Flood Estimation Research Articles

Stochastic simulation of streamflow and spatial extremes: a continuous, wavelet-based approach

Abstract. Stochastically generated streamflow time series are used for various water management and hazard estimation applications. They provide realizations of plausible but as yet unobserved streamflow time series with the same temporal and distributional characteristics as the observed data. However, the representation of non-stationarities and spatial dependence among sites remains a challenge in stochastic modeling. We investigate whether the use of frequency-domain instead of time-domain models allows for the joint simulation of realistic, continuous streamflow time series at daily resolution and spatial extremes at multiple sites. To do so, we propose the stochastic simulation approach called Phase Randomization Simulation using wavelets (PRSim.wave) which combines an empirical spatio-temporal model based on the wavelet transform and phase randomization with the flexible four-parameter kappa distribution. The approach consists of five steps: (1) derivation of random phases, (2) fitting of the kappa distribution, (3) wavelet transform, (4) inverse wavelet transform, and (5) transformation to kappa distribution. We apply and evaluate PRSim.wave on a large set of 671 catchments in the contiguous United States. We show that this approach allows for the generation of realistic time series at multiple sites exhibiting short- and long-range dependence, non-stationarities, and unobserved extreme events. Our evaluation results strongly suggest that the flexible, continuous simulation approach is potentially valuable for a diverse range of water management applications where the reproduction of spatial dependencies is of interest. Examples include the development of regional water management plans, the estimation of regional flood or drought risk, or the estimation of regional hydropower potential. Highlights. Stochastic simulation of continuous streamflow time series using an empirical, wavelet-based, spatio-temporal model in combination with the parametric kappa distribution. Generation of stochastic time series at multiple sites showing temporal short- and long-range dependence, non-stationarities, and spatial dependence in extreme events. Implementation of PRSim.wave in R package PRSim: Stochastic Simulation of Streamflow Time Series using Phase Randomization.

On future flood magnitudes and estimation uncertainty across 151 catchments in mainland China

AbstractAs atmospheric moisture holding capacity is positively dependent on temperatures, a large intensification of precipitation extremes is projected under foreseeable climate warming. Flooding that is mainly attributed to extreme storms usually accounts for an ambitious target in weather‐related hazard mitigation over China. Previous works seldom focused on flooding evolution patterns under climate change at a national scale, and fewer flooding projections considered the estimation uncertainty sourced from limited samples. This study systematically projected changes in flood quantiles based on annual maximum series and seasonality and also evaluated the variations of sampling uncertainty for 151 catchments over mainland China under the emission scenario of representative concentration pathway (RCP) 8.5. In order to project future streamflow series, the bias‐corrected outputs of six global climate models (GCMs) were input into a best‐performing hydrological model, which was selected from four calibrated hydrological models based on the KGE criteria. The Pearson type‐III (P‐III) distribution and L‐moments (L‐M) method were employed to derive the flood quantiles for different return periods during historical (1961–2005) and future (2056–2100) periods, and the bootstrapping method was applied to estimate the sampling uncertainty. A regression trend method was used to track the variations of flood seasonality in the context of climate warming. Our results project earlier flood timing and larger flood quantiles for most catchments in future period than those in the historical period, despite being accompanied by substantial spatial variations. We also project that the sampling uncertainty in estimating flood quantiles is increased in a warming future. Many catchments are exposed to dramatic changes in both flood quantile and estimation uncertainty by over 50%, while only a few catchments are projected to have decreasing flood risks. These results suggest an urgent need to improve the functionality of early warning systems and increase societal resilience to warming climates over China.

Comparison of two approaches for an estimation of the mean annual flood at ungauged sites in Slovakia

AbstractRegional flood frequency analysis is considered to be an important and popular method for estimating different hydrological variables at ungauged sites. The estimation of the index flood is the essential problem when this method is applied. The objective of the study is a comparison of the estimation of the mean annual flood (or index flood) by using two approaches based on the ‘so-called’ index flood method and top-kriging. The concept behind these methods permits estimating the mean annual flood at ungauged locations using information taken from gauged sites located within the same homogeneous pooling groups. The study area comprises 104 gauging stations on the whole territory of Slovakia. The observation period of the annual maximum discharges of the selected stations was from 1961-2010. The identification of the homogeneous pooling group was performed using a non-hierarchical k-means clustering algorithm. The optimal number of clusters is determined by the Silhouette method. As a result, eight homogeneous pooling group clusters were identified. Finally, the results of the estimated mean annual floods using the index flood method and top-kriging were compared with the observed data. Top-kriging provided better results than the classical index flood method for estimating the mean annual flood at ungauged sites.

