Regionalization of constraints on expected watershed response behavior for improved predictions in ungauged basins

Approaches to modeling the continuous hydrologic response of ungauged basins use observable physical characteristics of watersheds to either directly infer values for the parameters of hydrologic models, or to establish regression relationships between watershed structure and model parameters. Both these approaches still have widely discussed limitations, including impacts of model structural uncertainty. In this paper we introduce an alternative, model independent, approach to streamflow prediction in ungauged basins based on empirical evidence of relationships between watershed structure, climate and watershed response behavior. Instead of directly estimating values for model parameters, different hydrologic response behaviors of the watershed, quantified through model independent streamflow indices, are estimated and subsequently regionalized in an uncertainty framework. This results in expected ranges of streamflow indices in ungauged watersheds. A pilot study using 30 UK watersheds shows how this regionalized information can be used to constrain ensemble predictions of any model at ungauged sites. Dominant controlling characteristics were found to be climate (wetness index), watershed topography (slope), and hydrogeology. Main streamflow indices were high pulse count, runoff ratio, and the slope of the flow duration curve. This new approach provided sharp and reliable predictions of continuous streamflow at the ungauged sites tested.     

Regional assimilation of in situ observed soil moisture into the VIC model considering spatial variability

ABSTRACT

In order to improve the soil moisture (SM) modelling capacity, a regional SM assimilation scheme based on an empirical approach considering spatial variability was constructed to assimilate in situ observed SM data into a hydrological model. The daily variable infiltration capacity (VIC) model was built to simulate SM in the Upper Huai River Basin, China, with a resolution of 5 km × 5 km. Through synthetic assimilation experiments and validations, the assimilated SM was evaluated, and the assimilation feedback on evapotranspiration (ET) and streamflow are analysed and discussed. The results show that the assimilation scheme improved the SM modelling capacity, both spatially and temporally. Moreover, the simulated ET was continually affected by changes in SM simulation, and the streamflow predictions were improved after applying the SM assimilation scheme. This study demonstrates the potential value of in situ observations in SM assimilation, and provides valuable ways for improving hydrological simulations.     

Addressing uncertainty in reflectivity‐rainfall relations in mountain watersheds during summer convection

The use of precipitation estimates from weather radar reflectivity has become widespread in hydrologic predictions. However, uncertainty remains in the use of the nonlinear reflectivity–rainfall (Z‐R) relation, in particular for mountainous regions where ground validation stations are often lacking, land surface data sets are inaccurate and the spatial variability in many features is high. In this study, we assess the propagation of rainfall errors introduced by different Z‐R relations on distributed hydrologic model performance for four mountain basins in the Colorado Front Range. To do so, we compare spatially integrated and distributed rainfall and runoff metrics at seasonal and event time scales during the warm season when convective storms dominate. Results reveal that the basin simulations are quite sensitive to the uncertainties introduced by the Z‐R relation in terms of streamflow, runoff mechanisms and the water balance components. The propagation of rainfall errors into basin responses follows power law relationships that link streamflow uncertainty to the precipitation errors and streamflow magnitude. Overall, different Z‐R relations preserve the spatial distribution of rainfall relative to a reference case, but not the precipitation magnitude, thus leading to large changes in streamflow amounts and runoff spatial patterns at seasonal and event scales. Furthermore, streamflow errors from the Z‐R relation follow a typical pattern that varies with catchment scale where higher uncertainties exist for intermediate‐sized basins. The relatively high error values introduced by two operational Z‐R relations (WSR‐57 and NEXRAD) in terms of the streamflow response indicate that site‐specific Z‐R relations are desirable in the complex terrain region, particularly in light of other uncertainties in the modelling process, such as model parameter values and initial conditions. Copyright © 2012 John Wiley & Sons, Ltd.     

Combining a rainfall–runoff model and a regionalization approach for flood and water resource assessment in the western Po Valley,Italy

ABSTRACT

Selecting the best structure and parameterization of rainfall–runoff models is not straightforward and depends on a broad number of factors. In this study, the “Modello Idrologico Semi-Distribuito in continuo” (MISDc) was tested on 63 mountainous catchments in the western Po Valley (Italy) and the optimal model parameters were regionalized using different strategies. The model performance was evaluated through several indexes analysing hydrological regime, high-flow condition and flow–duration curve (FDC). In general, MISDc provides a good fit behaviour with a Kling-Gupta Efficiency index greater than 0.5 for 100% and 84% of cases for calibration and validation, respectively. Concerning the regionalization, spatial proximity approach is the most accurate solution obtaining satisfactory performance. Lastly, the predicted FDCs showed an excellent similarity with the observed ones. Results encourage to apply MISDc over the study area for flood forecasting and for assessing water resources availability thanks to the modest computational efforts and data requirements.     

