Rainfall-runoff modeling using the HEC-HMS flow modeling framework for the Halda River catchment, Bangladesh

Rainfall-runoff modeling using the HEC-HMS flow modeling framework for the Halda River catchment, Bangladesh | 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 Short Report Rainfall-runoff modeling using the HEC-HMS flow modeling framework for the Halda River catchment, Bangladesh Marjena Binte Haque, Shyamal Karmakar, Mohammad Mozaffar Hossain This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-3824469/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract The Halda River is a vital perennial river with significant ecosystem service throughout its course. We studied the characteristics of river monsoon flow using the HEC-HMS to determine the flash flood simulation potential of the cascade reservoir model. The curve numbers are optimized here based on SWAT simulation data. The NSE, R 2 (RMSE), RSE, and PBIAS estimate values agree with the observed discharge values for the calibration and validation periods. However, during the calibration period, the flow model showed a poor match for the baseflow part, which affected the model's efficiency. Using this approach, flash flood studies can potentially simulate flash floods in a relatively ungauged river basin with minimal discharge data and available water level data. Moreover, the computational cost is lower than that of a similar capacity flow model. Hydrology flow model Halda River river discharge rainfall-runoff watershed Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 INTRODUCTION River water, vital for water supply, irrigation, and the ecosystem, constantly threatens nearby settlements through flooding and contamination. Excessive precipitation exceeding the riverbed's capacity leads to flash floods in the lowlands or flood plains and water logging for a season or permanently. Precipitation, along with other factors such as land use and the soil profile, is considered the primary catalyst for the hydrological cycle. Accurately estimating runoff volume from rainfall is crucial for reservoir water storage and flood risk assessment. For a few decades, various hydrological models incorporating geographic information systems (GISs) have been utilized for different regional river basins to predict surface runoff patterns. Such models simulate runoff patterns based on time interval rainfall data. HEC-HMS, a rainfall-runoff simulation software package, addresses water availability, flood forecasting, urban drainage, and hydrological impact studies. Creating a data-driven model using this software requires fewer parameters that can easily be calibrated and validated. Knowledge of hydrological behavior and basin parameter factors is pivotal for developing this type of physical model. The literature review clearly showed that globally utilizing this software for regional stream flow forecasting was fairly compelling. Unfortunately, few studies have been performed on the Bangladesh region, where floods are the central natural calamity for socioeconomic loss every year. The Halda River basin in Bangladesh, known for its extensive agricultural importance (Haque et al. 2020), experiences substantial discharge during monsoons, which can cause floods in nearby areas and Chittagong City (Raihan et al. 2022). Severe land degradation adds to the basin's challenges. To address flooding and water scarcity in lean periods, a study aimed to estimate the basin's runoff by creating a tailored rainfall-runoff model using the HEC-HMS. This model aims to determine the performance of simulating the Halda River hydrology toward enhancing flood risk management. METHODOLOGY The study area focused on the region of the Halda River, where the outlet point is Punchpukuria (91.78°E; 22.67°N). The catchment stream flow from Khagrachari flows through Lakkhichari and meets the mainstream of the Halda River. Its hypsometry shows a relatively small mountainous river course; the floodwater lead time is short and affects most of the river (Datta et al., 2022 ). The terrain data SRTM (Shuttle Radar Topographic Mission) 90-meter pixel size DEM data were used (Fig. 1) since they show the best drainage network performance in these basins (Datta et al. 2022 ). The MODIS Globe covers LULC, and FAO soil data have been used to predict the initial curve number of basins (Fig. 2, 3). Daily rainfall and discharge data from January 2016 to August 2017 were collected from the Bangladesh Meteorological Department (BMD) and Bangladesh Water Development Board (BWDB), respectively. There is not much complexity in this catchment, so the SCS-CN loss method has been used to calculate rainfall. The SCS unit hydrograph transformation method, where the lag time and percentage impervious area are used, was used to calculate the flow out at Punchpukuria Station. Among the various methods of stream flow routing in HEC-HMS, lag time methods were used. The 2016 data were used for the calibration period, and the data from January to August 2017 were used for the validation period. The root means square error (RMSE) was minimized using the simplex method to obtain