Hydrologic Modeling System Research Articles

Hydraulic model for flood inundation in Diyala River Basin using HEC-RAS, PMP, and neural network

Abstract The Diyala River Basin in Iraq is vital for water supply to residential, agricultural, and the Tigris River (with approximately 4.5 billion cubic meters annually), but it faces frequent floods and droughts due to reliance on rainfall. This study aims to address these issues by simulating flood inundation using the hydrological engineering centre-river analysis system model and predicting high-intensity rainfall with artificial neural networks. ArcGIS and remote sensing tools aid model development with data from official sources and organizations such as national aeronautics and space administration and food and agriculture organization. The hydraulic model is calibrated using satellite imagery to depict a 2019 flood, and artificial intelligence predicts the precipitation patterns for the next 50 years based on historical data from 1981 to 2021. One of the challenges and difficulties encountered in the study is the scarcity of available data, as well as the absence of scientific research pertaining to the region regarding hydraulic modeling. The study identifies flood risks in March and April every year, notably for the Hemrin Dam, which may exceed permissible water levels (reach a level over 110 m where the Hemrin Crest level is 109.5 m). To mitigate this, an artificial canal is proposed to divert water annually, protecting the dam and downstream areas without disrupting operations. The diverted water could also augment the Tigris River in Kut Governorate during summer. The study demonstrates the value of integrating multiple modeling techniques and data sources for accurate hydraulic predictions. It offers insights for decision-makers in flood management and planning. This study contributes to efficient flood management strategies by adopting a multidisciplinary approach.

Assessing Hydrological Response in the Timah-Tasoh Reservoir Sub-Catchments: Calibration and Validation using the HEC-HMS Model

Hydrological modelling is a tool that is frequently used for assessing the hydrological response of a basin as a result of precipitation. It is also a vital component as water resources and environmental planning management. The study deals with calibrating and validating the hydrological response in the sub-catchments of the Timah-Tasoh reservoir using the hydrological model named Hydrologic Engineering Center – Hydrologic Modelling System (HEC-HMS). This study uses the SCS Curve Number, the SCS Unit Hydrograph, the constant monthly baseflow, and lag routing for the model development. The model was simulated for ten (10) years for calibration and nine (9) years for validation. The model calibration and validation efficiency were assessed using the coefficient of correlation (R). The findings show that the HEC-HMS model performs satisfactorily in simulating the observed daily inflow series, with the R-value of 0.4902-0.5139 during calibration and 0.5047-0.5559 during validation process. Thus, the result obtained from this study can be used as a preliminary development of hydrological modelling of the catchment of the Timah-Tasoh reservoir and can be used for extend application such as water inflow forecasting, impact of land use to the reservoir and others.

Hydrological Modelling with HEC-HMS in Krueng Peudada Sub-Watershed Bireuen Regency

The flood that occurred in Krueng Peudada was influenced by several factors, such as watershed conditions. Heavy rains caused Krueng Peudada to overflow so that a number of villages adjacent to the river were submerged. Based on these problems, to minimize the occurrence of flooding in Krueng Peudada building, namely by carrying out occurrence of flooding in Krueng Peudada to be used to obtain peak discharge as a reference in building planning in Krueng Peudada using HEC-HMS (Hydrologic Engineering Center’s Hydrologic Modelling System). The benefit of the research is that the resulting model can be useful as a guide in calculating flood discharge considerations. The scope of this research includes the research location at Krueng Peudada using annual maximum daily rainfall data, calculating the return period of rainfall using of Gumbel probability distribution, Normal Log, Normal, and Pearson III Log as the basis for calculating the discharge and continuing the calculation of the hours with Manonobe and ABM. The results of calculations of the Nakayasu Synthetic Unit Hydrograph Method and running from HEC-HMS found that the flow that occurred in the Krueng Peudada two sub-watershed was 2903m3/second and 2723,0 m3/second, it can be concluded that in determining watershed management the flood discharge obtainded has error as much as 6,2%. The difference in the results obtained is due to the number of sub-watersheds in the watershed based on different flows and the value of the curve number for each area of the sub-watershed.

Evaluation of a weather forecasting model and HEC-HMS for flood forecasting: case study of Talesh catchment

Reports demonstrate that floods are among the most prevalent and deadliest natural disasters affecting 520 million people annually. The present study seeks to evaluate flood forecasting using the weather research and forecasting (WRF) model and the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) model. To this end, WRF and HEC-HMS were calibrated by comparing their results with the data observed at measuring stations. Then, the output rainfall data of the WRF model were implemented by the calibrated HEC-HMS model and were examined using the statistical indices, which were revealed to be 4.13, 3.42, and 2.67 for the flow volume and 6.2, 2.46, and 5.11 for the peak flow, suggesting the accurate performance of WRF model alongside HEC-HMS in the Talesh catchment.