The applicability of a parsimonious model for local and regional prediction of runoff

Abstract

The Hydrological Recursive Model (HRM), a conceptual rainfall-runoff model, was applied for local and regional simulation of hourly discharges in the transnational Alzette River basin (Luxembourg-France-Belgium). The model was calibrated for a range of various sub-basins with a view to analysing its ability to reproduce the variability of basin responses during flood generation. The regionalization of the model parameters was obtained by fitting simultaneously the runoff series of calibration sub-basins after their spatial discretization in lithological contrasting isochronal zones. The runoff simulations of the model agreed well with the recorded runoff series. Significant correlations with some basin characteristics and, noticeably, the permeability of geological formations, could be found for two of the four free model parameters. The goodness of fit for runoff predictions using the derived regional parameter set was generally satisfactory, particularly for the statistical characteristics of streamflow. A more physically-based modelling approach, or at least an explicit treatment of quick surface runoff, is expected to give better results for high peak discharge.     

High-resolution simulation of the spatial pattern of water use in continental China

ABSTRACT

High-resolution data on the spatial pattern of water use are a prerequisite for appropriate and sustainable water management. Based on one well-validated hydrological model, the Distributed Time Variant Gains Model (DTVGM), this paper obtains reliable high-resolution spatial patterns of irrigation, industrial and domestic water use in continental China. During the validation periods, ranges of correlation coefficient (R) and Nash-Sutcliffe efficiency (NSE) coefficient are 0.67–0.96 and 0.51–0.84, respectively, between the observed and simulated streamflow of six hydrological stations, indicating model applicability to simulate the distribution of water use. The simulated water use quantities have relative errors (RE) less than 5% compared with the observed. In addition, the changes in streamflow discharge were also correctly simulated by our model, such as the Zhangjiafen station in the Hai River basin with a dramatic decrease in streamflow, and the Makou station in the Pearl River basin with no significant changes. These changes are combined results of basin available water resources and water use. The obtained high-resolution spatial pattern of water use could decrease uncertainty of hydrological simulation and guide water management efficiently.

Editor M.C. Acreman; Associate editor X. Fang     

Use of regionalized stormflow coefficients with a view to hydroclimatological hazard mapping

Abstract

An attempt was made to compensate for the lack of long hydrological time series and the lack of information on maximum streamflow in the Alzette River basin (Luxembourg) via the regionalization of stormflow coefficients. Streamflow data recorded since 1995 with a very dense streamgauge network allowed the determination of maximum stormflow coefficients in 18 sub-basins of the Alzette. The stormflow coefficients were then regionalized via stepwise multiple regression analysis for 83 different sub-basins of the Alzette. Combined with 10-year daily rainfall heights (statistical estimation), this regionalization allowed the spatial variability of storm runoff in the Alzette basin to be mapped, thus providing a view of hazard and risk-producing areas, as well as of risk-exposed areas. In a basin with little historical hydrological information this technique can help identify areas where storm runoff reducing measures should be applied from the outset.     

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.     

Comparison of local and global approximators in multivariate chaotic forecasting of daily streamflow

ABSTRACT

Although it is conceptually assumed that global models are relatively ineffective in modelling the highly unstable structure of chaotic hydrologic dynamics, there is not a detailed study of comparing the performances of local and global models in a hydrological context, especially with new emerging machine learning models. In this study, the performance of a local model (k-nearest neighbour, k-nn) and, as global models, several recent machine learning models – artificial neural network (ANN), least square-support vector regression (LS-SVR), random forest (RF), M5 model tree (M5), multivariate adaptive regression splines (MARS) – was analysed in multivariate chaotic forecasting of streamflow. The models were developed for Australia’s largest river, the River Murray. The results indicate that the k-nn model was more successful than the global models in capturing the streamflow dynamics. Furthermore, coupled with the multivariate phase-space, it was shown that the global models can be successfully used for obtaining reliable uncertainty estimates for streamflow.     

A variable-length block bootstrap method for multi-site synthetic streamflow generation

Abstract

The complexity of stochastic streamflow generators limits their practical use, highlighting the need for effective but simpler approaches. An attempt to meet this objective is presented using variable-length bootstrapping (VLB) of annual flows, and a weighted method of fragments for disaggregation and perturbing the bootstrapped annual flows. The perturbations enable generation of annual flows different from those present in the historical record, thereby overcoming one of the main limitations of the classical bootstrap method. The VLB replicates adequately nine historical annual statistics of a five-site problem, and reproduces the annual serial and cross-correlations better than STOMSA—a state-of-the-art parametric generator. The VLB achieves reasonable validation using the sum of minimum flows and the reservoir storage size test. Because of the modification of the monthly flow distribution caused by the weighted averaging of fragments, the VLB cannot be safely used for within-year analysis, but is a potentially robust annual streamflow generator.

