Spatial distribution of global runoff and its storage in river channels

The present dissertation attempts to improve our current understanding of some of the key elements of the surface runoff and its horizontal transfers in rivers. The dissertation presents an intensive analysis of the uncertainties in water balance calculations and the impact of uncertainties in the input data and the formulation of the water balance calculations on the runoff estimate. A simple technique is presented to combine observed river discharge and simulated runoff to derive accurate estimates of the spatially distributed runoff. Such composite runoff estimates are valuable for numerous earth science and water resource studies. The dissertation also discusses the representation of river networks for flow simulations. The performance of simulated river networks is analyzed with respect to resolution which provides guidance for the design of simulated river networks. New relationships are developed between river discharge and the riverbed geometry. These relationships provide the basis for the design of flow routing schemes incorporating the complete hydraulic dynamics of the riverine flow in the flow simulations. The dissertation demonstrates the use the composite runoff in a simulated river network context and the application of the relationships relating river discharge to flow properties to estimate the volume and surface of waters stored in rivers. The estimates agree well with previous estimates published in the scientific literature, but provide more insight into the spatial distribution of river water storage

TWINLATIN: Twinning European and Latin-American river basins for research enabling sustainable water resources management. Combined Report D3.1 Hydrological modelling report and D3.2 Evaluation report

Water use has almost tripled over the past 50 years and in some regions the water demand already exceeds supply (Vorosmarty et al., 2000). The world is facing a “global water crisis”; in many countries, current levels of water use are unsustainable, with systems vulnerable to collapse from even small changes in water availability. The need for a scientifically-based assessment of the potential impacts on water resources of future changes, as a basis for society to adapt to such changes, is strong for most parts of the world. Although the focus of such assessments has tended to be climate change, socio-economic changes can have as significant an impact on water availability across the four main use sectors i.e. domestic, agricultural, industrial (including energy) and environmental. Withdrawal and consumption of water is expected to continue to grow substantially over the next 20-50 years (Cosgrove & Rijsberman, 2002), and consequent changes in availability may drastically affect society and economies. One of the most needed improvements in Latin American river basin management is a higher level of detail in hydrological modelling and erosion risk assessment, as a basis for identification and analysis of mitigation actions, as well as for analysis of global change scenarios. Flow measurements are too costly to be realised at more than a few locations, which means that modelled data are required for the rest of the basin. Hence, TWINLATIN Work Package 3 “Hydrological modelling and extremes” was formulated to provide methods and tools to be used by other WPs, in particular WP6 on “Pollution pressure and impact analysis” and WP8 on “Change effects and vulnerability assessment”. With an emphasis on high and low flows and their impacts, WP3 was originally called “Hydrological modelling, flooding, erosion, water scarcity and water abstraction”. However, at the TWINLATIN kick-off meeting it was agreed that some of these issues resided more appropriately in WP6 and WP8, and so WP3 was renamed to focus on hydrological modelling and hydrological extremes. The specific objectives of WP3 as set out in the Description of Work are

Final Report of the DAUFIN project

DAUFIN = Data Assimulation within Unifying Framework for Improved river basiN modeling (EC 5th framework Project

Analysis and visualisation of digital elevation data for catchment management

River catchments are an obvious scale for soil and water resources management, since their shape and characteristics control the pathways and fluxes of water and sediment. Digital Elevation Models (DEMs) are widely used to simulate overland water paths in hydrological models. However, all DEMs are approximations to some degree and it is widely recognised that their characteristics can vary according to attributes such as spatial resolution and data sources (e.g. contours, optical or radar imagery). As a consequence, it is important to assess the ‘fitness for purpose’ of different DEMs and evaluate how uncertainty in the terrain representation may propagate into hydrological derivatives. The overall aim of this research was to assess accuracies and uncertainties associated with seven different DEMs (ASTER GDEM1, SRTM, Landform Panorama (OS 50), Landform Profile (OS 10), LandMap, NEXTMap and Bluesky DTMs) and to explore the implications of their use in hydrological analysis and catchment management applications. The research focused on the Wensum catchment in Norfolk, UK. The research initially examined the accuracy of the seven DEMs and, subsequently, a subset of these (SRTM, OS 50, OS10, NEXTMap and Bluesky) were used to evaluate different techniques for determining an appropriate flow accumulation threshold to delineate channel networks in the study catchment. These results were then used to quantitatively compare the positional accuracy of drainage networks derived from different DEMs. The final part of the thesis conducted an assessment of soil erosion and diffuse pollution risk in the study catchment using NEXTMap and OS 50 data with SCIMAP and RUSLE modelling techniques. Findings from the research demonstrate that a number of nationally available DEMs in the UK are simply not ‘fit for purpose’ as far as local catchment management is concerned. Results indicate that DEM source and resolution have considerable influence on modelling of hydrological processes, suggesting that for a lowland catchment the availability of a high resolution DEM (5m or better) is a prerequisite for any reliable assessment of the consequences of implementing particular land management measures. Several conclusions can be made from the research. (1) From the collection of DEMs used in this study the NEXTMap 5m DTM was found to be the best for representing catchment topography and is likely to prove a superior product for similar applications in other lowland catchments across the UK. (2) It is important that error modelling techniques are more routinely employed by GIS users, particularly where the fitness for purpose of a data source is not well-established. (3) GIS modelling tools that can be used to test and trial alternative management options (e.g. for reducing soil erosion) are particularly helpful in simulating the effect of possible environmental improvement measures