The Nature-Based Solutions and climate change scenarios toward flood risk management in the greater Athens area—Greece

AbstractThis research paper focuses on implementing two Nature-Based Solutions (NBS) in the Sarantapotamos river basin upstream of Magoula settlement, evaluating their effectiveness through flood hydrograph calculations before and after NBS, and under future climate scenarios, encompassing lower, mean, and upper conditions representing ± 95%. The study area covers an area of 226 km2 in Attica, Greece, susceptible to extreme flood events. The research contributes to NBS knowledge, emphasizing flood resilience and protecting settlements downstream. Land cover change and retention ponds, applied individually and combined, serve as NBS approaches. Flood hydrographs are calculated using the time–area (TA) diagram method in a geographic information system (GIS) with the Hydrological Engineering Center’s Hydrological Modeling System (HEC-HMS). Results demonstrate NBS effectiveness in current climate conditions, reducing peak discharge by 9.3% and 28% for land cover change and retention ponds, respectively. The combined NBS achieves a 40.5% peak discharge reduction and a significant 15.7% total flood volume decrease. Under climate change scenarios, impacts on design precipitation and flood hydrographs vary. The upper climate change scenario exhibits a 3348% increase in peak discharge and a 600% rise in total flood volume, while the lower scenario sees a 44.6% reduction in total flood volume. In the mean climate change scenario, land cover change and retention ponds reduce peak discharge by 9.73% and 23.11% and total flood volume by 9.25% and 2.17%, respectively. In conclusion, retention ponds show substantial peak discharge reduction, while land cover changes extend the time to peak, emphasizing their potential in flood risk management.

Integrated Hydrological Modeling for Watershed Analysis, Flood Prediction, and Mitigation Using Meteorological and Morphometric Data, SCS-CN, HEC-HMS/RAS, and QGIS

Flooding is a natural disaster with extensive impacts. Desert regions face altered flooding patterns owing to climate change, water scarcity, regulations, and rising water demands. This study assessed and predicted flash flood hazards by calculating discharge volume, peak flow, flood depth, and velocity using the Hydrologic Engineering Centre-River Analysis System and Hydrologic Modelling System (HEC-HMS and HEC-RAS) software. We employed meteorological and morphological data analyses, incorporating the soil conservation service (SCS) curve number method for precipitation losses and the SCS-Hydrograph for runoff transformation. The model was applied to two drainage basins (An-Nawayah and Al-Rashrash) in southeastern Cairo, Egypt, which recently encountered several destructive floods. The applied model revealed that 25-, 50-, and 100-year storms produced runoff volumes of 2461.8 × 103, 4299.6 × 103, and 5204.5 × 103 m3 for An-Nawayah and 6212 × 103, 8129.4 × 103, and 10,330.6 × 103 m3 for Al-Rashrash, respectively. Flood risk levels, categorised as high (35.6%), extreme (21.9%), and medium (21.12%) were assessed in low- and very-low-hazard areas. The study highlighted that the areas closer to the Nile River mouth faced greater flood impacts from torrential rain. Our findings demonstrate the effectiveness of these methods in assessing and predicting flood risk. As a mitigation measure, this study recommends the construction of five 10 m high dams to create storage lakes. This integrated approach can be applied to flood risk assessment and mitigation in comparable regions.

The effect of landuse dynamics on water balance components in the Upper Oum Er Rabia Basin, Morocco

The Upper Oum Er-Rbia Basin (UOERB) has been facing significant land use/land cover change and urban sprawl dynamics in recent years, in addition to significant climatic variability leading to disruption of precipitation intensity and quantity. Our approach is to identify the morphometric characteristics of the study region and monitor changes in land use and land cover by analyzing Landsat images. These factors form the input parameters for the HEC-HMS (Hydrologic Engineering Center - Hydrologic Modeling System) hydrological model for simulating daily historical hydro-climatic events. The classification of Landsat images shows that the Upper Oum Er-Rbia Basin has experienced significant landuse dynamics over the past 30 years, resulting in disrupted rainfall and recurrent flooding events. Overall, the hydrological simulation shows good agreement between observed and simulated flow hydrographs, with Nash criteria between 0.6 and 0.8. This knowledge enables us to better estimate the return flows in the catchment area, and to take appropriate action in terms of hydraulic management and development in the Upper Oum Er-Rbia Basin.

