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• A three-dimensional coupled model is used to quantify seepage from lined canals. • The effects of cracks on the hydraulic conductivity of lining materials are evaluated. • A quantitative relationship between hydraulic conductivity and its factors is formed. • The accuracy of empirical formula and numerical model for canal seepage is improved. The equivalent saturated hydraulic conductivity of concrete lining (K sce) is a key parameter to estimate seepage loss, while few studies have quantified the effect of cracks on K sce , potentially leading to significant errors in canal seepage estimation. A three-dimensional numerical model is employed to simulate seepage loss from canals lined with concrete, and then to obtain the value of K sce by an equivalent method. A total of 58,400 scenarios are simulated for different concrete lining and crack conditions (e.g., crack length, crack width, crack location, hydraulic conductivity of concrete (K sc), and underlying soil (K soil)), and the corresponding K sce values are estimated. Results show that the K sce value determined by the equivalent method is reliable in calculating seepage loss from concrete lined canals. K sce increases linearly with crack length with a slope C k , and C k exhibits a power function relationship with crack width, reaching a maximum value when the crack width surpasses the critical threshold, which ranges from 0.424 to 0.435 mm. When the crack width follows a log-normal distribution, the logarithmic value of C k increases linearly with the mean value of the logarithmic crack width. The influence of crack location and K sc on K sce can be negligible. The maximum increment of K sce of a crack is proportional to K soil. Considering the variation of K sce with crack parameters and K soil , equations to determine the value of K sce are established by adding the increment of K sce caused by cracks to K sc. This study establishes a quantitative relationship between K sce and crack parameters, thereby enhancing the accuracy of seepage loss calculations in lined canal under different damage status. [ABSTRACT FROM AUTHOR]

• Highlights the limitation of existing NFFA approaches in differentiating the mechanism of frequent versus rare flood quantiles. • Proposes a novel NRFFA approach to capture the variation of flood quantiles with different return periods in a changing climate. • Use regional information to ascertain the design flood quantiles and provide plausible changes in design flood extremes in the year 2100. There now exists clear evidence of the impact of climate change on flooding, creating need for new methodologies for design flood estimation that account for warming induced nonstationarity. Current alternatives for nonstationary flood frequency analysis require the specification of a nonstationary probability model (often with time-varying parameters) that requires sufficient data to be stable. Reliance on the trend in observed data often ignores the dissimilar behaviour of frequent and rare quantiles under a warming climate. This, in turn, results in the direction of change to be consistent across both rare and frequent projected flood quantiles. However, results of multiple recent studies suggest that rarer floods are likely to increase while more frequent floods may decrease in magnitude into the future. In this study, we highlight this limitation of existing nonstationary flood frequency approaches and propose a novel nonstationary regional flood frequency analysis approach that captures the differing behaviour of more frequent and rare flood quantiles under a warming climate. The need for longer flood data to model nonstationarity is accommodated by pooling regional information which makes the projections more precise. Data for 105 Australian catchments are used to validate our proposed approach. Results show the effectiveness of the proposed method in capturing the variation of flood quantiles with varying average recurrence intervals in a changing climate. Finally, a few important statistics of future projections are also presented. [ABSTRACT FROM AUTHOR]

