Probabilistic flood forecasting for a mountainous headwater catchment using a nonparametric stochastic dynamic approach

Abstract

Hydrological models are commonly used to perform real-time runoff forecasting for flood warning. Their application requires catchment characteristics and precipitation series that are not always available. An alternative approach is nonparametric modelling based only on runoff series. However, the following questions arise: Can nonparametric models show reliable forecasting? Can they perform as reliably as hydrological models? We performed probabilistic forecasting one, two and three hours ahead for a runoff series, with the aim of ascribing a probability density function to predicted discharge using time series analysis based on stochastic dynamics theory. The derived dynamic terms were compared to a hydrological model, LARSIM. Our procedure was able to forecast within 95% confidence interval 1-, 2- and 3-h ahead discharge probability functions with about 1.40 m³/s of range and relative errors (%) in the range [–30; 30]. The LARSIM model and the best nonparametric approaches gave similar results, but the range of relative errors was larger for the nonparametric approaches.

Editor D. Koutsoyiannis; Associate editor K. Hamed

Citation Costa, A.C., Bronstert, A. and Kneis, D., 2012. Probabilistic flood forecasting for a mountainous headwater catchment using a nonparametric stochastic dynamic approach. Hydrological Sciences Journal, 57 (1), 10–25.     

Flood season segmentation based on the probability change-point analysis technique

Abstract

The segmentation of flood seasons has both theoretical and practical importance in hydrological sciences and water resources management. The probability change-point analysis technique is applied to segmenting a defined flood season into a number of sub-seasons. Two alternative sampling methods, annual maximum and peaks-over-threshold, are used to construct the new flow series. The series is assumed to follow the binomial distribution and is analysed with the probability change-point analysis technique. A Monte Carlo experiment is designed to evaluate the performance of proposed flood season segmentation models. It is shown that the change-point based models for flood season segmentation can rationally partition a flood season into appropriate sub-seasons. China's new Three Gorges Reservoir, located on the upper Yangtze River, was selected as a case study since a hydrological station with observed flow data from 1882 to 2003 is located 40 km downstream of the dam. The flood season of the reservoir can be reasonably divided into three sub-seasons: the pre-flood season (1 June–2 July); the main flood season (3 July–10 September); and the post-flood season (11–30 September). The results of flood season segmentation and the characteristics of flood events are reasonable for this region.

Citation Liu, P., Guo, S., Xiong, L. & Chen, L. (2010) Flood season segmentation based on the probability change-point analysis technique. Hydrol. Sci. J. 55(4), 540–554.     

New fuzzy neural network–Markov model and application in mid- to long-term runoff forecast

ABSTRACT

In this paper, a mid- to long-term runoff forecast model is developed using an ideal point fuzzy neural network–Markov (NFNN-MKV) hybrid algorithm to improve the forecasting precision. Combining the advantages of the new fuzzy neural network and the Markov prediction model, this model can solve the problem of stationary or volatile strong random processes. Defined error statistics algorithms are used to evaluate the performance of models. A runoff prediction for the Si Quan Reservoir is made by utilizing the modelling method and the historical runoff data, with a comprehensive consideration of various runoff-impacting factors such as rainfall. Compared with the traditional fuzzy neural networks and Markov prediction models, the results show that the NFNN-MKV hybrid algorithm has good performance in faster convergence, better forecasting accuracy and significant improvement of neural network generalization. The absolute percentage error of the NFNN-MKV hybrid algorithm is less than 7.0%, MSE is less than 3.9, and qualification rate reaches 100%. For further comparison of the proposed model, the NFNN-MKV model is employed to estimate (training and testing for 120-month-ahead prediction) and predict river discharge for 156 months at Weijiabao on the Weihe River in China. Comparisons among the results of the NFNN-MKV model, the WNN model and the SVR model indicate that the NFNN-MKV model is able to significantly increase prediction accuracy.

Editor D. Koutsoyiannis; Associate editor Y. Gyasi-Agyei     

Recognition method for mid‐ to long‐term runoff forecasting factors based on global sensitivity analysis in the Nenjiang River Basin

Mid‐ to long‐term runoff forecasting is important to China. Forecasting based on physical causes has become the trend of this field, and recognition of key factors is central to recent development. Here, global sensitivity analysis based on back‐propagation arithmetic was used to calculate the sensitivity of up to 24 factors that affect runoff in the Nenjiang River Basin. The following five indices were found to be key factors for mid‐ to long‐term runoff forecasting during flood season: Tibetan Plateau B, index of the strength of the East Asian trough, index of the area of the northern hemisphere polar vortex, zonal circulation index over the Eurasian continent and index of the strength of the subtropical high over the western Pacific. The hydrological climate of the study area and the rainfall–runoff laws were then analysed in conjunction with its geographical position and topographic condition. The rationality of the results can be demonstrated from the positive analysis point of view. The results of this study provide a general method for selection of mid‐ to long‐term runoff forecasting factors based on physical causes. Copyright © 2012 John Wiley & Sons, Ltd.     