Some best‐fit probability distributions for at‐site flood frequency analysis of the Ume River

AbstractAt‐site flood frequency analysis is a direct method of flood estimation at a given site. The choice of an appropriate probability distribution and parameter estimation method plays a vital role in at‐site frequency analysis. In the current article, flood frequency analysis is carried out at five gauging sites of the Ume River in Sweden. Generalised extreme value, three‐parameter log‐normal, generalised logistic and Gumbel distributions are fitted to the annual maximum peak flow data. The L‐moment and the maximum likelihood methods are used to estimate the parameters of the distributions. Based on different goodness‐of‐fit tests and accuracy measures, the three‐parameter log‐normal distribution has been identified as the best‐fitted distribution by using the L‐moments method of estimation for gauging sites Harrsele Krv, Gardiken and Överuman Nedre. The generalised extreme value distribution with the L‐moments estimation provided the best fit to maximum annual streamflow at gauging sites Solberg and Stornorrfors Krv. Finally, the best‐fitted distribution for each gauging site is used to predict the maximum flow of water for return periods of 5, 10, 25, 50, 100, 200, 500, and 1000 years.

Urban flooding in Britain: an approach to comparing ancient and contemporary flood exposure

Using modified UK Environment Agency Flood Estimation Handbook techniques, inundation extent and likely flood hydrographs for 0.1% probability annual return periods are compared for twelve Roman town sites in the UK, both at the present day and for simulated Roman catchment conditions. Eight of the study sites appear to have suffered minimal urban flood liability as occupied in the Roman period. The exceptions were Canterbury, York, Leicester, and Chichester. It is reasonable to expect flood characteristics to have changed subsequently in response to transformations in catchment land use, urban expansion, wetland reclamation, and floodway engineering. However, modelling results suggest limited differences in flood flows attributable to such factors. Greater present-day urban damage liability essentially results from floodplain urban extension. There are also contrasts between sites: those Roman towns lying on floodplains themselves, rather than on slightly elevated terraces (Canterbury, Chichester), are dominated by groundwater regimes with attenuated flood peaks. Taken together, these results suggest some Roman awareness of the actualities of urban flood liability at the time. Site sensitivity has not been carried forward as urban expansion has flourished, especially from the nineteenth century with suburban and industrial expansion. The straightforward mapping approach here suggested should in future take account of multiple century-scale hydroclimatic changes, morphological river channel and floodplain transformations over similar time periods, and on-going improvements to inundation modelling.

Evaluation of Design Storms and Critical Rainfall Durations for Flood Prediction in Partially Urbanized Catchments

This study investigates and compares several design storms for flood estimation in partially urbanized catchments. Six different design storms were considered: Euler II, alternating block method, average variability method, Huff’s curves, and uniform rainfall. Additionally, two extreme historical storms were included for comparison. A small, ungauged, partially urbanized catchment in Novigrad (Croatia) was chosen as a study area to account for the infiltration impact on the rainfall-runoff process. The performance of each design storm was assessed based on the flood modeling results, namely the water depth, water velocity, flow rate, and overall flood extent. Furthermore, several rainfall durations were considered to identify a critical scenario. The excess rainfall was computed using the Soil Conservation Service’s Curve Number method, and two-dimensional flooding simulations were performed by the HEC-RAS model. The results confirmed that the choice of the design storm and the rainfall duration has a significant impact on the flood modeling results. Overall, design storms constructed only from IDF curves overestimated flooding in comparison to historical events, whereas design storms derived from the analysis of observed temporal patterns matched or slightly underestimated the flooding results. Of the six considered design storms, the average variability method showed the closest agreement with historical storms.

Flood Estimation for SMART Control Operation Using Integrated Radar Rainfall Input with the HEC-HMS Model

Accurate estimates of intense rainfall that induce flash floods in urban areas are necessary for flood hazard preparedness. The city of Kuala Lumpur is frequently hit by flash floods after prolonged heavy storms, causing substantial damage to property and infrastructure, and disruptions to the socioeconomic activities of urbanites. The flood mitigation measures that have been implemented include the 2007 construction of the Stormwater Management and Road Tunnel (SMART), which diverts the flood water coming out of the Upper Klang Ampang catchment from entering the city prime areas. This study developed an integrated hydrological model of the catchment with input from radar rainfall to estimate the flood volume threshold value for SMART operation. The hydrologic and hydraulic modeling were performed using HEC-HMS with the HEC-GeoHMS tool to extract the hydrologic parameter information using GIS as input data for the catchment model. A radar processing system named RAINRATE AUTO V2 was developed to efficiently process raw radar data from the Subang radar and produce calibrated and gridded rainfall to the HEC-HMS flood estimation model for the Upper Klang Ampang urban catchment area. The results show promising performance regarding the use of radar rainfall, and there was an acceptable percent error in the peak discharge simulations. The advanced integrated system can be applied in managing flood risks at the catchment scale by efficiently estimating incoming flood events in the future.

