Reliability assessment of water structures subject to data scarcity using the SCS-CN model

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     

Rainfall–runoff simulation using a normalized antecedent precipitation index

Abstract

The normalized antecedent precipitation index (NAPI) model by Heggen for the prediction of runoff yield is analytically derived from the water balance equation. Heggen's model has been simplified further to a rational form and its performance verified with the Soil Conservation Service Curve Number (SCS-CN) model. The simplified model has three coefficients specific to a watershed, and requires two inputs: rainfall and the derived parameter, NAPI. The characteristic behaviour of the NAPI has resonance with the curve number (CN) of the SCS model. The proposed NAPI model was applied to three watersheds in the semi-arid region of India to simulate runoff yield. The model showed improved correlation between the observed and predicted runoff data compared to the SCS-CN model. The F test and paired t test also confirmed the reliability of the model with significance levels of 0.01 and 0.001%, respectively. The proposed model could be used successfully for rainfall–runoff modelling in a watershed.

Citation Ali, S., Ghosh, N. C. & Singh, R. (2010) Rainfall–runoff simulation using a normalized antecedent precipitation index. Hydrol. Sci. J. 55(2), 266–274.     

Sensitivity and fuzzy uncertainty analyses in the determination of SCS-CN parameters from rainfall–runoff data

Spatial and seasonal variations of curve number (CN) and initial abstraction ratio (λ) in a watershed can result in inaccurate runoff volume estimations when using the US Natural Resources Conservation Service (SCS-CN) method with constant values for these parameters. In this paper, parameters of CN and λ are considered as calibration parameters and the sensitivity of estimated runoff to these parameters using the SCS-CN method is scrutinized. To incorporate the uncertainty associated with CN and λ, fuzzy linear regression (FLR) is applied to derive the relationships of CN and λ with rainfall depth (P) by employing a large dataset of storm events from four watersheds in Iran. Results indicate that the proposed approach provides more accuracy in estimation of runoff volume compared to the SCS method with constant values of CN and λ, and gives a straightforward technique for evaluating the hydrological effects of CN, λ, and P on runoff volume.     

Revised runoff curve number for runoff prediction in the Loess Plateau of China

The soil conservation service (now Natural Resources Conservation Service) Curve Number (SCS-CN), one of the most commonly used methods for surface runoff prediction. The runoff calculated by this method was very sensitive to CN values. In this study, CN values were calculated by both arithmetic mean (CN_C) and least square fit method (CN_F) using observed rainfall-runoff data from 43 sites in the Loess Plateau region, which are considerably different from the CN₂ values obtained from the USDA-SCS handbook table (CN_T). The results showed that using CN_C instead of CN_T for each watershed produce little improvement, while replacing CN_T with CN_F improves the performance of the original SCS-CN method, but still performs poorly in most study sites. This is mainly due to the SCS-CN method using a constant CN value and discounting of the temporal variation in rainfall-runoff process. Therefore, three factors—soil moisture, rainfall depth and intensity—affecting the surface runoff variability are considered to reflect the variation of CN in each watershed, and a new CN value was developed. The reliability of the proposed method was tested with data from 38 watersheds, and then applied to the remaining five typical watersheds using the optimized parameters. The results indicated that the proposed method, which boosted the model efficiencies to 81.83% and 74.23% during calibration and validation cases, respectively, performed better than the original SCS-CN and the Shi and Wang (2020b) method, a modified SCS-CN method based on tabulated CN value. Thus, the proposed method incorporating the influence of the temporal variability of soil moisture, rainfall depth, and intensity factors suggests an accurate runoff prediction for general applications under different hydrological and climatic conditions on the Loess Plateau region.     

Has urbanization changed ecological streamflow characteristics in Maine (USA)?

Abstract

This paper examines the potential effects of urbanization on streamflow in Maine, USA, from 1950 to 2000. The study contrasts nine watersheds in southern Maine, which has seen steady urban growth over the study period, with nine rural watersheds from northern Maine. Historical population data and current land cover data are used to develop an urbanization score for each watershed. Trends in watershed urbanization over the study period are compared to trends in ecologically relevant streamflow characteristics. The results indicate that trends in northern, rural watersheds are much more consistent than the trends in the southern watersheds. Additionally, trends in the southern watersheds are inconsistent with the hydrological characteristics observed in urban watersheds elsewhere, likely due to the comparatively low level of current urban development in Maine's urban watersheds. Our study suggests that urban areas in Maine have not yet reached an urbanization threshold where streamflow impacts become consistently detectable.

