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The effects of climate change and variability on river flows have been widely studied. However the impacts of such changes on sediment transport have received comparatively little attention. In part this is because modelling sediment production and transport processes introduces additional uncertainty, but it also results from the fact that, alongside the climate change signal, there have been and are projected to be significant changes in land cover which strongly affect sediment-related processes. Here we assess the impact of a range of climatic variations and land covers on the River Thames catchment (UK). We first calculate a response of the system to climatic stressors (average precipitation, average temperature and increase in extreme precipitation) and land-cover stressors (change in the extent of arable land). To do this we use an ensemble of INCA hydrological and sediment behavioural models. The resulting system response, which reveals the nature of interactions between the driving factors, is then compared with climate projections originating from the UKCP09 assessment (UK Climate Projections 2009) to evaluate the likelihood of the range of projected outcomes. The results show that climate and land cover each exert an individual control on sediment transport. Their effects vary depending on the land use and on the level of projected climate change. The suspended sediment yield of the River Thames in its lowermost reach is expected to change by −4% (−16% to +13%, confidence interval, p = 0.95) under the A1FI emission scenario for the 2030s, although these figures could be substantially altered by an increase in extreme precipitation, which could raise the suspended sediment yield up to an additional +10%. A 70% increase in the extension of the arable land is projected to increase sediment yield by around 12% in the lowland reaches. A 50% reduction is projected to decrease sediment yield by around 13%. [ABSTRACT FROM AUTHOR]

The article provides information on the effects of earthquake and cyclone sequencing on landsliding and fluvial sediment transfer in a mountain catchment. It is stated that strength, location, and sequencing of rain storms and earthquakes are the key determinants in identifying the patterns and rates of landsliding and fluvial sediment transfer. To be able to explore the scenario, mapping of landslides caused by three tropical cyclones and a very large earthquake in the Chenyoulan catchment in Taiwan Central Range has been done. Water and sediment discharges and rock strengths are also discussed to expound on the topic.

The physical river characteristics datasets described here provide spatially consistent information to support hydrological and inundation modelling at a 1 km × 1 km resolution across the United Kingdom, on the British National Grid. The datasets of physical river characteristics provide gridded datasets (outflow drainage directions, catchment areas, widths of bankfull rivers and depths of bankfull rivers) and a comma‐separated table of NRFA (National River Flow Archive) gauging station locations. These datasets are derived from a range of sources: outflow drainage directions, catchment area and bankfull river widths are derived from existing higher resolution datasets, whereas bankfull river depths were harder to source and instead are derived from sparse historical measurements. The new gridded datasets provide a derived value for each UK land cell on the British National Grid (BNG). The comma‐separated NRFA gauging station locations table provides the most appropriate locations of 1,499 river flow gauging stations on the 1 km resolution grids, together with the approximate error in the 1 km × 1 km gridded delineation of the upstream catchment area. This article explains how UK‐wide 1‐km grids of these variables were estimated, their format and how to use them. The data are available from the Environmental Information Data Centre (EIDC). [ABSTRACT FROM AUTHOR]

In this study, we quantify the climatological annual cycle of evaporation in the Congo Basin in Coupled Model Intercomparison Project 5 (CMIP5) models that took part in the Atmospheric Model Intercomparison Project (AMIP). We examine how the annual cycle of evaporation differs between models which perform well against the LandFlux-EVAL evaporation dataset, and models which do not. We then carry out a process-based assessment of the model evaporation to explain why these differences occur, and identify opportunities to improve how evaporation is represented across the model spectrum. In many models, evaporation decreases between March and November, despite an increase in rainfall. In better performing models, this drop in evaporation is particularly strong, and is typically explained by a strong drop in transpiration, as opposed to negligible changes in canopy evaporation and bare soil evaporation. Better performing models typically include a throughfall scheme based on rainfall intensity, which generates the strong drop in transpiration by adjusting canopy evaporation downward and transpiration upward, but only up to limits set by the annual cycle of leaf area. A secondary effect is to reduce evaporation across the annual cycle to values more comparable with LandFlux-EVAL. The results therefore suggest that extending a throughfall scheme based on rainfall intensity across the model spectrum has the potential to widely improve how models represent evaporation in the Congo Basin. [ABSTRACT FROM AUTHOR]