• Highlights the limitation of existing NFFA approaches in differentiating the mechanism of frequent versus rare flood quantiles. • Proposes a novel NRFFA approach to capture the variation of flood quantiles with different return periods in a changing climate. • Use regional information to ascertain the design flood quantiles and provide plausible changes in design flood extremes in the year 2100. There now exists clear evidence of the impact of climate change on flooding, creating need for new methodologies for design flood estimation that account for warming induced nonstationarity. Current alternatives for nonstationary flood frequency analysis require the specification of a nonstationary probability model (often with time-varying parameters) that requires sufficient data to be stable. Reliance on the trend in observed data often ignores the dissimilar behaviour of frequent and rare quantiles under a warming climate. This, in turn, results in the direction of change to be consistent across both rare and frequent projected flood quantiles. However, results of multiple recent studies suggest that rarer floods are likely to increase while more frequent floods may decrease in magnitude into the future. In this study, we highlight this limitation of existing nonstationary flood frequency approaches and propose a novel nonstationary regional flood frequency analysis approach that captures the differing behaviour of more frequent and rare flood quantiles under a warming climate. The need for longer flood data to model nonstationarity is accommodated by pooling regional information which makes the projections more precise. Data for 105 Australian catchments are used to validate our proposed approach. Results show the effectiveness of the proposed method in capturing the variation of flood quantiles with varying average recurrence intervals in a changing climate. Finally, a few important statistics of future projections are also presented. [ABSTRACT FROM AUTHOR]

• A fully coupled numerical model is used to quantify canal seepage from lined canal. • Effects of lining material and damage parameters on reduction factor are evaluated. • The main factors influencing seepage from canal with 3 lining materials are quantified. • Three empirical formulas are developed for the reduction factor of damaged lining. • The accuracy of empirical formula to calculate seepage from lined canal is improved. An increasing number of canals are designed with liners to decrease canal seepage. As the lining material and cracks or holes were previously considered equivalent porous media, few studies have quantified the effects of lining parameters on canal seepage, and the relationships between the reduction factor (β) of the lining and the crack width (d f) and hole density (h d) are not explicit, leading to large errors in the estimation of seepage loss. A three-dimensional numerical model is employed to simulate seepage loss from canals lined with concrete and geomembrane material in a total of 1159 scenarios, focusing on the crack locations, saturated hydraulic conductivity (K s) of concrete material and geomembrane material (K sc and K sg , respectively), thickness (T c), concrete lining d f , and geomembrane lining h d. For canals lined with concrete, d f is the main factor affecting canal seepage, followed by K sc and T c. Cracks with widths smaller than 0.02 mm have minimal influence on β, where β is reduced by a decrease in K sc or an increase in T c. When d f ranges from 0.02 to 0.2 mm, β increases gradually to a maximum value, while the impacts of K sc and T c weaken. For canals lined with geomembranes, β increases slightly with h d from 0 to 4.2 × 10−5, increases nearly linearly with log h d from 4.2 × 10−5 to 8.4 × 10−3, and then approaches 1.0. β is weakly influenced by K sg for particular h d values when K sg is smaller than 10−11 m/s, increases rapidly with K sg from 1 × 10−11 to 1 × 10−8 m/s, and then exceeds 0.938. For a canal lined with both concrete and a geomembrane, the trends in β with changes in d f and h d are identical to those of a canal with a single lining. Based on these results, the damage degree is proposed to evaluate the influence of cracks and holes on the lining effectiveness and as an intermediate variable for calculating β from d f and h d. Three empirical equations are proposed to calculate the β value of the concrete lining, geomembrane lining and combined lining with different d f and h d. The results show that the proposed equation improves the accuracy of the estimation of β compared with the multiplication model and can be further used for calculations of seepage loss from lined canals. [ABSTRACT FROM AUTHOR]

