Flood Simulation Research Articles

Hydrometeorological evaluation of two nowcasting systems for Mediterranean heavy precipitation events with operational considerations

Abstract. Heavy precipitation events and subsequent flash floods regularly affect the Mediterranean coastal regions. In these situations, forecasting rainfall and river discharges is crucial especially up to 6 h, which is a relevant lead time for emergency services in times of crisis. The present study investigates the hydrometeorological skills of two new nowcasting systems: a numerical weather model AROME-NWC and a nowcasting system blending numerical weather prediction and extrapolation of radar estimation called PIAF. Their performance is assessed for 10 past heavy precipitation events that occurred in southeastern France. Precipitation forecasts are evaluated at a 15- min time resolution and the availability times of forecasts, based on the operational Météo-France suites, are taken into account when performing the evaluation. Rainfall observations and forecasts were first compared using a point-to-point approach. Then the evaluation was conducted from an hydrological point of view, by comparing observed and forecast precipitation over watersheds affected by floods. In general, the results led to the same conclusions for both evaluations. On the very first lead times, up to 1 h 15 min and 1 h 30 min of forecast, the performance of PIAF was higher than AROME-NWC. For longer lead times (up to 3 h) their performances were generally equivalent. An assessment of river discharges simulated with the ISBA-TOP coupled system, which is dedicated to Mediterranean flash flood simulations and driven by AROME-NWC and PIAF rainfall forecasts, was also performed on two exceptional past flash flood events. The results obtained for these two events show that using AROME-NWC or PIAF rainfall forecasts is promising for flash flood forecasting in terms of peak intensity, timing, and first wave of discharge, with an anticipation of these phenomena that can reach several hours.

Estimation of Probable Maximum Flood for Dam Safety in Cameron Highlands Watershed

Dams that are not designed to withstand major storms may be destroyed and increase the flood damage opportunities downstream. For protecting the lives and land downstream of Cameron Highlands, Malaysia, the current research targeted to estimate the Probable Maximum Precipitation based on the updated rainfall and other meteorological data and predict the Probable Maximum Flood using the Hydrological Model (HEC-HMS) version 4.8. The Geographic Information System was utilized as well in order to identify the geometric and hydrologist parameters. The PMP data is obtained up to 2020 via the application of Hershfield’s Statistics and by applying the model mentioned earlier, the Probable Maximum Precipitation values can be predicted. For the calibrating the model, different sets of data were applied in which the Nash-Sutcliffe Efficiency and Percentage of Bias of 0.776 and -0.03% respectively are obtained while Nash-Sutcliffe Efficiency and Percent Bias of 0.861 and 1.47% respectively are obtained for Cameron Highland dams for model validation. The hydrological model in this study was adequately calibrated for Probable Maximum Flood simulation as it is credible to describe the hydrological process in Cameron Highlands.

Assimilation of surface soil moisture jointly retrieved by multiple microwave satellites into the WRF-Hydro model in ungauged regions: Towards a robust flood simulation and forecasting

This study investigates how assimilation of surface soil moisture jointly retrieved by multiple microwave satellites affects flood simulation and forecasting based on the experiments of simulation (Sim), Open Loop (OL), and Ensemble Kalman Filter (EnKF) in small and medium-sized watersheds without gauged soil moisture. We developed a framework for data assimilation (DA) of satellite soil moisture into the WRF-Hydro model based on the EnKF algorithm. Three statistical metrics to evaluate the impacts of DA, including net error reduction, normalized error reduction, and effectiveness criterion, are all positive values (>6.0%), indicating that DA gains reduced errors. Meanwhile, the deterministic coefficients of the EnKF experiment are also greater than those of the OL experiment. It is obvious that multi-satellite retrieved soil moisture and DA technology can improve the accuracy of flood simulation and forecasting in ungauged regions and play an important and positive role in hydrological forecasting.

Tailings storage facilities flood exposure assessment using a 2D hydrodynamic model

Minimizing environmental pollution from Tailings Storage Facilities (TSFs) is one of the key goals of the mining sector. While much attention is given to risks from potential catastrophic failures of large TSFs, there is also a need to assess risks due to noncatastrophic but more frequent releases of contaminants. In response to this need, this article proposes a method for prioritizing TSFs in terms of flood exposure, based on flood maps produced by the Shallow Water Integrated Flood Tool. The method was implemented using a case study of a flood event in the Copiapó city region (Atacama, Chile). A sensitivity analysis was carried out to evaluate the influence of different model configurations and input parameters. The results showed that 10% of all the TSFs in the case study region were exposed to flood waters due to the fluvial dynamics of the Copiapo River. Additionally, the sensitivity analysis revealed that in the event of extreme local precipitation, capable of generating runoff, up to 88% of all the TSFs could have some degree of flood exposure. The results also suggest that flood simulations using satellite-derived terrain data at moderate resolution can be used for a preliminary large-scale assessment of TSF flood exposure.

