Abstract. Research on regionalisation in hydrology has been constantly advancing due to the need for prediction of streamflow in ungauged catchments. There are two types of studies that use regionalisation techniques for ungauged catchments. One type estimates parameters of streamflow statistics, flood quantiles in most cases. The other type estimates parameters of a rainfall-runoff model for simulating continuous streamflow or estimates continuous streamflow without using a model. Almost all methods applied to the latter can be applied to the former. This paper reviews all methods that are applied to continuous streamflow estimation for ungauged catchments. We divide them into two general categories: (1) distance-based and (2) regression-based. Methods that fall within each category are reviewed first and followed with a discussion on merits or problems associated with these various methods.

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The evidence provided by modelled assessments of future climate impact on flooding is fundamental to water resources and flood risk decision making. Impact models usually rely on climate projections from global and regional climate models (GCM/RCMs). However, challenges in representing precipitation events at catchment-scale resolution mean that decisions must be made on how to appropriately pre-process the meteorological variables from GCM/RCMs. Here the impacts on projected high flows of differing ensemble approaches and application of Model Output Statistics to RCM precipitation are evaluated while assessing climate change impact on flood hazard in the Upper Severn catchment in the UK. Various ensemble projections are used together with the HBV hydrological model with direct forcing and also compared to a response surface technique. We consider an ensemble of single-model RCM projections from the current UK Climate Projections (UKCP09); multi-model ensemble RCM projections from the European Union's FP6 'ENSEMBLES' project; and a joint probability distribution of precipitation and temperature from a GCM-based perturbed physics ensemble.The ensemble distribution of results show that flood hazard in the Upper Severn is likely to increase compared to present conditions, but the study highlights the differences between the results from different ensemble methods and the strong assumptions made in using Model Output Statistics to produce the estimates of future river discharge. The results underline the challenges in using the current generation of RCMs for local climate impact studies on flooding.

ABSTRACT:The incorporation of numerical weather predictions (NWP) into a flood warning system can increase forecast lead times from a few hours to a few days. A single NWP forecast from a single forecast centre, however, is insufficient as it involves considerable non-predictable uncertainties and can lead to a high number of false or missed warnings. Weather forecasts using multiple NWPs from various weather centres implemented on catchment hydrology can provide significantly improved early flood warning. The availability of global ensemble weather prediction systems through the 'THORPEX Interactive Grand Global Ensemble' (TIGGE) offers a new opportunity for the development of state-of-theart early flood forecasting systems. This paper presents a case study using the TIGGE database for flood warning on a meso-scale catchment (4062 km 2 ) located in the Midlands region of England. For the first time, a research attempt is made to set up a coupled atmospheric-hydrologic-hydraulic cascade system driven by the TIGGE ensemble forecasts. A probabilistic discharge and flood inundation forecast is provided as the end product to study the potential benefits of using the TIGGE database. The study shows that precipitation input uncertainties dominate and propagate through the cascade chain. The current NWPs fall short of representing the spatial precipitation variability on such a comparatively small catchment, which indicates need to improve NWPs resolution and/or disaggregating techniques to narrow down the spatial gap between meteorology and hydrology. The spread of discharge forecasts varies from centre to centre, but it is generally large and implies a significant level of uncertainties. Nevertheless, the results show the TIGGE database is a promising tool to forecast flood inundation, comparable with that driven by raingauge observation.

Coastal regions are dynamic areas that often lie at the junction of different natural hazards. Extreme events such as storm surges and high precipitation are significant sources of concern for flood management. As climatic changes and sea-level rise put further pressure on these vulnerable systems, there is a need for a better understanding of the implications of compounding hazards. Recent computational advances in hydraulic modelling offer new opportunities to support decision-making and adaptation. Our research makes use of recently released features in the HEC-RAS version 5.0 software to develop an integrated 1D-2D hydrodynamic model. Using extreme value analysis with the Peaks-Over-Threshold method to define extreme scenarios, the model was applied to the eastern coast of the UK. The sensitivity of the protected wetland known as the Broads to a combination of fluvial, tidal and coastal sources of flooding was assessed, accounting for different rates of twenty-first century sea-level rise up to the year 2100. The 1D-2D approach led to a more detailed representation of inundation in coastal urban areas, while allowing for interactions with more fluvially dominated inland areas to be captured. While flooding was primarily driven by increased sea levels, combined events exacerbated flooded area by 5-40% and average depth by 10-32%, affecting different locations depending on the scenario. The results emphasise the importance of catchment-scale strategies that account for potentially interacting sources of flooding. Keywords Flooding Á Hydraulic modelling Á Storm surge Á Sea-level rise Á Compound hazard Á Extreme value analysis