In order to advance our ability to predict the future availability of water resources and the risk of water related disasters under a changing climate, it is necessary to bring together the land surface and hydrological modelling communities. This presentation will describe Hydro-JULES, a new research programme funded by the UK's Natural Environment Research Council. The Hydro-JULES programme will build a three-dimensional, open source, community model of the terrestrial water cycle to support and enable collaborative work across the research and academic communities in hydrology and land-surface science. An advanced terrestrial hydrological model will be generated that couples to the Joint UK Land Environment Simulator (JULES) and related models, including the UK Met Office Unified Model. This new five-year programme, is supported by NERC National Capability funding and will be delivered by the Centre for Ecology and Hydrology (CEH) in partnership with the British Geological Survey (BGS) and National Centre for Atmospheric Science (NCAS). Hydro-JULES aims to address critical research questions in the fields of hydrology, land-atmosphere feedbacks, carbon and nutrient cycles, data science and integration with novel instrumentation and Earth observation technologies; quantify the risks of hydro-climatic extremes (e.g., floods and drought) in a changing environment to support long-range planning and policy decisions; improve hydrological forecasting using new sensors and modelling technology. The Hydro-JULES project covers topics in land-surface science and hydrology including: quantification of hydro-meteorological risks, using high-resolution climate predictions for hydrological applications, calculation the impacts of environmental change on evaporation, transpiration, and soil moisture, modelling flood inundation over large areas, representing anthropogenic interventions in the water cycle, and application of new techniques including Earth observation and data assimilation. The presentation will explore the scientific drivers for integrated land surface and hydrological modelling and outline the main elements of the structure of the work programme. We discuss the development of interfaces between components of the terrestrial water cycle to support integrated modelling of the water cycle and associated Earth system feedbacks, and describe mechanisms for community engagement and collaboration. [ABSTRACT FROM AUTHOR]

The national-scale British Groundwater Model (BGWM) is implemented to simulate groundwater dynamics and budgets in Great Britain. Notwithstanding the challenges of integrating a very large amount of data, finding a trade-off between computational efficiency and realism, performing automatic calibration, and addressing multiple sources of structural and parameter uncertainty, a quantitative–qualitive evaluation approach showed that the BGWM provides a reasonably accurate digital representation of groundwater systems and processes at a national scale. In this work, the model was applied to understand the variability of budget components across multiple spatial and temporal scales. Comparisons showed regional differences linked to lithological and climatic factors, which in turn can be associated with more or less groundwater resilience to extreme climatic events. There is confidence that the current and future versions of the BGWM can become valuable tools for effective water resources management and adaptation strategies under future climatic and population changes. [ABSTRACT FROM AUTHOR]

Droughts are among the most complex and devastating natural hazards globally. High-resolution datasets of drought metrics are essential for monitoring and quantifying the severity, duration, frequency, and spatial extent of droughts at regional and particularly local scales. However, current global drought indices are available only at a coarser spatial resolution (>50 km). To fill this gap, we developed four high-resolution (5 km) gridded drought records based on the standardized precipitation evaporation index (SPEI) covering the period 1981–2022. These multi-scale (1–48 months) SPEI indices are computed based on monthly precipitation (P) from the Climate Hazards Group InfraRed Precipitation with Station Data (CHIRPS, version 2) and Multi-Source Weighted-Ensemble Precipitation (MSWEP, version 2.8), and potential evapotranspiration (PET) from the Global Land Evaporation Amsterdam Model (GLEAM, version 3.7a) and hourly Potential Evapotranspiration (hPET). We generated four SPEI records based on all possible combinations of P and PET datasets: CHIRPS_GLEAM, CHIRPS_hPET, MSWEP_GLEAM, and MSWEP_hPET. These drought records were evaluated globally and exhibited excellent agreement with observation-based estimates of SPEI, root zone soil moisture, and vegetation health indices. The newly developed high-resolution datasets provide more detailed local information and can be used to assess drought severity for particular periods and regions and to determine global, regional, and local trends, thereby supporting the development of site-specific adaptation measures. These datasets are publicly available at the Centre for Environmental Data Analysis (CEDA; 10.5285/ac43da11867243a1bb414e1637802dec) (Gebrechorkos et al., 2023). [ABSTRACT FROM AUTHOR]

