Precipitation patterns and associated hydrological extremes in the Yangtze River basin,China, using TRMM/PR data and EOF analysis

Abstract

A decadal-scale study to retrieve the spatio-temporal precipitation patterns of the Yangtze River basin, China, using the Tropical Rain Mapping Mission, Precipitation Radar (TRMM/PR) data is presented. The empirical orthogonal function (EOF) based on monthly TRMM/PR data extracts several leading precipitation patterns, which are largely connected with physical implications at the basin scale. With the aid of gauge station data, the amplitudes of major principal components (PCs) were used to examine the generic relationships between precipitation variations and hydrological extremes (e.g. floods and droughts) during summer seasons over the past decade. The emergence of such major precipitation patterns clearly reveals the possible linkages with hydrological processes, and the oscillations in relation to the amplitude of major PCs are consistent with these observed hydrological extremes. Although the floods in some sections of the Yangtze River were, to some extent, tied to human activities, such as the removal of wetlands, the variations in major precipitation patterns are recognized as the primary driving force of the flow extremes associated with floods and droughts. The research findings indicate that long-distance hydro-meteorological signals of large-scale precipitation variations over such a large river basin can be successfully identified with the aid of EOF analysis. The retrieved precipitation patterns and their low-frequency jumps of amplitude in relation to PCs are valuable tools to help understand the association between the precipitation variations and the occurrence of hydrological extremes. Such a study can certainly aid in disaster mitigation and decision-making in water resource management.

Editor Z.W. Kundzewicz; Associate editor A. Montanari

Citation Sun, Z., Chang, N.-B., Huang, Q., and Opp, C., 2013. Precipitation patterns and associated hydrological extremes in the Yangtze River basin, China, using TRMM/PR data and EOF analysis. Hydrological Sciences Journal, 57 (7), 1315–1324.     

Something old,something new,something red,something blue*

Abstract

Hydrologists responsible for flood management need real-time data in order to manage imminent or ongoing floods. In this paper, innovative methods for accessing hydrological data and their spatial visualization are introduced. A multitude of relevant real-time, forecast and historical information is provided in a single, self-updating hydrological map information system. The system consists of a central database and a cartographic user interface and provides harmonized and filtered data in the form of interactive, customizable maps. Maps may also be cross-referenced with historical maps or may be animated for improved comprehension and decision making. Emphasis is placed on the development of the hydrological real-time database that manages large amounts of spatial, temporal and attributive data. The paper focuses on the cartographic user interface, its functionality and the resulting interactive hydrological maps.

Citation Lienert, C., Weingartner, R. &; Hurni, L. (2011) An interactive, web-based, real-time hydrological map information system. Hydrol. Sci. J. 56(1), 1–16     

Design event selection in bivariate hydrological frequency analysis

Abstract

In the bivariate analysis of hydrological events, such as rainfall storms or flood hydrographs, the choice of an appropriate return period for structure design leads to infinite combinations of values of the related random variables (e.g. peak and volume in the analysis of floods). These combinations are generally not equivalent, from a practical point of view. In this paper, a methodology is proposed to identify a subset of the critical combinations set that includes a fixed and arbitrarily chosen percentage in probability of the events, on the basis of their probability of occurrence. Therefore, several combinations can be selected within the subset, taking into account the specific characteristic of the design problem, in order to evaluate the effects of different hydrological loads on a structure. The proposed method is applicable to any type of bivariate distribution, thus providing a simple but effective rule to narrow down the infinite possible choices for the hydrological design variables. In order to illustrate how the proposed methodology can be easily used in practice, it is applied to a study case in the context of bivariate flood frequency analysis.

Editor Z.W. Kundzewicz; Associate editor Sheng Yue

Citation Volpi, E. and Fiori, A., 2012. Design event selection in bivariate hydrological frequency analysis. Hydrological Sciences Journal, 57 (8), 1506–1515.     

The effective management of national hydrometric data: experiences from the United Kingdom

Abstract

Access to hydrometric information underpins many areas of effective water management. This paper explores the operational practices of one national hydrological information service, the UK National River Flow Archive, in collating, managing and providing access to river flow data. An information lifecycle approach to hydrometric data management is advocated, with the paper detailing current UK procedures in the areas of: monitoring network design and development; data sensing and recording; validation and archival; synthesis and analysis; and data dissemination. The methods and policies outlined herein are widely transferable to other hydrological data archives around the world.