Editor Z.W. Kundzewicz

Citation Martin, E.H., Kelleher, C., and Wagener, T., 2012. Has urbanization changed ecological streamflow characteristics in Maine (USA)? Hydrological Sciences Journal, 57 (7), 1337–1354.     

A two-stage fuzzy-stochastic factorial analysis method for characterizing effects of uncertainties in hydrological modelling

ABSTRACT

In this study, a two-stage fuzzy-stochastic factorial analysis (TFFA) method is developed and applied to the Vakhsh watershed (upper reaches of Aral Sea basin, Central Asia) for daily streamflow simulation. TFFA has advantages in identifying the major parameters that have important individual and interactive effects on model outputs, as well as assessing multiple uncertainties resulting from randomness and vagueness characteristics of model parameters. The results reveal that (a) nine major parameters (from a total of 24) have significant effects on Soil Water Assessment Tool (SWAT) simulation performance for the study watershed; and (b) snowmelt-related parameters (including snowfall temperature, threshold temperature for snowmelt and s nowmelt factor) and runoff curve number (CN2) are most sensitive parameters for the runoff generation. The results also show that the proposed TFFA method can help enhance the hydrological model’s capability for runoff simulation/prediction, particularly for in data-scarce and high-mountainous watersheds.     

Event-based estimation of water budget components using a network of multi-sensor capacitance probes

Abstract

A new approach was developed for estimating vertical soil water fluxes using soil water content time series data. Instead of a traditional fixed time interval, this approach utilizes the time interval between two sequential minima of the soil water storage time series to identify groundwater recharge events and calculate components of the soil water budget. We calculated water budget components: surface-water excess (Sw), infiltration less evapotranspiration (I – ET) and groundwater recharge (R) from May 2001 to January 2003 at eight locations at the USDA Agricultural Research Center, Beltsville, Maryland, USA. High uncertainty was observed for all budget components. This uncertainty was attributed to spatial and temporal variation in Sw, I – ET and R, and was caused by nonuniform rainfall distributions during recharge events, variability in the profile water content, and spatial variability in soil hydraulic properties. The proposed event-based approach allows estimating water budget components when profile water content monitoring data are available.

Citation Guber, A., Gish, T., Pachepsky, Y., McKee, L., Nicholson, T. & Cady, R. (2011) Event-based estimation of water budget components using a network of multi-sensor capacitance probes. Hydrol. Sci. J. 56(7), 1227–1241.     

Influence of coarse soils with high hydraulic conductivity on the applicability of the SCS-CN method

The impact of the existence of coarse soils with high hydraulic conductivity on the applicability of the Soil Conservation Service curve number (SCS-CN) method is investigated in a heterogeneous catchment in the Zagros mountain region, southwest Iran. The findings indicate that curve numbers (CN) decline steadily as rainfall depths increase, showing no evidence of reaching stable CN values. This is attributed to a small low permeability area in the catchment, although most parts of the region are covered by high to very high permeability soils. Although this behaviour has been attributed mainly to forested areas by some researchers, it is shown here that it can be observed in mountain regions with coarse soils. The results also reveal that a linear rainfall–runoff formula of the form Q = CP provides more accurate results than the SCS-CN method, and the runoff coefficient (C) can be taken as equal to the low-permeability area fraction, meaning that these parts can be considered to be the main runoff-producing areas.     

Effects of hillslope geometry on spatial infiltration using the TOPMODEL and SCS-CN models

ABSTRACT

The estimation of infiltration is a main issue in runoff simulation. The geometry of hillslopes (plan shape and profile curvature) may affect the responses, as well as infiltration over the hillslopes. In this study, the equations of TOPMODEL (a topography-based model) were applied to complex hillslopes to develop the complex TOPMODEL. This model was coupled with the SCS-CN (Soil Conservation Service Curve Number) model to examine the effects of geometry on infiltration and derive a saturation excess-based curve number (CN). The effects of plan shape and profile curvature upon the spatial distribution of CN and infiltration were studied. The results show that convergent hillslopes have 15.4% less infiltration and divergent hillslopes have 7.8% more infiltration than parallel ones. The infiltration over concave hillslopes is 13.5% lower and infiltration over convex hillslopes 5.8% higher than for straight ones. The degree of convergence/divergence has a greater effect on the CN compared to that of profile curvature.     