Citation Ndiritu, J. (2011) A variable length block bootstrap for multi-site synthetic streamflow generation. Hydrol. Sci. J. 56(3), 362–379.     

Suspended sediment estimation using neuro-fuzzy and neural network approaches/Estimation des matières en suspension par des approches neurofloues et à base de réseau de neurones

Abstract

The abilities of neuro-fuzzy (NF) and neural network (NN) approaches to model the streamflow–suspended sediment relationship are investigated. The NF and NN models are established for estimating current suspended sediment values using the streamflow and antecedent sediment data. The sediment rating curve and multi-linear regression are also applied to the same data. Statistic measures were used to evaluate the performance of the models. The daily streamflow and suspended sediment data for two stations—Quebrada Blanca station and Rio Valenciano station—operated by the US Geological Survey were used as case studies. Based on comparison of the results, it is found that the NF model gives better estimates than the other techniques.     

Diagnostic calibration and cross‐catchment transferability of a simple process‐consistent hydrologic model

The transferability of hydrologic models is of ever increasing importance for making improved hydrologic predictions and testing hypothesized hydrologic drivers. Here, we present an investigation into the variability and transferability of the recently introduced catchment connectivity model (Smith et al., 2013 ). The catchment connectivity model was developed following extensive experimental observations identifying the key drivers of streamflow in the Tenderfoot Creek Experimental Forest (Jencso et al., 2009 ; Jencso et al., 2010 ), with the goal of creating a simple model consistent with internal observations of catchment hydrologic connectivity patterns. The model was applied across seven catchments located within Tenderfoot Creek Experimental Forest to investigate spatial variability and transferability of model performance and parameterization. The results demonstrated that the model resulted in historically good fits (based on previous studies at the sites) to both the hydrograph and internal water table dynamics (corroborated with experimental observations). The impact of a priori parameter limits was also examined. It was observed that enforcing field‐based limits on model parameters resulted in slight reductions to streamflow hydrograph fits, but significant improvements to model process fidelity (as hydrologic connectivity), as well as moderate improvement in the transferability of model parameterizations from one catchment to the next. Copyright © 2016 John Wiley & Sons, Ltd.     

Streamflow forecasting using least-squares support vector machines

Abstract

This paper investigates the ability of a least-squares support vector machine (LSSVM) model to improve the accuracy of streamflow forecasting. Cross-validation and grid-search methods are used to automatically determine the LSSVM parameters in the forecasting process. To assess the effectiveness of this model, monthly streamflow records from two stations, Tg Tulang and Tg Rambutan of the Kinta River in Perak, Peninsular Malaysia, were used as case studies. The performance of the LSSVM model is compared with the conventional statistical autoregressive integrated moving average (ARIMA), the artificial neural network (ANN) and support vector machine (SVM) models using various statistical measures. The results of the comparison indicate that the LSSVM model is a useful tool and a promising new method for streamflow forecasting.

Editor D. Koutsoyiannis; Associate editor L. See

Citation Shabri, A. and Suhartono, 2012. Streamflow forecasting using least-squares support vector machines. Hydrological Sciences Journal, 57 (7), 1275–1293.     

Disaggregation modelling of monthly streamflows using a new approach of the method of fragments

Abstract

The method of fragments is applied to the generation of synthetic monthly streamflow series using streamflow data from 34 gauging stations in mainland Portugal. A generation model based on the random sampling of the log-Pearson Type III distribution was applied to each sample to generate 1200 synthetic series of annual streamflow with an equal length to that of the sample. The synthetic annual streamflow series were then disaggregated into monthly streamflows using the method of fragments, by three approaches that differed in terms of the establishment of classes and the selection of fragments. The results of the application of such approaches were compared in terms of the capacity of the method to preserve the main monthly statistical parameters of the historical samples.

Editor D. Koutsoyiannis; Associate editor C. Onof

Citation Silva, A.T. and Portela, M.M., 2012. Disaggregation modelling of monthly streamflows using a new approach of the method of fragments. Hydrological Sciences Journal, 57 (5), 942–955.     