Impact of land surface model schemes in snow-dominated arid and semiarid watersheds using the WRF-hydro modeling systems

<abstract> <p>In the past century, water demand increased extensively due to the rapid growth of the human population. Ground observations can reveal hydrological dynamics but are expensive in the long term. Alternatively, hydrological models could be utilized for assessing streamflow with historical observations as the control point. Despite the advancements in hydrological modeling systems, watershed modeling over mountainous regions with complex terrain remains challenging. This study utilized the multi-physical Weather Research and Forecasting Hydrological enhancement model (WRF-Hydro), fully distributed over the Amu River Basin (ARB) in Afghanistan. The calibration process focused on land surface model (LSM) physics options and hydrological parameters within the model. The findings emphasize the importance of LSM for accurate simulation of snowmelt–runoff processes over mountainous regions. Correlation coefficient (R), coefficient of determination (R<sup>2</sup>), Nash-Sutcliff efficiency (NSE), and Kling-Gupta efficiency (KGE) were adopted for accuracy assessment over five discharge observation stations at a daily time scale; overall performance results were as follows: R was 0.85–0.42, R<sup>2</sup> was 0.73–0.17, NSE was 0.52 to −8.64, and KGE was 0.74 to −0.56. The findings of the current study can support snowmelt process simulation within the WRF-Hydro model.</p> </abstract>

Rainfall-runoff process simulation using HEC-HMS model: Study case of Rhumel Smedou watershed

Hydrological modeling is a critical and decisive technique for estimating hydrological processes and the availability of water resources. In our research, we used Hydrologic Modeling System (HEC-HMS), a 4.4 version, to achieve the affected goals, and a watershed in the east of Algeria, known as Rhumel Smedou watershed, was chosen as a case study which covers an area of 1,083 km2. A Geographic Information System (GIS) was used to analyze and process the Digital Elevation Model 30-meter resolution data accompanied with Landsat of Land Use Land Cover 10-meter resolution with accuracy to extract and deduce the basic inputs of the simulation model, which are: curve number (%), lag time (mn), impermeability (%), and rainfall (Ia) (mm). The research purpose is to compute runoff depth and volume rate for four extreme events. Two events are chosen for model calibration and two for model validation. The results of the statistical tests [NSE (%) RMSE_PBIAS (%)] proved the success and ability of the model to achieve the research objectives, and their averages were as follows: [82%_0.45_32.55%] for calibration phase, and [77%_ 0.45_30.95%] for validation phase. After calibrating and validating the effectiveness of the model, the volume and flow were predicted for different return periods (2y, 10y, 50y, and 100y).

Urban Flood Analysis and Early Warning Solution for Disaster Resilience

The objective of this work is to present the experimental findings of an urban flood early warning system developed by combining a mesoscale numerical weather prediction model (WRF) forecast with a distributed hydrologic modelling system. Hydrodynamic models have been used in the simulation of intricate and interrelated dynamic systems, such as urban watersheds and urban water infrastructure. The use of these models in assessing the flood hazard, vulnerability, and risk is well-established. On the other hand, the Numerical weather prediction (NWP) such as WRF model output are crucial to increase the lead time for the flood forecasting. The Weather Research and Forecasting (WRF) model is employed for the purpose of generating precipitation forecasts, which are subsequently utilized to conduct hydrologic and hydrodynamic simulations. In accordance with the climatology of the study area, the WRF model forecast is juxtaposed with the observed rainfall data for days 1, 2, and 3. Statistical indicators of accuracy assessment suggest acceptable degree of correlation with the observed precipitation. The experiment successfully designed and implemented a comprehensive web-based urban flood forecast and early warning system. The system is able to predict possible inundation areas within the catchment due to projected rainfall. Additionally, the study develops a web-based Flood Management Information System (MIS) that is fully automated and disseminate early warning with a lead time of 72 hours.

