The erosion of mountain belts controls their topographic and structural evolution and is the main source of sediment delivered to the oceans. Mountain erosion rates have been estimated from current relief and precipitation, but a more complete evaluation of the controls on erosion rates requires detailed measurements across a range of timescales. Here we report erosion rates in the Taiwan mountains estimated from modern river sediment loads, Holocene river incision and thermochronometry on a million-year scale. Estimated erosion rates within the actively deforming mountains are high (3-6 mm yr(-1)) on all timescales, but the pattern of erosion has changed over time in response to the migration of localized tectonic deformation. Modern, decadal-scale erosion rates correlate with historical seismicity and storm-driven runoff variability. The highest erosion rates are found where rapid deformation, high storm frequency and weak substrates coincide, despite low topographic relief.

Email alerting servicescite this article to receive free e-mail alerts when new articles www.gsapubs.org/cgi/alerts click Subscribeto subscribe to Geology www.gsapubs.org/subscriptions/ click Permission requestto contact GSA http://www.geosociety.org/pubs/copyrt.htm#gsa click viewpoint. Opinions presented in this publication do not reflect official positions of the Society.positions by scientists worldwide, regardless of their race, citizenship, gender, religion, or political article's full citation. GSA provides this and other forums for the presentation of diverse opinions and articles on their own or their organization's Web site providing the posting includes a reference to the science. This file may not be posted to any Web site, but authors may post the abstracts only of their unlimited copies of items in GSA's journals for noncommercial use in classrooms to further education and to use a single figure, a single table, and/or a brief paragraph of text in subsequent works and to make GSA, employment. Individual scientists are hereby granted permission, without fees or further requests to

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Quantifying the effects of future changes in the frequency of precipitation extremes is a key challenge in assessing the vulnerability of hydrological systems to climate change but is difficult as climate models do not always accurately simulate daily precipitation. This article compares the performance of four published techniques used to reduce the bias in a regional climate model precipitation output: (1) linear, (2) nonlinear, (3) γ -based quantile mapping and (4) empirical quantile mapping. Overall performance and sensitivity to the choice of calibration period were tested by calculating the errors in the first four statistical moments of generated daily precipitation time series and using a cross-validation technique. The study compared the 1961-2005 precipitation time series from the regional climate model HadRM3.0-PPE-UK (unperturbed version) with gridded daily precipitation time series derived from rain gauges for seven catchments spread throughout Great Britain. We found that while the first and second moments of the precipitation frequency distribution can be corrected robustly, correction of the third and fourth moments of the distribution is much more sensitive to the choice of bias correction procedure and to the selection of a particular calibration period. Overall, our results demonstrate that, if both precipitation data sets can be approximated by a γ -distribution, the γ -based quantilemapping technique offers the best combination of accuracy and robustness. In circumstances where precipitation data sets cannot adequately be approximated using a γ -distribution, the nonlinear method is more effective at reducing the bias, but the linear method is least sensitive to the choice of calibration period. The empirical quantile mapping method can be highly accurate, but results were very sensitive to the choice of calibration time period. However, it should be borne in mind that bias correction introduces additional uncertainties, which are greater for higher order moments.

Flooding is a very costly natural hazard in the UK and is expected to increase further under future climate change scenarios. Flood defences are commonly deployed to protect communities and property from flooding, but in recent years flood management policy has looked towards solutions that seek to mitigate flood risk at flood-prone sites through targeted interventions throughout the catchment, sometimes using techniques which involve working with natural processes. This paper describes a project to provide a succinct summary of the natural science evidence base concerning the effectiveness of catchment-based ‘natural’ flood management in the UK. The evidence summary is designed to be read by an informed but not technically specialist audience. Each evidence statement is placed into one of four categories describing the nature of the underlying information. The evidence summary forms the appendix to this paper and an annotated bibliography is provided in the electronic supplementary material.