A review of flow estimation by runoff routing in Australia – and the way forward

ABSTRACT Flood hydrograph estimation in Australia is mostly undertakenby a class of models known as runoff routing models. These models have in common the sub-division of the catchment into a number of sub-catchments, with the application of excess rainfall to each sub-catchment and the routing through a series of nonlinear storages representing the channel flow through the catchment. The first Australian runoff routing model was developed in the 1960s, and there have been numerous models developed that contain the same basic structure, with enhancements. With the release of Australian Rainfall & Runoff there were significant changes in the way design floods are estimated in Australia, with flood estimation by runoff routing beingmodified to include a joint probability approach rather than a design flood approach, so that the variability and interaction of flood-producing factors are better allowed for. This paper reviews the development of runoff routing within Australia, from the original 1960s model to joint probability, and identifies issues associated with the models, including self-consistency and the limitation on the runoff processes that can be modelled. The required features of a model that address the limitations of current models are described.

Regional analysis of PROQ transforms for flood frequency estimation based on GRADEX principles

ABSTRACT The PROQ transform which converts rainfall P to runoff RO, then factored to produce peak discharge Q, can be used for regional design flood estimation. SPEED, a French method based on GRADEX principles is a PROQ transform. 1 in 100 annual exceedance probability discharges was estimated using SPEED for 40 Australian non-urban catchments. Inputs are catchment area and areal design rainfall depth. The SPEED transform involves three constant parameters: scaling factor a, non-linearity b and retention L. SPEED was found to be simple and effective (Nash-Sutcliffe E = 0.82). A local version of SPEED produced a similar performance (E = 0.74). A general form of PROQ was developed to explain similarities with other models such as the Probabilistic Rational Method and to develop the local SPEED transform. Gauge sites can be grouped based on a and L ‘bins’, using site-based mean values of these parameters. A PROQ model using two a bins and two L bins significantly enhanced predictive accuracy (E = 0.92).

An evaluation of a multi-day rainfall – runoff volume – peak discharge transform for flood frequency estimation

ABSTRACT A new method to estimate design discharge quantiles is described based on converting multi-day rainfall P to flood event runoff RO, factored to generate discharge Q. The so-called PROQ transfer function is founded on simple flood volume-peak and GRADEX rainfall-runoff tanh relationships. Performance testing of PROQ, in both at-site and regional design flood contexts up to 1 in 100 annual exceedance probability, was made using south east Queensland streamgauge data. A statistical comparison against proven methods showed that the PROQ transform has significant potential as an alternative for design flood estimation. An example of how PROQ can be used within a design flood framework and recommendations for further enhancement are provided. Abbreviations: AEP: Annual exceedance probability; AMS: Annual maximum series, extracted from the flood record at a gauge site; ANOVA: Analysis of variance; ARR: Australian Rainfall and Runoff guidelines; A-S: At-site. Describes a set of methods to estimate design flood quantiles by statistical analysis of the flood record at an individual gauge site; E: Nash–Sutcliffe efficiency; FFA: Flood frequency analysis; G-B: Multiple Grubbs-Beck test recommended by ARR 2019 for low flow censoring. Used for at-site flood frequency analysis; GEV: General extreme value probability distribution; GRADEX: Gradient of extreme values. Design flood probability concept originating in France based on parallelism of rainfall and runoff quantile curves; L: Retention of rainfall within the catchment during flood event, expressed as a depth; LP3: Log Pearson 3 probability distribution; P: Rainfall depth; PRM: Probabilistic Rational Method. An ARR method for ungauged, undeveloped Australian catchments superseded in 2016; PROQ: Transfer function based on converting P to RO and then factoring RO to estimate Q; PW: Palmen and Weeks. Regional method for ungauged, undeveloped Queensland catchments developed by Palmen and Weeks (2011); R: Retention curve number. Used in probabilistic charting of design floods based on PROQ; RE: Absolute relative error; REG: Regional. Describes a set of methods to estimate design flood quantiles using information obtained from at-site analyses of several representative catchments within a region; RO: Flood event runoff depth; SR30: Strike rate of estimates within ±30% tolerance.