Modelling daily suspended sediment of rivers in Turkey using several data-driven techniques / Modélisation de la charge journalière en matières en suspension dans des rivières turques à l'aide de plusieurs techniques empiriques

Abstract

The transport of sediment load in rivers is important with respect to pollution, channel navigability, reservoir filling, longevity of hydroelectric equipment, fish habitat, river aesthetics and scientific interest. However, conventional sediment rating curves cannot estimate sediment load accurately. An adaptive neuro-fuzzy technique is investigated for its ability to improve the accuracy of the streamflow—suspended sediment rating curve for daily suspended sediment estimation. The daily streamflow and suspended sediment data for four stations in the Black Sea region of Turkey are used as case studies. A comparison is made between the estimates provided by the neuro-fuzzy model and those of the following models: radial basis neural network (RBNN), feed-forward neural network (FFNN), generalized regression neural network (GRNN), multi-linear regression (MLR) and sediment rating curve (SRC). Comparison of results reveals that the neuro-fuzzy model, in general, gives better estimates than the other techniques. Among the neural network techniques, the RBNN is found to perform better than the FFNN and GRNN.     

A NOTE ON THE ESTIMATION OF THE PARAMETERS IN LOGARITHMIC STAGE-DISCHARGE RELATIONSHIPS WITH ESTIMATES OF THEIR ERROR

Abstract

Under certain assumptions the stage-discharge relationship of a channel cross-section can be approximated by a logarithmic relationship. Observational pairs of stage and discharge plotted on log-log paper often cluster around a straight line and this suggests that the assumptions involved are often approximately satisfied.

In such cases the parameters of the logarithmic relationship are usually estimated graphically from the position and slope of the straight line on the log-log paper. In this paper principles and methods are outlined for the estimation of the parameters with estimates of their standard error, via regression analysis. Because the water level of zero flows is usually one of the unknown parameters, the regression is non-linear and least squares optimal estimates can be obtained by a step-by-step approximation. The variances of the parameter estimates can be obtained from the dispersion matrix of the joint distribution of the least squares estimators via the likelihood function. An estimate of the error in predictions of the discharge depending on the corresponding stage may be obtained.     

赣江流域多种数据同化方案的径流模拟比较

为了探讨水文模型在不同水文数据同化方案下的径流模拟差异,本文采用集合卡尔曼滤波算法,以遥感蒸散发产品、实测径流为观测数据,构建了基于新安江模型的数据同化框架。基于此框架设计了4种不同同化方案(DA-ET、DAET(K)、DA-ET-Q、DA-ET-Q(K))以及1种对照方案OL,以赣江流域开展实例研究,评估了水文数据同化中遥感蒸散发产品的时间分辨率、模型蒸散发相关参数时变与否以及多源数据同化对径流模拟的影响。结果表明:在DA-ET方案下,同化两种不同时间分辨率的蒸散发产品均能提高模型整体的径流模拟精度,且时间分辨率更高的产品的同化效果更好;在DA-ET方案的基础上,考虑加入实测径流进行同化能够提升模型径流模拟精度,且DA-ET(K)与DA-ET-Q(K)方案所得径流相对误差的减幅均超过了20%,说明在蒸散发同化过程中同时考虑蒸散发参数动态变化的结果更优;相较于OL方案,4种同化方案均能不同程度地提高模型对径流高水部分的模拟能力,但DA-ET-Q(K)方案表现最差,而其余方案差异并不显著。本研究有助于进一步了解不同数据同化方案在径流模拟中的差异,从而为水资源高效利用与科学管理提供科学依据...     

Use of a parsimonious rainfall–run‐off model for predicting hydrological response in ungauged basins

A new parameter parsimonious rainfall–run‐off model, the Distance Distribution Dynamics (DDD) model, is used to simulate hydrological time series at ungauged sites in the Lygne basin in Norway. The model parameters were estimated as functions of catchment characteristics determined by geographical information system. The multiple regression equations relating catchment characteristics and model parameters were trained from 84 calibrated catchments located all over Norway, and all model parameters showed significant correlations with catchment characteristics. The significant correlation coefficients (with p‐value < 0.05) ranged from 0.22 to 0.55. The suitability of DDD for predictions in ungauged basins was tested for 17 catchments not used to estimate the multiple regression equations. For ten of the 17 catchments, deviations in Nash–Sutcliffe efficiency (NSE) criteria between the calibrated and regionalised model were less than 0.1, and for two calibrated catchments within the Lygne basin, the deviations were less than 0.08. The median NSE for the regionalized DDD for the 17 catchments for two time series was 0.66 and 0.72. Deviations in NSE between calibrated and regionalised models are well explained by the deviations between calibrated and regressed parameters describing spatial snow distribution and snowmelt respectively. The quality of the simulated run‐off series for the ungauged sites in the Lygne basin was assessed by comparing flow indices describing high, medium and low flow estimated from observed run‐off at the 17 catchments and for the simulated run‐off series. The indices estimated for the simulated series were generally well within the ranges defined by the 17 observed series. Copyright © 2014 John Wiley & Sons, Ltd.