A drought outlook study in Korea

Abstract

Techniques are proposed for developing a monthly and weekly drought outlook and the drought outlook components are evaluated. A drought index, the surface water supply index (SWSI) was modified and used for the drought outlook. A water balance model (abcd) was successfully calibrated using a regional regression, including monthly and weekly factors, and was used to convert meteorology to hydrology. For the monthly drought outlook, an ensemble technique was applied, both with and without monthly industrial meteorology information (MIMI). For the weekly drought outlook, a deterministic forecasting technique was applied employing the Global Data Assimilation and Prediction System (GDAPS). The methodologies were applied to the Geum River basin in Korea. While only the weekly outlook using the GDAPS has sufficient forecasting capability to suggest it might be useful, the accuracy of the monthly drought outlook is expected to improve as the climate forecast accuracy increases.

Editor Z.W. Kundzewicz; Associate editor D. Hughes

Citation Kim, Y.-O., Lee, J.-K., and Palmer, R.N., 2012. A drought outlook study in Korea. Hydrological Sciences Journal, 57 (6), 1141–1153.     

Atlantic Ocean sea-surface temperatures and regional streamflow variability in the Adour-Garonne basin,France

Abstract

The identification of Atlantic Ocean (AO) climatic drivers may prove valuable in long lead-time forecasting of streamflow in the Adour-Garonne basin in southwestern France. Previous studies have identified the Atlantic Multidecadal Oscillation (AMO) and the North Atlantic Oscillation (NAO) as drivers of European hydrology. The current research applied the singular value decomposition (SVD) statistical method to AO sea-surface temperatures (SSTs) to identify the primary AO climatic drivers of the Adour-Garonne basin streamflow. Annual and seasonal streamflow volumes were selected as the hydrological response, while average AO SSTs were calculated for three different 6-month averages (January–June, April–September and July–December) for the year preceding streamflow. The results identified a region along the Equator as the probable driver of the basin streamflow. Additional analysis evaluated the influence of the AMO and NAO on Adour-Garonne basin streamflow.

Editor Z.W. Kundzewicz; Associate editor H. Aksoy

Citation Oubeidillah, A.A., Tootle, G. and Anderson, S.-R., 2012. Atlantic Ocean sea-surface temperatures and regional streamflow variability in the Adour-Garonne basin, France. Hydrological Sciences Journal, 57 (3), 496–506.     

Estimation of phosphorus loads with sparse data for agricultural watersheds in the Czech Republic

Abstract

Agricultural watersheds in the Czech Republic are one of the primary sources of non-point-source phosphorus (P) loads in receiving waters. Since such non-point sources are generally located in headwater catchments, streamflow and P concentration data are sparse. We show how very short daily streamflow and P concentration records can be combined with nearby longer existing daily streamflow records to result in reliable estimates of daily and annual P concentrations and loads. Maintenance of variance streamflow record extension methods (MOVE) can be employed to extend short streamflow records. Constituent load regressions are used to predict daily P constituent loads from streamflow and other time varying characteristics. Annual P loads are then estimated for individual watersheds. Resulting annual P load estimates ranged from 0.21 to 95.4 kg year^-1 with a mean value of 11.77 kg year^-1. Similarly annual P yield estimates ranged from 0.01 to 0.3 kg ha^-1 year^-1 with an average yield of 0.07 kg ha^-1 year^-1. We document how short records of daily streamflow and P concentrations can be combined with a national network of daily streamflow records in the Czech Republic to arrive at meaningful and reliable estimates of annual P loads for small agricultural watersheds.

Citation Beránková, T., Vogel, R. M., Fiala, D. & Rosendorf, P. (2010) Estimation of phosphorus loads with sparse data for agricultural watersheds in the Czech Republic. Hydrol. Sci. J. 55(8), 1417–1426.     

Long-term pan evaporation observations as a resource to understand the water cycle trend: case studies from Australia

Abstract

Acceleration of the global water cycle over recent decades remains uncertain because of the high inter-annual variability of its components. Observations of pan evaporation (E_pan), a proxy of potential evapotranspiration (ET_p), may help to identify trends in the water cycle over long periods. The complementary relationship (CR) states that ET_p and actual evapotranspiration (ET_a) depend on each other in a complementary manner, through land–atmosphere feedbacks in water-limited environments. Using a long-term series of E_pan observations in Australia, we estimated monthly ET_a by the CR and compared our estimates with ET_a measured at eddy covariance Fluxnet stations. The results confirm that our approach, entirely data-driven, can reliably estimate ET_a only in water-limited conditions. Furthermore, our analysis indicated that ET_a did not show any significant trend in the last 30 years, while short-term analysis may indicate a rapid climate change that is not perceived in a long-term perspective.

