{"id":1606,"date":"2022-07-23T15:41:05","date_gmt":"2022-07-23T15:41:05","guid":{"rendered":"https:\/\/ganeshrghimire.com\/?page_id=1606"},"modified":"2026-02-02T02:00:48","modified_gmt":"2026-02-02T02:00:48","slug":"journal-papers-2","status":"publish","type":"page","link":"https:\/\/ganeshrghimire.com\/?page_id=1606","title":{"rendered":"Journal Papers"},"content":{"rendered":"\t\t
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[32] Talchabhadel, R., Panthi, J., Pandey, V.P., Rakhal, B., Ghimire, G.R.<\/strong>, Bista, S., Bhattarai, S., Poudel, S., Bhattarai, Y., Prajapati, R., Thapa, B.R., Nepal, B., and Sharma, S. 2025. Yesterday\u2019s Extremes, Today\u2019s New Normal – Flood Risk in the Kathmandu Valley, Nepal. Natural Hazards,\u00a0<\/strong><\/em>https:\/\/doi.org\/10.1007\/s11069-025-07524-5<\/u><\/a>.<\/i><\/p>\n

[31] Ghimire, G.R.<\/strong>, Liu, Y.,\u00a0Parish, E.,\u00a0<\/span>Gangrade, S., Kao, SC., DeRolph, C., Maguire, K., and\u00a0<\/span>Jager, H.\u00a0<\/span>2025: Integrated Modeling driven Evaluation of Opportunities for Climate-Resilient Perennial Biomass Crop Plantings in Flood-Prone Agricultural Landscapes. <\/span>Journal of Flood Risk Management, <\/em>18, e70056,<\/em> https:\/\/doi.org\/10.1111\/jfr3.70056<\/u><\/a>.<\/span><\/p>\n

[30] <\/span>Ghimire, G.R.<\/strong>, Kao, S.C., and Gangrade, S. 2025: Enhancing Streamflow Reanalysis Across the Conterminous U.S. Leveraging Multiple Gridded Precipitation Datasets. <\/span>Water Resources Research,\u00a0<\/em>61,\u00a0<\/i>e2024WR038256.\u00a0<\/i>https:\/\/doi.org\/10.1029\/2024WR038256<\/a><\/span><\/p>\n

[29] Broman, D., Voisin, N., Kao, S.C., Fernandez, A., and Ghimire, <\/strong>G.R<\/b>.<\/strong>\u00a0 2024: Multi-scale impacts of climate change on hydropower for long-term water-energy planning in the contiguous United States. Environmental Research Letters <\/em>https:\/\/doi.org\/10.1088\/1748-9326\/ad6ceb<\/span><\/a><\/p>\n

[28] Turner, S.W.D., Ghimire, G.R.<\/b>, Hansen, C., Singh, D., and Kao, S.C. 2024: Hydropower capacity factors trending down in the United States. Nature Communications.<\/b><\/i> https:\/\/doi.org\/10.1038\/s41467-024-49553-x<\/a><\/span>\u00a0\u00a0<\/p>\n

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[27] Bista, S., Baniya, R., Sharma, S., Ghimire, G.R.<\/strong>, Panthi, J., Prajapati, R., Thapa, B.R.,\u00a0Talchabhadel, R.<\/span> 2024: Hydrologic applicability of satellite precipitation estimates for irrigation water management in the data-scarce region. <\/span>Journal of Hydrology. <\/em>https:\/\/doi.org\/10.1016\/j.jhydrol.2024.131310<\/a><\/span><\/p>\n

[26] Baniya R., Regmi, R.K., Talchabhadel, R., Sharma, S., Panthi, J.,\u00a0<\/span>Ghimire, G.R.<\/span>, Bista, S., Thapa, B.R., Pradhan, A.M.S., and Tamrakar, J.<\/span>\u00a02024: Integrated modeling for assessing climate change impacts on water resources and hydropower potential in the Himalayas.\u00a0<\/span>Theoretical and Applied Climatology.<\/b><\/em> https:\/\/doi.org\/10.1007\/s00704-024-04863-4<\/u><\/a>.<\/span><\/p>\n