Prediction and modelling of rainfall–runoff during typhoon events using a physically-based and artificial neural network hybrid model

Abstract

The accurate prediction of hourly runoff discharge in a watershed during heavy rainfall events is of critical importance for flood control and management. This study predicts n-h-ahead runoff discharge in the Sandimen basin in southern Taiwan using a novel hybrid approach which combines a physically-based model (HEC-HMS) with an artificial neural network (ANN) model. Hourly runoff discharge data (1200 datasets) from seven heavy rainfall events were collected for the model calibration (training) and validation. Six statistical indicators (i.e. mean absolute error, root mean square error, coefficient of correlation, error of time to peak discharge, error of peak discharge and coefficient of efficiency) were employed to evaluate the performance. In comparison with the HEC-HMS model, the single ANN model, and the time series forecasting (ARMAX) model, the developed hybrid HEC-HMS–ANN model demonstrates improved accuracy in recursive n-h-ahead runoff discharge prediction, especially for peak flow discharge and time.     

Wavelet analysis-based projection pursuit autoregression model and its application in the runoff forecasting of Li Xiangjiang basin

ABSTRACT

The wavelet analysis technique was combined in this study with the projection pursuit autoregression (PPAR) model, and a new mid- and long-term runoff forecasting model, the wavelet analysis-based PPAR (PPAR-WA) is proposed, which realizes runoff forecasting from the perspective of the internal mechanism of a sequence. The runoff forecasting of the leading hydropower station in the Li Xianjiang cascade reservoirs in China was carried out to test the performance of the proposed model, and the accuracy and stability of the forecasting results were evaluated and analysed. The results show that the average relative error of the forecasting period can reach 9.6%, and the best relative error is less than 5% in some years. In addition, compared with PPAR, a back-propagation neural network and autoregression moving average model through three evaluation indexes, the results of PPAR-WA have higher accuracy and stronger stability. So, it has a certain value of popularization and application.     

Catchment-scale storm velocity: quantification,scale dependence and effect on flood response

Abstract

The concept of “catchment-scale storm velocity” quantifies the rate of storm motion up and down the basin accounting for the interaction between the rainfall space–time variability and the structure of the drainage network. It provides an assessment of the impact of storm motion on flood shape. We evaluate the catchment-scale storm velocity for the 29 August 2003 extreme storm that occurred on the 700 km²-wide Fella River basin in the eastern Italian Alps. The storm was characterized by the high rate of motion of convective cells across the basin. Analysis is carried out for a set of basins that range in area from 8 to 623 km² to: (a) determine velocity magnitudes for different sub-basins; (b) examine the relationship of velocity with basin scale and (c) assess the impact of storm motion on simulated flood response. Two spatially distributed hydrological models of varying degree of complexity in the representation of the runoff generation processes are used to evaluate the effects of the storm velocity on flood modelling and investigate model dependencies of the results. It is shown that catchment-scale storm velocity has a non-linear dependence on basin scale and generally exhibits rather moderate values, in spite of the strong kinematic characteristics of individual storm elements. Consistently with these observations and for both models, hydrological simulations show that storm motion has an almost negligible effect on the flood response modelling.

Editor Z.W. Kundzewicz; Guest editor R.J. Moore

Citation Nikolopoulos, E.I., Borga, M., Zoccatelli, D., and Anagnostou, E.N., 2014. Catchment-scale storm velocity: quantification, scale dependence and effect on flood response. Hydrological Sciences Journal, 59 (7), 1363–1376. http://dx.doi.org/10.1080/02626667.2014.923889     

Development of a thresholds approach for real‐time flash flood prediction in complex geomorphological river basins

