The influence of soil moisture conditions on the spatio-temporal variability of event rainfall-runoff coefficients in UK catchments

2021 ◽  
Author(s):  
Yanchen Zheng ◽  
Ross Woods ◽  
Jianzhu Li ◽  
Ping Feng
Keyword(s):  
Soil Moisture ◽  
Temporal Variability ◽  
Estimation Methods ◽  
Runoff Coefficient ◽  
Rainfall Runoff ◽  
Design Flood ◽  
Ungauged Catchments ◽  
Flood Estimation ◽  
Spatio Temporal ◽  
Moisture Conditions

<p>Since the bias and uncertainties of the current design flood estimation methods for ungauged catchments are inevitable, estimation of the design flood in ungauged catchments still remains an unsolved problem. The derived distribution approach appears to be the one of the promising design flood estimation methods, as this method can improve the understanding on which processes contribute most to flood in ungauged catchments. Generally, the distribution of rainfall characteristics and lumped rainfall-runoff modelling was incorporated to estimate the flood magnitude in this method. However, we should note that rainfall is not the only driving factor of flood events. Soil moisture conditions are also an important driving factor affecting the rainfall-runoff transformation, and may even control rainfall-runoff coefficients to a higher degree than does rainfall. Hence, here we perform soil moisture analysis at national scale by employing GLDAS-Noah datasets, and link this to observed event runoff coefficients from a large sample of UK catchments. The relationship between soil moisture conditions and rainfall-runoff coefficient was explored to analyse the spatio-temporal variability of runoff coefficient. This study laid the foundation for further development of a practical derived distribution method, by considering the statistical distribution of rainfall-runoff coefficients and the influence of soil moisture conditions.</p>

scholarly journals Effects of Probability-Distributed Losses on Flood Estimates Using Event-Based Rainfall-Runoff Models

Water ◽  
2021 ◽  
Vol 13 (15) ◽  
pp. 2049
Author(s):  
Melanie Loveridge ◽  
Ataur Rahman
Keyword(s):  
Probability Distributions ◽  
Data Sets ◽  
Rainfall Runoff ◽  
Design Flood ◽  
Ungauged Catchments ◽  
Large Dataset ◽  
Loss Data ◽  
Flood Estimation ◽  
Historic Data ◽  
Event Based

Probability distributions of initial losses are investigated using a large dataset of catchments throughout Australia. The variability in design flood estimates caused by probability-distributed initial losses and associated uncertainties are investigated. Based on historic data sets in Australia, the Gamma and Beta distributions are found to be suitable for describing initial loss data. It has also been found that the central tendency of probability-distributed initial loss is more important in design flood estimation than the form of the probability density function. Findings from this study have notable implications on the regionalization of initial loss data, which is required for the application of Monte Carlo methods for design flood estimation in ungauged catchments.

scholarly journals A revision of daily egg production estimation methods, with application to Atlanto-Iberian sardine. 2. Spatially and environmentally explicit estimates of egg production

2011 ◽  
Vol 68 (3) ◽  
pp. 528-536 ◽  
Author(s):  
Miguel Bernal ◽  
Yorgos Stratoudakis ◽  
Simon Wood ◽  
Leire Ibaibarriaga ◽  
Luis Valdés ◽  
...  
Keyword(s):  
Temporal Variability ◽  
Environmental Variables ◽  
Egg Production ◽  
Stock Assessment ◽  
Production Model ◽  
Estimation Methods ◽  
Statistical Framework ◽  
Spatio Temporal ◽  
The Relationship ◽  
Made In

Abstract Bernal, M., Stratoudakis, Y., Wood, S., Ibaibarriaga, L., Uriarte, A., Valdés, L., and Borchers, D. 2011. A revision of daily egg production estimation methods, with application to Atlanto-Iberian sardine. 2. Spatially and environmentally explicit estimates of egg production. – ICES Journal of Marine Science, 68: . A spatially and environmentally explicit egg production model is developed to accommodate a number of assumptions about the relationship between egg production and mortality and associated environmental variables. The general model was tested under different assumptions for Atlanto-Iberian sardine. It provides a flexible estimator of egg production, in which a range of assumptions and hypotheses can be tested in a structured manner within a well-defined statistical framework. Application of the model to Atlanto-Iberian sardine increased the precision of the egg production time-series, and allowed improvements to be made in understanding the spatio-temporal variability in egg production, as well as implications for ecology and stock assessment.

Flood estimation for ungauged catchments in the Philippines using multiple archival data records

2021 ◽  
Author(s):  
Trevor Hoey ◽  
Pamela Tolentino ◽  
Esmael Guardian ◽  
Richard Williams ◽  
Richard Boothroyd ◽  
...  
Keyword(s):  
Catchment Area ◽  
Daily Rainfall ◽  
The Philippines ◽  
Data Availability ◽  
Estimation Methods ◽  
Annual Maximum ◽  
Ungauged Catchments ◽  
Pearson Type ◽  
Flood Estimation ◽  
Best Fit