Non-Stationary Flood Frequency Analysis Using Cubic B-Spline-Based GAMLSS Model

Under changing environments, the most widely used non-stationary flood frequency analysis (NFFA) method is the generalized additive models for location, scale and shape (GAMLSS) model. However, the model structure of the GAMLSS model is relatively complex due to the large number of statistical parameters, and the relationship between statistical parameters and covariates is assumed to be unchanged in future, which may be unreasonable. In recent years, nonparametric methods have received increasing attention in the field of NFFA. Among them, the linear quantile regression (QR-L) model and the non-linear quantile regression model of cubic B-spline (QR-CB) have been introduced into NFFA studies because they do not need to determine statistical parameters and consider the relationship between statistical parameters and covariates. However, these two quantile regression models have difficulties in estimating non-stationary design flood, since the trend of the established model must be extrapolated infinitely to estimate design flood. Besides, the number of available observations becomes scarcer when estimating design values corresponding to higher return periods, leading to unreasonable and inaccurate design values. In this study, we attempt to propose a cubic B-spline-based GAMLSS model (GAMLSS-CB) for NFFA. In the GAMLSS-CB model, the relationship between statistical parameters and covariates is fitted by the cubic B-spline under the GAMLSS model framework. We also compare the performance of different non-stationary models, namely the QR-L, QR-CB, and GAMLSS-CB models. Finally, based on the optimal non-stationary model, the non-stationary design flood values are estimated using the average design life level method (ADLL). The annual maximum flood series of four stations in the Weihe River basin and the Pearl River basin are taken as examples. The results show that the GAMLSS-CB model displays the best model performance compared with the QR-L and QR-CB models. Moreover, it is feasible to estimate design flood values based on the GAMLSS-CB model using the ADLL method, while the estimation of design flood based on the quantile regression model requires further studies.

A Hydro-Informatic Approach For Estimation Of Design Flash-Flood In Bargi Dam Cross-Section Of Narmada River, India

Estimation of design flood is imperative for hydraulic designs of spillways and various other water resources development projects as well as very essential for flood risk assessment. The objective of the present study is to apply Geographical Information System (GIS) supported hydro informatics approach for estimation of design flash-flood in Bargi dam cross-section. A criterion used for estimation of design flash flood is validated by central water commission (CWC). A hydrologic modelling software (HEC-GeoHMS) is used for the delineation of basin characterises for simulation of the precipitation-runoff process of the dendritic basin system. The SUH (Synthetic Unit Hydrograph) and flood hydrographs for 25, 50 and 100 year return periods are computed along with time distribution curve which can be used to derive the time distribution co-efficient of storm rainfall in the sub-basins for the rainstorm of any duration. It is observed in this research that the peak characteristics of the design flash-flood are more perceptive to the various design storm pattern. It is demonstrated that flood hydrographs are important in flood-risk management. The results attained exhibit the capability of the flood hydrograph to describe the effects of different hydraulic systems.

Estimating the UK Index Flood: an Improved Spatial Flooding Analysis

Flooding is one of the major natural hazards in the UK. Accurate flood estimation at ungauged catchment is an important component to understand and mitigate flood hazards, but still a difficult issue. This study therefore attempts to explore and improve an index flood estimation model, known as the FEH-QMED model, popular in the UK. It was developed under the assumption that the index flood of QMED, i.e., the median of the set of annual maximum (AMAX) flood data, standing for a flooding level of 2-year return period, can be explained by catchment descriptors. In this study, two fundamentals are empirically explored, including assessing reliability of the nonlinear functional impacts of the catchment descriptors on the logarithmic transformation of QMED, specified by the FEH-QMED model, and the potential to improve the model for more accurate index flood estimation, based on the flooding data of 586 gauged stations across the UK. Through a spatial additive regression analysis, we empirically find that the nonlinear impacts of the catchment descriptors in an updated FEH-QMED model appear reliable. However, spatial correlation tests including Moran’s I and Lagrange multiplier tests show that strong spatial dependence exists in the residuals of, but was not fully taken into account by, the QMED type models. We have therefore empirically established new spatial index flood estimation models by proposing spatial autoregressive models to model the impacts of the neighboring sites. Cross-validation assessments demonstrate that the suggested spatial error-based index flood model outperforms the updated FEH-QMED model with a significant improvement, which is robust in the sense of different error measures, say by a reduction of 13.8% of the mean squared error of prediction, for the UK index flood estimation.

