An approach to propagate streamflow statistics along the river network

Streamflow at ungauged sites is often predicted by means of regional statistical procedures. The standard regional approaches do not preserve the information related to the hierarchy among gauged stations deriving from their location along the river network. However, this information is important when estimating runoff at a site located immediately upstream or downstream of a gauging station. We propose here a novel approach, referred to as the Along-Stream Estimation (ASE) method, to improve runoff estimation at ungauged sites. The ASE approach starts from the regional estimate at an ungauged (target) site, and corrects it based on regional and sample estimates of the same variable at a donor site, where sample data are available. A criterion to define the domain of application around each donor site of the ASE approach is proposed, and the uncertainty inherent in the estimates obtained is evaluated. This allows one to compare the variance of the along-stream estimates to that of other models that eventually become available for application (e.g. regional models), and thus to choose the most accurate method (or to combine different estimates). The ASE model was applied in the northwest of Italy in connection with an existing regional model for flood frequency analysis. The analysed variables are the first L-moments of the annual discharge maxima. The application demonstrates that the ASE approach can be used effectively to improve the regional estimates for the L-moment of order one (the index flood), particularly when the area ratio of a pair of donor-target basins is less than or equal to ten. However, in this case study, the method does not provide significant improvements to the estimation of higher-order L-moment

A Process‐Based Framework to Characterize and Classify Runoff Events: The Event Typology of Germany

This study proposes a new process‐based framework to characterize and classify runoff events of various magnitudes occurring in a wide range of catchments. The framework uses dimensionless indicators that characterize space–time dynamics of precipitation events and their spatial interaction with antecedent catchment states, described as snow cover, distribution of frozen soils, and soil moisture content. A rigorous uncertainty analysis showed that the developed indicators are robust and regionally consistent. Relying on covariance‐ and ratio‐based indicators leads to reduced classification uncertainty compared to commonly used (event‐based) indicators based on absolute values of metrics such as duration, volume, and intensity of precipitation events. The event typology derived from the proposed framework is able to stratify events that exhibit distinct hydrograph dynamics even if streamflow is not directly used for classification. The derived typology is therefore able to capture first‐order controls of event runoff response in a wide variety of catchments. Application of this typology to about 180,000 runoff events observed in 392 German catchments revealed six distinct regions with homogeneous event type frequency that match well regions with similar behavior in terms of runoff response identified in Germany. The detected seasonal pattern of event type occurrence is regionally consistent and agrees well with the seasonality of hydroclimatic conditions. The proposed framework can be a useful tool for comparative analyses of regional differences and similarities of runoff generation processes at catchment scale and their possible spatial and temporal evolution

Soil water content in southern England derived from a cosmic-ray soil moisture observing system - COSMOS-UK

Cosmic-ray soil moisture sensors have the advantage of a large measurement footprint (approximately 700 m in diameter) and are able to operate continuously to provide area-averaged near-surface (top 10-20 cm) volumetric soil moisture content at the field scale. This paper presents the application of this technique at four sites in southern England over almost 3 years. Results show the soil moisture response to contrasting climatic conditions during 2011-2014, and are the first such field-scale measurements made in the UK. These four sites are prototype stations for a UK COsmic-ray Soil Moisture Observing System (COSMOS-UK), and particular consideration is given to sensor operating conditions in the UK. Comparison of these soil water content observations with the Joint UK Land Environment Simulator (JULES) 10 cm soil moisture layer shows that these data can be used to test and diagnose model performance, and indicates the potential for assimilation of these data into hydro-meteorological models. The application of these large-area soil water content measurements to evaluate remotely-sensed soil moisture products is also demonstrated. Numerous applications and the future development of a national COSMOS-UK network are discussed

Super Storm Desmond: a process-based assessment

“Super” Storm Desmond broke meteorological and hydrological records during a record warm year in the British-Irish Isles (BI). The severity of the storm may be a harbinger of expected changes to regional hydroclimate as global temperatures continue to rise. Here, we adopt a process-based approach to investigate the potency of Desmond, and explore the extent to which climate change may have been a contributory factor. Through an Eulerian assessment of water vapour flux we determine that Desmond was accompanied by an Atmospheric River (AR) of severity unprecedented since at least 1979, on account of both high atmospheric humidity and high wind speeds. Lagrangian air-parcel tracking and moisture attribution techniques show that long-term warming of North Atlantic sea surface temperatures (SSTs) has significantly increased the chance of such high humidity in ARs in the vicinity of the BI. We conclude that, given exactly the same dynamical conditions associated with Desmond, the likelihood of such an intense AR has already increased by 25% due to long-term climate change. However, our analysis represents a first-order assessment, and further research is needed into the controls influencing AR dynamics