An Evaluation of the Impact of Urban Growth on Runoff in Abeokuta, Southwestern Nigeria

Abeokuta is one of the urban areas in Nigeria with high cases of runoff fatalities in recent times, indicating the need for a proper understanding of prominent runoff-generating mechanisms, as well as the causative factors. Consequently, this paper, which is focused on flood-prone settlements, is aimed at providing information on the impact of change in urban land use on runoff in the study area. The specific objectives were to determine the change in average runoff in terms of the Soil Conservation Service Curve Number (SCN-CN), and to assess the impact of urban growth on runoff in the area. The SCN-CN was derived from the 30m spatial Shuttle Radar Topography Mission Digital Elevation Model (SRTM DEM). At the same time, land cover change was estimated using Landsat TM+ from 2000 and Landsat 8 OLI from 2018. Data were analysed using the Hydrologic Engineering Centre’s Hydrologic Modelling System (HEC-HMS) and ArcGIS (version 10.1). The results showed a 14% increase (from 39% in 2000 to 53% in 2018) in urban areas of selected catchments; and a relative increase in average CN from 76.9 units in 2000 to 79.9 units in 2018, suggesting an increase in runoff potential relative to the increase in urban/impermeable space in the catchment. Annual discharge depth increased from 891.84mm to 956.9mm, while peak discharge increased from 161.9m3 /s to 196.2m3 /s. Runoff in the study area tends to exhibit spatial variability that is similar to the pattern exhibited by built-up areas across the study area, suggesting that the development of built-up areas can explain runoff exacerbation in part of the area. The use of SCN-CN and satellite images makes the approach reproducible, and the mixed methods of geographic information system and hydrological model revealed the spatial variability typically hidden in stand-alone hydrological models. The paper recommends further studies with the use of less coarse datasets, as well as the implementation of policies that focus on sustainable urban growth in the region, and other cities.

The Alteration of Flood Peak Discharge by Land Cover Change in Prek Thnot Watershed, Kampong Speu Provine, Cambodia

This study analyses the alterations of peak catchment runoff from Prek Thnot watershed using the Soil Conservation Service Curve Number (SCS-CN) methodology. Two major studies using different approaches have previously been conducted in the catchment, albeit producing inconsistent results. The Snowy Mountain Hydro-electric Authority published the first study in 1967 and found that the peak surface flow runoff over a 10-year return period was 710 m3/s. The second study was conducted by the Japanese International Cooperation Agency (JICA) between 1991 and 2006 and reported a peak catchment discharge of 1,380 m3/s. To date, there has been no discussion comparing the two studies to determine why the discharge during the later study was double that of the first. As the annual rainfall during the two study periods was similar, it is suggested that this discrepancy may be attributed to physical changes in the watershed, such as changes to forest cover. We deployed the Hydrologic Engineering Centre-Hydrologic Modeling System to simulate the peak runoff of the catchment. Our result was very similar to the JICA finding. Our data suggested that the increase in catchment discharge may be attributed to the conversion of 26% of forest cover in the catchment to agricultural land since the early 2000s. This information is useful for flood management practices, particularly with respect to managing catchment runoff in the context of rapid deforestation and the hydrological impacts of climate change within the watershed. The paper analyzes the impact of land-use changes on catchment runoff and provides valuable insights for flood management practices in the context of climate change and deforestation.

Ensemble rainfall–runoff modeling of physically based semi-distributed models using multi-source rainfall data fusion

Abstract This study was aimed at ensemble rainfall–runoff modeling by Soil and Water Analysis Tool (SWAT), the Hydrologic Engineering Center's Hydraulic Modeling System, and Hydrologiska Byråns Vattenbalansavdelning of Gilgel-Abay watershed, Blue Nile basin, Ethiopia. For modeling, daily rainfall datasets of five gauges and three satellites, streamflow, and spatial data were used. In the modeling stage, first, the runoff was simulated separately using the rainfall data of gauges, satellites, and their fusion. Second, ensemble rainfall–runoff simulation of the rainfall dataset fusion-based runoff result was conducted via the proposed weighted average, simple average, and neural network (NNE) ensemble techniques. The results exhibited that all models are good in capturing the rainfall–runoff relationship; however, SWAT showed slight superiority by Nash–Sutcliffe efficiency of 0.807 and 0.821 for gauge and fusion data, respectively. The rainfall fusion ensemble model revealed significant improvement over modeling by satellite rainfall owing to the bias-correcting gauge rainfall over satellite rainfall. The NNE technique enhanced the efficiency of the low-performing satellite-rainfall-based model by 17.5% and the rainfall fusion-based model by 13.3% at the validation stage. In general, the result of this study points out that the rainfall datasets’ fusion from multi-sources would be worthy for the rainfall–runoff simulation of ungauged basins.

