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The Pearl River Delta (PRD) is a complicated criss-cross river network. The booming economy and intensifying human activity have greatly altered the natural water levels, which threatens regional sustainable development. The Mann-Kendall trend test and the kriging interpolation method were used to detect the spatial and temporal patterns in the trends of extreme high/low water levels related to different magnitudes of streamflow, in order to explore the impacts of hydrological processes on the water-level changes throughout the PRD. The results indicate that: (a) streamflow changes at the Sanshui and Makou stations exhibit different characteristics. No significant trend can be identified in the streamflow changes at Makou station; however, the streamflow at Sanshui station shows a significant increasing trend, especially in low-flow periods. The decreasing Makou/Sanshui streamflow ratio exerts tremendous impacts on the water-level changes in the hinterland of the PRD region. (b) Extreme high/low water levels exhibit similar changing patterns. The extreme high/low water levels in the high/normal flow periods are decreasing in both the upper PRD and the hinterland of the PRD region. Increasing extreme high/low water levels in low-flow periods can be identified in the hinterland of the PRD region. The coastal regions are characterized by increasing extreme high/low water levels. (c) Extreme high/low water levels for high/normal flow periods in the hinterland of the PRD are heavily impacted by topographic changes due to in-channel dredging. Increasing extreme high/low water levels along the coastal regions are mainly backwater effects caused by serious siltation and rising sea level. This study has scientific and practical merits in regional fluvial management and mitigation of natural hazards. Citation Zhang, Q., Xu, C.-Y. & Chen, Y. D. (2010) Variability of water levels and impacts from streamflow changes and human activity within the Pearl River Delta, China. Hydrol. Sci. J. 55(4), 512-525. [ABSTRACT FROM AUTHOR]

Hydrological models are often used for studying the hydrological effects of climate change; however, the stability of model performance and parameter values under changing climate conditions has seldom been evaluated and compared. In this study, three widely-used rainfall–runoff models, namely the SimHYD model, the HBV model and the Xin’anjiang model, are evaluated on two catchments subject to changing climate conditions. Evaluation is carried out with respect to the stability in their performance and parameter values in different calibration periods. The results show that (a) stability of model performance and parameter values depends on model structure as well as the climate of catchments, and the models with higher performance scores are more stable in changing conditions; (b) all the tested models perform better on a humid catchment than on an arid catchment; (c) parameter values are also more stable on a humid catchment than on an arid catchment; and (d) the differences in stability among models are somewhat larger in terms of model efficiency than in model parameter values. [ABSTRACT FROM AUTHOR]

Climate and soil characteristics vary considerably around the Lake Victoria basin resulting in high spatial and temporal variability in catchment inflows. However, data for estimating the inflows are usually sparsely distributed and error-prone. Therefore, modelled estimates of the flows are highly uncertain, which could explain early difficulties in reproducing the lake water balance. The aim of this study was to improve the estimates of catchment flow to Lake Victoria. The WASMOD model was applied to the Nzoia River, one of the major tributaries to Lake Victoria. Uncertainty was assessed within the GLUE framework. During calibration, log-transformation was performed on both simulated and observed flows. The results showed that, despite its simple structure, WASMOD produces acceptable results for the basin. For a Nash-Sutcliffe efficiency (NS) threshold of 0.6, the percentage of observations bracketed by simulations (POBS) was 74%, the average relative interval length (ARIL) was 0.93, and the maximum NS value was 0.865. The residuals were shown to be homoscedastic, normally distributed and nearly independent. When the NS threshold was increased to 0.8, POBS decreased to 54% with an improvement of ARIL to 0.49, highlighting the effect of the subjective choice of likelihood threshold. Citation Kizza, M., Rodhe, A., Xu, C.-Y. & Ntale, H. K. (2011) Modelling catchment inflows into Lake Victoria: uncertainties in rainfall–runoff modelling for the Nzoia River. Hydrol. Sci. J. 56(7), 1210–1226. [ABSTRACT FROM PUBLISHER]

Editors of several journals in the field of hydrology met during the General Assembly of the European Geosciences Union—EGU in Vienna in April 2017. This event was a follow-up of similar meetings held in 2013 and 2015. These meetings enable the group of editors to review the current status of the journals and the publication process, and to share thoughts on future strategies. Journals were represented at the 2017 meeting by their editors, as shown in the list of authors. The main points on invigorating hydrological research through journal publications are communicated in this joint editorial published in the above journals. [ABSTRACT FROM AUTHOR]

Quantifying the uncertainty in hydrological forecasting is valuable for water resources management and decision-making processes. The hydrological uncertainty processor (HUP) can quantify hydrological uncertainty and produce probabilistic forecasts under the hypothesis that there is no input uncertainty. This study proposes a HUP based on a copula function, in which the prior density and likelihood function are explicitly expressed, and the posterior density and distribution obtained using Monte Carlo sampling. The copula-based HUP was applied to the Three Gorges Reservoir, and compared with the meta-Gaussian HUP. The Nash-Sutcliffe efficiency and relative error were used as evaluation criteria for deterministic forecasts, while predictive QQ plot, reliability, resolution and continuous rank probability score (CRPS) were used for probabilistic forecasts. The results show that the proposed copula-based HUP is comparable to the meta-Gaussian HUP in terms of the posterior median forecasts, and that its probabilistic forecasts have slightly higher reliability and lower resolution compared to the meta-Gaussian HUP. Based on the CRPS, both HUPs were found superior to deterministic forecasts, highlighting the effectiveness of probabilistic forecasts, with the copula-based HUP marginally better than the meta-Gaussian HUP. [ABSTRACT FROM PUBLISHER]

Most conceptual rainfall–runoff models use as input spatially averaged rainfall fields which are typically associated with significant errors that affect the model outcome. In this study, it was hypothesised that a simple spatially and temporally averaged event-dependent rainfall multiplier can account for errors in the rainfall input. The potentials and limitations of this lumped multiplier approach were explored by evaluating the effects of multipliers on the accuracy and precision of the predictive distributions. Parameter sets found to be behavioural across a range of different flood events were assumed to be a good representation of the catchment dynamics and were used to identify rainfall multipliers for each of the individual events. An effect of the parameter sets on identified multipliers was found; however, it was small compared to the differences between events. Accounting for event-dependent multipliers improved the reliability of the predictions. At the cost of a small decrease in precision, the distribution of identified multipliers for past events can be used to account for possible rainfall errors when predicting future events. By using behavioural parameter sets to identify rainfall multipliers, the method offers a simple and computationally efficient way to address rainfall errors in hydrological modelling. [ABSTRACT FROM PUBLISHER]

Water operating rules have been universally used to operate single reservoirs because of their practicability, but the efficiency of operating rules for multi-reservoir systems is unsatisfactory in practice. For better performance, the combination of water and power operating rules is proposed and developed in this paper. The framework of deriving operating rules for multi-reservoirs consists of three modules. First, a deterministic optimal operation module is used to determine the optimal reservoir storage strategies. Second, a fitting module is used to identify and estimate the operating rules using a multiple linear regression analysis (MLR) and artificial neural networks (ANN) approach. Last, a testing module is used to test the fitting operating rules with observed inflows. The Three Gorges and Qing River cascade reservoirs in the Changjiang River basin, China, are selected for a case study. It is shown that the combination of water and power operating rules can improve not only the assurance probability of output power, but also annual average hydropower generation when compared with designed operating rules. It is indicated that the characteristics of flood and non-flood seasons, as well as sample input (water or power), should be considered if the operating rules are developed for multi-reservoirs. EDITOR D. Koutsoyiannis ASSOCIATE EDITOR not assigned [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM PUBLISHER]