Study on urban flood early warning system considering flood loss

As an effective way to reduce flood loss, flood early warning system (FEWS) plays an important role in the disaster reduction paradigm. With the frequent occurrence of urban floods, it is of great significance to study urban FEWS. Considering the spatial difference characteristics of flood loss, this paper proposed to build a multi-information early warning system including rainfall information, inundation information and disaster information. First of all, establishing the land use type division and flood simulation superposition model, the rainfall and inundation information of all kinds of building property types can be obtained. Then the disaster information can be obtained through the calculation of submergence depth-damage rate-loss value relationship of different building property types. Finally, dividing the loss threshold through the Iterative Self-Organizing Data Analysis Technique clustering method. Through the comparative analysis of submergence depth early warning and flood loss early warning, it is found that there were differences in the direct loss of building property types under the same submergence depth, in which the residential areas were most affected by floods and the commercial areas had the greatest economic loss. At the same time, due to the high population density in residential and commercial areas, the government and relevant departments should make preparation for waterlogging emergency and rescue in those areas in advance, pay close attention to the rainfall situation and release early warning information in time. It is expected that the research results can provide scientific basis and guidance for disaster prevention and mitigation decision-making and the development of FEWS for flood affected areas in the world.

Numerical effects on the simulation of surfactant flooding for enhanced oil recovery

Numerical simulation of surfactant flooding using conventional reservoir simulation models can lead to unreliable forecasts and bad decisions due to the appearance of numerical effects. The simulations give approximate solutions to systems of nonlinear partial differential equations describing the physical behavior of surfactant flooding by combining multiphase flow in porous media with surfactant transport. The approximations are made by discretization of time and space which can lead to spurious pulses or deviations in the model outcome. In this work, the black oil model was simulated using the decoupled implicit method for various conditions of reservoir scale models to investigate behavior in comparison with the analytical solution obtained from fractional flow theory. We investigated changes to cell size and time step as well as the properties of the surfactant and how it affects miscibility and flow. The main aim of this study was to understand pulse like behavior in the water bank, which we report for the first time, Our aim was to identify their cause and associated conditions. The pulses are induced by a sharp change in relative permeability as the interfacial tension changes. Pulses are diminished when adsorption is modeled, and ranged from 0.0002 kg/kg to 0.0005 kg/kg. The pulses are absent for high-resolution model of 5000 cells in x direction with a typical cell size as used in well-scale models. The growth or dampening of these pulses may vary from case to case but in this instance was a result of the combined impact of relative mobility, numerical dispersion, interfacial tension and miscibility. Oil recovery under the numerical problems reduced the performance of the flood, due to large amounts of pulses produced. Thus, it is important to improve existing models and use appropriate guidelines to stop oscillations and remove errors.

Testing of a hydrodynamic chemical flooding simulator by comparing the results of polymer flooding simulation with similar results of existing simulators

The use of numerical modeling tools, including reservoir simulators, helps oil companies in making decisions and ensuring successful field development. This work is devoted to the testing of a reservoir simulator based on a new formulation in partial derivatives of a compositional model of chemical flooding by comparing the results of polymer flooding simulation with similar results of Eclipse 100.

High-Expansion Foam: A Risk Control Option to Increase Passenger Ship Safety during Flooding

In naval architecture, the standard way adopted to reduce the risk of potential loss of life for passenger ships after an accident is via regulations. In case of flooding, this explicitly implies the introduction of fixed watertight bulkheads, permanently modifying the internal ship’s layout. Damage stability regulations constantly aim at higher safety standards; therefore, the layout reconfiguration of an existing vessel may be essential to meet new requirements, leading to higher costs for retrofitting. Furthermore, increasing fragmentation of the internal layout has a physical limit, neglecting the possibility to elevate standards above a particular upper limit. In this view, innovative solutions give the chance to exceed such a limit. The present work describes the advantages of high-expansion foam application for passive and active protection from flooding events. The possibility to have a material granting sufficient water tightness allows installing fixed or deployable barriers that increase the safety level of the ship. Here, besides the description of the foam characteristics, the application on a reference passenger ship highlights the advantages of passive and active foam barriers to limit flooding and drastically reduce the risk of loss of lives. The changes in the limiting stability margins required by regulations and the analysis of dynamic flooding simulations for specific damage cases demonstrate the benefits of foam installation onboard passenger ships as a risk control option.