Tuberculosis and Indoor Biomass and Kerosene Use in Nepal: A Case–Control Study

BackgroundIn Nepal, tuberculosis (TB) is a major problem. Worldwide, six previous epidemiologic studies have investigated whether indoor cooking with biomass fuel such as wood or agricultural wastes is associated with TB with inconsistent results.ObjectivesUsing detailed information on potential confounders, we investigated the associations between TB and the use of biomass and kerosene fuels.MethodsA hospital-based case-control study was conducted in Pokhara, Nepal. Cases (n = 125) were women, 20-65 years old, with a confirmed diagnosis of TB. Age-matched controls (n = 250) were female patients without TB. Detailed exposure histories were collected with a standardized questionnaire.ResultsCompared with using a clean-burning fuel stove (liquefied petroleum gas, biogas), the adjusted odds ratio (OR) for using a biomass-fuel stove was 1.21 [95% confidence interval (CI), 0.48-3.05], whereas use of a kerosene-fuel stove had an OR of 3.36 (95% CI, 1.01-11.22). The OR for use of biomass fuel for heating was 3.45 (95% CI, 1.44-8.27) and for use of kerosene lamps for lighting was 9.43 (95% CI, 1.45-61.32).ConclusionsThis study provides evidence that the use of indoor biomass fuel, particularly as a source of heating, is associated with TB in women. It also provides the first evidence that using kerosene stoves and wick lamps is associated with TB. These associations require confirmation in other studies. If using kerosene lamps is a risk factor for TB, it would provide strong justification for promoting clean lighting sources, such as solar lamps

Urban and river flooding: Comparison of flood risk management approaches in the UK and China and an assessment of future knowledge needs

Increased urbanisation, economic growth, and long-term climate variability have made both the UK and China more susceptible to urban and river flooding, putting people and property at increased risk. This paper presents a review of the current flooding challenges that are affecting the UK and China and the actions that each country is undertaking to tackle these problems. Particular emphases in this paper are laid on (1) learning from previous flooding events in the UK and China, and (2) which management methodologies are commonly used to reduce flood risk. The paper concludes with a strategic research plan suggested by the authors, together with proposed ways to overcome identified knowledge gaps in flood management. Recommendations briefly comprise the engagement of all stakeholders to ensure a proactive approach to land use planning, early warning systems, and water-sensitive urban design or redesign through more effective policy, multi-level flood models, and data driven models of water quantity and quality

Combining information from multiple flood projections in a hierarchical Bayesian framework

This study demonstrates, in the context of flood frequency analysis, the potential of a recently proposed hierarchical Bayesian approach to combine information from multiple models. The approach explicitly accommodates shared multi-model discrepancy as well as the probabilistic nature of the flood estimates, and treats the available models as a sample from a hypothetical complete (but unobserved) set of models. The methodology is applied to flood estimates from multiple hydrological projections (the Future Flows Hydrology dataset) for 135 catchments in the UK. The advantages of the approach are shown to be: 1) to ensure adequate ‘baseline' with which to compare future changes; 2) to reduce flood estimate uncertainty; 3) to maximise use of statistical information in circumstances where multiple weak predictions individually lack power, but collectively provide meaningful information; 4) to diminish the importance of model consistency when model biases are large; and 5) to explicitly consider the influence of the (model performance) stationarity assumption. Moreover, the analysis indicates that reducing shared model discrepancy is the key to further reduction of uncertainty in the flood frequency analysis. The findings are of value regarding how conclusions about changing exposure to flooding are drawn, and to flood frequency change attribution studies. This article is protected by copyright. All rights reserved

Artificial drainage of peatlands: hydrological and hydrochemical process and wetland restoration

Peatlands have been subject to artificial drainage for centuries. This drainage has been in response to agricultural demand, forestry, horticultural and energy properties of peat and alleviation of flood risk. However, the are several environmental problems associated with drainage of peatlands. This paper describes the nature of these problems and examines the evidence for changes in hydrological and hydrochemical processes associated with these changes. Traditional black-box water balance approaches demonstrate little about wetland dynamics and therefore the science of catchment response to peat drainage is poorly understood. It is crucial that a more process-based approach be adopted within peatland ecosystems. The environmental problems associated with peat drainage have led, in part, to a recent reversal in attitudes to peatlands and we have seen a move towards wetland restoration. However, a detailed understanding of hydrological, hydrochemical and ecological process-interactions will be fundamental if we are to adequately restore degraded peatlands, preserve those that are still intact and understand the impacts of such management actions at the catchment scale