Flash floods represent one of the deadliest and costliest natural disasters worldwide. The hydrological analysis of a flash flood event contributes in the understanding of the runoff creation process. This study presents the analysis of some flash flood events that took place in a complex geomorphological Mediterranean River basin. The objective of the present work is to develop the thresholds for a real‐time flash flood forecasting model in a complex geomorphological watershed, based on high‐frequency data from strategically located hydrological and meteorological telemetric stations. These stations provide hourly real‐time data which were used to determine hydrological and meteorological parameters. The main characteristics of various hydrographs specified in this study were the runoff coefficients, lag time, time to peak, and the maximum potential retention. The estimation of these hydrometeorological parameters provides the necessary information in order to successfully manage flash floods events. Especially, the time to peak is the most significant hydrological parameter that affects the response time of an oncoming flash flood event. A study of the above parameters is essential for the specification of thresholds which are related to the geomorphological characteristics of the river basin, the rainfall accumulation of an event, the rainfall intensity, the threshold runoff through karstic area, the season during which the rainfall takes place and the time intervals between the rainstorms that affect the soil moisture conditions. All these factors are combined into a real‐time‐threshold flash flood prediction model. Historical flash flood events at the downstream are also used for the validation of the model. An application of the proposed model is presented for the Koiliaris River basin in Crete, Greece. Copyright © 2011 John Wiley & Sons, Ltd.     

Challenges of hydrological analysis for water resource development in semi-arid mountainous regions: case study in Iran

Abstract

This study modified the BTOPMC (Block-wise TOPMODEL with the Muskingum-Cunge routing method) distributed hydrological model to make it applicable to semi-arid regions by introducing an adjustment coefficient for infiltration capacity of the soil surface, and then applied it to two catchments above the dams in the Karun River basin, located in semi-arid mountain ranges in Iran. The application results indicated that the introduced modification improved the model performance for simulating flood peaks generated by infiltration excess overland runoff at a daily time scale. The modified BTOPMC was found to fulfil the need to reproduce important signatures of basin hydrology for water resource development, such as annual runoff, seasonal runoff, low flows and flood flows. However, it was also very clear that effective model use was significantly constrained by the scarcity of ground-gauged precipitation data. Considerable efforts to improve the precipitation data acquisition should precede water resource development planning.

Editor D. Koutsoyiannis     

Response of runoff to climate change in the Wei River basin,China

Abstract

Climate change will likely have severe effects on water shortages, flood disasters and the deterioration of aquatic systems. In this study, the hydrological response to climate change was assessed in the Wei River basin (WRB), China. The statistical downscaling method (SDSM) was used to downscale regional climate change scenarios on the basis of the outputs of three general circulation models (GCMs) and two emissions scenarios. Driven by these scenarios, the Soil and Water Assessment Tool (SWAT) was set up, calibrated and validated to assess the impact of climate change on hydrological processes of the WRB. The results showed that the average annual runoff in the periods 2046–2065 and 2081–2100 would increase by 12.4% and 45%, respectively, relative to the baseline period 1961–2008. Low flows would be much lower, while high flows would be much higher, which means there would be more extreme events of droughts and floods. The results exhibited consistency in the spatial distribution of runoff change under most scenarios, with decreased runoff in the upstream regions, and increases in the mid- and lower reaches of the WRB.

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

A revisit of NRCS-CN inspired models coupled with RS and GIS for runoff estimation

The Natural Resource Conservation Service – Curve Number (NRCS-CN) methodology is a widely used tool for estimating surface runoff, which is of prime importance in hydrological engineering, agricultural planning and management, environmental impact assessment, flood forecasting, and others fields. This article reviews the methodology and associated hydrological models used for runoff estimation along with their advantages and limitations. Furthermore, discussion focuses on the potential applications of Remote Sensing (RS) and Geographical Information System (GIS) techniques for estimating hydrological variables, such as rainfall, soil moisture and CN required for the NRCS-CN methodology, as well as future research and opportunities for improved runoff estimation at the macro scale.

EDITOR D. Koutsoyiannis

ASSOCIATE EDITOR A. Efstratiadis     

Rainfall–runoff–inundation analysis of the 2010 Pakistan flood in the Kabul River basin

Abstract

Pakistan has suffered a devastating flood disaster in 2010. In the Kabul River basin (92 605 km²), large-scale riverine and flash floods caused destructive damage with more than 1100 casualties. This study analysed rainfall–runoff and inundation in the Kabul River basin with a newly developed model that simulates the processes of rainfall–runoff and inundation simultaneously based on two-dimensional diffusion wave equations. The simulation results showed a good agreement with an inundation map produced based on MODIS for large-scale riverine flooding. In addition, the simulation identified flash flood-affected areas, which were confirmed to be severely damaged based on a housing damage distribution map. Since the model is designed to be used even immediately after a disaster, it can be a useful tool for analysing large-scale flooding and to provide supplemental information to agencies for relief operations.

Editor Z.W. Kundzewicz

Citation Sayama, T., Ozawa, G., Kawakami, T., Nabesaka, S. and Fukami, K., 2012. Rainfall–runoff–inundation analysis of the 2010 Pakistan flood in the Kabul River basin. Hydrological Sciences Journal, 57 (2), 298–312.     