the optimized model parameters for estimating the best-simulated flow. The R2 RMSE, PBIAS, and Nash-Sutcliffe efficiency were used to evaluate the model performance. RESULTS AND DISCUSSION The watershed is delineated into seven subbasins, and three reaches are based on the breaking point. Land use and land cover (LULC) data show that most catchment areas are agricultural and forest lands, indicating that the curve number (CN) will range from moderate to high. After optimizing the parameters for the different subbasins and reaches during calibration, we obtained the optimal value of the CN (Table 1). The optimization results indicated that the runoff-rainfall relationship was highly sensitive to subbasin CN, which depended on the LULC. A linear regression was performed to check the accuracy of the daily discharge data between the simulated and observed flows. Table 2 represents the statistical performance parameters for both calibration and validation. Even though the calibration R 2 value was moderate, it was 0.84 during validation. We assumed that keeping land cover data could be the reason for this. Figure 4 shows that, except for a few peaks, the model performance for simulating runoff well matches where baseflow is underestimated in the dry season. Hence, we achieved Nash-Sutcliffe efficiency (NSE) values of 0.72 and 0.82 and root mean squared error (R 2 ) values of 0.68 and 0.84; RSR values of 0.53 and 0.43; and PBIAS 22 and 6.5 for the calibration and validation periods, respectively. The validation performance is better than the calibration performance since it considers a peak discharge hydrograph rather than a base flow. Baseflow estimation is a more complex process than direct runoff. The base flow of a river is affected more by the infiltration-percolation process and groundwater-surface water exchange, which vary with water level (surface water and groundwater), spatial variation in geology, conductance of the riverbed, hydraulic conductivity, and storage of geological formations. Hence, integrating the groundwater flow process model with HEC-HMS at least offline coupling would improve the model performance. Conclusion The Halda River experiences flash flooding annually, causing massive damage to its low-elevation floodplains, mainly agricultural crops. Since the Halda River course lies primarily on the low flood plain, its hypsometry shows a relatively small mountainous river course; the floodwater lead time is short and has the most significant effect. In those circumstances, the HEC-HMS flow model will be efficient at simulating and predicting flood water, where the computational cost is also lower than that of a similar flow model. Based on these results, we can conclude that the HEC-HMS-based rainfall-runoff model can be used at Punchpukuria Station for flood forecasting. References Datta, S., Karmakar S*, Mezbahuddin, S., Chaudhary, B.S. Hossain, M.M. Hoque, M. E. Abdullah-Al-Mamun, M. M. and Baul T.K. 2022, The limits of watershed delineation: implications of different DEMs, DEM resolutions, and area threshold values, Hydrology Research (2022) 53 (8): 1047–1062. https://doi.org/10.2166/nh.2022.126 Haque M. B., Karmakar* a S , Datta a S, Sajid A. P. a , Islam N a , Mamun MMA a , Hossain MM a 2024, Discharge and sediment load modeling using rating curve-based missing data management for the Halda River Catchment of Bangladesh , in review-Hydrology Research. Haque, M. P., & Chowdhury, S. M. K. H. (2020). Trend of irrigation water requirement in the Halda River basin of Bangladesh. Journal of Science, Technology & Environment Informatics, 10 (01), 673-684. https://doi.org/10.18801/jstei.100120.68 Raihan, F. (2022). The impact of climate change on the hydrology of the Halda Basin, southeastern Bangladesh (Doctoral dissertation, Macquarie University). http://hdl.handle.net/1959.14/1275572 Tables Tables 1 to 2 are available in the Supplementary Files section Additional Declarations The authors declare no competing interests. Supplementary Files Table1.png Table2.png Cite Share Download PDF Status: Posted Version 1 posted 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. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. 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-3824469","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Short Report","associatedPublications":[],"authors":[{"id":264493189,"identity":"66050020-1943-426b-8d53-1baa21cbad01","order_by":0,"name":"Marjena Binte Haque","email":"","orcid":"","institution":"Institute of Forestry and Environmental Sciences, University of Chittagong","correspondingAuthor":false,"prefix":"","firstName":"Marjena","middleName":"Binte","lastName":"Haque","suffix":""},{"id":264493190,"identity":"813c0980-c5d9-4ffd-83af-19ea8b5d1c3a","order_by":1,"name":"Shyamal 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Bangladesh\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"INTRODUCTION","content":"\u003cp\u003eRiver water, vital for water supply, irrigation, and the ecosystem, constantly threatens nearby settlements through flooding and contamination. Excessive precipitation exceeding the