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[25] Gangrade, S., <\/span>Ghimire, G.R.<\/strong>, Kao, S.C., Morales-Hern\u00e1ndez, M., Tavakoly, A.A., Gutenson, J.L., Sparrow, K.H., Darkwah, G.K., Kalyanapu, A.J., and Follum, M.L. 2022: Unraveling 2021 Central Tennessee flood event using a hierarchical multi-model inundation modeling framework. <\/span>Journal of Hydrology <\/em>https:\/\/doi.org\/10.1016\/j.jhydrol.2023.130157<\/u><\/a>.\u00a0<\/span><\/p>\n

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[24] Baniya R., Talchabhadel, R., Panthi, J., Ghimire, G.R.<\/strong>, Sharma, S., Khadka, P., Shin, S., Pokhrel, Y., Bhattarai, U., Prajapati, R., Thapa, B.R., and Maskey, R.K. 2022: Nepal Himalaya offers considerable potential for pumped storage hydropower.\u00a0Sustainable Energy Technologies and Assessments<\/em>\u00a0https:\/\/doi.org\/10.1016\/j.seta.2023.103423<\/u><\/a>.\u00a0<\/p>\n

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[23] Ghimire, G.R.<\/strong>, Hansen, C., Gangrade, S., Kao, S.C., Thornton, P., and Singh, D. 2022: Insights from Dayflow: A historical streamflow reanalysis dataset for the Conterminous United States.\u00a0Water Resources Research\u00a0<\/em>https:\/\/doi.org\/10.1029\/2022WR032312<\/u><\/a>.<\/p>\n

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[22] Sharma, S.,\u00a0Ghimire, G.R.<\/strong>, and Siddique, R. 2022: Machine Learning for Postprocessing Ensemble Streamflow Forecasts.\u00a0Journal of Hydroinformatics\u00a0<\/em>https:\/\/doi.org\/10.2166\/hydro.2022.114<\/u><\/a>.<\/p>\n

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[21] Shrestha R., Rakhal, B., Adhikari, T.R.,\u00a0Ghimire, G.R.<\/strong>, Talchabhadel, R., Tamang, D., KC, R., and Sharma, S. 2022: Farmers\u2019 Perception of Climate Change and its Impacts on Agriculture.\u00a0Hydrology<\/em>,\u00a09<\/em>, 212. https:\/\/doi.org\/10.3390\/hydrology9120212<\/a>3<\/u><\/p>\n

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[20] Hansen, C.,\u00a0Ghimire, G.R.<\/strong>, and Kao, S.C. 2022: Evaluation of nominal energy storage at existing hydropower reservoirs in the US.\u00a0Water Resources Research<\/em> https:\/\/doi.org\/10.1029\/2022WR032210<\/u><\/a><\/p>\n

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[19] Sharma, S., Talchabhadel, R., Nepal, S.,\u00a0<\/span>Ghimire, G.R.<\/strong>, Rakhal, B., Panthi, J., Adhikari, B.R., Pradhanang, S.M., Maskey, S., and Kumar, S. 2022: Increasing risk of cascading hazards in the central Himalayas.\u00a0<\/span>Natural Hazards<\/em>\u00a0<\/span>https:\/\/doi.org\/10.1007\/s11069-022-05462-0<\/u><\/a><\/p>\n

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[18] Ghimire, G. R.<\/strong>, Krajewski, W.F., Ayalew, T.B., and Goska, R. 2022: Hydrologic investigations of radar-rainfall errors propagation to rainfall-runoff model hydrographs.\u00a0Advances in Water Resources <\/em>https:\/\/doi.org\/10.1016\/j.advwatres.2022.104145<\/u><\/a><\/p>\n

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[17] Sharma, S., Dahal, K., Nava, L., Gouli, M. R., Talchabhadel, R., Panthi, J., Roy, T., and\u00a0Ghimire, G.R.<\/strong>\u00a02022: Natural Hazards Perspectives on Integrated, Coordinated, Open, Networked (ICON) Science\u00a0Earth and Space Science\u00a0<\/em>https:\/\/doi.org\/10.1029\/2021EA002114<\/u><\/a>\u00a0<\/a><\/em>(Featured as a Research Spotlight on AGU\u00a0EOS<\/em>\u00a0issue\u00a0https:\/\/eos.org\/research-spotlights\/icon-principles-underused-as-a-natural-hazards-research-tool<\/u><\/a>).<\/p>\n

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[16] Krajewski, W.F.,\u00a0Ghimire, G. R.<\/strong>, Demir, I., and Mantilla, R. 2021: Real-time streamflow forecasting: AI vs. Hydrologic insights.\u00a0Journal of Hydrology X\u00a0<\/em>https:\/\/doi.org\/10.1016\/j.hydroa.2021.100110<\/u><\/a><\/p>\n

