{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T01:39:03Z","timestamp":1773193143622,"version":"3.50.1"},"reference-count":80,"publisher":"MDPI AG","issue":"2","license":[{"start":{"date-parts":[[2023,1,12]],"date-time":"2023-01-12T00:00:00Z","timestamp":1673481600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"<jats:p>Remote sensing precipitation or precipitation from numerical weather prediction (NWP) is considered to be the best substitute for in situ ground observations for flood simulations in transboundary, data-scarce catchments. This research was aimed to evaluate the possibility of using a combination of a satellite precipitation product and NWP precipitation for better flood forecasting in the transboundary Chenab River Basin (CRB) in Pakistan. The gauge-calibrated satellite precipitation product, i.e., Global Satellite Mapping of Precipitation (GSMaP_Gauge), was selected to calibrate the Integrated Flood Analysis System (IFAS) model for the 2016 flood event in the Chenab River at the Marala Barrage gauging site in Pakistan. Precipitation from the Global Forecast System (GFS) NWP, with nine different lead times up to 4 days, was used in the calibrated IFAS model to predict the flood hydrograph in the Chenab River. The hydrologic simulations, with global GFS forecasts, were unable to predict the flood peak for all lead times. Then, the Weather Research and Forecasting (WRF) model was used to downscale the precipitation forecasts with one-way and two-way nesting approaches. In the WRF model, the CRB was centered in two domains of 25 km and 5 km resolutions. The downscaled precipitation forecasts were subsequently supplied to the IFAS model, and the predicted simulations were compared to obtain the optimal flood peak simulation in the Chenab River. It was found in this study that the simulated hydrographs, at different lead times, from the precipitation of two-way WRF nesting exhibited superior performance with the highest R2 and Nash\u2013Sutcliffe efficiency (NSE) and the lowest percent bias (PBIAS) compared with one-way nesting. Moreover, it was concluded that the combination of GFS forecast and two-way WRF nesting can provide high-quality precipitation prediction to simulate flood hydrographs with a remarkable lead time of 96 h when applying coupled hydrometeorological flow simulation.<\/jats:p>","DOI":"10.3390\/rs15020457","type":"journal-article","created":{"date-parts":[[2023,1,12]],"date-time":"2023-01-12T05:03:03Z","timestamp":1673499783000},"page":"457","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":10,"title":["Flood Predictability of One-Way and Two-Way WRF Nesting Coupled Hydrometeorological Flow Simulations in a Transboundary Chenab River Basin, Pakistan"],"prefix":"10.3390","volume":"15","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7453-3630","authenticated-orcid":false,"given":"Ehtesham","family":"Ahmed","sequence":"first","affiliation":[{"name":"Institute of Urban and Industrial Water Management, Technische Universit\u00e4t Dresden, 01069 Dresden, Germany"}]},{"given":"Naeem","family":"Saddique","sequence":"additional","affiliation":[{"name":"Institute of Hydrology and Meteorology, Technische Universit\u00e4t Dresden, 01062 Dresden, Germany"},{"name":"Department of Irrigation and Drainage, University of Agriculture, Faisalabad 38000, Pakistan"}]},{"given":"Firas","family":"Al Janabi","sequence":"additional","affiliation":[{"name":"Global Water and Climate Adaption Centre, Technische Universit\u00e4t Dresden, 01062 Dresden, Germany"}]},{"given":"Klemens","family":"Barfus","sequence":"additional","affiliation":[{"name":"Institute of Hydrology and Meteorology, Technische Universit\u00e4t Dresden, 01062 Dresden, Germany"}]},{"given":"Malik Rizwan","family":"Asghar","sequence":"additional","affiliation":[{"name":"Flood Forecasting Division, Pakistan Meteorological Department, Islamabad 44000, Pakistan"}]},{"ORCID":"https:\/\/orcid.org\/0000-0001-7402-2825","authenticated-orcid":false,"given":"Abid","family":"Sarwar","sequence":"additional","affiliation":[{"name":"Department of Irrigation and Drainage, University of Agriculture, Faisalabad 38000, Pakistan"}]},{"given":"Peter","family":"Krebs","sequence":"additional","affiliation":[{"name":"Institute of Urban and Industrial Water Management, Technische Universit\u00e4t Dresden, 01069 Dresden, Germany"}]}],"member":"1968","published-online":{"date-parts":[[2023,1,12]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"436","DOI":"10.1080\/02626667.2021.2022152","article-title":"Hydrological evaluation of 14 satellite-based, gauge-based and reanalysis precipitation products in a data-scarce mountainous catchment","volume":"67","author":"Saddique","year":"2022","journal-title":"Hydrol. 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