The contribution of soil structural degradation to catchment flooding: a preliminary investigation of the 2000 floods in England and Wales

Holman, Ian; Hollis, J. M.; Bramley, M. E.; Thompson, T. R. E.

doi:10.5194/hess-7-755-2003

Cited by 67 publications

(53 citation statements)

References 19 publications

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“…The Soil Conservation Service model was originally derived using data from small agricultural basins in the Midwest, including extensive areas of single land uses. As they were derived under specific conditions, the importability and relevance of curve number values to other locations is a hypothesis that has been suggested by several previous studies [Godwin and Dresser, 2003;Holman et al, 2003]. Note that curve numbers are not intended here to be applied directly for simulation of design rainfallrunoff events but as values that characterize the asymptotic features of rainfall-runoff time series [Hawkins, 1993;Van Mullem et al, 2002].…”

Section: Introductionmentioning

confidence: 95%

Bayesian conditioning of a rainfall-runoff model for predicting flows in ungauged catchments and under land use changes

Bulygina¹,

McIntyre²,

Ballard³

et al. 2010

Role of Hydrology in Managing Consequences of a Changing Global Environment

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[1] A novel method is presented for conditioning rainfall-runoff models for ungauged catchment and land use impact applications. The method conditions the model on information from multiple regionalized response indices using a formal Bayesian approach. Two indices that hold information about soil type and land use effects are the base flow index from the Hydrology of Soil Type (HOST) classification and curve number from the U.S. Department of Agriculture's Soil Conservation Service soil and land use classification. These indices are used to constrain a five-parameter probability distributed moisture model for subcatchments of the Wye (grazed grassland) and Severn (mainly afforested) catchments in the United Kingdom. The base flow index and curve number constrain only two of the five model parameters, indicating that ideally, other sources of information would be sought. Nevertheless, the procedure significantly reduces the prior uncertainty in runoff prediction and gives predictions close to those of the calibrated models. For the case study, the introduction of the curve number in addition to the base flow index has only a small effect on model performance and uncertainty; however, it allows a distinction between the effects of soil type and land management for the purpose of scenario analysis. The principal assumptions used in the method are the applicability of the curve number classification system and its mapping to UK soil types and the likelihood function used for Bayesian conditioning.

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Section: Introductionmentioning

confidence: 95%

Bayesian conditioning of a rainfall-runoff model for predicting flows in ungauged catchments and under land use changes

Bulygina¹,

McIntyre²,

Ballard³

et al. 2010

Role of Hydrology in Managing Consequences of a Changing Global Environment

View full text Add to dashboard Cite

show abstract

“…It was also evolved well beyond its original scope and it became an integral part of continuous simulation models (e.g. Adornado and Yoshida, 2010;Holman et al, 2003;Mishra and Singh, 2004;Moretti and Montanari, 2008;Soulis and Dercas, 2007). Many studies aiming at finding a theoretical basis for the method, facilitating its use in regions and for climate conditions not previously evaluated, and supporting its further improvement, were carried out as well (Hjelmfelt, 1991;Tramblay et al, 2010;Yu, 1998).…”

Section: Introductionmentioning

confidence: 99%

SCS-CN parameter determination using rainfall-runoff data in heterogeneous watersheds – the two-CN system approach

Soulis

Valiantzas

2012

Hydrol. Earth Syst. Sci.

207

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Abstract. The Soil Conservation Service Curve Number (SCS-CN) approach is widely used as a simple method for predicting direct runoff volume for a given rainfall event. The CN parameter values corresponding to various soil, land cover, and land management conditions can be selected from tables, but it is preferable to estimate the CN value from measured rainfall-runoff data if available. However, previous researchers indicated that the CN values calculated from measured rainfall-runoff data vary systematically with the rainfall depth. Hence, they suggested the determination of a single asymptotic CN value observed for very high rainfall depths to characterize the watersheds' runoff response. In this paper, the hypothesis that the observed correlation between the calculated CN value and the rainfall depth in a watershed reflects the effect of soils and land cover spatial variability on its hydrologic response is being tested. Based on this hypothesis, the simplified concept of a two-CN heterogeneous system is introduced to model the observed CNrainfall variation by reducing the CN spatial variability into two classes. The behaviour of the CN-rainfall function produced by the simplified two-CN system is approached theoretically, it is analysed systematically, and it is found to be similar to the variation observed in natural watersheds. Synthetic data tests, natural watersheds examples, and detailed study of two natural experimental watersheds with known spatial heterogeneity characteristics were used to evaluate the method. The results indicate that the determination of CN values from rainfall runoff data using the proposed two-CN system approach provides reasonable accuracy and it over performs the previous methods based on the determination of a single asymptotic CN value. Although the suggested method increases the number of unknown parameters to three (instead of one), a clear physical reasoning for them is presented.

