Reliability assessment of water structures subject to data scarcity using the SCS-CN model
When discharge measurements are not available, design of water structures relies on using frequency analysis of rainfall data and applying a rainfall-runoff model to estimate a hydrograph. The Soil Conservation Service (SCS) method estimates the design hydrograph first through a rainfall-runoff tran...
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| Published in | Hydrological sciences journal Vol. 61; no. 4; pp. 696 - 710 |
|---|---|
| Main Authors | , , , |
| Format | Journal Article |
| Language | English |
| Published |
Abingdon
Taylor & Francis
11.03.2016
Taylor & Francis Ltd |
| Subjects | |
| Online Access | Get full text |
| ISSN | 0262-6667 2150-3435 2150-3435 |
| DOI | 10.1080/02626667.2015.1027709 |
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| Abstract | When discharge measurements are not available, design of water structures relies on using frequency analysis of rainfall data and applying a rainfall-runoff model to estimate a hydrograph. The Soil Conservation Service (SCS) method estimates the design hydrograph first through a rainfall-runoff transformation and next by propagating runoff to the basin outlet via the SCS unit hydrograph (UH) method. The method uses two parameters, the Curve Number (CN) and the time of concentration (T
c
). However, in data-scarce areas, the calibration of CN and T
c
from nearby gauged watersheds is limited and subject to high uncertainties. Therefore, the inherent uncertainty/variability of the SCS parameters may have considerable ramifications on the safety of design. In this research, a reliability approach is used to evaluate the impact of incorporating the uncertainty of CN and T
c
in flood design. The sensitivity of the probabilistic outcome against the uncertainty of input parameters is calculated using the First Order Reliability Method (FORM). The results of FORM are compared with the conventional SCS results, taking solely the uncertainty of the rainfall event. The relative importance of the uncertainty of the SCS parameters is also estimated. It is found that the conventional approach, used by many practitioners, might grossly underestimate the risk of failure of water structures, due to neglecting the probabilistic nature of the SCS parameters and especially the Curve Number. The most predominant factors against which the SCS-CN method is highly uncertain are when the average rainfall value is low (less than 20 mm) or its coefficient of variation is not significant (less than 0.5), i.e. when the resulting rainfall at the design return period is low. A case study is presented for Egypt using rainfall data and CN values driven from satellite information, to determine the regions of acceptance of the SCS-CN method.
EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR A. Efstratiadis |
|---|---|
| AbstractList | When discharge measurements are not available, design of water structures relies on using frequency analysis of rainfall data and applying a rainfall-runoff model to estimate a hydrograph. The Soil Conservation Service (SCS) method estimates the design hydrograph first through a rainfall-runoff transformation and next by propagating runoff to the basin outlet via the SCS unit hydrograph (UH) method. The method uses two parameters, the Curve Number (CN) and the time of concentration (T sub(c)). However, in data-scarce areas, the calibration of CN and T sub(c) from nearby gauged watersheds is limited and subject to high uncertainties. Therefore, the inherent uncertainty/variability of the SCS parameters may have considerable ramifications on the safety of design. In this research, a reliability approach is used to evaluate the impact of incorporating the uncertainty of CN and T sub(c) in flood design. The sensitivity of the probabilistic outcome against the uncertainty of input parameters is calculated using the First Order Reliability Method (FORM). The results of FORM are compared with the conventional SCS results, taking solely the uncertainty of the rainfall event. The relative importance of the uncertainty of the SCS parameters is also estimated. It is found that the conventional approach, used by many practitioners, might grossly underestimate the risk of failure of water structures, due to neglecting the probabilistic nature of the SCS parameters and especially the Curve Number. The most predominant factors against which the SCS-CN method is highly uncertain are when the average rainfall value is low (less than 20 mm) or its coefficient of variation is not significant (less than 0.5), i.e. when the resulting rainfall at the design return period is low. A case study is presented for Egypt using rainfall data and CN values driven from satellite information, to determine the regions of acceptance of the SCS-CN method.EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR A. Efstratiadis When discharge measurements are not available, design of water structures relies on using frequency analysis of rainfall data and applying a rainfall-runoff model to estimate a hydrograph. The Soil Conservation Service (SCS) method estimates the design hydrograph first through a rainfall-runoff transformation and next by propagating runoff to the basin outlet via the SCS unit hydrograph (UH) method. The method uses two parameters, the Curve Number (CN) and the time of concentration (T c ). However, in data-scarce areas, the calibration of CN and T c from nearby gauged watersheds is limited and subject to high uncertainties. Therefore, the inherent uncertainty/variability of the SCS parameters may have considerable ramifications on the safety of design. In this research, a reliability approach is used to evaluate the impact of incorporating the uncertainty of CN and T c in flood design. The sensitivity of the probabilistic outcome against the uncertainty of input parameters is calculated using the First Order Reliability Method (FORM). The results of FORM are compared with the conventional SCS results, taking solely the uncertainty of the rainfall event. The relative importance of the uncertainty of the SCS parameters is also estimated. It is found that the conventional approach, used by many practitioners, might grossly underestimate the risk of failure of water structures, due to neglecting the probabilistic nature of the SCS parameters and especially the Curve Number. The most predominant factors against which the SCS-CN method is highly uncertain are when the average rainfall value is low (less than 20 mm) or its coefficient of variation is not significant (less than 0.5), i.e. when the