Editor D. Koutsoyiannis

Citation Dixon, H., Hannaford, J., and Fry, M.J., 2013. The effective management of national hydrometric data: experiences from the United Kingdom. Hydrological Sciences Journal, 58 (7), 1383–1399.     

Book reviews

Abstract

Statistical and deterministic modelling estimates of flood magnitudes and frequencies that can affect flood-plain ecology in the upper Ahuriri River catchment, a mountainous high country catchment in the New Zealand Southern Alps, were evaluated. Statistical analysis of 46 years of historical data showed that floods are best modelled by the generalized extreme value and lognormal distributions. We evaluated application of the HEC-HMS model to this environment by modelling flood events of various frequencies. Model results were validated and compared with the statistical estimates. The SCS curve number method was used for losses and runoff generation, and the model was very sensitive to curve number. The HEC-HMS flood estimates matched the statistical estimates reasonably well, and, over all return periods, were on average approximately 1% greater. However, the model generally underestimated flood peaks up to the 25-year event and overestimated magnitudes above this. The results compared well with other regional estimates, including studies based on L-moments, and showed that this catchment has smaller floods than other similarly-sized catchments in the Southern Alps.

Editor D. Koutsoyiannis; Associate editor H. Aksoy

Citation Caruso, B.S., Rademaker, M., Balme, A., and Cochrane, T.A., 2013. Flood modelling in a high country mountain catchment, New Zealand: comparing statistical and deterministic model estimates for ecological flows. Hydrological Sciences Journal, 58 (2), 328–341.     

A new seasonal design flood method based on bivariate joint distribution of flood magnitude and date of occurrence

Abstract

Seasonal design floods which consider information on seasonal variation are very important for reservoir operation and management. The seasonal design flood method currently used in China is based on seasonal maximum (SM) samples and assumes that the seasonal design frequency is equal to the annual design frequency. Since the return period associated with annual maximum floods is taken as the standard in China, the current seasonal design flood cannot satisfy flood prevention standards. A new seasonal design flood method, which considers dates of flood occurrence and magnitudes of the peaks (runoff), was proposed and established based on copula function. The mixed von Mises distribution was selected as marginal distribution of flood occurrence dates. The Pearson Type III and exponential distributions were selected as the marginal distribution of flood magnitude for annual maximum flood series and peak-over-threshold samples, respectively. The proposed method was applied at the Geheyan Reservoir, China, and then compared with the currently used seasonal design flood methods. The case study results show that the proposed method can satisfy the flood prevention standard, and provide more information about the flood occurrence probabilities in each sub-season. The results of economic analysis show that the proposed design flood method can enhance the floodwater utilization rate and give economic benefits without lowering the annual flood protection standard.

Citation Chen, L., Guo, S. L., Yan, B. W., Liu, P. & Fang, B. (2010) A new seasonal design flood method based on bivariate joint distribution of flood magnitude and date of occurrence. Hydrol. Sci. J. 55(8), 1264–1280.     

Improvement of mid- to long-term runoff forecasting based on physical causes: application in Nenjiang basin,China

Abstract

An artificial neural network, mid- to long-term runoff forecasting model of the Nenjiang basin was established by deciding predictors using the physical analysis method, combined with long-term hydrological and meteorological information. The forecasting model was gradually improved while considering physical factors, such as the main flood season and non-flood season by stage, runoff sources and hydrological processes. The average relative errors in the simulation tests of the prediction model were 0.33 in the main flood season and 0.26 in the non-flood season, indicating that the prediction accuracy during the non-flood season was greater than that in the main flood season. Based on these standards, forecasting accuracy evaluation was conducted by comparing forecasting results with actual conditions: for 2001 to 2003 data, the pass rate of forecasting in the main flood season was 50%, while it was 93% in the non-flood season; for 2001–2010, the respective values were 45% and 72%. The accuracy of prediction was found to decrease as the length of record increases.

Editor D. Koutsoyiannis, Associate editor A. Viglione

Citation Li, H.-Y. Tian, L., Wu, Y., and Xie, M., 2013. Improvement of mid- to long-term runoff forecasting based on physical causes: application in Nenjiang basin, China. Hydrological Sciences Journal, 58 (7), 1414–1422.     