<p>Assessment of flood and drought risks, and changes to these risks under climate change, is a critical issue worldwide. Statistical methods are commonly used in data-rich regions to estimate the magnitudes of river floods of specified return period at ungauged sites. However, data availability can be a major constraint on reliable estimation of flood and drought magnitudes, particularly in the Global South. Statistical flood and drought magnitude estimation methods rely on the availability of sufficiently long data records from sites that are representative of the hydrological region of interest. In the Philippines, although over 1000 locations have been identified where flow records have been collected at some time, very few records exist of over 20 years duration and only a limited number of sites are currently being gauged. We collated data from three archival sources: (1) Division of Irrigation, Surface Water Supply (SWS) (1908-22; 257 sites in total); (2) Japan International Cooperation Agency (JICA) (1955-91; 90 sites); and, (3) Bureau of Research and Standards (BRS) (1957-2018; 181 sites). From these data sets, 176 contained sufficiently long and high quality records to be analysed. Series of annual maximum floods were fit using L-moments with Weibull, Log-Pearson Type III and Generalised Logistic Distributions, the best-fit of these being used to estimate 2-, 10- and 100-year flood events, Q<sub>2</sub>, Q<sub>10</sub> and Q<sub>100</sub>. Predictive equations were developed using catchment area, several measures of annual and extreme precipitation, catchment geometry and land-use. Analysis took place nationally, and also for groups of hydrologically similar regions, based on similar flood growth curve shapes, across the Philippines. Overall, the best fit equations use a combination of two predictor variables, catchment area and the median annual maximum daily rainfall. The national equations have R<sup>2</sup> of 0.55-0.65, being higher for shorter return periods, and regional groupings R<sup>2</sup> are 0.60-0.77 for Q<sub>10</sub>. These coefficients of determination, R<sup>2</sup>, are lower than in some comprehensive studies worldwide reflecting in part the short individual flow records. Standard errors of residuals for the equations are between 0.19 and 0.51 (log<sub>10</sub> units), which lead to significant uncertainty in flood estimation for water resource and flood risk management purposes. Improving the predictions requires further analysis of hydrograph shape across the different climate types, defined by seasonal rainfall distributions, in the Philippines and between catchments of different size. The results here represent the most comprehensive study to date of flood magnitudes in the Philippines and are being incorporated into guidance for river managers alongside new assessments of river channel change across the country. The analysis illustrates the potential, and the limitations, for combining information from multiple data sources and short individual records to generate reliable estimates of flow extremes.</p>

scholarly journals Contrasting seasonality of storm rainfall and flood runoff in the UK and some implications for rainfall-runoff methods of flood estimation

2019 ◽  
Vol 50 (5) ◽  
pp. 1309-1323 ◽  
Author(s):  
Jamie Ledingham ◽  
David Archer ◽  
Elizabeth Lewis ◽  
Hayley Fowler ◽  
Chris Kilsby
Keyword(s):  
Soil Moisture ◽  
Risk Estimation ◽  
Daily Rainfall ◽  
Annual Rainfall ◽  
Rainfall Runoff ◽  
Frequency Model ◽  
Soil Moisture Storage ◽  
Flood Estimation ◽  
Storm Rainfall ◽  
The Uk

Abstract Using data from 520 gauging stations in Britain and gridded rainfall datasets, the seasonality of storm rainfall and flood runoff is compared and mapped. Annual maximum (AMAX) daily rainfall occurs predominantly in summer, but AMAX floods occur most frequently in winter. Seasonal occurrences of annual daily rainfall and flood maxima differ by more than 50% in dry lowland catchments. The differences diminish with increasing catchment wetness, increase with rainfalls shorter than daily duration and are shown to depend primarily on catchment wetness, as illustrated by variations in mean annual rainfall. Over the whole dataset, only 34% of AMAX daily flood events are matched to daily rainfall annual maxima (and only 20% for 6-hour rainfall maxima). The discontinuity between rainfall maxima and flooding is explained by the consideration of coincident soil moisture storage. The results have serious implications for rainfall-runoff methods of flood risk estimation in the UK where estimation is based on a depth–duration–frequency model of rainfall highly biased to summer. It is concluded that inadequate treatment of the seasonality of rainfall and soil moisture seriously reduces the reliability of event-based flood estimation in Britain.

scholarly journals Regional analysis using the Geomorphologic Instantaneous Unit Hydrograph (GIUH) method

2014 ◽  
Vol 9 (No. 1) ◽  
pp. 25-30 ◽  
Author(s):  
M.R. Khaleghi ◽  
J. Ghodusi ◽  
H. Ahmadi
Keyword(s):  
High Efficiency ◽  
Linear Regression Analysis ◽  
Regional Analysis ◽  
Suitable Model ◽  
Rainfall Runoff ◽  
Unit Hydrograph ◽  
Design Flood ◽  
Ungauged Catchments ◽  
Northern Iran ◽  
Simulation Accuracy

The construction of design flood hydrographs for ungauged drainage areas has traditionally been approached by regionalization, i.e. the transfer of information from the gauged to the ungauged catchments in a region. Such approaches invariably depend upon the use of multiple linear regression analysis to relate unit hydrograph parameters to catchment characteristics and generalized rainfall statistics. In the present study, Geomorphologic Instaneous Unit Hydrograph (GIUH) was applied to simulate the rainfall-runoff process and also to determine the shape and dimensions of outlet runoff hydrographs in a 37.1 km<sup>2</sup> area in the Ammameh catchment, located at northern Iran. The first twenty-one equivalent rainfall-runoff events were selected, and a hydrograph of outlet runoff was calculated for each event. An intercomparison was made for the three applied approaches in order to propose a suitable model approach that is the overall objective of this study. Hence, the time to peak and peak flow of outlet runoff in the models were then compared, and the model that most efficiently estimated hydrograph of outlet flow for similar regions was determined. Statistical analyses of the models demonstrated that the GIUH model had the smallest main relative and square error. The results obtained from the study confirmed the high efficiency of the GIUH and its ability to increase simulation accuracy for runoff and hydrographs. The modified GIUH approach as described is therefore recommended for further investigation and intercomparison with regression-based regionalization methods.

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