The land surface, hydrological, and groundwater modelling communities all have expertise in simulating the hydrological processes at play in the terrestrial component of the Earth system. However, these communities, and the wider Earth system modelling community, have largely remained distinct with limited collaboration between disciplines, hindering progress in the representation of hydrological processes in the land component of Earth system models (ESMs). In order to address key societal questions regarding the future availability of water resources and the intensity of extreme events such as floods and droughts in a changing climate, these communities must come together and build on the strengths of one another to produce next-generation land system models that are able to adequately simulate the terrestrial water cycle under change. The development of a common modelling infrastructure can contribute to stimulating cross-fertilisation by structuring and standardising the interactions. This paper presents such an infrastructure, a land system framework, which targets an intermediate level of complexity and constrains interfaces between components (and communities) and, in doing so, aims to facilitate an easier pipeline between the development of (sub-)community models and their integration, both for standalone use and for use in ESMs. This paper first outlines the conceptual design and technical capabilities of the framework; thereafter, its usage and useful characteristics are demonstrated through case studies. The main innovations presented here are (1) the interfacing constraints themselves; (2) the implementation in Python (the Unified Framework for Hydrology, unifhy); and (3) the demonstration of standalone use cases using the framework. The existing framework does not yet meet all our goals, in particular, of directly supporting integration into larger ESMs, so we conclude with the remaining limitations of the current framework and necessary future developments. [ABSTRACT FROM AUTHOR]

Poor water quality is a widespread issue in urban rivers and streams in London. Localised pollution can have impacts on local communities, from health issues to environmental degradation and restricted recreational use of water. The Salmons and Pymmes Brooks, located in the London Borough of Enfield, flow into the River Lee, and in this paper, the impacts of misconnected sewers, urban runoff and atmospheric pollution have been evaluated. The first step towards finding a sustainable and effective solution to these issues is to identify sources and paths of pollutants and to understand their cycle through catchments and rivers. The INCA water quality model has been applied to the Salmons and Pymmes urban catchments in north-east London, with the aim of providing local communities and community action groups such as Thames21 with a tool they can use to assess the water quality issue. INCA is a process-based, dynamic flow and quality model, and so it can account for daily changes in temperature, flow, water velocity and residence time that all affect reaction kinetics and hence chemical flux. As INCA is process-based, a set of mitigation strategies have been evaluated including constructed wetland across the catchment to assess pollution control. The constructed wetlands can make a significant difference reducing sediment transport and improving nutrient control for nitrogen and phosphorus. The results of this paper show that a substantial reduction in nitrate, ammonium and phosphorus concentrations can be achieved if a proper catchment-scale wetland implementation strategy is put in place. Furthermore, the paper shows how the nutrient reduction efficiency of the wetlands should not be affected by climate change. [ABSTRACT FROM AUTHOR]