Optimization of cumulative trapped sediment curve for an arid zone reservoir: Foum El Kherza (Biskra,Algeria)

Abstract

Reservoir silting is one of the principal problems affecting the performance of dams in Algeria from the standpoint of reservoir capacity for storage. Foum El Kherza Reservoir (also known as Foum El Gherza), near Biskra Town, Algeria, is subject to dredging operations with the intent of recovering 70% of its initial storage capacity of 47 hm³ (million cubic metres). The forecasting of sediment volume trapped in the reservoir is essential to plan the future use of this resource and to sustain irrigation for the palm groves characteristic of the region. However, there are currently no sediment data, nor a sediment rating curve, for predicting sediment inflow based on hydrological data. This paper describes the optimization of a cumulative trapped sediment curve for Foum El Kherza Reservoir based on 44 years of daily inflows, by using a spreadsheet optimization tool, Microsoft Excel® Solver to calibrate the cumulative sediment load against the cumulative sediment inflow as documented by eight bathymetric surveys since the dam construction.

Editor D. Koutsoyiannis; Associate editor A. Montanari

Citation Tebbi, F.Z., Dridi, H., and Morris, G.L., 2012. Optimization of cumulative trapped sediment curve for an arid zone reservoir: Foum El Kherza (Biskra, Algeria). Hydrological Sciences Journal, 57 (7), 1368–1377.     

Flood frequency analysis using historical data: accounting for random and systematic errors

Abstract

Flood frequency analysis based on a set of systematic data and a set of historical floods is applied to several Mediterranean catchments. After identification and collection of data on historical floods, several hydraulic models were constructed to account for geomorphological changes. Recent and historical rating curves were constructed and applied to reconstruct flood discharge series, together with their uncertainty. This uncertainty stems from two types of error: (a) random errors related to the water-level readings; and (b) systematic errors related to over- or under-estimation of the rating curve. A Bayesian frequency analysis is performed to take both sources of uncertainty into account. It is shown that the uncertainty affecting discharges should be carefully evaluated and taken into account in the flood frequency analysis, as it can increase the quantiles confidence interval. The quantiles are found to be consistent with those obtained with empirical methods, for two out of four of the catchments.

Citation Neppel, L., Renard, B., Lang, M., Ayral, P.-A., Coeur, D., Gaume, E., Jacob, N., Payrastre, O., Pobanz, K. & Vinet, F. (2010) Flood frequency analysis using historical data: accounting for random and systematic errors. Hydrol. Sci. J. 55(2), 192–208.     

Spillway design floods in Sweden: I. New guidelines

Abstract

The new Swedish guidelines for the estimation of design floods for dams and spillways are presented, with emphasis on high-hazard dams. The method is based on a set of regional design precipitation sequences, rescaled for basin area, season and elevation above sea level, and a full hydrological model. A reservoir operation strategy is also a fundamental component of the guidelines. The most critical combination of flood generating factors is searched by systematically inserting the design precipitation sequence into a ten year climatological record, where the initial snowpack has been replaced by a statistical 30-year snowpack. The new guidelines are applicable to single reservoir systems as well as more complex hydroelectric schemes, and cover snowmelt floods, rain floods and combinations of the two. In order to study the probabilities of the computed floods and to avoid regional inconsistencies, extensive comparisons with observed floods and frequency analyses have been carried out.     

Validation of methods to estimate design discharge flow rates for dam spillways with large regulating capacity

Abstract

The estimation and review of discharge flow rates in hydraulic works is a fundamental problem in water management. In the case of dams with large regulating capacity, in order to estimate return periods of discharge flow rates from the spillways, it becomes necessary to consider both peak flow and volume of the incoming floods. In this paper, the results of the validation for several methods of assessing design floods for spillways of dams with a large flood control capacity are presented; the validation is performed by comparing the maximum outflows (or the maximum levels reached in the reservoir) obtained from the routing of the design floods with those obtained from the routing of the historical annual maximum floods. The basin of Malpaso Dam, Mexico, is used as the case study.

Editor D. Koutsoyiannis

Citation Domínguez, M.R. and Arganis, J.M.L., 2012. Validation of methods to estimate design discharge flow rates for dam spillways with large regulating capacity. Hydrological Sciences Journal, 57 (3), 460–478.     

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.     

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.     