riverbed's capacity leads to flash floods in the lowlands or flood plains and water logging for a season or permanently. Precipitation, along with other factors such as land use and the soil profile, is considered the primary catalyst for the hydrological cycle. Accurately estimating runoff volume from rainfall is crucial for reservoir water storage and flood risk assessment. For a few decades, various hydrological models incorporating geographic information systems (GISs) have been utilized for different regional river basins to predict surface runoff patterns. Such models simulate runoff patterns based on time interval rainfall data. HEC-HMS, a rainfall-runoff simulation software package, addresses water availability, flood forecasting, urban drainage, and hydrological impact studies. Creating a data-driven model using this software requires fewer parameters that can easily be calibrated and validated. Knowledge of hydrological behavior and basin parameter factors is pivotal for developing this type of physical model. The literature review clearly showed that globally utilizing this software for regional stream flow forecasting was fairly compelling. Unfortunately, few studies have been performed on the Bangladesh region, where floods are the central natural calamity for socioeconomic loss every year.\u003c/p\u003e \u003cp\u003eThe Halda River basin in Bangladesh, known for its extensive agricultural importance (Haque et al. 2020), experiences substantial discharge during monsoons, which can cause floods in nearby areas and Chittagong City (Raihan et al. 2022). Severe land degradation adds to the basin's challenges. To address flooding and water scarcity in lean periods, a study aimed to estimate the basin's runoff by creating a tailored rainfall-runoff model using the HEC-HMS. This model aims to determine the performance of simulating the Halda River hydrology toward enhancing flood risk management.\u003c/p\u003e"},{"header":"METHODOLOGY","content":"\u003cp\u003eThe study area focused on the region of the Halda River, where the outlet point is Punchpukuria (91.78\u0026deg;E; 22.67\u0026deg;N). The catchment stream flow from Khagrachari flows through Lakkhichari and meets the mainstream of the Halda River. Its hypsometry shows a relatively small mountainous river course; the floodwater lead time is short and affects most of the river (Datta et al., \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The terrain data SRTM (Shuttle Radar Topographic Mission) 90-meter pixel size DEM data were used (Fig.\u0026nbsp;1) since they show the best drainage network performance in these basins (Datta et al. \u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e2022\u003c/span\u003e). The MODIS Globe covers LULC, and FAO soil data have been used to predict the initial curve number of basins (Fig.\u0026nbsp;2, 3). Daily rainfall and discharge data from January 2016 to August 2017 were collected from the Bangladesh Meteorological Department (BMD) and Bangladesh Water Development Board (BWDB), respectively. There is not much complexity in this catchment, so the SCS-CN loss method has been used to calculate rainfall. The SCS unit hydrograph transformation method, where the lag time and percentage impervious area are used, was used to calculate the flow out at Punchpukuria Station. Among the various methods of stream flow routing in HEC-HMS, lag time methods were used. The 2016 data were used for the calibration period, and the data from January to August 2017 were used for the validation period. The root means square error (RMSE) was minimized using the simplex method to obtain the optimized model parameters for estimating the best-simulated flow. The R2 RMSE, PBIAS, and Nash-Sutcliffe efficiency were used to evaluate the model performance.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"RESULTS AND DISCUSSION","content":"\u003cp\u003eThe watershed is delineated into seven subbasins, and three reaches are based on the breaking point. Land use and land cover (LULC) data show that most catchment areas are agricultural and forest lands, indicating that the curve number (CN) will range from moderate to high. After optimizing the parameters for the different subbasins and reaches during calibration, we obtained the optimal value of the CN (Table\u0026nbsp;1). The optimization results indicated that the runoff-rainfall relationship was highly sensitive to subbasin CN, which depended on the LULC. A linear regression was performed to check the accuracy of the daily discharge data between the simulated and observed flows. Table\u0026nbsp;2 represents the statistical performance parameters for both calibration and validation. Even though the calibration R\u003csup\u003e2\u003c/sup\u003e value was moderate, it was 0.84 during validation. We assumed that keeping land cover data could be the reason for this. Figure\u0026nbsp;4 shows that, except for a few peaks, the model performance for simulating runoff well matches where baseflow is underestimated in the dry season. Hence, we achieved Nash-Sutcliffe efficiency (NSE) values of 0.72 and 0.82 and root mean squared error (R\u003csup\u003e2\u003c/sup\u003e) values of 0.68 and 0.84; RSR values of 0.53 and 0.43; and PBIAS 22 and 6.5 for the calibration and validation periods, respectively. The validation performance is better than the calibration performance since it considers a peak discharge hydrograph rather than a base flow. Baseflow estimation is a more complex process than direct runoff. The base flow of a river is affected more by the infiltration-percolation process and groundwater-surface water exchange, which vary with water level (surface water and groundwater), spatial variation in geology, conductance of the riverbed, hydraulic conductivity, and storage of geological formations. Hence, integrating the groundwater flow process model with HEC-HMS at least offline coupling would improve the model performance.\u003c/p\u003e \u003cp\u003e \u003c/p\u003e"},{"header":"Conclusion","content":"\u003cp\u003eThe Halda River experiences flash flooding annually, causing massive damage to its low-elevation floodplains, mainly agricultural crops. Since the Halda River course lies primarily on the low flood plain, its hypsometry shows a relatively small mountainous river course; the floodwater lead time is short and has the most significant effect. In those circumstances, the HEC-HMS flow model will be efficient at simulating and predicting flood water, where the computational cost is also lower than that of a similar flow model. Based on these results, we can conclude that the HEC-HMS-based rainfall-runoff model can be used at Punchpukuria Station for flood forecasting.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\n\u003cli\u003eDatta, S., \u003cstrong\u003eKarmakar S*,\u003c/strong\u003e Mezbahuddin, S., Chaudhary, B.S. Hossain, M.M. Hoque, M. E. Abdullah-Al-Mamun, M. M. and Baul T.K. 2022, The limits of watershed delineation: implications of different DEMs, DEM resolutions, and area threshold values, Hydrology Research (2022) 53 (8): 1047\u0026ndash;1062. https://doi.org/10.2166/nh.2022.126\u003c/li\u003e\n\u003cli\u003eHaque M. B.,\u003cstrong\u003e Karmakar*\u003csup\u003ea\u003c/sup\u003e S\u003c/strong\u003e, Datta\u003csup\u003ea\u003c/sup\u003e S, Sajid A. P. \u003csup\u003ea\u003c/sup\u003e, Islam N \u003csup\u003ea\u003c/sup\u003e, Mamun MMA \u003csup\u003ea\u003c/sup\u003e, Hossain MM \u003csup\u003ea \u003c/sup\u003e2024, Discharge and sediment load modeling using rating curve-based missing data management for the Halda River Catchment of Bangladesh\u003cstrong\u003e, \u003c/strong\u003ein review-Hydrology Research.\u003c/li\u003e\n\u003cli\u003eHaque, M. P., \u0026amp; Chowdhury, S. M. K. H. (2020). Trend of irrigation water requirement in the Halda River basin of Bangladesh. Journal of Science, Technology \u0026amp; Environment Informatics, \u003cem\u003e10\u003c/em\u003e(01), 673-684. https://doi.org/10.18801/jstei.100120.68\u003c/li\u003e\n\u003cli\u003eRaihan, F. (2022). The impact of climate change on the hydrology of the Halda Basin, southeastern Bangladesh (Doctoral dissertation, Macquarie University). http://hdl.handle.net/1959.14/1275572\u003c/li\u003e\n\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTables 1 to 2 are available in the Supplementary Files section\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"flow model, Halda River, river discharge, rainfall-runoff, watershed","lastPublishedDoi":"10.21203/rs.3.rs-3824469/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-3824469/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe Halda River is a vital perennial river with significant ecosystem service throughout its course. We studied the characteristics of river monsoon flow using the HEC-HMS to determine the flash flood simulation potential of the cascade reservoir model. The curve numbers are optimized here based on SWAT simulation data. The NSE, R\u003csup\u003e2\u003c/sup\u003e(RMSE), RSE, and PBIAS estimate values agree with the observed discharge values for the calibration and validation periods. However, during the calibration period, the flow model showed a poor match for the baseflow part, which affected the model's efficiency. Using this approach, flash flood studies can potentially simulate flash floods in a relatively ungauged river basin with minimal discharge data and available water level data. Moreover, the computational cost is lower than that of a similar capacity flow model.\u003c/p\u003e","manuscriptTitle":"Rainfall-runoff modeling using the HEC-HMS flow modeling framework for the Halda River catchment, Bangladesh","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-01-03 06:02:03","doi":"10.21203/rs.3.rs-3824469/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d0726687-aa27-42a4-badd-6b0dadbc02c5","owner":[],"postedDate":"January 3rd, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":27875942,"name":"Hydrology"}],"tags":[],"updatedAt":"2024-01-03T06:02:03+00:00","versionOfRecord":[],"versionCreatedAt":"2024-01-03 06:02:03","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-3824469","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-3824469","identity":"rs-3824469","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}