Assessment of Open Access Global Elevation Model Errors Impact on Flood Extents in Southern Niger

Recent studies have estimated annual flood loss at over two billion USD dollars in damage per year globally. This figure is likely to increase as populations grow, people move to flood prone areas, and flooding dynamics change. Digital Elevation Models are a primary input into many flood models; therefore, the accuracy and resolution of these data sets have implications for model accuracy that are not completely understood. An increasing number of DEMs are becoming open and freely available, which presents analysts with the challenge of selecting the most appropriate inputs for their specific use case, especially in countries such as Niger where these global DEMs have not been formally evaluated. This study compares the absolute vertical accuracy of four global and freely available DEMs: Shuttle Radar Topography Mission, ASTER, Advanced Land Observing Satellite, and MERIT, with reference to a high-resolution LiDAR DEM, in southern Niger. Specifically, the Height Above Nearest Drainage (HAND) model is used to investigate the impact of resolution and error on simulated flood extent. There are currently no studies that assess the vertical accuracy of global DEMs in Niger nor that investigate the impact of the DEM geometric variability on flood extents. The ALOS DEM showed the lowest Root Mean Square Error of 1.19 m when compared to the LiDAR DEM, while ASTER had the highest RMSE of 4.2 m. The results of the Height Above Nearest Drainage model showed that at floods under 3 m in depth, the higher resolution DEMs simulated less flood extent; however, once the flood depth exceeded 3 m, the higher the resolution the DEM, the larger the flood extent. These findings suggest that both absolute error and relative error, as well as resolution, should be addressed when applying a DEM to a flood model.

The Erosional and Depositional Potential of Holocene Tibetan Megafloods Through the Yarlung Tsangpo Gorge, Eastern Himalaya: Insights From 2D Hydraulic Simulations

AbstractProfound effects of episodic megafloods (≥106 m3/s) have been observed on Earth and Mars. Quaternary megafloods sourced from valley‐blocking glaciers on the Tibetan Plateau likely play an important role in the geomorphic evolution of the Yarlung‐Tsangpo Gorge and mountain landscape of the eastern Himalaya. We use the first 2D numerical simulation of a megaflood sourced from a reconstructed 81 km3 Tibetan lake to analyze flood hydraulics and examine the erosional and depositional potential of megafloods in mountain landscapes. The simulated flood has a duration >60 hr and a peak discharge of 3.1 × 106 m3/s. We find that the extent of inundated features like terraces, narrow valley sections, tight meander bends, and overtopped ridges influences locations of observed maximum depth (370 m), speed (76 m/s), and bed shear stress (>100 kPa), creating dynamic patterns of erosive potential. Consequently, it is difficult to predict local (≤1 km) patterns of megaflood erosional potential from either unit stream power or flood power from smaller magnitude outburst floods. However, both are useful when predicting regional (≥25 km) order‐of‐magnitude shifts in megaflood flood power. Portions of the flood domain downstream of the Gorge experience lower bed shear stresses and flood power <5 kW/m2, indicating potential for significant deposition. We suggest widespread deposition of boulders within the modern channel and fine‐grained particles on hillslopes during a megaflood likely impedes subsequent erosion and affects channel width and longitudinal form throughout the flood pathway. Our findings show the legacy of megaflooding in mountainous terrain includes both extensive erosion and deposition.

Evaluating performance dependency of a geomorphologic instantaneous unit hydrograph-based hydrological model on DEM resolution

