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This paper applied the fuzzy function approach, combined with the ridge regression model, to produce daily rainfall projections from large-scale climate variables. This study developed a statistical downscaling model based on principal components, c-means fuzzy clustering, Volterra series, and ridge regression. The model is known, hereafter as SDC2R2. In the developed downscaling model, the use of ridge regression, instead of multiple linear regression, is proposed to downscale daily rainfall with wide range (WR) predictors. The WR predictors were applied to sufficiently incorporate climate change signals. The developed model also captured the non-linear interactions of the climate variables by applying the transformation of Volterra series realization over WR predictors. This transformation was performed by applying principal components as orthogonal filters. Further, these principal components were clustered by using c-means clustering and non-linear transformations were applied on these membership functions, to improve the prediction ability of the model. The reanalysis of climate data from the National Centres for Environmental Prediction (NCEP) was used to develop the model and was validated by using the Global Climate Model (GCM) for four locations in the Manawatu River basin. The developed model was used to obtain future daily rainfall projections from three Representative Concentrative Pathways (RCP 2.6, RCP 4.5, and RCP 8.5) scenarios from the Canadian Earth System Model (CanESM2) GCM. The performance of the model was compared with a widely used statistical downscaling model (SDSM). It was observed that the model performed better than SDSM in downscaling rainfall on a daily basis. Every scenario indicated that there is a probability of obtaining high future rainfall frequency. The results of this study provide valuable information for decision-makers since climate change may potentially impact the Manawatu basin. [ABSTRACT FROM AUTHOR]

Migrating bedforms in alluvial rivers can exacerbate scour damage at instream structures and lead to structural failure. This study investigates the interaction between scour at instream structures and bedform migration. Both two-dimensional (submerged weirs) and three-dimensional (uniform and complex piers) structures are considered. Two components constitute live-bed scour depth: the dynamic scour amplification Δds caused by bedforms and the local flow-induced baseline scour depth dsNB. Results show that, for 2D structures, the baseline scour depth is negligible, while the live-bed scour is mainly caused by approaching bedforms. The dynamic scour amplification normalised by the approaching bedform height (Δds/Hb) decreases with the decrease of upstream angle and varies between 0.5 and 2. For uniform 3D structures, the local flow could cause a considerable baseline scour depth, and Δds/Hb varies between 0.25 and 0.5 and decreases with the increase in the flow capacity to damp bedforms. For complex 3D structures, flow pressurisation beneath the pile-cap magnifies Δds/Hb to near 1. In general, Δds/Hb is inversely correlated with ds_NB/y0, where y0 is flow depth. New equations are proposed for estimating the dynamic scour amplification at various instream structures with design rules recommended. [ABSTRACT FROM AUTHOR]

Stormwater management systems rely on an acyclic network structure, making the network more vulnerable to failure. Existing stormwater resilience studies have predominantly focused on hydraulic and hydrological characteristics of the system with no robust frameworks to evaluate the resilience of the stormwater piped network in terms of network connectivity. This paper introduces a new index-based quantitative framework to characterise the resilience of acyclic stormwater network structure using graph theory and resilience theories. This includes an index developed to evaluate the overall independency of a pipe within an acyclic piped network. The framework was applied to various simple network structures, and an existing stormwater network demonstrating the influence of network structure, pipeline connectivity and number of outlets on the network resilience. This framework can be used to test different network layouts and structures in urban design and pipeline renewal projects to maximise the resilience of the structure of stormwater networks. [ABSTRACT FROM AUTHOR]