Using Remote Sensing Observations And Model Simulations For The Analysis Of Hydrological Extremes

Using Remote Sensing Observations and Model Simulations for the Analysis of Hydrological Extremes

Hydrological extremes can harm society and ecosystems. However, many parts of the world lack in situ observations for quantifying hydrological extremes. Physically-based distributed hydrological model simulations driven by atmospheric simulations and remote sensing precipitation observations can be used to alleviate the issue of data scarcity in estimating return periods of hydrological extremes, but the short data record length associated with these datasets limits the application of traditional statistical methods (GEV/LP3/GPD) that rely on extreme value theory. Also, the errors in these indirect measurements or model simulations may lead to large biases in the quantification of extremes. The novel Metastatistical Extreme Value Distribution (MEVD) framework is proposed in this research as a mean of overcoming the limitations imposed by the short record length and obtaining more reliable assessment of high quantiles. The error estimates of MEVD applied on the data generated from satellite-based precipitation products and hydrological model simulations are thoroughly evaluated across different regions and hydroclimatic conditions. It is shown that MEVD is able to address the fundamental issue of data record limitations in deriving robust estimation of hydrological extremes, and alleviate the biases in hydrological model simulations of flood peaks. The application of the MEVD framework in conjunction with simulated streamflows and high-resolution precipitation products from remote sensing observations bring new opportunities for estimating hydrological extremes at global scale, including areas with limited or no in situ records.

Understanding Hydrological Extremes and their Impact in a Changing Climate: Observations, Modeling and Attribution

Remote Sensing of Hydrological Extremes

This volume provides in-depth coverage of the latest in remote sensing of hydrological extremes: both floods and droughts. The book is divided into two distinct sections – floods and droughts – and offers a variety of techniques for monitoring each. With rapid advances in computer modelling and observing systems, floods and droughts are studied with greater precision today than ever before. Land surface models, especially over the entire Continental United States, can map the hydrological cycle at kilometre and sub-kilometre scales. In the case of smaller areas there is even higher spatial resolution and the only limiting factor is the resolution of input data. In-situ sensors are automated and the data is directly relayed to the world wide web for many hydrological variables such as precipitation, soil moisture, surface temperature and heat fluxes. In addition, satellite remote sensing has advanced to providing twice a day repeat observations at kilometre to ten-kilometre spatial scales. We are at a critical juncture in the study of hydrological extremes, and the GPM and SMAP missions as well as the MODIS and GRACE sensors give us more tools and data than were ever available before. A global variety of chapter authors provides wide-ranging perspectives and case studies that will make this book an indispensable resource for researchers, engineers, and even emergency management and insurance professionals who study and/or manage hydrological extremes.