Hydrological simulation of the Betwa River basin (India) using the SWAT model

A seasonal water budget analysis was carried out to quantify various components of the hydrological cycle using the Soil and Water Assessment Tool (SWAT) model for the Betwa River basin (43?500 km²) in central India. The model results were satisfactory in calibration and validation. The seasonal water budget analysis showed that about 90% of annual rainfall and 97% of annual runoff occurred in the monsoon season. A seasonal linear trend analysis was carried out to detect trends in the water balance components of the basin for the period 1973–2001. In the monsoon season, an increasing trend in rainfall and a decreasing trend in ET were observed; this resulted in an increasing trend in groundwater storage and surface runoff. The winter season followed almost the same pattern. A decreasing trend was observed in summer season rainfall. The study evokes the need for conservation structures in the study area to reduce monsoon runoff and conserve it for basin requirements in water-scarce seasons.

EDITOR Z.W. Kundzewicz

ASSOCIATE EDITOR F. Hattermann     

Probabilistic calibration of a distributed hydrological model for flood forecasting

Abstract

The complexity of distributed hydrological models has led to improvements in calibration methodologies in recent years. There are various manual, automatic and hybrid methods of calibration. Most use a single objective function to calculate estimation errors. The use of multi-objective calibration improves results, since different aspects of the hydrograph may be considered simultaneously. However, the uncertainty of estimates from a hydrological model can only be taken into account by using a probabilistic approach. This paper presents a calibration method of probabilistic nature, based on the determination of probability functions that best characterize different parameters of the model. The method was applied to the Real-time Interactive Basin Simulator (RIBS) distributed hydrological model using the Manzanares River basin in Spain as a case study. The proposed method allows us to consider the uncertainty in the model estimates by obtaining the probability distributions of flows in the flood hydrograph.

Citation Mediero, L., Garrote, L. & Martín-Carrasco, F. J. (2011) Probabilistic calibration of a distributed hydrological model for flood forecasting. Hydrol. Sci. J. 56(7), 1129–1149.     

Influence of changes in river system structure on hydrological processes in Taihu Basin,China

ABSTRACT

With the rapid economic development and urbanization in Taihu Basin (eastern China), the river system has decayed and the connectivity of rivers and lakes has weakened, resulting in frequent floods. The impact of changes in river system structure on hydrological processes in the plain river network area was analysed against a background of urbanization. An indicator system was built to describe the quantitative, morphological and spatial structure of the river system. Analysis of the change in annual average and extreme water levels revealed the influencing mechanism of the changes in river system structure on the hydrological processes. The results indicate a decreasing tendency in the density of the river system in the study area, with a reduction in water surface ratio by about 20% in the past 50 years. Since the 1960s, the maximum and annual average water levels have increased. The degree of change in the mean monthly, annual lowest and annual highest water levels was great, with that in the non-flood season being higher than in the flood season. The decrease in the number of rivers directly reduced the storage and adjustable capacity of the basin.     

UTILIZATION OF THE RESULTS FROM REPRESENTATIVE AND EXPERIMENTAL BASINS WITH A VIEW TO THE MANAGEMENT OF WATER RESOURCES / Utilisation des résultats obtenus sur les bassins représentatifs et expérimentaux en vue de l'aménagement des ressources en eau

Abstract

The management of water resources requires knowledge of the spatial and temporal distribution of surface and groundwater resources, and an assessment of the influence of man on the hydrological regime.

For small water courses regional estimates can be made from representative basins which offer guidelines (1) for the computation of mean annual flow and in some cases for the determination of the statistical distribution of the annual flow; (2) for the computation of the 10-year flood maximum discharge and volume.

An example concerning the tropical African Sahel is given. From a general study of the daily precipitation, a simple rainfall/runoff model used on a daily basis and calibrated on data from representative basins, and also the direct comparison of results from 55 representative basins, statistical distribution curves were established for annual runoff based on mean annual precipitation and the geomorphological characteristics of the basins.

Another example concerning tropical Africa west of Congo presents a methodology for the computation of the 10-year flood (maximum discharge and volume).

The systematic study of 60 representative basins makes it possible to plot the runoff coefficient R/P as a function of basin climate, mean slope and soil permeability. Other curves are used to determine the time of rise and the base time of the hydrograph as a function of the basin area and the mean slope.

The experimental basin is a good tool for the assessment of the influence of man on hydrological parameters. An example shows the influence of land use on the regression between annual precipitation and annual runoff.     