Editor Z.W. Kundzewicz; Associate editor D. Gerten

Citation Lugato, E., Alberti, G., Gioli. B., Kaplan, J.O., Peressotti, A., and Miglietta, F., 2013. Long-term pan evaporation observations as a resource to understand the water cycle trend: case studies from Australia. Hydrological Sciences Journal, 58 (6), 1287–1296.     

Use of soil moisture data and curve number method for estimating runoff in the Loess Plateau of China

The Soil Conservation Service curve number (CN) method commonly uses three discrete levels of soil antecedent moisture condition (AMC), defined by the 5‐day antecedent rainfall depth, to describe soil moisture prior to a runoff event. However, this way may not adequately represent soil water conditions of fields and watersheds in the Loess Plateau of China. The objectives of this study were: (1) to determine the effective soil moisture depth to which the CN is most related; (2) to evaluate a discrete and a linear relationship between AMC and soil moisture; and (3) to develop an equation between CN and soil moisture to predict runoff better for the climatic and soil conditions of the Loess Plateau of China. The dataset consisted of 10 years of rainfall, runoff and soil moisture measurements from four experimental plots cropped with millet, pasture and potatoes. Results indicate that the standard CN method underestimated runoff depths for 85 of the 98 observed plot‐runoff events, with a model efficiency E of only 0·243. For our experimental conditions, the discrete and linear approaches improved runoff estimation, but still underestimated most runoff events, with E values of 0·428 and 0·445 respectively. Based on the measured CN values and soil moisture values in the top 15 cm of the soil, a non‐linear equation was developed that predicted runoff better with an E value of 0·779. This modified CN equation was the most appropriate for runoff prediction in the study area, but may need adjustments for local conditions in the Loess Plateau of China. Copyright © 2006 John Wiley & Sons, Ltd.     

Analytical procedures for weekly hydrological droughts: a case of Canadian rivers

Abstract

Two entities of importance in hydrological droughts, viz. the longest duration, L_T , and the largest magnitude, M_T (in standardized terms) over a desired time period (which could also correspond to a specific return period) T, have been analysed for weekly flow sequences of Canadian rivers. Analysis has been carried out in terms of week-by-week standardized values of flow sequences, designated as SHI (standardized hydrological index). The SHI sequence is truncated at the median level for identification and evaluation of expected values of the above random variables, E(L_T ) and E(M_T ). SHI sequences tended to be strongly autocorrelated and are modelled as autoregressive order-1, order-2 or autoregressive moving average order-1,1. The drought model built on the theorem of extremes of random numbers of random variables was found to be less satisfactory for the prediction of E(L_T ) and E(M_T ) on a weekly basis. However, the model has worked well on a monthly (weakly Markovian) and an annual (random) basis. An alternative procedure based on a second-order Markov chain model provided satisfactory prediction of E(L_T ). Parameters such as the mean, standard deviation (or coefficient of variation), and lag-1 serial correlation of the original weekly flow sequences (obeying a gamma probability distribution function) were used to estimate the simple and first-order drought probabilities through closed-form equations. Second-order probabilities have been estimated based on the original flow sequences as well as SHI sequences, utilizing a counting method. The E(M_T ) can be predicted as a product of drought intensity (which obeys the truncated normal distribution) and E(L_T ) (which is based on a mixture of first- and second-order Markov chains).

Citation Sharma, T. C. & Panu, U. S. (2010) Analytical procedures for weekly hydrological droughts: a case of Canadian rivers. Hydrol. Sci. J. 55(1), 79–92.     

A framework for sourcing of evaporation between saturated and unsaturated zone in bare soil condition

ABSTRACT

Sourcing subsurface evaporation (E_ss) into groundwater (E_g) and unsaturated zone (E_u) components has received little scientific attention so far, despite its importance in water management and agriculture. We propose a novel sourcing framework, with its implementation in dedicated post-processing software called SOURCE (used along with the HYDRUS1D model), to study evaporation sourcing dynamics, define quantitatively “shallow” and “deep” water table conditions and test the applicability of water table fluctuation (WTF) and “bucket” methods for estimation of E_g and E_u separately.

