Computer Program for Project Formulation: Hydrology (TR-20) Revisited

Cronshey, Roger G.; Woodward, Donald E.

doi:10.1061/40499(2000)16

Cited by 12 publications

(21 citation statements)

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“…We focus on infrastructure safety at the DoD MCMWTC site due to its critical role in force training to defend U.S. national security interests. The test basin has an area of 2.36 km 2 , which aligns with the TR-55 design scale for small watersheds (Cronshey et al, 1986). The test basin has uniform bedrock-derived soil but contains multiple land covers.…”

Section: Study Areamentioning

confidence: 89%

“…Based on the observations from nearly 400 Snowpack Telemetry (SNOTEL) stations across the western United States, Yan, Sun, Wigmosta, Skaggs, Hou, et al. (2019) compared the design flood estimates by using PREC‐IDF and NG‐IDF curves coupled with the NRCS TR‐55 single‐event rainfall‐runoff model (Cronshey et al., 1986). They showed that about 70% of the stations in the western United States were subject to underdesign with the use of PREC‐IDF curves, for which the PREC‐IDF curves generated lower design floods by 324%.…”

Section: Introductionmentioning

confidence: 99%

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The Role of Snowmelt Temporal Pattern in Flood Estimation for a Small Snow‐Dominated Basin in the Sierra Nevada

Yan,

Sun,

Wigmosta

et al. 2023

Water Resources Research

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Prior research confirmed the substantial bias from using precipitation‐based intensity‐duration‐frequency curves (PREC‐IDF) in design flood estimates and proposed next‐generation IDF curves (NG‐IDF) that represent both rainfall and snow processes in runoff generation. This study improves the NG‐IDF technology for a snow‐dominated test basin in the Sierra Nevada. A well‐validated physics‐based hydrologic model, the Distributed Hydrology Soil Vegetation Model (DHSVM), is used to continuously simulate snowmelt and streamflow that are used as benchmark data sets to systematically assess the NG‐IDF technology. We find that, for the studied small snow‐dominated basin, the use of standard rainfall hyetographs in the NG‐IDF technology leads to substantial underestimation of design floods. Thus, we propose probabilistic hyetographs that can represent unique patterns of events with different underlying mechanisms. For the test basin where flooding events are generated entirely by snowmelt, we develop a hyetograph that characterizes snowmelt temporal patterns, which greatly improves the performance of NG‐IDF technology in design flood estimates. In contrast to the standard rainfall hyetographs characterized by a symmetrically peaked, bell‐shaped curve, the snowmelt hyetograph displays a more rapid rise (i.e., greater intensity) and a distinct diurnal pattern influenced by solar energy input. The results also show that the uncertainty of hyetography plays an important role in design flood estimation and can have important implications for future flood projections.

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Section: Study Areamentioning

confidence: 89%

Section: Introductionmentioning

confidence: 99%

The Role of Snowmelt Temporal Pattern in Flood Estimation for a Small Snow‐Dominated Basin in the Sierra Nevada

Yan,

Sun,

Wigmosta

et al. 2023

Water Resources Research

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“…In this section, inside the study area, a public garden with a total area of (2670 m²) in the (Bakhtyary Nwe) neighborhood has been chosen to evaluate its potential to harvest rainwater. It's essential in calculating rainwater harvesting (runoff) generally to select a method that is suitable to the data and parameters that are available and also take into account the complexity and the object of the work with a reasonable error level (Cronshey et al, 1986;Harb, 2015). Considering the previous points, the Soil Conservation Service (SCS) method is regarded as the most appropriate method to calculate runoff (rainwater harvesting) in the case of the garden (our case).…”

Section: Green Area Rainwater Harvestingmentioning

confidence: 99%

Estimation of Water and Energy Saving by Rainwater Harvesting: Sulaimani City as a Case Study

