In this paper, we present a study of assessing regional water resources in a highly regulated river basin, the Dee river basin in the UK. The aims of this study include: 1) to address the issue of hydrological simulations for regulated river catchments; 2) to develop a new method revealing the trends of water resources for different scenarios (e.g. dry and wet) and 3) to facilitate water resources assessment under both climate change impacts and regulations. We use the SWAT model to model the hydrological process of the river basin with carefully designed configurations to isolate the impact from the water use regulations and practice. The spatially-distributed model simulations are then analysed with the quantile regression method to reveal the spatial and temporal patterns of regional water resources. The results show that this approach excels in presenting distributed, spatially focused trend information for extremely dry and wet scenarios, which can well address the needs of practitioners and decisionmakers in dealing with long-term planning and climate change impact. The representation of the management practice in the modelling process helps identify the impact from both climate change and necessary regulatory practices, and as such lays a foundation for further study on how various management practices can mitigate the impact from other sources such as those from climate change. The novelty of the study lies in three aspects: 1) it devises a new way of isolating and representing management practice in the hydrological modelling process for regulated river basins; 2) it integrates the QR technique to study spatial-temporal trends of catchment water yield in a distributed fashion, for wet and dry scenarios instead of the mean; 3) the combination of the methods are able to reveal the impacts from various sources as well as their interactions with catchment water resources.

Zirconia-toughened alumina (ZTA) using yttria-stabilised zirconia is a good option for ceramic-ceramic bearing couples for hip joint replacement. Gelcasting is a colloidal processing technique capable of producing complex products with a range of dimensions and materials by a relatively low-cost production process. Using gelcasting, ZTA samples were prepared, optimising the stages of fabrication, including slurry preparation with varying solid loadings, moulding and de-moulding, drying and sintering. Density, hardness, fracture toughness, flexural strength and grain size were observed relative to slurry solid loadings between 58 and 62 vol. %, as well as sintering temperatures of 1550 °C and 1650 °C. Optimal conditions found were plastic mould, 4000 g/mol PEG with 30 vol. % concentration, 61% solid loading and Ts = 1550 °C. ZTA samples of high density (maximum 99.1%), high hardness (maximum 1902 HV), high fracture toughness (maximum 5.43 MPa m1/2) and high flexural strength (maximum 618 MPa) were successfully prepared by gelcasting and pressureless sintering.

Effective representation of precipitation inputs is one of the essential components in hydrological model structures, especially when gauge measurements for the modelled catchment are sparse. Assessment of the impact of precipitation pre-processing is often nontrivial as precipitation data are very limited in the first place. In this paper, we demonstrate a study using a semi-distributed hydrological model, the Soil and Water Assessment Tool (SWAT) to examine the impact of different precipitation pre-processing methods on model calibration and the overall model performance with regards to the operational use. A river catchment in the UK is modelled to test against the three pre-processing methods: the Centroid Point Estimation Method (CPEM), the Grid Area Method (GAM) and the Grid Point Method (GPM). Cross-calibration and validation are then carried out by using the high-resolution Centre for Ecology & Hydrology–Gridded Estimate Areal Rainfall (CEH-GEAR) dataset. The results show that the proposed methods GAM and GPM can improve the model calibration significantly against the one calibrated with the existing CPEM method used by the model; the performance differences in the validation among the calibrated models, however, remain small and become irrelevant. The findings indicate that it is preferable to always make use of high-quality rainfall data, when available, with a better pre-processing method, even with models that are previously calibrated with low-quality rainfall inputs. It is also shown that such improvements are affected by the size of catchment and become less significant for smaller catchments.

Accurate simulation of both land surface and groundwater hydrologic processes in river catchments is an important step for integrated water resources management, particularly for catchments where both surface water and groundwater resources are used conjunctively. In this paper, we present a study on a complex river catchmentthe Dee River catchment in the United Kingdom using a coupled land surface model (SWAT) and groundwater model (MODFLOW) to improve the performances of both models otherwise used separately, hence serving the IWRM goals of optimizing conjunctive use of surface and groundwater. The model can also be used to evaluate the sensitivity of stream flows to changing climate, groundwater extraction, and land use alternations. Preliminary results show that the coupled model can improve river flow simulation especially baseflow simulation while significantly improving the overall water balance model simulations during periods of low flow.