Highlights • GloFAS was calibrated using daily streamflow data from 1287 stations worldwide. • Evolutionary Algorithm with parallel co-evolution of multiple simulations was used. • Parameters will be used in operational flood forecasting (www.globalfloods.eu). • Bias reduction in the forcings is needed to further improve the forecast skill. Abstract This paper presents the calibration and evaluation of the Global Flood Awareness System (GloFAS), an operational system that produces ensemble streamflow forecasts and threshold exceedance probabilities for large rivers worldwide. The system generates daily streamflow forecasts using a coupled H-TESSEL land surface scheme and the LISFLOOD model forced by ECMWF IFS meteorological forecasts. The hydrology model currently uses a priori parameter estimates with uniform values globally, which may limit the streamflow forecast skill. Here, the LISFLOOD routing and groundwater model parameters are calibrated with ECMWF reforecasts from 1995 to 2015 as forcing using daily streamflow data from 1287 stations worldwide. The calibration of LISFLOOD parameters is performed using an evolutionary optimization algorithm with the Kling-Gupta Efficiency (KGE) as objective function. The skill improvements are quantified by computing the skill scores as the change in KGE relative to the baseline simulation using a priori parameters. The results show that simulation skill has improved after calibration (KGE skill score > 0.08) for the large majority of stations during the calibration (67% globally and 77% outside of North America) and validation (60% globally and 69% outside of North America) periods compared to the baseline simulation. However, the skill gain was impacted by the bias in the baseline simulation (the lowest skill score was obtained in basins with negative bias) due to the limitation of the model in correcting the negative bias in streamflow. Hence, further skill improvements could be achieved by reducing the bias in the streamflow by improving the precipitation forecasts and the land surface model. The results of this work will have implications on improving the operational GloFAS flood forecasting (www.globalfloods.eu). [ABSTRACT FROM AUTHOR]

The combined indirect and direct impacts of land use change and climate change on river water quality were assessed. A land use allocation model was used to evaluate the response of the catchment land use to long-term climatic changes. Its results were used to drive a water quality model and assess the impact of climatic alterations on freshwater nitrate and phosphorus concentrations. Climatic projections were employed to estimate the likelihood of such response. The River Thames catchment (UK) was used as a case-study. If land use is considered as static parameter, according to the model results, climate change alone should reduce the average nitrate concentration, although just by a small amount, by the 2050s in the Lower Thames, due to reduced runoff (and lower export of nitrate from agricultural soils) and increased instream denitrification, and should increase the average phosphorus concentration by 12% by the 2050s in the Lower Thames, due to a reduction of the effluent dilution capacity of the river flow. However, the results of this study also show that these long-term climatic alterations are likely to lead to a reduction in the arable land in the Thames, replaced by improved grassland, due to a decrease in agriculture profitability in the UK. Taking into account the dynamic co-evolution of land use with climate, the average nitrate concentration is expected to be decreased by around 6% by the 2050s in both the upper and the lower Thames, following the model results, and the average phosphorus concentration increased by 13% in the upper Thames and 5% in the lower Thames. On the long term (2080s), nitrate is expected to decrease by 9% and 8% (upper and lower Thames respectively) and phosphorus not to change in the upper thames and increase by 5% in the lower Thames. [ABSTRACT FROM AUTHOR]

Potential increases of phytoplankton concentrations in river systems due to global warming and changing climate could pose a serious threat to the anthropogenic use of surface waters. Nevertheless, the extent of the effect of climatic alterations on phytoplankton concentrations in river systems has not yet been analysed in detail. In this study, we assess the impact of a change in precipitation and temperature on river phytoplankton concentration by means of a physically-based model. A scenario-neutral methodology has been employed to evaluate the effects of climate alterations on flow, phosphorus concentration and phytoplankton concentration of the River Thames (southern England). In particular, five groups of phytoplankton are considered, representing a range of size classes and pigment phenotypes, under three different land-use/land-management scenarios to assess their impact on phytoplankton population levels. The model results are evaluated within the framework of future climate projections, using the UK Climate Projections 09 (UKCP09) for the 2030s. The results of the model demonstrate that an increase in average phytoplankton concentration due to climate change is highly likely to occur, with the magnitude varying depending on the location along the River Thames. Cyanobacteria show significant increases under future climate change and land use change. An expansion of intensive agriculture accentuates the growth in phytoplankton, especially in the upper reaches of the River Thames. However, an optimal phosphorus removal mitigation strategy, which combines reduction of fertiliser application and phosphorus removal from wastewater, can help to reduce this increase in phytoplankton concentration, and in some cases, compensate for the effect of rising temperature. [ABSTRACT FROM AUTHOR]