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[15] Sharma, S.,\u00a0Ghimire, G.R.<\/strong>, Talchabhadel, R., Panthi, J., Lee, B.S., Sun, F., Baniya, R., and Adhikari, T.R. 2021: Bayesian characterization of uncertainties surrounding fluvial flood hazard estimates.\u00a0Hydrologic Sciences Journal\u00a0<\/em>https:\/\/doi.org\/10.1080\/02626667.2021.1999959<\/u><\/a><\/p>\n

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[14] Ghimire, G. R.,\u00a0<\/strong>Jadidoleslam, N., Goska, R., and Krajewski, W.F. 2021: Insights into storm direction effect on flood response.\u00a0Journal of Hydrology\u00a0<\/em>https:\/\/doi.org\/10.1016\/j.jhydrol.2021.126683<\/u><\/a><\/p>\n

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[13] Panthi, J., Talchabhadel, R.,\u00a0Ghimire, G.R.<\/strong>, Sharma, S., Dahal, P., Baniya, R., Boving, T., Pradhanang, S.M., and Parajuli, B. 2021: Hydrologic regionalization under data scarcity: An implication for streamflow prediction\u00a0ASCE Journal of Hydrologic Engineering,\u00a0<\/em>https:\/\/doi.org\/10.1061\/(ASCE)HE.1943-5584.0002121<\/u><\/a><\/p>\n

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[12] Ghimire, G. R.<\/strong>, Krajewski, W.F., and Quintero, F. 2021: Scale-dependent value of QPF for real-time streamflow forecasting.\u00a0Journal of Hydrometeorology,\u00a0<\/em>https:\/\/doi.org\/10.1175\/JHM-D-20-0297.1<\/u><\/a><\/p>\n

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[11] Rakhal, B., Sharma, S.,\u00a0Ghimire, G.R.<\/strong>, Adhikari, T.R., and Shrestha, R. Nepal\u2019s communities brace for multihazard risks.\u00a0EOS,\u00a0<\/em>102,\u00a0https:\/\/doi.org\/10.1029\/2021EO159039<\/u><\/a><\/p>\n

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[10] Talchabhadel, R.,\u00a0Ghimire, G.R.<\/strong>, Sharma, S., Dahal, P., Panthi, J., Baniya, R., Pudashine, J., Thapa, B.R., PC, S., and Parajuli, B. 2020: Weather radar in Nepal: Opportunities and challenges in a mountainous region.\u00a0Weather,<\/em> https:\/\/doi.org\/10.1002\/wea.3994<\/u><\/a>\u00a0<\/p>\n

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[9] Talchabhadel, R., Panthi, J., Sharma, S.,\u00a0Ghimire, G.R.<\/strong>, Baniya, R., Dahal, P., Baniya, M.P., K.C, S., Jha, B., Kaini, S., Dahal, K., Gnyawali, K.R., Parajuli, B., and Kumar, S. 2021: Insights on the impacts of hydroclimatic extremes and anthropogenic activities on sediment yield of a river basin\u00a0Earth<\/em>,\u00a02<\/em>(1), 32-50,\u00a0https:\/\/doi.org\/10.3390\/earth2010003<\/u><\/a><\/p>\n

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[8] Rakhal, B., Adhikari, T.R., Sharma, S., and\u00a0Ghimire, G.R.<\/strong>2021:\u00a0Assessment of channel shifting of Karnali Megafan in Nepal using remote sensing and GIS.\u00a0Annals of GIS,<\/em> https:\/\/doi.org\/10.1080\/19475683.2021.1871950<\/u><\/a><\/p>\n

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[7] Ghimire, G.R.<\/strong>, DeVantier, B.A., and Sharma, S. 2020: Site-specific sediment deposition model for dredging planning: Case study of Olmstead locks and dam.\u00a0ASCE Journal of Waterway, Port, Coastal and Oceanic Engineering.\u00a0<\/em>https:\/\/doi.org\/10.1061\/(ASCE)WW.1943-5460.0000598<\/u><\/a><\/p>\n

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[6] Ghimire, G. R.<\/strong>, Sharma, S., Panthi, J., Talchabhadel, R., Parajuli, B., Dahal, P., and Baniya, R. 2020: Benchmarking real-time streamflow forecasting skill in the Himalayan region.\u00a0Forecasting<\/em>, 2, 3, 230-247,\u00a0https:\/\/doi.org\/10.3390\/forecast2030013<\/u><\/a><\/p>\n