Ways

Ibrahim

2023

jcoeng

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Rainwater harvesting could be a possible solution to decrease the consequences of water scarcity and energy deficiency in Iraq and the Kurdistan Region of Iraq (KRI). This study aims to calculate the water and energy (electricity) saved by rainwater harvesting for rooftops and green areas in Sulaimani city, KR, Iraq. Various data were acquired from different formal entities in Sulaimani city. Moreover, Google Earth and ArcMap 10.4 software were used for digitizing and calculating the total rooftop and green areas. The results showed that for the used runoff coefficients (0.8 and 0.95), the harvested rainwater volumes were 2901563 and 12197131 m³ during the study period (2005 – 2006) and (2019-2020). Moreover, by comparing the study area's rainwater harvesting volume and water production, the water-saving percentage was 8.21 to 22.68%. Furthermore, the energy-saving percentage recorded was from 7.70 to 22.5% by implementing rooftop rainwater harvesting. On the other hand, using average daily rainfall data for the year (2005-2020), the total water-saving percentage and the total energy-saving rate for both runoff coefficients were very close. Water and energy-saving results were calculated using year-by-year rainfall data, taking more time and effort for its computation. Moreover, the water-saving percentage for the selected green area was not encouraging, and the results were between 0.73 and 11.15%. Additionally, the storage size for three typical buildings was calculated, and the results show the average storage size required for rainwater harvesting using daily rainfall data was 11.2 to 14.68 m³ (house), 291.42 to 422.33 m³ (school), and 10.5 to 11.41 m³ (hotel) for runoff coefficients of 0.8 and 0.95, respectively.

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“…As for the creation of curve number map, the SCS-CN method was applied. In terms of this method, the map of hydrological soil groups (Figure S3a), map of land cover (Figure S3b), and official SCS-CN tables [48] were combined (Table S1) using the HEC-GeoHMS extension for ArcGIS software to derive the curve numbers (Figure S4a). Hydrological soil groups were derived from the vector Soil Texture Map at a scale of 1:500,000 [49] while the CORINE Land Cover vector layer from 2018 was used to derive the land cover in the study area.…”

Section: Input Data and Gis Processing Of Flood Conditioning Factorsmentioning

confidence: 99%

GIS-Based Spatial and Multi-Criteria Assessment of Riverine Flood Potential: A Case Study of the Nitra River Basin, Slovakia

Vojtek

Vojteková

Pham

2021

IJGI

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The aim of this study was to identify the areas with different levels of riverine flood potential (RFP) in the Nitra river basin, Slovakia, using multi-criteria evaluation (MCE)-analytical hierarchical process (AHP), geographic information systems (GIS), and seven flood conditioning factors. The RFP in the Nitra river basin had not yet been assessed through MCE-AHP. Therefore, the methodology used can be useful, especially in terms of the preliminary flood risk assessment required by the EU Floods Directive. The results showed that classification techniques of natural breaks (Jenks), equal interval, quantile, and geometric interval classified 32.03%, 29.90%, 41.84%, and 53.52% of the basin, respectively, into high and very high RFP while 87.38%, 87.38%, 96.21%, and 98.73% of flood validation events, respectively, corresponded to high and very high RFP. A single-parameter sensitivity analysis of factor weights was performed in order to derive the effective weights, which were used to calculate the revised riverine flood potential (RRFP). In general, the differences between the RFP and RRFP can be interpreted as an underestimation of the share of high and very high RFP as well as the share of flood events in these classes within the RFP assessment. Therefore, the RRFP is recommended for the assessment of riverine flood potential in the Nitra river basin.

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Computer Program for Project Formulation: Hydrology (TR-20) Revisited

Cited by 12 publications

References 0 publications

The Role of Snowmelt Temporal Pattern in Flood Estimation for a Small Snow‐Dominated Basin in the Sierra Nevada

The Role of Snowmelt Temporal Pattern in Flood Estimation for a Small Snow‐Dominated Basin in the Sierra Nevada

Estimation of Water and Energy Saving by Rainwater Harvesting: Sulaimani City as a Case Study

GIS-Based Spatial and Multi-Criteria Assessment of Riverine Flood Potential: A Case Study of the Nitra River Basin, Slovakia

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