Article
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Associating Stochastic Modelling of Flow Sequences With Climatic Trends
Version 1
: Received: 12 May 2021 / Approved: 14 May 2021 / Online: 14 May 2021 (11:43:06 CEST)
A peer-reviewed article of this Preprint also exists.
Patidar, S.; Tanner, E.; Soundharajan, B.-S.; SenGupta, B. Associating Climatic Trends with Stochastic Modelling of Flow Sequences. Geosciences 2021, 11, 255. Patidar, S.; Tanner, E.; Soundharajan, B.-S.; SenGupta, B. Associating Climatic Trends with Stochastic Modelling of Flow Sequences. Geosciences 2021, 11, 255.
Abstract
Water is essential to all life-forms including various ecological, geological, hydrological, and climatic processes/activities. With changing climate, associated El Nino/Southern Oscillation (ENSO) events appear to stimulate highly uncertain patterns of precipitation (P) and evapotranspiration (EV) processes across the globe. Changes in P and EV patterns are highly sensitive to temperature variation and thus also affecting natural streamflow processes. This paper presents a novel suite of stochastic modelling approaches for associating streamflow sequences with climatic trends. The present work is built upon a stochastic modelling framework HMM_GP that integrates a Hidden Markov Model with a Generalised Pareto distribution for simulating synthetic flow sequences. The GP distribution within HMM_GP model is aimed to improve the model's efficiency in effectively simulating extreme events. This paper further investigated the potentials of Generalised Extreme Value Distribution (EVD) coupled with an HMM model within a regression-based scheme for associating impacts of precipitation and evapotranspiration processes on streamflow. The statistical characteristic of the pioneering modelling schematic has been thoroughly assessed for their suitability to generate/predict synthetic river flows sequences for a set of future climatic projections. The new modelling schematic can be adapted for a range of applications in the area of hydrology, agriculture and climate change.
Keywords
Stochastic modelling; Climate change; Streamflow; El Nino/Southern Oscillation (ENSO), Extreme events modelling
Subject
Engineering, Automotive Engineering
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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