State-of-the-art hydrological models and application of the HEC-HMS model: a review

Sahu, Mukul Kumar; Rangaswamy, S.; Dwarakish, G. S.

doi:10.1007/s40808-023-01704-7

Cited by 27 publications

(12 citation statements)

References 133 publications

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“…The model is potential for the Keureuto watershed, considering that HEC-HMS is suitable for the dendritic type of the river system [11]. The simplicity of the SCS-CN method and the SCS-UH with less data requirement [12], [13] applies to watershed with less data availability [14], [15].…”

Section: Resultsmentioning

confidence: 99%

Flood peak estimation for the keureuto watershed using the hydrological modeling system HEC-HMS

Rama,

Fadhliani,

Khairullah

et al. 2024

IOP Conf. Ser.: Earth Environ. Sci.

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The Keureuto watershed has been the water resource used mainly for irrigation and municipal use. Extreme rainfall along with changes in the system may trigger rainfall excess causing flood at downstream. The occurrences may impact the usability of the system that supports the water resources supply. Investigating the impact of the floods requires initial research on the rainfall-runoff process of the watershed system. Rainfall-runoff modeling is an approach widely used for estimating the discharge hydrograph of the river as the result of the processes. The HEC-HMS rainfall-runoff model tool is applied in this study to estimate the peak flood discharge for the Keureto watershed located in the North Aceh region. The data used are satellite Global Precipitation Measurement (GPM) data and Automatic Water Level Recorder (AWLR) data at the watershed outlet. The 302 km2 Keureuto Watershed is divided into 23 sub-basins for the HEC-HMS model. The SCS Curve Number is applied to the model. The simulated freturncompared to the observed flow using the Nash Sutcliffe Efficiency criteria which returns the NSE value of 0.38 for seven years simulation, based on data of year 2015 to 2021. At an event based on October 2020 to March 2021, the NSE value returns 0.52, satisfactory for the simulation data range. The highest peak of the event is captured by the model simulation in the timing and the magnitude which value lower 20% from the observed flow.

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Section: Resultsmentioning

confidence: 99%

Flood peak estimation for the keureuto watershed using the hydrological modeling system HEC-HMS

Rama,

Fadhliani,

Khairullah

et al. 2024

IOP Conf. Ser.: Earth Environ. Sci.

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“…Inability to indicate moisture levels near saturated soil conditions can be also limiting for hydrological applications at watershed scale. Watershed monitoring and modeling tools related to surface and ground water need to distinguish between dry and saturated conditions to establish runoff and infiltration related processes [42][43][44][45]. Despite these limitations, the relatively low cost of the T-Higrow sensor, combined with the simplified correction procedure discussed in this work, provides some merit to its utility.…”

Section: Discussionmentioning

confidence: 99%

Versatile simplistic correction of T-higrow sensors for improved soil moisture measurement accuracy

Abdelal,

Al-Kilani

2024

Meas. Sci. Technol.

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The use of soil moisture sensors for irrigation can help reduce water and energy consumption and risks of groundwater contamination, which are essential aspects for pursuing sustainable development goals. However, increased adoption of this technology is limited by calibration requirements, technical complexities, and sensor costs. In this work, a simplified method for reducing the measurement error of a recently released low-cost soil sensor (T-Higrow) is presented. The method only requires measurements of a dry sample from the target soil, which are inputted into a simple correction formula to reduce the measurement error at higher moisture levels. The requirements of the proposed method are simple enough for most labs or extension services. This method was compared to the commonly used linear, polynomial, and logarithmic regression models based on repeated bench-scale experiments within 0-35% moisture range in silt and sandy loam soils and in silica sand. Uncorrected sensor readings correlated well with soil moisture (r: 0.94-0.98), but with significant overestimation (25-60% error). The simplified correction method showed comparable error reduction to regression models across all soil types. All methods reduced error down to 2-10% (0.02-0.1 cm3/cm3) and maintained high correlations (r >0.94), except for logarithmic regression which reduced correlation by around 3%. Variability amongst sensor measurements was generally low (Standard Deviation: 0.01-0.03) particularly at moisture ranges below 20%, this was also the case for sensor-to-sensor variability (Standard Deviation: 0.01-0.03). Sensor evaluation and calibration works are needed to increase the accessibility to this technology for improved water and energy conservation.

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“…HEC-HMS encompasses a comprehensive suite of features, including the modelling of losses, runoff transformation, open-channel routing, meteorological data analysis, rainfall-runoff simulation, and parameter estimation. It achieves this through the utilization of distinct models that represent each component of the runoff process, including those that calculate runoff volume, models for direct runoff, and models for base flow (24) .…”

Section: Hydrologic Modellingmentioning

confidence: 99%

“…In regions with limited historical flood data, HEC-HMS plays a pivotal role in predicting streamflow patterns across complex watersheds. The model's adaptability and accuracy have been demonstrated through calibration and testing in various river basins (16,17) . Hydraulic modeling, performed using the Hydrologic Engineering Center-River Analysis System (HEC-RAS), further assesses flood impacts on irrigation projects.…”

Section: Introductionmentioning

confidence: 99%

Flood Risk Assessment for an Irrigation Project in Odissa, India

Kumar,

Guganesh,

Babu

et al. 2024

IJST

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Objectives: Flood risk assessment is a fundamental aspect of disaster management, particularly in regions heavily reliant on irrigation infrastructure for agriculture. This study employs advanced hydrological and hydraulic modeling techniques to evaluate flood risk for the Lower Suktel region in Odisha, India. Methods: The methodology integrates Intensity-Duration-Frequency (IDF) curves, Isopluvial maps, and the Hydrologic Engineering Center-River Analysis System (HEC-RAS) to comprehensively analyze flood risk and its implications. Findings: IDF curves further reveal that the design rainfall intensity for a one-hour duration with a 100-year return period is 152 mm/h, aiding in characterizing rainfall intensity for specific return periods. Model simulation identifies the pump house's susceptibility to flooding, with maximum flood depths ranging from 0 to 2 meters. These findings underscore the significance of employing advanced modeling techniques and Isopluvial maps for precise flood risk assessment. Novelty: The novelty of this paper lies in its pioneering effort to introduce a comprehensive flood risk assessment in an area where it has not been previously conducted. The integration of advanced modeling techniques and spatial analysis tools contributes to the novelty of the research, making it a valuable and innovative contribution to the field of flood risk management. Understanding extreme rainfall events, hydraulic behavior, and potential flood depths is imperative for developing effective flood mitigation strategies. Keywords: Flood risk assessment, Irrigation infrastructure, IDF curves, Hydrological modeling, Hydraulic modeling, GIS

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State-of-the-art hydrological models and application of the HEC-HMS model: a review

Cited by 27 publications

References 133 publications

Flood peak estimation for the keureuto watershed using the hydrological modeling system HEC-HMS

Flood peak estimation for the keureuto watershed using the hydrological modeling system HEC-HMS

Versatile simplistic correction of T-higrow sensors for improved soil moisture measurement accuracy

Flood Risk Assessment for an Irrigation Project in Odissa, India

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