A process-based phytoplankton model developed to simulate the movement and growth of phytoplankton in river systems is presented in this paper. The model is based on mass-balance, and takes into account water temperature, light, self-shading, dissolved phosphorus and silicon concentrations. It was implemented in five reaches of the River Thames (UK), and the results compared to a novel dataset of cytometric data which includes concentrations of chlorophytes, diatoms, cyanobacteria and picoalgae. A Multi-Objective General Sensitivity Analysis was carried out in order to test the model robustness and to quantify the sensitivity to its parameters. The results show a good agreement between the simulations and the measured phytoplankton abundance. The most influential parameters were phytoplankton growth and death rates, while phosphorus concentration showed little influence, due to the high concentration of phosphorus in the Thames. The model is an important step forward towards understanding and predicting algal dynamics in river systems. [ABSTRACT FROM AUTHOR]

Soil moisture is an important component of the Earth system and plays a key role in land-atmosphere interactions. Remote sensing of soil moisture is of great scientific interest and the scientific community has made significant progress in soil moisture estimation using Earth observations. Currently, several satellite-based coarse spatial resolution soil moisture datasets have been produced and widely used for various applications in climate science, hydrology, ecosystem research and agriculture. Owing to the strong demand for soil moisture data with high spatial resolution for regional applications, much effort has recently been devoted to the generation of high spatial resolution soil moisture data from either high-resolution satellite observations or by downscaling existing coarse-resolution satellite-based soil moisture datasets. In addition, land surface models provide an alternative way to obtain consistent high-resolution soil moisture information when forced with high-resolution inputs. The aim of this study is to create and evaluate high-resolution soil moisture products derived from multiple sources including satellite observations and land surface model simulations. The JULES-CHESS simulated soil moisture and satellite-based soil moisture datasets including SMAP L3E, SMAP L4, SMOS L4, Sentinel 1, ASCAT, and Sentinel 1/SMAP combined products were first validated against observed soil moisture from COSMOS-UK, a network of in-situ cosmic-ray based sensors. Second, an approach based on triple collocation was applied to compare these satellite products in the absence of a known reference dataset. Third, a combined soil moisture product was generated to integrate the better-performing soil moisture estimates based on triple collocation error estimation and a least-squares merging scheme. From further evaluation, it is found that the merged soil moisture integrates the characteristics of model simulation and satellite observations and particularly improves the limited temporal variability of the JULES-CHESS simulation. Therefore, we conclude that the triple collocation merging scheme is a simple and reliable way to combine satellite-based soil moisture products with outputs from the JULES-CHESS simulation for estimating model-data fused high-resolution soil moisture for the British mainland. • Evaluation of satellite and JULES-CHESS soil moisture against 38 COSMOS-UK sites. • SMAP L3E and JULES-CHESS show better performance compared to other products. • All products show high errors over surface with organic soils. • Blended soil moisture integrates both model and satellite characteristics. [ABSTRACT FROM AUTHOR]

• Water risks to the hydropower sector are estimated for 1.5C and 2.0C warmer worlds. • More frequent high river flows would be the dominant risk. • Longer droughts importantly expose planned capacities in developing regions. • Current and future hydropower capacities face combined water risks. Hydropower plays an important role within the renewable energy sector and supports the achievement of international energy security targets. Yet this sector is also vulnerable to droughts which affect generation potential, and high flows which can cause structural and operational damage. Here we use river flows calculated using a multi-model ensemble to investigate the potential water risks which current and planned global hydropower generation capacities may face at 1.5 °C and 2.0 °C warmer worlds. We find that the global hydropower sector will have to face diverse, simultaneous, and compound water risks. We estimate that about 65% of current global hydropower installed capacity will be exposed to risk from recurrent high river flows (here understood as the change in the 1-in-100-years flow). Up to 75% of existing hydropower capacity in Europe, North America and MENA is located in areas where droughts are projected to become at least 10% longer when compared to historical conditions. Achieving a 1.5 °C warming target would reduce these risks, compared to a 2.0 °C scenario. [ABSTRACT FROM AUTHOR]

