
10/09/2020

Evidence of Increasing Nonstationary Flood Risk in the Central Himalayas

Extreme floods provide a design basis for flood-sensitive infrastructure...
02/03/2020

Approximately Optimal Spatial Design: How Good is it?

The increasing recognition of the association between adverse human heal...
This week in AI

Get the week's most popular data science and artificial intelligence research sent straight to your inbox every Saturday.