Evaluation of precipitation reanalysis products for regional hydrological modelling in the Yellow River Basin

This study evaluates six precipitation reanalysis products for the Yellow River Basin using gridded rain gauge data, runoff data and the Atmospheric and Hydrological Modelling System (AHMS) simulations. The assessment begins with comparing the annual, seasonal, monthly and daily precipitation of the products with gridded rain gauge data. The AHMS is then run with each of the precipitation reanalysis products under two scenarios: one with calibrated rainfall-runoff and the other without. The simulated streamflow is then compared with the corresponding observations. It is found that non-gauge-corrected products tend to overestimate precipitation, especially for mountainous regions. Amongst the six products evaluated, the China Meteorological Forcing Dataset (CMFD) and WATCH Forcing Data methodology applied to ERA5 (WFDE5/CRU+GPCC) are identified as the most accurate products, supported by both statistical and hydrological comparisons. This consistency in statistical and hydrological comparisons suggests the potential applicability of the hydrological comparison method using the AHMS in ungagged catchments, even in the presence of significant anthropogenic impacts. Furthermore, the calibration of the hydrological model significantly impacts the model’s response to precipitation, effectively compensating for deficiencies in rainfall data within certain limits. This study highlights accurate representation of extreme rainfall events in precipitation products has a significant impact on calibrated soil parameters and is particularly important in hydrological modelling. It enhances our understanding of the reliability of hydrological simulations and provides valuable insights for the assessment of precipitation reanalysis products in large arid and semiarid basins affected by human activities.

Assessing future flood inundation in Nandigama through land use, land cover, and rainfall analysis

Abstract Frequent occurrences of high-intensity rainfall have made urban flooding a significant problem. In the present study, flood inundation maps were prepared for the years 2030 and 2035 based on changes in future land use and land cover (LULC) and rainfall patterns in Nandigama, located in Andhra Pradesh, India. The Hydrologic Engineering Center's Hydrologic Modelling System Hydrologic and Hydrologic Engineering Center–River Analysis System hydraulic models were used to assess future runoff and flood inundation areas for the above years. Future LULC and hydro-meteorological data were analysed and incorporated into the models. Predicted LULC maps showed a high level of agreement with actual LULC maps, as indicated by a Kappa index of 88.34%. The average peak runoff flowing out of the basin increased by 1.82%–3.43% for years 2030–2035, respectively. When considering the average inundation percentage area in Nandigama, it was found that 12.73% and 13.83% of the area flooded in both years. The study recommendations give more attention to the Nandigama flood management authority.

Integrated evaluation and attribution of urban flood risk mitigation capacity: A case of Zhengzhou, China

Study regionThe Zhengzhou City in China Study focusUrban flood risk mitigation (UFRM) refers to the runoff retention capacity of land surface in urban regions. Previous studies have focused on assessing the UFRM change in central urban areas. Nevertheless, analysis of the UFRM change considering the heterogeneity of urban and rural gradient is scarce. This study aims to evaluate the spatiotemporal change of UFRM and its influencing factors in different urban functional zones. An integrated framework combining the hydrological model and geographic information system (GIS) has been established to assess the evolution of UFRM in Zhengzhou between 2000 and 2020. New hydrological insights for the regionThe findings illustrate the following: (1) The UFRM of Zhengzhou experienced a 10.76% increase from 2000 to 2010, followed by a subsequent 3.38% decrease from 2010 to 2020.(2) UFRM increased in ecological areas while decreasing in urban regions, revealing a disparity between UFRM supply and demand. (3) The adverse impact of impervious surfaces on UFRM surpasses the influence of precipitation intensity in urban regions. As a result, this study suggests that urban areas should avoid extensive expansion of impervious surfaces and prioritize implementing low-impact development practices. The ecological zones should implement rigorous policies to protect natural preservation. These findings provide policymakers a scientific foundation for devising sustainable urban development strategies to enhance urban flood resilience.

Early Flood Monitoring and Forecasting System Using a Hybrid Machine Learning-Based Approach

The occurrence of flash floods in urban catchments within the Mediterranean climate zone has witnessed a substantial rise due to climate change, underscoring the urgent need for early-warning systems. This paper examines the implementation of an early flood monitoring and forecasting system (EMFS) to predict the critical overflow level of a small urban stream on Lesvos Island, Greece, which has a history of severe flash flood incidents requiring rapid response. The system is supported by a network of telemetric stations that measure meteorological and hydrometric parameters in real time, with a time step accuracy of 15 min. The collected data are fed into the physical Hydrologic Engineering Center’s Hydrologic Modeling System (HEC-HMS), which simulates the stream’s discharge. Considering the HEC-HMS’s estimated outflow and other hydro-meteorological parameters, the EMFS uses long short-term memory (LSTM) neural networks to enhance the accuracy of flood prediction. In particular, LSTMs are employed to analyze the real-time data from the telemetric stations and make multi-step predictions of the critical water level. Hydrological time series data are utilized to train and validate the LSTM models for short-term leading times of 15 min, 30 min, 45 min, and 1 h. By combining the predictions obtained by the HEC-HMS with those of the LSTMs, the EMFS can produce accurate flood forecasts. The results indicate that the proposed methodology yields trustworthy behavior in enhancing the overall resilience of the area against flash floods.