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“…Cropping and stock management can have an impact on soil hydrology because access during wet periods can cause soil compaction and thus increased run-off (Holman et al, 2003). Soil structural degradation may be particularly related to late harvested crops such as maize, sugar beet, main crop potatoes and autumn sown crops.…”

Section: Impact Of Climate and Land Use Change On Recharge And Resourcesmentioning

confidence: 99%

A review of the impact of climate change on future nitrate concentrations in groundwater of the UK

Stuart

Gooddy

Bloomfield

et al. 2011

Science of The Total Environment

142

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This paper reviews the potential impacts of climate change on nitrate concentrations in groundwater of the UK using a Source-Pathway-Receptor framework. Changes in temperature, precipitation quantity and distribution, and atmospheric carbon dioxide concentrations will affect the agricultural nitrate source term through changes in both soil processes and agricultural productivity. Non-agricultural source terms, such as urban areas and atmospheric deposition, are also expected to be affected. The implications for the rate of nitrate leaching to groundwater as a result of these changes are not yet fully understood but predictions suggest that leaching rate may increase under future climate scenarios. Climate change will affect the hydrological cycle with changes to recharge, groundwater levels and resources and flow processes. These changes will impact on concentrations of nitrate in abstracted water and other receptors, such as surface water and groundwater-fed wetlands.The implications for nitrate leaching to groundwater as a result of climate changes are not yet well enough understood to be able to make useful predictions without more site-specific data.The few studies which address the whole cycle show likely changes in nitrate leaching ranging from limited increases to a possible doubling of aquifer concentrations by 2100.These changes may be masked by nitrate reductions from improved agricultural practices, but a range of adaption measures need to be identified. Future impact may also be driven by economic responses to climate change. The study draws on extensive literature mainly from the UK and so presents a UK-based perspective, although literature for other temperate climates is included to augment that from Keywordsthe UK and to demonstrate that the proposed framework and general conclusions have a wider applicability.The principal N input to UK groundwater is derived from manures, fertilisers, sewage sludges and crop residues in agricultural areas (DEFRA, 2006). There are also smaller inputs from urban point sources and aerial deposition (Wakida and Lerner, 2005). N fertiliser can be applied as urea or ammonia, as well as nitrate, but the non-nitrate forms are generally converted rapidly to nitrate in the soils of the UK (MAFF, 1999). A small percentage of applied N is lost to the atmosphere as NH 3 , NO or N 2 O (Destouni and Darracq, 2009;Skiba et al., 1997;Sommer and Hutchings, 1995). A proportion of soil N is leached as nitrate from the base of the soil. This is either stored in, or transmitted through, the unsaturated zone to groundwater. groundwater. They found that although an ensemble average suggests there will be about a 5% reduction in annual potential groundwater recharge across the study area, this was not statistically significant at the 95% confidence level and more importantly observed that the spread of results for simulated changes in annual potential groundwater recharge range from a 26% decrease to a 31% increase by the 2080s, with ten GCMs predicting a decrease and three a...

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The contribution of soil structural degradation to catchment flooding: a preliminary investigation of the 2000 floods in England and Wales

Cited by 67 publications

References 19 publications

Bayesian conditioning of a rainfall-runoff model for predicting flows in ungauged catchments and under land use changes

Bayesian conditioning of a rainfall-runoff model for predicting flows in ungauged catchments and under land use changes

SCS-CN parameter determination using rainfall-runoff data in heterogeneous watersheds – the two-CN system approach

A review of the impact of climate change on future nitrate concentrations in groundwater of the UK

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