Flood Predictability of One-Way and Two-Way WRF Nesting Coupled Hydrometeorological Flow Simulations in a Transboundary Chenab River Basin, Pakistan
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...
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| Format: | Article |
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MDPI AG
2023-01-01
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| Series: | Remote Sensing |
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| Online Access: | https://www.mdpi.com/2072-4292/15/2/457 |
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| author | Ehtesham Ahmed Naeem Saddique Firas Al Janabi Klemens Barfus Malik Rizwan Asghar Abid Sarwar Peter Krebs |
| author_facet | Ehtesham Ahmed Naeem Saddique Firas Al Janabi Klemens Barfus Malik Rizwan Asghar Abid Sarwar Peter Krebs |
| author_sort | Ehtesham Ahmed |
| collection | DOAJ |
| description | 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 R<sup>2</sup> and Nash–Sutcliffe 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. |
| first_indexed | 2024-03-09T11:20:47Z |
| format | Article |
| id | doaj.art-f9f90a07237340cca3b97d8026d29064 |
| institution | Directory Open Access Journal |
| issn | 2072-4292 |
| language | English |
| last_indexed | 2024-03-09T11:20:47Z |
| publishDate | 2023-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Remote Sensing |
| spelling | doaj.art-f9f90a07237340cca3b97d8026d290642023-12-01T00:21:09ZengMDPI AGRemote Sensing2072-42922023-01-0115245710.3390/rs15020457Flood Predictability of One-Way and Two-Way WRF Nesting Coupled Hydrometeorological Flow Simulations in a Transboundary Chenab River Basin, PakistanEhtesham Ahmed0Naeem Saddique1Firas Al Janabi2Klemens Barfus3Malik Rizwan Asghar4Abid Sarwar5Peter Krebs6Institute of Urban and Industrial Water Management, Technische Universität Dresden, 01069 Dresden, GermanyInstitute of Hydrology and Meteorology, Technische Universität Dresden, 01062 Dresden, GermanyGlobal Water and Climate Adaption Centre, Technische Universität Dresden, 01062 Dresden, GermanyInstitute of Hydrology and Meteorology, Technische Universität Dresden, 01062 Dresden, GermanyFlood Forecasting Division, Pakistan Meteorological Department, Islamabad 44000, PakistanDepartment of Irrigation and Drainage, University of Agriculture, Faisalabad 38000, PakistanInstitute of Urban and Industrial Water Management, Technische Universität Dresden, 01069 Dresden, GermanyRemote 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 R<sup>2</sup> and Nash–Sutcliffe 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.https://www.mdpi.com/2072-4292/15/2/457sub-daily simulationdistributed hydrologic modellingflood forecastingIFAStransboundary rivernumerical weather prediction (NWP) |
| spellingShingle | Ehtesham Ahmed Naeem Saddique Firas Al Janabi Klemens Barfus Malik Rizwan Asghar Abid Sarwar Peter Krebs Flood Predictability of One-Way and Two-Way WRF Nesting Coupled Hydrometeorological Flow Simulations in a Transboundary Chenab River Basin, Pakistan Remote Sensing sub-daily simulation distributed hydrologic modelling flood forecasting IFAS transboundary river numerical weather prediction (NWP) |
| title | Flood Predictability of One-Way and Two-Way WRF Nesting Coupled Hydrometeorological Flow Simulations in a Transboundary Chenab River Basin, Pakistan |
| title_full | Flood Predictability of One-Way and Two-Way WRF Nesting Coupled Hydrometeorological Flow Simulations in a Transboundary Chenab River Basin, Pakistan |
| title_fullStr | Flood Predictability of One-Way and Two-Way WRF Nesting Coupled Hydrometeorological Flow Simulations in a Transboundary Chenab River Basin, Pakistan |
| title_full_unstemmed | Flood Predictability of One-Way and Two-Way WRF Nesting Coupled Hydrometeorological Flow Simulations in a Transboundary Chenab River Basin, Pakistan |
| title_short | Flood Predictability of One-Way and Two-Way WRF Nesting Coupled Hydrometeorological Flow Simulations in a Transboundary Chenab River Basin, Pakistan |
| title_sort | flood predictability of one way and two way wrf nesting coupled hydrometeorological flow simulations in a transboundary chenab river basin pakistan |
| topic | sub-daily simulation distributed hydrologic modelling flood forecasting IFAS transboundary river numerical weather prediction (NWP) |
| url | https://www.mdpi.com/2072-4292/15/2/457 |
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