The livelihoods of millions of people living in the world's deltas are deeply interconnected with the sediment dynamics of these deltas. In particular a sustainable supply of fluvial sediments from upstream is critical for ensuring the fertility of delta soils and for promoting sediment deposition that can offset rising sea levels. Yet, in many large river catchments this supply of sediment is being threatened by the planned construction of large dams. In this study, we apply the INCA hydrological and sediment model to the Mekong River catchment in South East Asia. The aim is to assess the impact of several large dams (both existing and planned) on the suspended sediment fluxes of the river. We force the INCA model with a climate model to assess the interplay of changing climate and sediment trapping caused by dam construction. The results show that historical sediment flux declines are mostly caused by dams built in PR China and that sediment trapping will increase in the future due to the construction of new dams in PDR Lao and Cambodia. If all dams that are currently planned for the next two decades are built, they will induce a decline of suspended sediment flux of 50% (47–53% 90% confidence interval (90%CI)) compared to current levels (99 Mt/year at the delta apex), with potentially damaging consequences for local livelihoods and ecosystems. Unlabelled Image • A sediment model has been used to estimate the impact of constructed and planned dams and climate change on the Mekong River • Reservoir storage capacity is forecasted to increase in the next two decades, with consequences for the sediment flux • Planned dams will reduce suspended sediment fluxes to the delta by up to 50% in the next twenty years • Climate change play a secondary role compared to dams • Historical declines are mostly attributed to dams in China, but future declines will be triggered by dams in Lao and Cambodia [ABSTRACT FROM AUTHOR]

Soil moisture observations are of broad scientific interest and practical value for a wide range of applications. The scientific community has made significant progress in estimating soil moisture from satellite-based Earth observation data, particularly in operationalizing coarse-resolution (25-50 km) soil moisture products. This review summarizes existing applications of satellite-derived soil moisture products and identifies gaps between the characteristics of currently available soil moisture products and the application requirements from various disciplines. We discuss the efforts devoted to the generation of high-resolution soil moisture products from satellite Synthetic Aperture Radar (SAR) data such as Sentinel-1 C-band backscatter observations and/or through downscaling of existing coarse-resolution microwave soil moisture products. Open issues and future opportunities of satellite-derived soil moisture are discussed, providing guidance for further development of operational soil moisture products and bridging the gap between the soil moisture user and supplier communities. • Applications of high-resolution satellite-based soil moisture products are reviewed. • The gaps between product characteristics and user requirements are identified. • Open issues and opportunities for developments of high-resolution satellite-based soil moisture products are discussed. [ABSTRACT FROM AUTHOR]

• The newly developed global long-term QA4ECV albedo and LAI datasets were applied for latent and sensible heat fluxes estimation. • The QA4ECV LAI leads to worse latent heat flux estimation due to its use of effective LAI rather than green leaf LAI. • The combined use of QA4ECV albedo and GLOBMAP LAI was suggested for latent and sensible heat fluxes estimation based on HOLAPS. The High resOlution Land Atmosphere surface Parameters from Space (HOLAPS) programme provides a modeling system to maximize the use of satellite-based products and ensure internally consistent estimation of surface water and energy fluxes. Leaf area index (LAI) and land surface albedo are two key parameters for estimation of latent and sensible heat fluxes with HOLAPS. Thus, to facilitate the generation of long-term high accuracy latent and sensible heat fluxes, high quality global long-term LAI and land surface albedo datasets are essential. The Quality Assurance for Essential Climate Variables (QA4ECV) project released quality-assured long-term LAI and albedo datasets with traceable and reliable uncertainty information provided in the dataset. Taking MODIS-BNU-LAI and MODIS albedo as reference, different global long-term LAI and albedo datasets including GlobAlbedo, QA4ECV and GLOBMAP were investigated for estimation of latent/sensible heat fluxes with HOLAPS in this study. The results show that all albedo datasets show similar accuracy for estimation of latent and sensible heat fluxes when validated against FLUXNET observations. The QA4ECV LAI leads to worse latent heat flux estimation due to its use of effective LAI rather than green leaf LAI. Sensitivity analysis also shows that the HOLAPS estimated latent heat flux (LE) is more sensitive to uncertainty in LAI than land surface albedo. Overall, the combined use of QA4ECV albedo and GLOBMAP LAI is suggested for estimation of latent/sensible heat fluxes with HOLAPS. The root mean square differences (RMSD) between estimations and FLUXNET measurements are 54 (30) W/m2 for hourly (monthly) latent heat flux, and 80.5 (24.5) W/m2 for sensible heat flux, which are comparable to estimates with MODIS and other reported studies. [ABSTRACT FROM AUTHOR]