Flood Prediction and Mitigation in Data-Sparse Environments

In the last three decades many sophisticated tools have been developed that can accurately predict the dynamics of flooding. However, due to the paucity of adequate infrastructure, this technological advancement did not benefit ungauged flood-prone regions in the developing countries in a major way. The overall research theme of this dissertation is to explore the improvement in methodology that is essential for utilising recently developed flood prediction and management tools in the developing world, where ideal model inputs and validation datasets do not exist. This research addresses important issues related to undertaking inundation modelling at different scales, particularly in data-sparse environments. The results indicate that in order to predict dynamics of high magnitude stream flow in data-sparse regions, special attention is required on the choice of the model in relation to the available data and hydraulic characteristics of the event. Adaptations are necessary to create inputs for the models that have been primarily designed for areas with better availability of data. Freely available geospatial information of moderate resolution can often meet the minimum data requirements of hydrological and hydrodynamic models if they are supplemented carefully with limited surveyed/measured information. This thesis also explores the issue of flood mitigation through rainfall-runoff modelling. The purpose of this investigation is to assess the impact of land-use changes at the sub-catchment scale on the overall downstream flood risk. A key component of this study is also quantifying predictive uncertainty in hydrodynamic models based on the Generalised Likelihood Uncertainty Estimation (GLUE) framework. Detailed uncertainty assessment of the model outputs indicates that, in spite of using sparse inputs, the model outputs perform at reasonably low levels of uncertainty both spatially and temporally. These findings have the potential to encourage the flood managers and hydrologists in the developing world to use similar data sets for flood management

Mapping run-of-river hydropower resource of large catchments

There is overwhelming scientific evidence that shows the temperature of the Earth’s atmosphere is rising at an unprecedented rate. This is attributed to increased levels of greenhouse gas emissions, a large proportion of which originates from anthropogenic combustion of carbon-based fossil fuels for energy. There is therefore a strong argument for the increased role of less environmentally damaging, low carbon energy sources including renewable energy technologies. Run-of-river hydropower is one such renewable energy option, considered more environmentally benign than traditional hydropower which requires the construction of large dams to create a reservoir. The aim of this study was to develop a model to search for, and map, economically viable run-of-river hydropower resource that can function on any global catchment of any size. Development and testing of the model was conducted on China’s 2 million km2 Yangtze River drainage basin, the third longest river in the world and a rich landscape for hydropower. A gridded, distributed hydrological model was developed integrating high-resolution meteorological datasets and a digital elevation model (DEM). Using the model, the surface hydrology of the Yangtze catchment was simulated at a timestep of 6 minutes to obtain the mean daily surface runoff for every day from the beginning of 1979 to the end of 2007. Observed river flow data from sub-catchments of the Yangtze were used to calibrate the model by differential optimisation, an evolutionary computation technique. Validation was carried out on a 1.6 million km2 sub-catchment resulting in a mean objective function of 0.95 (where a perfect fit would be 1.0) across 8 objective functions commonly used in hydrology. Catchment wide mean daily runoff data was used to develop flow duration curves across the catchment river network. Virtual power stations were constructed at each river cell, iteratively testing differing scheme configurations, and costed using the RETScreen methodology. A best performing hydropower network was determined by a conflict algorithm, designed to prioritise high profit schemes and to remove lower performing and conflicting schemes. This resulted in a potential run-of-river installed capacity across the Yangtze catchment of 103GW (at 10% discount rate), generating 394TWh per annum. This model would be a valuable tool in finding optimal locations for future hydropower resource

Application of Topographic Analyses for Mapping Spatial Patterns of Soil Properties

Landscape topography is a key parameter impacting soil properties on the earth surface. Strong topographic controls on soil morphological, chemical, and physical properties have been reported. This chapter addressed applications of topographical information for mapping spatial patterns of soil properties in recent years. Objectives of this chapter are to provide an overview of (1) impacts of topographic heterogeneity on the spatial variability in soil properties and (2) commonly used topography-based models in soil science. A case study was provided to demonstrate the feasibility of applying topography-based models developed in field sites to predict soil property over a watershed scale. A large-scale soil property map can be obtained based on topographic information derived from high-resolution remotely sensed data, which would benefit studies in areas with limited data accesses or needed to extrapolate findings from representative sites to larger regions