The digital elevation model (DEM) is a type of model that has been widely used in terrain analysis and hydrological modeling. DEM resolution influences the hydrological and geomorphologic features of delineated catchments and consequently affects hydrological simulations. This study investigated the impacts of DEM resolution on the performance of the XAJ-GIUH hydrological model, a model coupling the widely used Xinanjiang (XAJ) hydrological model with the geomorphologic instantaneous unit hydrograph (GIUH), in flood simulations in small and medium-sized catchments. To test the model performance, the model parameters were calibrated at a fine DEM resolution (30 m) and then directly transferred to the simulation runs using coarser DEMs. Afterwards, model recalibration was conducted at coarser DEM resolutions. In the simulation runs with the model parameters calibrated at the 30-m resolution, the DEM resolution slightly affected the overall shape of the simulated flood hydrographs but presented a greater impact on the simulated peak discharges in the two study catchments. The XAJ-GIUH model consistently underestimated the peak discharges when the DEM resolution became coarser. The qualified ratio of peak simulations decreased by 35% when the DEM resolution changed from 30 m to 600 m. However, model recalibration produced comparable model performances when DEMs with different resolutions were used. This study showed that the impact of DEM resolution on model performance can be mitigated by model recalibration to some extent, if the DEM resolution is not too coarse.

Physics-Guided Long Short-Term Memory Network for Streamflow and Flood Simulations in the Lancang–Mekong River Basin

A warming climate will intensify the water cycle, resulting in an exacerbation of water resources crises and flooding risks in the Lancang–Mekong River Basin (LMRB). The mitigation of these risks requires accurate streamflow and flood simulations. Process-based and data-driven hydrological models are the two major approaches for streamflow simulations, while a hybrid of these two methods promises advantageous prediction accuracy. In this study, we developed a hybrid physics-data (HPD) methodology for streamflow and flood prediction under the physics-guided neural network modeling framework. The HPD methodology leveraged simulation information from a process-based model (i.e., VIC-CaMa-Flood) along with the meteorological forcing information (precipitation, maximum temperature, minimum temperature, and wind speed) to simulate the daily streamflow series and flood events, using a long short-term memory (LSTM) neural network. This HPD methodology outperformed the pure process-based VIC-CaMa-Flood model or the pure observational data driven LSTM model by a large margin, suggesting the usefulness of introducing physical regularization in data-driven modeling, and the necessity of observation-informed bias correction for process-based models. We further developed a gradient boosting tree method to measure the information contribution from the process-based model simulation and the meteorological forcing data in our HPD methodology. The results show that the process-based model simulation contributes about 30% to the HPD outcome, outweighing the information contribution from each of the meteorological forcing variables (<20%). Our HPD methodology inherited the physical mechanisms of the process-based model, and the high predictability capability of the LSTM model, offering a novel way for making use of incomplete physical understanding, and insufficient data, to enhance streamflow and flood predictions.

Flood Management, Characterization and Vulnerability Analysis Using an Integrated RS-GIS and 2D Hydrodynamic Modelling Approach: The Case of Deg Nullah, Pakistan

One-dimensional (1D) hydraulic models have been extensively used to conduct flood simulations for investigating flood depth and extent maps. However, the 1D models cannot simulate many other flood characteristics, such as flood velocity, duration, arrival time and recession time when the flow is not restricted within the channel. These flood characteristics cannot be disregarded as they play an important role in developing flood mitigation and evacuation strategies. This study formulates a two-dimensional (2D) hydrodynamic model combined with remote sensing (RS) and geographic information system (GIS) approach to generate additional flood characteristic maps that cannot be produced with 1D models. The model was applied to a transboundary river of Deg Nullah in Pakistan to simulate an extreme flood event experience in 2014. The flood extent images from the moderate resolution imaging spectroradiometer (MODIS) and observed flood extents were used to evaluate the model performance. Moreover, an entropy distance-based approach was proposed to facilitate the integrated multivariate flood vulnerability classification. The simulated 2D flood modeling results showed a good agreement with the flood extents registered by MODIS and the observed ones. The northwest parts of Deg Nullah near Seowal, Dullam Kahalwan and Zafarwal were the most vulnerable areas due to high flood depths and prolonged flooding duration. Whereas high flood velocities, short flood arrival time, prolonged flood duration and recession times were observed in the upper reach of Deg Nullah thereby making it the most susceptible, critical and vulnerable region to flooding events.

Flash flood inundation assessment for an arid catchment, case study at Wadi Al Jizzi, Oman

Abstract Lack of high-resolution data and inappropriate integration of different data sources make modelling flash flood even more complicated. The IHACRES and AHP models were used to estimate floods for the period 1987 to 2007 for Wadi Al Jizzi arid catchment. The IHACRES model results showed that the average simulated flood was 0.36 m3/s, while that observed for all flood storms was 0.30 m3/s. The average readjusted AHP Simulated Flood for three statically defined clusters: low, moderate, and high rainfall was 3.55, 3.20, and 3.75 m3/s, respectively. The average observed flooding for low, moderate, and high rainfall were 3.23, 1.54, 3.07 m3/s. Pearson correlation between observed and simulated flood showed significant values for IHACRES and AHP with a range of 0.84 and 0.89 respectively. The Nash-Sutcliffe efficiency of the IHACRES model was 0.78, while it shows a good performance for low and high AHP re-adjusted values, which was 0.81 and 0.82.