Abstract. Dynamical downscaling of Global Climate Models (GCMs) through regional climate models (RCMs) potentially improves the usability of the output for hydrological impact studies. However, a further downscaling or interpolation of precipitation from RCMs is often needed to match the precipitation characteristics at the local scale. This study analysed three Model Output Statistics (MOS) techniques to adjust RCM precipitation; (1) a simple direct method (DM), (2) quantile-quantile mapping (QM) and (3) a distributionbased scaling (DBS) approach. The modelled precipitation was daily means from 16 RCMs driven by ERA40 reanalysis data over the 1961-2000 provided by the ENSEM-BLES (ENSEMBLE-based Predictions of Climate Changes and their Impacts) project over a small catchment located in the Midlands, UK. All methods were conditioned on the entire time series, separate months and using an objective classification of Lamb's weather types. The performance of the MOS techniques were assessed regarding temporal and spatial characteristics of the precipitation fields, as well as modelled runoff using the HBV rainfall-runoff model. The results indicate that the DBS conditioned on classification patterns performed better than the other methods, however an ensemble approach in terms of both climate models and downscaling methods is recommended to account for uncertainties in the MOS methods.

Agricultural diffuse water pollution remains a notable global pressure on water quality, posing risks to aquatic ecosystems, human health and water resources and as a result legislation has been introduced in many parts of the world to protect water bodies. Due to their efficiency and cost-effectiveness, water quality models have been increasingly applied to catchments as Decision Support Tools (DSTs) to identify mitigation options that can be introduced to reduce agricultural diffuse water pollution and improve water quality. In this study, the Soil and Water Assessment Tool (SWAT) was applied to the River Wensum catchment in eastern England with the aim of quantifying the long-term impacts of potential changes to agricultural management practices on river water quality. Calibration and validation were successfully performed at a daily time-step against observations of discharge, nitrate and total phosphorus obtained from high-frequency water quality monitoring within the Blackwater sub-catchment, covering an area of 19.6 km(2). A variety of mitigation options were identified and modelled, both singly and in combination, and their long-term effects on nitrate and total phosphorus losses were quantified together with the 95% uncertainty range of model predictions. Results showed that introducing a red clover cover crop to the crop rotation scheme applied within the catchment reduced nitrate losses by 19.6%. Buffer strips of 2 m and 6 m width represented the most effective options to reduce total phosphorus losses, achieving reductions of 12.2% and 16.9%, respectively. This is one of the first studies to quantify the impacts of agricultural mitigation options on long-term water quality for nitrate and total phosphorus at a daily resolution, in addition to providing an estimate of the uncertainties of those impacts. The results highlighted the need to consider multiple pollutants, the degree of uncertainty associated with model predictions and the risk of unintended pollutant impacts when evaluating the effectiveness of mitigation options, and showed that high-frequency water quality datasets can be applied to robustly calibrate water quality models, creating DSTs that are more effective and reliable.

Located in a transition zone between the northern and southern climates in China, the Huai River Basin is prone to extreme events such as drought and flood. Based on the daily precipitation data at 134 stations between 1961 and 2013, this paper analyzed the spatial and temporal patterns of the dry and wet conditions in the Huai River Basin through the statistical analysis of the rainfall stations' annual and seasonal standard precipitation index (SPI) series. Annual SPI series exhibited a decreasing trend at 86 stations and an increasing trend at the remaining stations. None of the increasing trend was significant, while the decreasing trend was significant at two stations at 5% significance level (=0.05) and one station at 10% level. Seasonal-wise, there has been a prevailing trend of drying in spring and autumn, and wetting in summer and winter.The trends in the spring and summer SPI series have been mostly insignificant, while those in autumn and winter significant (=0.10) at over 30 stations. The Pettitt test results indicated that the significant transitions (=0.10) in the autumn and winter SPI series mostly occurred in the middle to late 1980's. Comparison of the average number of dry and wet years between the two sub-periods of 1961-1984 and 1990-2013 suggested a significant increase (=0.05) in the average number of severely wet years across much of the basin. Overall, significant changes have already occurred in the dry and wet conditions of the Huai River Basin, which could have profound impacts on the food and water safety situation of the region.