• A 3D numerical model for canal seepage is established based on finite element method. • The model is calibrated and validated by ponding tests with four lining conditions. • The model is accommodated to concrete and geomembrane lining with cracks and holes. • The main factors influencing canal seepage under different scenarios are quantified. Concrete and geomembranes are common materials used in canal linings to decrease canal seepage. Current numerical studies focus on concrete linings only by equivalent continuous models and seldom are about geomembrane and are suitable to quantify the seepage loss from canals with damaged linings. In this study, a new model is developed for the coupled numerical simulation of seepage through concrete with cracks and a geomembrane with holes in canal lining damage based on the finite element method. In this model, the porous media is discretized into solid elements, whereas discrete cracks and geomembranes are modelled by zero-thickness elements, with the Richards equation and cubic law applied to describe the water seepage process. The porous media and crack zones are implicitly coupled in time and space through the exchange flow between the concrete and the crack zones in that the heads are integrated in a single matrix equation. The domain area is divided into two subdomain areas by the geomembrane. For the two subdomain areas, the surfaces of both sides in the geomembrane are treated as two flux boundaries. The proposed model is calibrated and validated by the results of ponding tests conducted on a canal with four lining treatments and additional experiments, which showed that the model fit the experiments very well. The model is applied to sensitivity analyses by varying the model parameters. The model is shown to be capable of simulating the seepage of canals lined by concrete and geomembrane lining with different cracks and holes. The sensitivity analysis shows that canal seepage mainly depends on the lining characteristics, such as the crack width, hole density, saturated hydraulic conductivity (K s) of the geomembrane, K s of the concrete, and K s of the soil layers adjacent to the canal bottom. [ABSTRACT FROM AUTHOR]

• A new basis for presenting illustrations of spatial dependence related to extreme rain. • Extreme rainfall spatial connectivity increases under ENSO phases. • RC weakens at warmer temperatures, with localized lower relative connectivity. The frequency and severity of extreme weather events have been noted to be changing in both time and space as a result of rising global temperatures. In this regard, the analysis of joint occurrences of extreme climate events has gained considerable importance for planning and emergency management as such events often result in system failures that extend beyond a single location in the region impacted. By their very definition, extremes cannot be sampled frequently, necessitating approaches that are robust and efficient and can take advantage of the Big Data movement we are now a part of. This study introduces a new concept for characterizing such dependence, termed relative connectivity, formulated using the theory of empirical copulas which represent a non-parametric method to describe the joint dependence of random variables. The spatial relative connectivity of extreme rainfall events across 2,708 rainfall stations in Australia is ascertained and conclusions drawn. The extreme rainfall events in Western Australia, southeast South Australia, and southwest Victoria exhibit higher relative connectivity than other regions, suggesting a stronger spatial dependence and higher possibility of concurrence when compared to other regions. The overall variation of relative connectivity is also examined under different low-frequency climatic anomalies (i.e. El Nino and La Nina events) and temperature states. We observe that spatial dependence across raingauges increases under both El Nino and La Nina periods, while it weakens at warmer temperatures, with localized lower relative connectivity at target raingauges. [ABSTRACT FROM AUTHOR]

• A model for partly and fully saturated soils using water balance method is developed. • The field capacity is modified to represent the impact of the capillary rise. • The capillary fringe is stable to soil type and not sensitive to boundary conditions. • The model uses easily available parameters and is suitable for large-scale problems. Accurate estimation of soil water content and water table depth is important for making irrigation measures and rational groundwater use in arid agricultural areas with shallow water table depth. Soil water balance models are widely used due to their high computational efficiency, while they are less applicable in areas with shallow water table depths because they usually ignore the matric potential. In addition, the effect of capillary rise on soil water state is also ignored. To address these problems, a flow model for partly and fully saturated soil, referred to as modified UBMOD, was developed in this study based on UBMOD and the water table depth fluctuation analysis. UBMOD is a soil water balance model that differs from other water balance models by considering soil water movement driven by matric potential. In the modified UBMOD, soil water flow and groundwater recharge rate are calculated using the original UBMOD algorithm, and water table depth is calculated using the water table depth fluctuation analysis. The field capacity used in the modified UBMOD was considered as a variable related to the water table depth to reflect the impact of capillary rise, which helps to obtain accurate water flux across the saturated–unsaturated interface. Two synthetic cases, simulated with HYDRUS, were used to test the sensitivities of the model parameters and specifications. Two real-world cases were used to show the fidelity of the model to the observed data. The results demonstrated that the model could solve the unsaturated–saturated problems based on more readily available parameters, without stringent requirements on spatial and time steps, with a full guarantee of water balance and low computational cost. This study provides an effective tool for hydrodynamic studies in areas with shallow water table depths. [ABSTRACT FROM AUTHOR]