A robust multi-purpose hydrological model for Great Britain

PhD ThesisRobust numerical models are an essential tool for informing ood and water management and policy around the world. Physically-based hydrological models have traditionally not been used for such applications due to prohibitively large data, time and computational resource requirements. Given recent advances in computing power and data availability, this study creates, for the rst time, a robust, physically-based hydrological modelling system for Great Britain using the SHETRAN model and national datasets. Such a model has several advantages over less complex systems. Firstly, compared with conceptual models, a national physically-based model is more readily applicable to ungauged catchments, in which hydrological predictions are also required. Secondly, the results of a physically-based system may be more robust under changing conditions such as climate and land cover, as physical processes and relationships are explicitly accounted for. Finally, a fully integrated surface and subsurface model such as SHETRAN o ers a wider range of applications compared with simpler schemes, such as assessments of groundwater resources, sediment transport and ooding from multiple sources. In order to develop a national modelling system based on SHETRAN, a large array of data for the whole of Great Britain and the period 1960-2006 has been integrated into a framework that features a new, user-friendly graphical interface, which extracts and prepares the data required for a SHETRAN simulation of any catchment in Great Britain. This has vastly reduced the time it takes to set up and run a model from months to seconds. Structural changes have also been incorporated into SHETRAN to better represent lakes, handle pits in elevation data and accept gridded meteorological inputs. 306 catchments spanning Great Britain were then modelled using this system. The standard con guration of this system performs satisfactorily (NSE > 0.5) for 72% of catchments and well (NSE > 0.7) for 48%. Many of the remaining 28% of catchments that performed relatively poorly (NSE < 0.5) are located in the chalk in the south east of England. As such, the British Geological Survey 3D geology model for Great Britain (GB3D) has been incorporated for the rst time in any hydrological model to pave the way for improvements to be made to simulations of catchments with important groundwater regimes. This coupling has involved development i of software to allow for easy incorporation of geological information into SHETRAN for any model setup. The addition of more realistic subsurface representation following this approach is shown to greatly improve model performance in areas dominated by groundwater processes. The sensitivity of the modelling system to key inputs and parameters was tested, particularly with respect to the distribution and rates of rainfall and potential evapotranspiration. As part of this, a new national dataset of gridded hourly rainfall was created by disaggregating the 5km UK Climate Projections 2009 (UKCP09) gridded daily rainfall product with partially quality controlled hourly rain gauge data from over 1300 observation stations across the country. Of the sensitivity tests undertaken, the largest improvements in model performance were seen when this hourly gridded rainfall dataset was combined with potential evapotranspiration disaggregated to hourly intervals, with 61% of catchments showing an increase in NSE as a result of more realistic sub-daily meteorological forcing. Additional sensitivity analysis revealed that the slight over-estimation of runo using the initial model con guration which has a median water balance bias of 5% was reduced in 62% of catchments by increasing daily potential evapotranspiration rates by 5%. Similarly, model performance was also found to improve by universally decreasing rainfall rates slightly, which together indicate the possibility of slight under-estimation of potential evapotranspiration derived from available data. In addition to extensive sensitivity testing, the national modelling system for Great Britain has also been coupled with the UKCP09 spatial weather generator to demonstrate the capability of the system to conduct climate change impact assessments. A set of 100 simulations for each of 20 representative catchments across the country were processed for a medium emissions scenario in the 2050s, in order to establish and demonstrate the methodology for conducting such an assessment. The results of these initial simulations suggest that higher potential evapotranspiration rates, combined with modest increases in rainfall under this climate change projection, lead to a general decrease in mean annual river ows. Changes in mean annual ow across the country vary between -26% to +8%, with the biggest reductions in ow found in the south of England and modest increases in runo across Scotland. This work represents a step-change in how the physically-based hydrological model SHETRAN can be used. Not only has this project made SHETRAN much easier to use on its own, but the model can now also be used in conjunction with external applications such as the UKCP09 spatial weather generator and GB3D. This means that the modelling system has great potential to be used as a resource at national, regional and local scales in an array of di erent applications, including climate change impact assessments, land cover change studies and integrated assessments of groundwater and surface water resources

Uncertainty analysis of 100-year flood maps under climate change scenarios

Floods are natural disastrous hazards that throughout history have had and still have major adverse impacts on people’s life, economy, and the environment. One of the useful tools for flood management are flood maps, which are developed to identify flood prone areas and can be used by insurance companies, local authorities and land planners for rescue and taking proper actions against flood hazards. Developing flood maps is often carried out by flood inundation modeling tools such as 2D hydrodynamic models. However, often flood maps are generated using a single deterministic model outcome without considering the uncertainty that arises from different sources and propagates through the modeling process. Moreover, the increasing number of flood events in the last decades combined with the effects of global climate change requires developing accurate and safe flood maps in which the uncertainty has been considered. Therefore, in this thesis the uncertainty of 100-year flood maps under 3 scenarios (present and future RCP4.5 and RCP8.5) is assessed through intensive Monte Carlo simulations. The uncertainty introduced by model input data namely, roughness coefficient, runoff coefficient and precipitation intensity (which incorporates three different sources of uncertainty: RCP scenario, climate model, and probability distribution function), is propagated through a surrogate hydrodynamic/hydrologic model developed based on a physical 2D model. The results obtained from this study challenge the use of deterministic flood maps and recommend using probabilistic approaches for developing safe and reliable flood maps. Furthermore, they show that the main source of uncertainty comes from the precipitation, namely the selected probability distribution compared to the selected RCP and climate model.publishedVersio