•INCA-sediment model applied to the Thames catchment (UK).•Scenario-neutral methodology used to assess response to climate and land-use.•Model uncertainty is estimated within a Monte Carlo-based ...framework.•Climate change and land use change exert a joint control on sediment transport.•Reducing the arable land is a robust mitigation strategy under a changing climate.
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%.
Water Science, Policy and Management Simon James Dadson, Dustin E. Garrick, Edmund C. Penning-Rowsell, Jim W. Hall, Rob Hope, Jocelyne Hughes / Simon James Dadson, Dustin E. Garrick, Edmund C. Penning-Rowsell, Jim W. Hall, Rob Hope, Jocelyne Hughes
2019, 2020, 2019-11-07, 2019-10-25
eBook
Provides an in-depth look at science, policy and management in the water sector across the globe Sustainable water management is an increasingly complex challenge and policy priority facing global ...society. This book examines how governments, municipalities, corporations, and individuals find sustainable water management pathways across competing priorities of water for ecosystems, food, energy, economic growth and human consumption. It looks at the current politics and economics behind the management of our freshwater ecosystems and infrastructure and offers insightful essays that help stimulate more intense and informed debate about the subject and its need for local and international cooperation. This book celebrates the 15-year anniversary of Oxford University's MSc course in Water Science, Policy and Management. Edited and written by some of the leading minds in the field, writing alongside alumni from the course, Water Science, Policy and Management: A Global Challenge offers in-depth chapters in three parts: Science; Policy; and Management. Topics cover: hydroclimatic extremes and climate change; the past, present, and future of groundwater resources; water quality modelling, monitoring, and management; and challenges for freshwater ecosystems. The book presents critical views on the monitoring and modelling of hydrological processes; the rural water policy in Africa and Asia; the political economy of wastewater in Europe; drought policy management and water allocation. It also examines the financing of water infrastructure; the value of wastewater; water resource planning; sustainable urban water supply and the human right to water. * Features perspectives from some of the world's leading experts on water policy and management * Identifies and addresses current and future water sector challenges * Charts water policy trends across a rapidly evolving set of challenges in a variety of global areas * Covers the reallocation of water; policy process of risk management; the future of the world's water under global environmental change; and more Water Science, Policy and Management: A Global Challenge is an essential book for policy makers and government agencies involved in water management, and for undergraduate and postgraduate students studying water science, governance, and policy.
Long short-term memory (LSTM) models are recurrent neural networks from the field of deep learning (DL) which have shown promise for time series modelling, especially in conditions when data are ...abundant. Previous studies have demonstrated the applicability of LSTM-based models for rainfall–runoff modelling; however, LSTMs have not been tested on catchments in Great Britain (GB). Moreover, opportunities exist to use spatial and seasonal patterns in model performances to improve our understanding of hydrological processes and to examine the advantages and disadvantages of LSTM-based models for hydrological simulation. By training two LSTM architectures across a large sample of 669 catchments in GB, we demonstrate that the LSTM and the Entity Aware LSTM (EA LSTM) models simulate discharge with median Nash–Sutcliffe efficiency (NSE) scores of 0.88 and 0.86 respectively. We find that the LSTM-based models outperform a suite of benchmark conceptual models, suggesting an opportunity to use additional data to refine conceptual models. In summary, the LSTM-based models show the largest performance improvements in the north-east of Scotland and in south-east of England. The south-east of England remained difficult to model, however, in part due to the inability of the LSTMs configured in this study to learn groundwater processes, human abstractions and complex percolation properties from the hydro-meteorological variables typically employed for hydrological modelling.
Evaporation is a crucial driver of Congo Basin climate, but the dynamics controlling the seasonality of basin evaporation are not well understood. This study aims to discover why evaporation on the ...basin-wide average is lower at the November rainfall peak than the March rainfall peak, despite similar rainfall. Using 16-year mean LandFlux-EVAL data, we find that evaporation is lower in November than March in the rainforest and the eastern savannah. The ERA5-Land reanalysis, which effectively reproduces this pattern, shows that transpiration is the main component responsible for lower evaporation in these regions. Using ERA5-Land, we find the following contrasting controls on transpiration, and therefore evaporation, at the two rainfall peaks: (a) In the northern rainforest, there is lower leaf area index (LAI) in November, driven by lower surface downward shortwave radiation (DSR), and lower vapour pressure deficit (VPD) in November, driven by lower sensible heat flux that results from lower net radiation. The combination of lower LAI and VPD explains lower transpiration, and therefore lower evaporation, in November. (b) In the southern rainforest, and in the north-eastern savannah, there is lower LAI in November, driven by lower surface DSR, and this explains lower transpiration, and therefore lower evaporation, in November. (c) In the south-eastern savannah, there is lower LAI in November, driven by lower volumetric water content (VWC), and this explains lower transpiration, and therefore lower evaporation, in November. Collectively, these contrasting controls at the two rainfall peaks explain why the basin-wide average evaporation is lower in November than March.
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.
•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.
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).
Statistics Analysis of Geographical Data: An Introduction provides a comprehensive and accessible introduction to the theory and practice of statistical analysis in geography. It covers a wide range ...of topics including graphical and numerical description of datasets, probability, calculation of confidence intervals, hypothesis testing, collection and analysis of data using analysis of variance and linear regression. Taking a clear and logical approach, this book examines real problems with real data from the geographical literature in order to illustrate the important role that statistics play in geographical investigations. Presented in a clear and accessible manner the book includes recent, relevant examples, designed to enhance the reader’s understanding.
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.
Key Points
We estimate that ARs contribute to about 22% of total global runoff with a number of regions reaching 50% or more
In several regions ARs are linked with up to 80% of floods; ARs absence may increase up to 90% the frequency of hydrological droughts events
Globally, we find that ~300 million people are exposed to additional flood and drought risk due to ARs
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. Long-term partitioning varies widely among catchments and the available data are currently not sufficient to discriminate control parameters effectively.
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