Alteration of River Flow and Flood Dynamics by Existing and Planned Hydropower Dams in the Amazon River Basin

AbstractHydropower dams have received increased global attention due to their detrimental socioenvironmental ramifications. Such attention has led to an increase in studies on the impacts of reservoir operation on river flow; however, a holistic understanding of the compounded effects of hydropower dams on different hydrological characteristics is lacking, especially for large river basins such as the Amazon where hydropower development is on the rise. Here, we mechanistically quantify the historical impacts of existing dams and the potential impacts of the collective operation of existing and planned dams on a basin‐wide scale in the Amazon for the 1981–2019 period. We build on the recently developed high‐resolution (3‐arcmin; ∼5 km) river‐floodplain‐reservoir model, the CaMa‐Flood‐Dam, which is enhanced to realistically simulate hydropower dam operation considering maximized power production. Flood simulations are further downscaled to 3 arc‐seconds (∼90 m) resolution to investigate the impacts of dams on fine‐scale flood dynamics across the basin. Results indicate that existing dams have substantially altered downstream river flow and flooding patterns across the Amazon River basin. Specifically, large dams in the Amazonian subbasins, including the Xingu, Madeira, and Tocantins, have altered downstream river flow amplitude by up to 3 orders of magnitude. Further, the collective operation of existing and planned dams could increasingly alter river flow patterns, causing ∼10% decrease in flood duration in many parts of the Amazon mainstem. Our results provide quantitative evidence on the severity of the hydrologic impacts of large hydropower dams and have important implications for sustainable hydropower operation and development in the Amazon and worldwide.

Critical facility accessibility rapid failure early-warning detection and redundancy mapping in urban flooding

System-wide functionality failure emerges when a collection of components collapse simultaneously. Aiming to detect the early warning of the rapid critical facilities accessibility loss after flooding, this paper presents a network-theory-based detection model to identify the critical point after which the rate of road access loss to critical facilities starts to accelerate. The road network of Harris County, Texas during Hurricane Harvey 2017 flooding and simulated 500-year flooding (1,000 flooding sequences) is used for the case study. We also considered the travel radius for reaching critical facilities (e.g., 5 miles travel radius for hospitals, and 4 miles for groceries and pharmacies) in the accessibility assessment to show the flood impact on daily life. Additionally, we link the critical threshold to the spatial network to identify the corresponding critical roads whose disruption will likely trigger the rapid critical facility accessibility loss. This result will facilitate the decision-making on targeted infrastructure protection. Moreover, we map the number of critical facilities that each network component has access to within reach and reveal the resource redundancy inequity and risk disparity across the network. Integrating with the social vulnerability mapping, our result can help inform the resilience planning toward an equitable community.

Iron reduction process and antimony behavior change in paddy soils under stationary flooding conditions

Although iron reduction coupled with antimony (Sb) behavior change has attracted increasing interest in recent years, this process has not yet been well addressed in paddy soils under natural flooding conditions. This study investigates the iron reduction process in paddy soils using a stationary flooding incubation experiment. The paddy soils used in the study contained 199, 329 and 450 mg/kg of Sb (referred to as LS, MS and HS, respectively). Results showed that iron reduction lasted for 12–14 d under simulated flooding conditions at 25 °C, with the highest total Fe(II) being 778, 791 and 782 mg/kg in LS, MS and HS, respectively. Through the iron reduction process, easily reducible iron (Fe2) and reducible iron (Fe3) decreased by 26.1–38.4% and 4.03–12.8%, respectively, indicating that small fractions of iron oxides underwent reductive dissolution. The abundant phyla of iron-reducing bacteria in these soils were Proteobacteria, Firmicutes and Actinobacteriota. Moreover, up to 14 genera were identified as abundant iron-reducing bacteria in these paddy soils. Among, the most abundant genera were Azospirillum and Magnetospirillum, which are also known to mediate the iron nutrition supply for plants and magnetite formation, respectively. Along with iron reduction, iron oxide-incorporated Sb decreased by 7.87–17.3%, while soil surface-bound Sb increased by 42.4–60.4%. This demonstrates that substantial Sb released from iron reductive dissolution was adsorbed on the soil surface. In addition, the total aqueous Sb increased by 24.9–33.0 μg/L through iron reduction in these flooding soils, indicating that iron reduction promoted Sb mobilization in paddy soils under flooding conditions. Sb was synchronously reduced to Sb(III), with Sb(III) accounting for 51.1–59.4% of the total citric acid extracted Sb at the end of iron reduction. However, the aqueous Sb(III) was lower by orders of magnitude than the corresponding Sb(V) in these soils. This might imply that the strong adsorption affinity of Sb(III) to the soil solid facilitated the increase in soil surface-bound Sb in all flooded paddy soils.

