Witnessing ENSO with Precipitation and Flood Dynamics in the Karnali River Basin of Nepal

Witnessing ENSO with Precipitation and Flood Dynamics in the Karnali River Basin of Nepal | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Witnessing ENSO with Precipitation and Flood Dynamics in the Karnali River Basin of Nepal Tirtha Raj Adhikari, Binod Baniya, Qiuhong Tang, He Li, Suraj Shrestha, and 3 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-6569027/v1 This work is licensed under a CC BY 4.0 License Status: Published Journal Publication published 26 Mar, 2026 Read the published version in Natural Hazards → Version 1 posted 5 You are reading this latest preprint version Abstract El Niño Southern Oscillation (ENSO), encompassing El Niño and La Niña, significantly influences river flooding patterns, prompting this study to investigate its relationship with floods in Nepal's transboundary Karnali River Basin (KRB). Focusing on extreme flood events during El Niño and La Niña years, the research aims to enhance the understanding of ENSO's impact on hydrological and hydrodynamic processes. Precipitation and discharge data spanning 1964 to 2020, sourced from the Department of Hydrology and Meteorology (DHM), Government of Nepal, were analyzed. Hydrodynamic modeling, employing HEC-HMS and HEC-RAS, simulated extreme floods of 1983, 2000, 2014 (La Niña years), and 2015 (a strong El Niño year) at the DHM hydrological station. The study examined basin characteristics, precipitation depth, river discharge, and gauge height during these events, utilizing daily data for model estimation of flood discharge and depth. Analysis of ENSO-related variability, including Sea Surface Temperature (SST), Southern Oscillation Index (SOI), and Multivariate ENSO Index (MEI), alongside pressure, temperature, and discharge data across the KRB, was conducted using a three-year running mean. The Soil Conservation Service (SCS) method was integrated within the HEC-HMS and HEC-RAS models to evaluate rainfall duration and flood response considering terrain, soil, and land use. Model simulations revealed river channel shifts, particularly along the right bank, during the 2015 ENSO event. Intensity-duration-frequency (IDF) and correlation/regression analyses further elucidated the impact of ENSO, with the lowest recorded precipitation and discharge observed during the 2015 El Niño event despite localized heavy rainfall. Comparative analysis of flood discharge, gauge height, inundation extents, depths, and velocities across ENSO years highlighted a significant relationship between observed and modeled discharge during the monsoon season. These findings offer valuable insights for water resource management and development, aiding in the anticipation of future strong ENSO and El Niño events in the region. ENSO Precipitation Extreme Floods River Channel Shifts Transboundary Karnali River Basin Nepal Full Text Supplementary Files SupplementaryAppendixAE.docx Cite Share Download PDF Status: Published Journal Publication published 26 Mar, 2026 Read the published version in Natural Hazards → Version 1 posted Reviewers agreed at journal 05 May, 2025 Reviewers invited by journal 05 May, 2025 Editor invited by journal 03 May, 2025 Editor assigned by journal 03 May, 2025 First submitted to journal 02 May, 2025 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-6569027","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":451825522,"identity":"d5ce63a6-59c4-41fc-b4e4-2ffb4d615d5e","order_by":0,"name":"Tirtha Raj Adhikari","email":"","orcid":"","institution":"Tribhuvan University","correspondingAuthor":false,"prefix":"","firstName":"Tirtha","middleName":"Raj","lastName":"Adhikari","suffix":""},{"id":451825523,"identity":"c5820fdb-9076-481b-a3e3-27941b590d00","order_by":1,"name":"Binod Baniya","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA3UlEQVRIiWNgGAWjYBACAwkgkcDAIAcmGRiYiddiTKIWIEhsIFqLuXTzswcP2+zS+9uTD39gqLBObJDuPYBXi+WcY+YGiW3JuTPOPEuTYDiTntggcy4Bv8NuJJhJJLYx526QyDFjYGw7nNggkWNAQEv6N6CW+nQDifzPHxj/EaUlB2TL4QQDiRwGCcYGIrRYzjlTJpFw7rgh0C9mEgnH0o3bJPLw+8Vcun2b5I+yann+9uTHHz7UWMv2S+QewKsFDBjZoAyQ8WwMPIR1MDD8QeERpWUUjIJRMApGEAAA/aBHUjfYx1cAAAAASUVORK5CYII=","orcid":"","institution":"Tribhuvan University","correspondingAuthor":true,"prefix":"","firstName":"Binod","middleName":"","lastName":"Baniya","suffix":""},{"id":451825524,"identity":"bf8db163-1aa0-44c4-9186-744ed437998c","order_by":2,"name":"Qiuhong Tang","email":"","orcid":"","institution":"IGSNRR CAS: Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"Qiuhong","middleName":"","lastName":"Tang","suffix":""},{"id":451825525,"identity":"5fe728e9-2826-47d1-8c11-dc83f3b77cee","order_by":3,"name":"He Li","email":"","orcid":"","institution":"IGSNRR CAS: Institute of Geographic Sciences and Natural Resources Research Chinese Academy of Sciences","correspondingAuthor":false,"prefix":"","firstName":"He","middleName":"","lastName":"Li","suffix":""},{"id":451825526,"identity":"cd2497d4-74ed-480e-95a7-f65c4764ddd1","order_by":4,"name":"Suraj Shrestha","email":"","orcid":"","institution":"Institute of Fundamental Research","correspondingAuthor":false,"prefix":"","firstName":"Suraj","middleName":"","lastName":"Shrestha","suffix":""},{"id":451825527,"identity":"c41c3e64-c57b-44e9-b126-9a93875e0570","order_by":5,"name":"Ram Prasad Awasthi","email":"","orcid":"","institution":"Department of Hydrology and Meteorology","correspondingAuthor":false,"prefix":"","firstName":"Ram","middleName":"Prasad","lastName":"Awasthi","suffix":""},{"id":451825528,"identity":"4d5187eb-35e3-4dfb-8d65-f485a9e2f103","order_by":6,"name":"Paul P.J. 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Focusing on extreme flood events during El Ni\u0026ntilde;o and La Ni\u0026ntilde;a years, the research aims to enhance the understanding of ENSO's impact on hydrological and hydrodynamic processes. Precipitation and discharge data spanning 1964 to 2020, sourced from the Department of Hydrology and Meteorology (DHM), Government of Nepal, were analyzed. Hydrodynamic modeling, employing HEC-HMS and HEC-RAS, simulated extreme floods of 1983, 2000, 2014 (La Ni\u0026ntilde;a years), and 2015 (a strong El Ni\u0026ntilde;o year) at the DHM hydrological station. The study examined basin characteristics, precipitation depth, river discharge, and gauge height during these events, utilizing daily data for model estimation of flood discharge and depth. Analysis of ENSO-related variability, including Sea Surface Temperature (SST), Southern Oscillation Index (SOI), and Multivariate ENSO Index (MEI), alongside pressure, temperature, and discharge data across the KRB, was conducted using a three-year running mean. The Soil Conservation Service (SCS) method was integrated within the HEC-HMS and HEC-RAS models to evaluate rainfall duration and flood response considering terrain, soil, and land use. Model simulations revealed river channel shifts, particularly along the right bank, during the 2015 ENSO event. Intensity-duration-frequency (IDF) and correlation/regression analyses further elucidated the impact of ENSO, with the lowest recorded precipitation and discharge observed during the 2015 El Ni\u0026ntilde;o event despite localized heavy rainfall. Comparative analysis of flood discharge, gauge height, inundation extents, depths, and velocities across ENSO years highlighted a significant relationship between observed and modeled discharge during the monsoon season. 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