The partitioning of the total sediment load of a river into suspended load and bedload is an important problem in fluvial geomorphology, sedimentation engineering and sedimentology. Bedload transport rates are notoriously hard to measure and, at many sites, only suspended load data are available. Often the bedload fraction is estimated with 'rule of thumb' methods such as Maddock's Table, which are inadequately field-tested. Here, the partitioning of sediment load for the Pitzbach is discussed, an Austrian mountain stream for which high temporal resolution data on both bedload and suspended load are available. The available data show large scatter on all scales. The fraction of the total load transported in suspension may vary between zero and one at the Pitzbach, while its average decreases with rising discharge (i.e. bedload transport is more important during floods). Existing data on short-term and long-term partitioning is reviewed and an empirical equation to estimate bedload transport rates from measured suspended load transport rates is suggested. The partitioning averaged over a flood can vary strongly from event to event. Similar variations may occur in the year-to-year averages. Using published simultaneous short-term field measurements of bedload and suspended load transport rates, Maddock's Table is reviewed and updated. Long-term average partitioning could be a function of the catchment geology, the fraction of the catchment covered by glaciers and the extent of forest, but the available data are insufficient to draw final conclusions. At a given drainage area, scatter is large, but the data show a minimal fraction of sediment transported in suspended load, which increases with increasing drainage area and with decreasing rock strength for gravel-bed rivers, whereby in large catchments the bedload fraction is insignificant at ca 1%. For sand-bed rivers, the bedload fraction may be substantial (30% to 50%) even for large catchments. However, available data are scarce and of varying quality. Longterm partitioning varies widely among catchments and the available data are currently not sufficient to discriminate control parameters effectively.

Abstract. It is hypothesized that more accurate prediction and warning of natural hazards, such as of the impacts of severe weather mediated through various components of the environment, require a more integrated Earth System approach to forecasting. This hypothesis can be explored using regional coupled prediction systems, in which the known interactions and feedbacks between different physical and biogeochemical components of the environment across sky, sea and land can be simulated. Such systems are becoming increasingly common research tools. This paper describes the development of the UKC2 regional coupled research system, which has been delivered under the UK Environmental Prediction Prototype project. This provides the first implementation of an atmosphere-land-ocean-wave modelling system focussed on the United Kingdom and surrounding seas at km-scale resolution. The UKC2 coupled system incorporates models of the atmosphere (Met Office Unified Model), land surface with river routing (JULES), shelf-sea ocean (NEMO) and ocean waves (WAVEWATCH III). These components are coupled, via OASIS3-MCT libraries, at unprecedentedly high resolution across the UK within a north-western European regional domain. A research framework has been established to explore the representation of feedback processes in coupled and uncoupled modes, providing a new research tool for UK environmental science. This paper documents the technical design and implementation of UKC2, along with the associated evaluation framework. An analysis of new results comparing the output of the coupled UKC2 system with relevant forced control simulations for six contrasting case studies of 5-day duration is presented. Results demonstrate that performance can be achieved with the UKC2 system that is at least comparable to its component control simulations. For some cases, improvements in air temperature, sea surface temperature, wind speed, significant wave height and mean wave period highlight the potential benefits of coupling between environmental model components. Results also illustrate that the coupling itself is not sufficient to address all known model issues. Priorities for future development of the UK Environmental Prediction framework and component systems are discussed.

While emerging regional evidence shows that atmospheric rivers (ARs) can exert strong impacts on local water availability and flooding, their role in shaping global hydrological extremes has not yet been investigated. Here we quantify the relative contribution of ARs variability to both flood hazard and water availability. We find that globally, precipitation from ARs contributes 22% of total global runoff, with a number of regions reaching 50% or more. In areas where their influence is strongest, ARs may increase the occurrence of floods by 80%, while absence of ARs may increase the occurrence of hydrological droughts events by up to 90%. We also find that ~300 million people are exposed to additional floods and droughts due the occurrence of ARs. ARs provide a source of hydroclimatic variability whose beneficial or damaging effects depend on the capacity of water resources managers to predict and adapt to them.