Mechanism study of enhanced oil recovery by entrapped gas in extra high water-cut reservoir

Water control is an effective method to enhance the oil recovery in the high water-cut reservoir. It is proved that the water production can be reduced by the entrapped gas in the oil field. But the mechanism is not well studied. In this paper, the mechanism of enhanced oil recovery by entrapped gas is studied by experiments and numerical simulation. Based on the core flooding tests and simulation study, the increments of oil recovery caused by entrapped gas are 8% and 2%, respectively. After the gas is entrapped in the core sample, the water relative permeability is decreased by 10.5% and the oil relative permeability is only decreased by 3.5%, which proved that the entrapped gas has a dramatic effect on blocking water phase. The more gas is entrapped, the more oil is produced. Different methods to achieve entrapped gas are also discussed, simultaneous water, and gas injection is a preferred entrapped gas formation method than gas injection method and water alternating gas injection method. Under the immiscible condition, the entrapped methane has a better performance on enhancing oil recovery than the entrapped nitrogen.

Di- and Mono-Rhamnolipids Produced by the Pseudomonas putida PP021 Isolate Significantly Enhance the Degree of Recovery of Heavy Oil from the Romashkino Oil Field (Tatarstan, Russia)

Around the globe, only 30–50% of the amount of oil estimated to be in reservoirs (“original oil in place”) can be obtained using primary and secondary oil recovery methods. Enhanced oil recovery methods are required in the oil processing industry, and the use of microbially produced amphiphilic molecules (biosurfactants) is considered a promising efficient and environmentally friendly method. In the present study, biosurfactants produced by the Pseudomonas putida PP021 isolate were extracted and characterized, and their potential to enhance oil recovery was demonstrated. It was found that the cell-free biosurfactant-containing supernatant decreased the air–water interface tension from 74 to 28 mN m−1. Using TLC and FTIR methods, the biosurfactants produced by the isolate were classified as mono- and di-rhamnolipid mixtures. In the isolates’ genome, the genes rhlB and rhlC, encoding enzymes involved in the synthesis of mono- and di-rhamnolipids, respectively, were revealed. Both genes were expressed when the strain was cultivated on glycerol nitrate medium. As follows from the sand-packed column and core flooding simulations, biosurfactants produced by P. putida PP021 significantly enhance the degree of recovery, resulting in additional 27% and 21%, respectively.

Global sensitivity analysis in hydrodynamic modeling and flood inundation mapping

Flood simulation with two-dimensional hydrodynamic models is subject to different sources of uncertainties in model configuration, boundary conditions, and model parametrization. HEC-RAS 2D is a widely used hydrodynamic model. Here, we assess the sensitivity of the HEC-RAS 2D to its configuration factors and parameters. We evaluate the impacts of different model configuration factors, including the floodplain and channel roughness coefficients, terrain and mesh size, as well as river boundary conditions on the dynamic of water levels, maximum water level, and flood extent, and determine the importance of these contributing factors for reliable flood inundation modeling using both variogram and variance-based analyses. For our case study, we found that depending on the perturbation scale, the performance measure, and the predicted output, the sensitivity to input factors changes. While for simulation of water level dynamics, the DEM and mesh resolutions are the most important factors, for flood extent mapping the floodplain roughness coefficient and the upstream boundary condition are the key factors. In addition, our analyses indicated that for a reliable simulation of maximum flood water level, modelers need to spend resources on the calibration of floodplain roughness coefficient while using fine DEM and mesh resolutions. Here, we also investigate the role of computational time interval and mesh resolution on the model's run time and accuracy. Our results suggested that reducing the computational time interval has minimum impact, as it increases the model run time without much improving the model accuracy.