Optimization of dam's spillway design under climate change conditions

AbstractThe present research introduces a model to find the best shape of a dam's spillway under climate change impacts, considering a benchmark problem (i.e., Ute Dam's labyrinth spillway in the Canadian River watershed, New Mexico, USA). A spillway design is based not only on historical data but also on the future hydrologic events. Climate variables were predicted for the years 2021–2050 based on three representative concentration pathway (RCP2.6, RCP4.5, and RCP8.5) scenarios of the general circulation model from the fifth phase of the coupled model intercomparison project (CMIP5) using the statistical downscaling model. Streamflow at the USGS 07226500 streamgage was simulated by a rainfall–runoff model with predicted data. Instantaneous peak flow was estimated using an empirical method. Flood frequency analysis was used for the estimation of the design flood. The shuffled frog-leaping algorithm (SFLA) is used to optimize a labyrinth spillway design and its results were compared with two other nature-inspired algorithms: invasive weed optimization (IWO) and cuckoo search (CS). The spillway was optimized once with the actual design flood (16,143 m3/s) and again with the design flood under climate change (12,250 m3/s). Results revealed that optimization with realistic design flood reduced the concrete volume of the spillway by 37% and under climate change by 43% using the SFLA.

New hourly extreme precipitation regions and regional annual probability estimates for the UK

AbstractRecent flooding related to extreme precipitation in the UK has highlighted the importance of better understanding these events. Many studies have quantified annual exceedance probabilities (or return periods) for UK extreme daily precipitation using fixed regions (e.g., HadUKP) and region of interest (ROI) (e.g., Flood Estimation Handbook) approaches, although fewer have evaluated short‐duration events, which are important for flash flooding. Existing UK extreme precipitation regions are based on daily datasets which have different characteristics compared to sub‐daily extremes, and their application to quantify short‐duration extremes may therefore be inappropriate. We use a recently available, quality‐controlled hourly precipitation dataset for the UK from 1992 to 2014 to derive various extreme precipitation indices (e.g., annual maxima, 0.99 quantile) which are combined with additional climatological variables (e.g., temperature), geographical characteristics (e.g., latitude), and weather patterns (WPs) to characterize the UK hourly extreme precipitation climatology and to define five new hourly extreme regions. These regions fulfil regional homogeneity and discordancy statistical measures, and reflect the dynamical processes associated with the weather pattern categorisation defined over the UK and surrounding European area. Thereafter, we use regional frequency analysis (RFA) to fit generalized extreme value (GEV) and generalized Pareto (GP) distributions to 1 hr annual maxima (AMAX) and 0.99 quantile (Q99) precipitation, respectively, to calculate regional annual probability estimates (AEP) for 20%, 10%, and 2% (i.e., 5‐, 10‐, and 50‐year return periods). The new regions capture the spatial variation of hourly precipitation across the UK. Furthermore, the AEP estimates using both distributions are similar for each region. Finally, the WPs associated with the frequency and intensity of the most extreme hourly precipitation accumulations are not identical to results reported by others for daily precipitation.

Stochastic seasonal rainfall simulation model for Irbid region, Northern Jordan

ABSTRACT A stochastic hourly simulation model is developed for the synthesis of the rainfall pattern in the northern part of Jordan. The generation of synthetic rainfall data is an attempt to provide longer data sequences. The simulation model is based on statistical properties of rainfall data for three stations in the Northern region of Jordan for the period 1975–2004. The mean and variances of important rainfall characteristics were reasonably well preserved in the synthesized data. The simulated characteristics include the duration, total depth and depth at 50% duration and mass curves of the storms. The intensity-duration-frequency curves generated by this model compared well with locally available curves. The resulting IDF curves based on the stochastically generated storm sequences are usually used for flood estimation in urban/rural watersheds. Using the resulting IDF curves is highly recommended for rigorous, efficient and safe design of hydraulic structures and flood protection works.