BIBLIOGRAPHY—BIBLIOGRAPHIE

Abstract

The Coupled Routing and Excess STorage model (CREST, jointly developed by the University of Oklahoma and NASA SERVIR) is a distributed hydrological model developed to simulate the spatial and temporal variation of land surface, and subsurface water fluxes and storages by cell-to-cell simulation. CREST's distinguishing characteristics include: (1) distributed rainfall–runoff generation and cell-to-cell routing; (2) coupled runoff generation and routing via three feedback mechanisms; and (3) representation of sub-grid cell variability of soil moisture storage capacity and sub-grid cell routing (via linear reservoirs). The coupling between the runoff generation and routing mechanisms allows detailed and realistic treatment of hydrological variables such as soil moisture. Furthermore, the representation of soil moisture variability and routing processes at the sub-grid scale enables the CREST model to be readily scalable to multi-scale modelling research. This paper presents the model development and demonstrates its applicability for a case study in the Nzoia basin located in Lake Victoria, Africa.

Citation Wang, J., Yang, H., Li, L., Gourley, J. J., Sadiq, I. K., Yilmaz, K. K., Adler, R. F., Policelli, F. S., Habib, S., Irwn, D., Limaye, A. S., Korme, T. &; Okello, L. (2011) The coupled routing and excess storage (CREST) distributed hydrological model. Hydrol. Sci. J. 56(1), 84–98.     

Forecasting flash floods using data-based mechanistic models and NORA radar rainfall forecasts

Abstract

Data-based mechanistic (DBM) models can offer a parsimonious representation of catchment dynamics. They have been shown to provide reliable accurate flood forecasts in many hydrological situations. In this work, the DBM methodology is applied to forecast flash floods in a small Alpine catchment. Compared to previous DBM modelling studies, the catchment response is rapid. The use of novel radar-derived ensemble quantitative precipitation forecasts based on analogues to drive the DBM model allows the forecast horizon to be increased to a level useful for emergency response. The characterization of the predictive uncertainty in the resulting hydrological forecasts is discussed and a framework for its representation illustrated.

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

Hydrological behaviour of a drained agricultural peat catchment in the tropics. 1: Rainfall,runoff and water table relationships

Abstract

Hydrological data of a drained tropical peat catchment have been analysed through conventional quantitative hydrological approaches to characterize its hydrological behaviours and changes due to continuous drainage for a long period. The results show that the hydrology of the catchment is extremely dynamic and the catchment is flashy in nature. A decreasing trend in peak flow amount and an increasing trend in baseflow amount was observed in the catchment, indicating that continuous drainage has reduced the risk of both flooding and water scarcity in the catchment. Correlation analysis among rainfall, runoff and groundwater table reveals that saturation excess-near surface flow is the dominant mechanism responsible for rapid runoff generation in the catchment. Therefore, any physical alterations or disturbances to the upper part of the peat profile would definitely affect the overall hydrological behaviour of the peat catchment.

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

Citation Katimon, A., Shahid, S., Abd Wahab, A.K., and Ali, M.H., 2013. Hydrological behaviour of a drained agricultural peat catchment in the tropics. Part 1: Rainfall, runoff and water table relationships. Hydrological Sciences Journal, 58 (6), 1297–1309.     

Grid parameterization of a conceptual distributed hydrological model through integration of a sub-grid topographic index: necessity and practicability

Abstract

Grid-based distributed models have become popular for describing spatial hydrological processes. However, the influence of non-homogeneity within a grid on streamflow simulation was not adequately addressed in the literature. In this study, we investigated how the statistical characteristics of soil moisture storage within a grid impacts on streamflow simulations. The spatial variation of the topographic index, TI, within a grid was used to determine parameter B of the statistical curve of soil moisture storage in the Xinanjiang model. For comparison of influences of the non-homogeneity within a grid on streamflow simulation, two parameterization schemes of soil moisture storage capacity were developed: a grid-parameterization scheme for a distributed model and a catchment-averaged scheme for a semi-distributed model. The practicability and usefulness of the grid-parameterization method were evaluated through model comparisons. The two models were applied in Jiangwan experimental catchment Zhejiang Province, China. Streamflow discharge data at the catchment outlet from 1971 to 1986 at different temporal resolutions, e.g. 15 min and daily time step, were used for model calibration and validation. Statistical results for different grid scales demonstrated that the mean and variation of TI and B decline significantly as the grid scale increases. The simulated streamflow discharges of the two models were similar and the semi-distributed model outperformed the distributed model slightly when the streamflow at the outlet of the catchment was used as the only basis for comparison. In addition, a relatively larger bias in the predicted discharges between these two models was observed along with an abrupt increase of soil moisture saturation ratio. A further analysis of the simulated soil moisture content distribution revealed that the distributed model can provide a reasonable representation of the variable source area concept, which was justified to some extent by the field experiment data.