resulting rainfall at the design return period is low. A case study is presented for Egypt using rainfall data and CN values driven from satellite information, to determine the regions of acceptance of the SCS-CN method. EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR A. Efstratiadis When discharge measurements are not available, design of water structures relies on using frequency analysis of rainfall data and applying a rainfall–runoff model to estimate a hydrograph. The Soil Conservation Service (SCS) method estimates the design hydrograph first through a rainfall–runoff transformation and next by propagating runoff to the basin outlet via the SCS unit hydrograph (UH) method. The method uses two parameters, the Curve Number (CN) and the time of concentration (T c). However, in data-scarce areas, the calibration of CN and T c from nearby gauged watersheds is limited and subject to high uncertainties. Therefore, the inherent uncertainty/variability of the SCS parameters may have considerable ramifications on the safety of design. In this research, a reliability approach is used to evaluate the impact of incorporating the uncertainty of CN and T c in flood design. The sensitivity of the probabilistic outcome against the uncertainty of input parameters is calculated using the First Order Reliability Method (FORM). The results of FORM are compared with the conventional SCS results, taking solely the uncertainty of the rainfall event. The relative importance of the uncertainty of the SCS parameters is also estimated. It is found that the conventional approach, used by many practitioners, might grossly underestimate the risk of failure of water structures, due to neglecting the probabilistic nature of the SCS parameters and especially the Curve Number. The most predominant factors against which the SCS-CN method is highly uncertain are when the average rainfall value is low (less than 20 mm) or its coefficient of variation is not significant (less than 0.5), i.e. when the resulting rainfall at the design return period is low. A case study is presented for Egypt using rainfall data and CN values driven from satellite information, to determine the regions of acceptance of the SCS-CN method. When discharge measurements are not available, design of water structures relies on using frequency analysis of rainfall data and applying a rainfall-runoff model to estimate a hydrograph. The Soil Conservation Service (SCS) method estimates the design hydrograph first through a rainfall-runoff transformation and next by propagating runoff to the basin outlet via the SCS unit hydrograph (UH) method. The method uses two parameters, the Curve Number (CN) and the time of concentration (Tc). However, in data-scarce areas, the calibration of CN and Tc from nearby gauged watersheds is limited and subject to high uncertainties. Therefore, the inherent uncertainty/variability of the SCS parameters may have considerable ramifications on the safety of design. In this research, a reliability approach is used to evaluate the impact of incorporating the uncertainty of CN and Tc in flood design. The sensitivity of the probabilistic outcome against the uncertainty of input parameters is calculated using the First Order Reliability Method (FORM). The results of FORM are compared with the conventional SCS results, taking solely the uncertainty of the rainfall event. The relative importance of the uncertainty of the SCS parameters is also estimated. It is found that the conventional approach, used by many practitioners, might grossly underestimate the risk of failure of water structures, due to neglecting the probabilistic nature of the SCS parameters and especially the Curve Number. The most predominant factors against which the SCS-CN method is highly uncertain are when the average rainfall value is low (less than 20 mm) or its coefficient of variation is not significant (less than 0.5), i.e. when the resulting rainfall at the design return period is low. A case study is presented for Egypt using rainfall data and CN values driven from satellite information, to determine the regions of acceptance of the SCS-CN method. EDITOR D. Koutsoyiannis; ASSOCIATE EDITOR A. Efstratiadis |
| Author | Elmoustafa, Ashraf Awadallah, Ayman G. Saad, Haitham Hassan, Ahmed |
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| CitedBy_id | crossref_primary_10_1007_s12517_019_4473_2 crossref_primary_10_1007_s13201_015_0292_0 crossref_primary_10_1155_2018_7056858 crossref_primary_10_1002_2017WR020947 crossref_primary_10_1007_s11269_017_1787_2 crossref_primary_10_1007_s12517_020_06267_w crossref_primary_10_1016_j_ssci_2018_03_013 crossref_primary_10_1088_1755_1315_191_1_012117 crossref_primary_10_1016_j_ress_2021_107733 crossref_primary_10_1080_02626667_2017_1334166 crossref_primary_10_1007_s11069_022_05220_2 crossref_primary_10_1007_s12517_017_2984_2 crossref_primary_10_1080_02626667_2018_1525616 |
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| References | Ministry of Municipal Affairs and Agriculture (CIT0023) 1997 CIT0031 Chen C.L. (CIT0002) 1982 CIT0012 CIT0034 CIT0011 CIT0033 Ministry of Transportation (CIT0024) 1997 USDA (United States Department of Agriculture (CIT0035) 1972 CIT0014 USDA (United States Department of Agriculture (CIT0036) 1985 CIT0013 CIT0016 CIT0015 CIT0018 CIT0039 CIT0019 Nataf A. (CIT0028) 1962; 225 CIT0041 CIT0040 CIT0021 USDA (United States Department of Agriculture (CIT0037) 1986 CIT0020 CIT0042 CIT0001 USDA (United States Department of Agriculture (CIT0038) 2004 Pilgrim D.H. (CIT0029) 1993 Ministry of Housing Utilities and Urban Development (CIT0022) 2008 Mockus V. (CIT0027) 1949 CIT0003 Ebrahimian M. (CIT0005) 2012; 21 CIT0025 Sherman L.K. (CIT0030) 1932; 108 Singh V.P. (CIT0032) 1992 CIT0026 CIT0007 CIT0006 |
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| Snippet | When discharge measurements are not available, design of water structures relies on using frequency analysis of rainfall data and applying a rainfall-runoff... When discharge measurements are not available, design of water structures relies on using frequency analysis of rainfall data and applying a rainfall–runoff... |
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| SubjectTerms | arid region basins Brackish case studies curve number Egypt first order reliability method (FORM) hydrograph hydrologic models meteorological data rain risk runoff satellites SCS soil conservation time of concentration uncertainty watersheds |
| Title | Reliability assessment of water structures subject to data scarcity using the SCS-CN model |
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