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[5] Ghimire, G. R.<\/strong>, and Krajewski, W. F. 2020: Hydrologic implications of wind farm effect on radar\u2010rainfall observations.\u00a0Geophysical Research Letters<\/em>, 47,\u00a0https:\/\/doi.org\/10.1029\/2020GL089188<\/u><\/a><\/p>\n

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[4] Ghimire, G. R.<\/strong>, Jadidoleslam, N., Krajewski, W.F., and Tsonis, A. A. 2020: Insights on streamflow predictability across scales using horizontal visibility graph-based networks.\u00a0Frontiers in Water<\/em>, 2, 17, 1-15,\u00a0https:\/\/doi:10.3389\/frwa.2020.00017<\/u><\/a><\/p>\n

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[3] Krajewski, W. F.,\u00a0Ghimire, G. R.<\/strong>, and Quintero, F. 2020: Streamflow forecasting without models.\u00a0Journal of Hydrometeorology<\/em>, 21, 1689-1704,\u00a0https:\/\/doi.org\/10.1175\/JHM-D-19-0292.1<\/u><\/a><\/p>\n

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[2] Ghimire, G. R.<\/strong>, and W. F. Krajewski, 2020: Exploring persistence in streamflow forecasting.\u00a0Journal of the American Water Resources Association<\/em>, 56, 542\u2013550,\u00a0https:\/\/doi.org\/10.1111\/1752-1688.12821<\/u><\/a><\/p>\n

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[1] Ghimire, G.R.<\/strong>, W.F. Krajewski, and R. Mantilla. 2018: A power law model for river flow velocity in Iowa basins.\u00a0Journal of the American Water Resources Association<\/em>, 1\u201313,\u00a0https:\/\/doi.org\/10.1111\/1752-1688.12665<\/u><\/a><\/p>\n

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[32] Talchabhadel, R., Panthi, J., Pandey, V.P., Rakhal, B., Ghimire, G.R., Bista, S., Bhattarai, S., Poudel, S., Bhattarai, Y., Prajapati, R., Thapa, B.R., Nepal, B., and Sharma, S. 2025. Yesterday\u2019s Extremes, Today\u2019s New Normal – Flood Risk in the Kathmandu Valley, Nepal. Natural Hazards,\u00a0https:\/\/doi.org\/10.1007\/s11069-025-07524-5. [31] Ghimire, G.R., Liu, Y.,\u00a0Parish, E.,\u00a0Gangrade, S., Kao, SC., DeRolph, C., […]<\/p>\n","protected":false},"author":1,"featured_media":0,"parent":0,"menu_order":0,"comment_status":"closed","ping_status":"closed","template":"","meta":{"om_disable_all_campaigns":false,"_monsterinsights_skip_tracking":false,"_monsterinsights_sitenote_active":false,"_monsterinsights_sitenote_note":"","_monsterinsights_sitenote_category":0,"site-sidebar-layout":"default","site-content-layout":"default","ast-site-content-layout":"default","site-content-style":"default","site-sidebar-style":"default","ast-global-header-display":"","ast-banner-title-visibility":"","ast-main-header-display":"","ast-hfb-above-header-display":"","ast-hfb-below-header-display":"","ast-hfb-mobile-header-display":"","site-post-title":"","ast-breadcrumbs-content":"","ast-featured-img":"","footer-sml-layout":"","ast-disable-related-posts":"","theme-transparent-header-meta":"default","adv-header-id-meta":"","stick-header-meta":"","header-above-stick-meta":"","header-main-stick-meta":"","header-below-stick-meta":"","astra-migrate-meta-layouts":"default","ast-page-background-enabled":"default","ast-page-background-meta":{"desktop":{"background-color":"var(--ast-global-color-4)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"ast-content-background-meta":{"desktop":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"tablet":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""},"mobile":{"background-color":"var(--ast-global-color-5)","background-image":"","background-repeat":"repeat","background-position":"center center","background-size":"auto","background-attachment":"scroll","background-type":"","background-media":"","overlay-type":"","overlay-color":"","overlay-opacity":"","overlay-gradient":""}},"footnotes":""},"class_list":["post-1606","page","type-page","status-publish","hentry"],"aioseo_notices":[],"aioseo_head":"\n\t\t\n\t\n\t\n\t\n\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t\n\t\t