Editor D. Koutsoyiannis

Citation Liu, J.T., Chen, X., Wu, J.C., Zhang, X.N., Feng, D.Z. and Xu, C.-Y., 2012. Grid parameterization of a conceptual, distributed hydrological model through integration of a sub-grid topographic index: necessity and practicability. Hydrological Sciences Journal, 57 (2), 282–297.     

The largest floods in the High Rhine basin since 1268 assessed from documentary and instrumental evidence

Abstract

The magnitudes of the largest known floods of the River Rhine in Basel since 1268 were assessed using a hydraulic model drawing on a set of pre-instrumental evidence and daily hydrological measurements from 1808. The pre-instrumental evidence, consisting of flood marks and documentary data describing extreme events with the customary reference to specific landmarks, was “calibrated” by comparing it with the instrumental series for the overlapping period between the two categories of evidence (1808–1900). Summer (JJA) floods were particularly frequent in the century between 1651–1750, when precipitation was also high. Severe winter (DJF) floods have not occurred since the late 19th century despite a significant increase in winter precipitation. Six catastrophic events involving a runoff greater than 6000 m ³ s^‐1 are documented prior to 1700. They were initiated by spells of torrential rainfall of up to 72 h (1480 event) and preceded by long periods of substantial precipitation that saturated the soils, and/or by abundant snowmelt. All except two (1999 and 2007) of the 43 identified severe events (SEs: defined as having runoff > 5000 and < 6000 m ³ s ^‐1) occurred prior to 1877. Not a single SE is documented from 1877 to 1998. The intermediate 121-year-long “flood disaster gap” is unique over the period since 1268. The effect of river regulations (1714 for the River Kander; 1877 for the River Aare) and the building of reservoirs in the 20th century upon peak runoff were investigated using a one-dimensional hydraulic flood-routing model. Results show that anthropogenic effects only partially account for the “flood disaster gap” suggesting that variations in climate should also be taken into account in explaining these features.

Citation Wetter, O., Pfister, C., Weingartner, R., Luterbacher, J., Reist, T., & Trösch, J. (2011) The largest floods in the High Rhine basin since 1268 assessed from documentary and instrumental evidence. Hydrol. Sci. J. 56(5), 733–758.     

A new measure for assessing the efficiency of hydrological data-driven forecasting models

Abstract

There is a lack of consistency and generality in assessing the performance of hydrological data-driven forecasting models, and this paper presents a new measure for evaluating that performance. Despite the fact that the objectives of hydrological data-driven forecasting models differ from those of the conventional hydrological simulation models, criteria designed to evaluate the latter models have been used until now to assess the performance of the former. Thus, the objectives of this paper are, firstly, to examine the limitations in applying conventional methods for evaluating the data-driven forecasting model performance, and, secondly, to present new performance evaluation methods that can be used to evaluate hydrological data-driven forecasting models with consistency and objectivity. The relative correlation coefficient (RCC) is used to estimate the forecasting efficiency relative to the naïve model (unchanged situation) in data-driven forecasting. A case study with 12 artificial data sets was performed to assess the evaluation measures of Persistence Index (PI), Nash-Sutcliffe coefficient of efficiency (NSC) and RCC. In particular, for six of the data sets with strong persistence and autocorrelation coefficients of 0.966–0.713 at correlation coefficients of 0.977–0.989, the PIs varied markedly from 0.368 to 0.930 and the NSCs were almost constant in the range 0.943–0.972, irrespective of the autocorrelation coefficients and correlation coefficients. However, the RCCs represented an increase of forecasting efficiency from 2.1% to 37.8% according to the persistence. The study results show that RCC is more useful than conventional evaluation methods as the latter do not provide a metric rating of model improvement relative to naïve models in data-driven forecasting.

Editor D. Koutsoyiannis, Associate editor D. Yang

Citation Hwang, S.H., Ham, D.H., and Kim, J.H., 2012. A new measure for assessing the efficiency of hydrological data-driven forecasting models. Hydrological Sciences Journal, 57 (7), 1257–1274.