Seamlessly Coupling Hydrological Modelling Systems and GIS through Object-Oriented Programming

Coupling hydrological modelling systems (HMS) with a geographic information system (GIS) can significantly enhance hydrological research and expand its applications. The calculation for HMS requires geographic information data; however, the current GIS data structure is not equipped to support the object-oriented hydrological modelling. Due to different objectives and design concepts, the differences between HMS and GIS have been profound, especially in their data structures from the perspective of object-oriented programming (OOP). This research introduces a novel approach to extend ArcGIS data structures for HMS, facilitating seamless coupling. This approach employs Microsoft Component Object Model (COM) technology to construct custom data structures that align with hydrological OOP principles. These can then be integrated into ArcGIS through a custom ArcGIS layer as an add-on. As a result, the HMS can leverage the full functionality of ArcGIS without the need for re-coding existing modelling systems. Moreover, HMS can be readily developed by using COM compatible computer languages, enabling the easy adaptation of this coupling approach to other HMS to ensure computational efficiency and to maximise the benefits of ArcGIS features. This new approach has been successfully implemented with the Xin’anjiang model, and the results validate its effectiveness in coastal areas.

Improving flood forecasting in Narmada river basin using hierarchical clustering and hydrological modelling

The purpose of the study was to use hierarchical clustering and Thiessen polygon algorithms to identify the significant rain gauge stations for flood forecasting at Sardar Sarovar Dam. Rainfall data from 2010 to 2018 was utilized to analyze the catchment region between Omkareshwar Dam and Sardar Sarovar Dam. The study identified two clusters of rain gauge stations with similar rainfall patterns and divided the study area into seventeen regions using Thiessen polygons. The land use map showed that the study area was mostly covered by crop lands, and the soil map divided the area into three types of sedimentary claystone soil. A hydrological model, Hydrologic Engineering Center – Hydrologic Modelling System (HEC-HMS), was used for rainfall-runoff modeling, and the computed runoff was compared with observed gauge discharge and inflow of Sardar Sarovar Dam. Regression analysis was performed to assess the performance of the model, and the results showed a good correlation between observed rainfall and estimated runoff values for 2012 and 2016. The study concludes that the existing rain gauge network is sufficient for flood forecasting, and the developed model along with the Thiessen polygon method can provide more accurate predictions of flow. The study highlights the importance of selecting suitable rain gauge stations for reliable flood forecasting in flood-prone basins. The study findings can be useful for future runoff prediction and flood forecasting in the study area.

Climate Change Impact On Upper Layang Reservoir Operation

The goal of reservoir operation policies is to get the most out of the water that can be stored and delivered as a water supply. Water shortages and floods may become more common in Malaysia because of climate change and global warming. The biggest impediment to developing reliable water storage and supplies in Sg Layang Reservoir, Johor, Malaysia, is a lack of water. Forecasting reservoir water levels is critical for storage management, particularly in water supply systems. As a result, the objective of this research is to create a reservoir simulation model using the Hydrologic Modeling System (HEC-HMS) to generate water levels to compare with observed water levels and to predict water levels using input variables such as future daily rainfall to examine the reservoir’s performance under changing conditions. Rainfall data from 2011 is utilized to calibrate the system, while data from 2012 to 2013 is used to validate it. The observed rainfall data was applied to the Sungai Layang watershed region. The correlation coefficient, R2, was employed to show the watershed’s best value. The calibration procedure has an R2 of 0.91, whereas the validation procedure has an R2 of 0.88. The accuracy of the model is satisfactory, as the R2 is near to 1.0, and calibration parameters can be employed in the following design processes, according to the analysis completed by HEC-HMS applications. The simulation was carried out using the same parameters in 2017, 2030, and 2050 with four distinct scenarios to evaluate water level behavior using future rainfall data. According to the simulation, most of the water level in the future will be below the crucial threshold of 23.5m. The findings reveal that climate change has an impact on reservoir functioning in terms of rainfall intensity.