As recent events have shown, simultaneous crop losses in different parts of the world can cause serious risks to global food security. However, to date, little is known about the spatial dependency of lower than expected crop yields from global breadbaskets. This especially applies in the case of extreme events, i.e., where one or more breadbaskets are experiencing far below average yields. Without such information, risk management approaches cannot be applied and vulnerability to extremes may remain high or even increase in the future around the world. We tackle both issues from an empirical perspective focusing on wheat yield. Interdependencies between historically observed wheat yield deviations in five breadbaskets (United States, Argentina, India, China, and Australia) are estimated via copula approaches that can incorporate increasing tail dependencies. In doing so, we are able to attach probabilities to interregional as well as global yield losses. To address the robustness of our results, we apply three different methods for constructing multivariate copulas: vine copulas, ordered coupling using a minimax approach, and hierarchical structuring. We found interdependencies between states within breadbaskets that led us to the conclusion that risk pooling for extremes is less favorable on the regional level. However, notwithstanding evidence of global climatic teleconnections that may influence crop production, we also demonstrate empirically that wheat production losses are independent between global breadbaskets, which strengthens the case for interregional risk pooling strategies. We argue that through interregional risk pooling, postdisaster liabilities of governments and international donors could be decreased., (© 2016 Society for Risk Analysis.)

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.

Understanding the competing pressures on water resources requires a detailed knowledge of the future water balance under uncertain environmental change. The need for a robust, scientifically rigorous evidence base for effective policy planning and practice has never been greater. Environmental change includes, but is not limited to, climate change; it also includes land-use and land-cover change, including deforestation for agriculture, and occurs alongside changes in anthropogenic interventions that are used in natural resource management such as the regulation of river flows using dams, which can have impacts that frequently exceed those arising in the natural system. In this paper, we examine the role that land surface models can play in providing a robust scientific basis for making resource management decisions against a background of environmental change. We provide some perspectives on recent developments in modelling in land surface hydrology. Among the range of current land surface and hydrology models, there is a large range of variability, which indicates that the specification and parametrization of several basic processes in the models can be improved. Key areas that require improvement in order to address hydrological applications include (i) the representation of groundwater in models, particularly at the scales relevant to land surface modelling, (ii) the representation of human interventions such as dams and irrigation in the hydrological system, (iii) the quantification and communication of uncertainty, and (iv) improved understanding of the impact on water resources availability of multiple use through treatment, recycling and return flows (and the balance of consumptive and conservative uses). Through a series of examples, we demonstrate that changes in water use could have important reciprocal impacts on climate over a wide area. The effects of water management decisions on climate feedbacks are only beginning to be investigated-they are still only rarely included in climate impact assessments-and the links between the hydrological system and climate are rarely acknowledged in studies of ecosystem services. Nevertheless, because water is essential not only for its direct uses but also for the indirect functions that it serves (including food production, fisheries and industry), it is vital that these connected systems are studied. Building on the examples above, we highlight recent research showing that assessment of these trade-offs is particularly complex in wetland areas, especially in situations where these trade-offs play to the advantage of different communities.