For the “shallow” and “deep” water table we propose E_g?>?0.95E_ss and E_g = 0 criteria, respectively. Assessment of the WTF method allowed sourcing of very small fluxes otherwise neglected by standard hydrological methods. Sourcing with SOURCE software was more accurate than the standard “bucket” method mainly because of greater flexibility in spatio-temporal discretization. This study emphasized the dry condition relevance of groundwater evaporation which should be analysed by applying coupled flow of heat, vapour and liquid water.

Editor D. Koutsoyiannis; Associate editor S. Kanae     

Improving streamflow estimation in ungauged basins using a multi-modelling approach

ABSTRACT

In this study, a multi-modelling approach is proposed for improved continuous daily streamflow estimation in ungauged basins using regionalization—the process of transferring hydrological data from gauged to ungauged watersheds. Four regionalization models, two data-driven and two hydrological, were used for continuous daily streamflow estimation. Comparison of the individual models reveals that each of the four models performed well on a limited number of ungauged basins while none of them performed well for the entire 90 selected watersheds. The results obtained from the four models are evaluated and reported in a deterministic way by a model combination approach along with its uncertainty range consisting of 16 ensemble members. It is shown that a combined model of the four individual models performed well on all 90 watersheds and the ensemble range can account for the uncertainty of models. The combined model was more efficient and appeared more robust compared to the individual models. Furthermore, continuous ranked probability scores (CRPS) calculated for the ensemble model outputs indicate better performance compared to individual models and competitive with the combined model.

EDITOR A. Castellarin ASSOCIATE EDITOR G. Di Baldassarre     

Temporal dynamics of soil water balance components in a karst range in southeastern Spain: estimation of potential recharge

Abstract

This paper analyses the temporal dynamics of soil water balance components in a representative recharge area of the Sierra de Gádor (Almeria, southeastern Spain) in two hydrological years. Two approaches are used to estimate daily potential recharge (PR): Approach 1 based on deriving PR from the water balance as the difference between measurements of rainfall (P) and actual evapotranspiration (E) obtained by eddy covariance; and Approach 2 with PR obtained from the dynamic pattern of the soil moisture (θ) recorded at two depths in the site's thin soil (average 0.35 m thickess). For the hydrological year 2003/04, which was slightly drier than the 30-year average, E accounted for 64% of rainfall and occurred mainly in late spring and early summer. The PR estimated by Approach 1 was 181 ± 18 mm year^-1 (36% of rainfall), suggesting an effective groundwater recharge in the study area. In the unusually dry hydrological year 2004/05, E was about 215 mm year^-1, close to the annual rainfall input, and allowing very little (8 ± 12 mm year^-1) PR according to Approach 1. Estimation of PR based on Approach 2 resulted in PR rates lower than those found by Approach 1, because Approach 2 does not take into account the recharge that occurs through preferential flow pathways (cracks, joints and fissures) which were not monitored with the θ probes. Moreover, using Approach 2, the PR estimates differed widely depending on the time scale considered: with daily mean θ data, PR estimation was lower, especially in late spring, while θ data at 30 min resolution yielded a more reliable prediction of the fraction of total PR resulting from the downward movement of soil water by gravity.

Citation Cantón, Y., Villagarcía, L., Moro, M. J., Serrano-Ortíz, P., Were, A., Alcalá, F. J., Kowalski, A. S., Solé-Benet, A., Lázaro, R. & Domingo, F. (2010) Temporal dynamics of soil water balance components in a karst range in southeastern Spain: estimation of potential recharge. Hydrol. Sci. J. 55(5), 737–753.     

Derivation of a curve number and kinematic-wave based flood frequency distribution

Abstract

The physically-based flood frequency models use readily available rainfall data and catchment characteristics to derive the flood frequency distribution. In the present study, a new physically-based flood frequency distribution has been developed. This model uses bivariate exponential distribution for rainfall intensity and duration, and the Soil Conservation Service-Curve Number (SCS-CN) method for deriving the probability density function (pdf) of effective rainfall. The effective rainfall-runoff model is based on kinematic-wave theory. The results of application of this derived model to three Indian basins indicate that the model is a useful alternative for estimating flood flow quantiles at ungauged sites.