Brief communication: Hurricane Dorian: automated near-real-time mapping of the “unprecedented” flooding in the Bahamas using synthetic aperture radar

Abstract. In this communication, we present application of the automated near-real-time (NRT) system called RAdar-Produced Inundation Diary (RAPID) to European Space Agency Sentinel-1 synthetic aperture radar (SAR) images to produce flooding maps for Hurricane Dorian in the northern Bahamas. RAPID maps, released 2 d after the event, show that coastal flooding in the Bahamas reached areas located more than 10 km inland, covering more than 3000 km2 of continental area. RAPID flood estimates from subsequent SAR images show the recession of the flood across the islands and present high agreement scores when compared to Copernicus Emergency Management Service (Copernicus EMS) estimates.

Consideration of uncertainty in sea level rise in Australia's most exposed estuary: A discussion on allowances under different epistemic uncertainties

Water surface level exceedances and extreme flooding for Australia's most exposed estuary, Swansea Channel, was estimated using sea level rise epistemic uncertainty with symmetric and asymmetric shapes. Flood estimates were obtained using a simple hydraulic model what was applied within a statistical simulation, included atmospheric and oceanic forcing and their aleatory uncertainties. These predictions are then used to discuss vertical allowances for coastal planning. There are different allowance approaches to include sea level rise epistemic uncertainty ranging from asset independent (allowance includes a particular degree of sea level rise uncertainty) to asset specific approaches (allowance that ensures frequency of inundation does not increase). Regardless of the allowance approach, the sea level rise uncertainty distribution and its shape are expected to influence these allowances. The impact on flood estimates and derived allowances from symmetric and asymmetric uncertainties includes expected features of increasing water level variations and allowances in both time and in space (Swansea Channel becomes more hydraulically efficient as its depth increases). Using asymmetrical shaped uncertainty for coastal planning constrained by low risk tolerance would, for example, increase the 1% annual exceedance probability flood elevation that includes 99% of sea level rise uncertainty by ca 0.8 m along Swansea Channel when compared to symmetric uncertainties. If the future sea level rise uncertainty is indeed asymmetric then application of allowances based on the symmetrically shaped distributions underestimate possibilities of future extreme water levels and may be exceeded earlier than anticipated. Annual exceedance duration estimates indicate that in 2120, epistemic (sea level rise) uncertainty is greater than aleatory (weather related flooding) variational along Swansea Channel.

An Assessment of Continuous Modeling for Robust Design Flood Estimation in Urban Environments

Catchment management is a complex task that, over the past decade, has become increasingly important to the community. This is particularly the case for urban environments. Of the many catchment management issues, estimation of the magnitude and likelihood of flood events is one that remains an issue. Data is an essential component of any approach for estimation of the magnitude and likelihood of design flood characteristics. This data can be obtained from both catchment monitoring and catchment modelling with these data sources being complementary rather than competitive. However, the absence of monitored data in urban environments has resulted in the data being obtained predominantly from the use of catchment modelling. A number of alternative approaches for catchment modelling have been developed; these approaches can be categorised as either single event or continuous models. The philosophical basis behind the use of a continuous modelling approach is the concept that the model predictions will replicate the data that would have been recorded if catchment monitoring were to be undertaken at that location and for the modelled catchment conditions. When using this philosophy, a modeller must determine when the predicted data suitably replicates the true data. Presented herein is an analysis of continuous and event modelling undertaken for design flood estimation in an urban catchment located in Sydney, Australia where monitored data is available to assess the utility of the catchment model. It will be shown that frequency analysis of the predicted flows from the continuous model more closely resemble the frequency analysis of the recorded data.

Assessing the applicability of conceptual hydrological models for design flood estimation in small-scale watersheds of northern China

The estimation of design flood is mainly focused on the peak flow and the volume, ignoring the underlying surface factor and flood rising and falling process. Three basic conceptual hydrological models, XAJ, TANK and SCS, are selected and applied for design flood estimation in two small-scale basins of northern China. Model parameter calibration is based on both the optimization algorithm SCE-UA and artificial adjusting, by using a combined objecting function of flood peak, volume and process. Each model singles out a set of optimal parameters as input to simulate the design flood process. The simulation results are compared with original engineering design standards and instantaneous unit hydrograph method. The results show that the XAJ model has the best performance in simulating the 100-year design flood in study basins. The SCS model also gives acceptable results, but the TANK model on the other hand in an underestimated flood peak with a prolonged recession period, which is not likely to be applicable. This study is to test the applicability of the conceptual hydrological models in simulating the design flood process in small-scale watersheds and should be a supplement to the traditional methods and further deliberation to a ungauged basin. Starting from the most basic models with simple structures, it is hoped that the methodology can be transferred to more complicated and physically based models with more realistic description of the rainfall-runoff transformation mechanism and dynamic mechanism for climate change.