Basin-scale water resources decisions need to have a decision support system (DSS) that models all water quantity and quality elements. Common integrated water resources management (IWRM) models such as Weap and Modsim can quantitatively model a water system well. However, although certain insertions to such software have been incorporated to simulate quality parameters in rivers, none of these can model such parameters in reservoirs. To solve this issue, researchers have coupled IWRM models with water quality models of reservoirs (WQMRs). WQMRs such as Cequal-W2 usually require voluminous and various input and output information. They are not user friendly and have a high running time. Because of these shortcomings, coupled IWRM and WQMR models cannot be considered as a DSS to assess a variety of scenarios. This paper represents an attempt to introduce a DSS based on the system dynamics approach to utilise in basin-scale integrated water resources quantitative and qualitative management. The proposed model uses a one-dimensional water quality approach for the reservoir to overcome the quality modelling disadvantages of IWRM models. The final results of the proposed model for different scenarios are compared with Modsim and Cequal-W2.

Different definitions of the bankfull condition in rivers are based on morphological characteristics, boundary conditions and geometrical properties. Consequently, the magnitude and associated return period of the bankfull discharge can be ambiguous. Knowledge of this discharge is important in index flood estimation and subsequent regional flood frequency analysis. This study investigates bankfull discharges and recurrence intervals at 88 locations in the Irish river network using a combination of surveyed bankfull levels, rating curves and equations and photographic records at the sites in question. Catchments ranged in area from approximately 23 km² to 2778 km². Recurrence intervals were determined by fitting generalised extreme value (GEV) distributions to the annual maximum flow series at the sites investigated. These intervals were found to be less than 2 years (the median annual flood) at 42 stations (48%) and less than 2·33 years (the mean annual flood assuming a GEV type 1 distribution) at 47 stations (53%). Higher return periods of between 2·33 and 10 years and 10 and 25 years were observed at a further 20% and 6% of locations respectively. Using multivariate regression analysis, the computed bankfull discharges are correlated with catchment descriptors and three expressions are presented for estimating bankfull flows.

The scale effects of incipient cavitation in high-speed flows have been studied in experiments in which series of sudden enlargements in pipes with different expansion ratios are employed. The relationship between the incipient cavitation and flow velocity is also investigated and shows that the scale effect indeed exists. Based on the test data, an empirical formula for incipient cavitation that takes scale effects into account is derived and validated. The formula has been validated with corresponding experimental data and good agreement has been obtained. The proposed formula can be used to forecast incipient cavitation of hydraulic structures in prototype with high-speed flow.

The Muskingum model is a hydrologic flood routing method in which the accuracy of the parameter estimation affects the routed hydrograph, especially in both the value and time of the flood peak. Meta-heuristic algorithms are good candidates to determine optimal/near-optimal parameters in the Muskingum model. In this paper, two meta-heuristic algorithms – the simulated annealing (SA) algorithm and the shuffled frog leaping algorithm (SFLA) – are applied and compared in two benchmark and real case studies, considering the sum of the squared deviation (SSQ) between observed and routed outflows and the sum of the absolute value of deviation (SAD) between observed and routed outflow as the objective functions, and deviation of value and occurrence time of the routed flood peak (DPO and DPOT) as the important parameters on the routed flood hydrograph. Results show that the SFLA improves (decreases) the SSQ and SAD by 0·03% and 0·39% in the benchmark problem, and by 3·59% and 2·03% in the real case study, respectively, compared to reported results using various optimisation algorithms. In addition, the SFLA improves (decreases) the DPO of the routed hydrograph in the benchmark problem by 56·67% compared to the best (minimum) result using the Tung method.

Vegetation porosity in a vegetated channel has been identified as the main parameter that contributes to the flow behaviour and resistance in the channel. Estimation of vegetation porosity is quite a challenging task due to the diverse characteristics of vegetation. In this study, several porosity measurement methods based on vegetation frontal area and vegetation volume were used to estimate the porosity of vegetation (Lepironia articulata) in a laboratory flume for various flow and vegetation characteristics. Digital image analysis was one of the methods used to estimate porosity. The study also involved measurements of velocity using a three-dimensional acoustic Doppler velocimeter and flow depths at different spatial locations along the flume. The volumetric method for porosity measurement, which considers the fraction of the actual volume of the vegetation to the volume of water, is considered more practical and accurate than the other methods that were studied. The results of this study indicate that, by assuming vegetation to be cylindrical in shape and considering only the frontal area of the most upstream vegetation, porosity could be underestimated by 14%. Digital image analysis gave a difference of only 5%. From the laboratory data, correlations between the mean velocity, water depth and vegetation porosity were established. It was observed that by reducing the vegetation porosity by 8%, the velocity could reduce by between 35–60% depending on flow rate.