On-line estimation of unit hydrographs using the wavelet-based LMS algorithm / Estimation en ligne des hydrogrammes unitaires grâce à l'algorithme des moindres carrés moyens à base d'ondelettes

Abstract

This study applies the discrete wavelet transform (DWT) to decompose the unit hydrograph, thereby generating parsimonious reparameterizations of the unit hydrograph. A model compression method is then employed to significantly compress the unit hydrograph requiring that fewer coefficients be estimated. Moreover, a wavelet-based linearly constrained least mean squares (WLCLMS) algorithm is also used to estimate on-line the wavelet coefficients of the unit hydrograph. The updated wavelet coefficients of the unit hydrograph, convoluted with effective rainfall input in the wavelet domain, allow for accurate prediction of one-step-ahead runoff in the time domain. The proposed approach allows the unit hydrographs to vary in time and accurately predicts runoff from a basin in Taiwan, thus making it highly promising for flood forecasting.     

Effect of modelling scale on the assessment of climate change impact on river runoff

Abstract

The effect of using two distributed hydrological models with different degrees of spatial aggregation on the assessment of climate change impact on river runoff was investigated. Analyses were conducted in the Narew River basin situated in northeast Poland using a global hydrological model (WaterGAP) and a catchment-scale hydrological model (SWAT). Climate change was represented in both models by projected changes in monthly temperature and precipitation between the period 2040–2069 and the baseline period, resulting from two general circulation models: IPSL-CM4 and MIROC3.2, both coupled with the SRES A2 emissions scenario. The degree of consistency between the global and the catchment model was very high for mean annual runoff, and medium for indicators of high and low runoff. It was observed that SWAT generally suggests changes of larger magnitude than WaterGAP for both climate models, but SWAT and WaterGAP were consistent as regards the direction of change in monthly runoff. The results indicate that a global model can be used in Central and Eastern European lowlands to identify hot-spots where a catchment-scale model should be applied to evaluate, e.g. the effectiveness of management options.

Editor D. Koutsoyiannis; Associate editor F.F. Hattermann

Citation Piniewski, M., Voss, F., Bärlund, I., Okruszko, T., and Kundzewicz. Z.W., 2013. Effect of modelling scale on the assessment of climate change impact on river runoff. Hydrological Sciences Journal, 58 (4), 737–754.     

Terrestrial hydrological responses to precipitation variability in Southwest China with emphasis on drought

Abstract

This study investigates the terrestrial hydrological processes during a dry climate period in Southwest China by analysing the frequency-dependent runoff and soil moisture responses to precipitation variability. Two headwater sub-basins, the Nanpan and Guihe basins of the West River (Xijiang), are studied to compare and contrast the terrestrial responses. The variable infiltration capacity (VIC) model is used to simulate the hydrological processes. Using wavelets, the relationships between observed precipitation and simulated runoff/soil moisture are expressed quantitatively. The results indicate that: (a) the Guihe basin shows a greater degree of high-frequency runoff variability in response to regional precipitation; and (b) the Nanpan basin exhibits less capability in accommodating/smoothing extreme precipitation deficits, reflected in terms of both higher scale-averaged (for 3–6 months) and time-averaged (for the year 1963) wavelet power of soil moisture.

Editor Z.W. Kundzewicz; Associate editor C.-Y. Xu

Citation Niu, J. and Chen, J., 2013. Terrestrial hydrological responses to precipitation variability in Southwest China with emphasis on drought. Hydrological Sciences Journal, 59 (2), 325–335.     

Changes in flood characteristics and the flood driving mechanism in the mountainous Haihe River Basin,China

ABSTRACT

Recently, the land surface in the Haihe River basin has changed, influencing the flood processes in the basin. To quantify this impact, seven typical sub-catchments were selected from different hydrological regions of the Haihe River basin for study. The non-parametric Mann-Kendall test was used to analyse for trends, and the non-parametric Pettitt test was adopted to detect any change point in the flood time series. Then, a hydrological model was established to simulate the effects of each potential driving factor on flood peak and volume. It was shown that flood peak and volume time series had decreased significantly, and the change point was around the year 1980. Groundwater depletion was not the main contribution to flood peak (FP) and volume (FV) decrease. In the Shifokou, Mubi and Lengkou sub-catchments, small hydraulic structures are the main driving factors for FP and FV decreasing. In the Xitaiyu, Daomaguan and Fuping sub-catchments, both land-use change and hydraulic structures are the main driving factors. The decreasing percentage decreases with the increase of the flood magnitude. The results provide valuable information for flood simulation and control in the Haihe River basin.