scholarly journals Development of a Large Flood Regionalisation Model Considering Spatial Dependence—Application to Ungauged Catchments in Australia

Water ◽  
2019 ◽  
Vol 11 (4) ◽  
pp. 677 ◽  
Author(s):  
Khaled Haddad ◽  
Ataur Rahman

Estimation of large floods is imperative in planning and designing large hydraulic structures. Due to the limited availability of observed flood data, estimating the frequencies of large floods requires significant extrapolation beyond the available data. This paper presents the development of a large flood regionalisation model (LFRM) based on observed flood data. The LFRM assumes that the maximum observed flood data over a large number of sites in a region can be pooled together by accounting for the at-site variations in the mean and coefficient of variation. The LFRM is enhanced by adding a spatial dependence model, which accounts for the net information available for regional analysis. It was found that the LFRM, which accounts for spatial dependence and that pools 1 or 3 maxima from a site, was able to estimate the 1 in 1000 annual exceedance probability flood quantile with consistency, showing a positive bias on average (5–7%) and modest median relative errors (30–33%).

2014 ◽  
Vol 2014 ◽  
pp. 1-7
Author(s):  
Jean-Luc Menet

The implantation of wind turbines generally follows a wind potential study which is made using specific numerical tools; the generated expenses are only acceptable for great projects. The purpose of the present paper is to propose a simplified methodology for the evaluation of the wind potential, following three successive steps for the determination of (i) the mean velocity, either directly or by the use of the most occurrence velocity (MOV); (ii) the velocity distribution coming from the single knowledge of the mean velocity by the use of a Rayleigh distribution and a Davenport-Harris law; (iii) an appropriate approximation of the characteristic curve of the turbine, coming from only two technical data. These last two steps allow calculating directly the electric delivered energy for the considered wind turbine. This methodology, called the SWEPT approach, can be easily implemented in a single worksheet. The results returned by the SWEPT tool are of the same order of magnitude than those given by the classical commercial tools. Moreover, everybody, even a “neophyte,” can use this methodology to obtain a first estimation of the wind potential of a site considering a given wind turbine, on the basis of very few general data.


2001 ◽  
Vol 47 (156) ◽  
pp. 147-151 ◽  
Author(s):  
He Yuanqing ◽  
Wilfred H. Theakstone ◽  
Yao Tandong ◽  
Shi Yafeng

AbstractStratigraphic variations of oxygen isotopes in the snow which accumulates during the winter at the Norwegian glacier Austre Okstindbreen are not entirely eliminated after 1–2 months of ablation in the following summer. The relationship between regional temperature changes and δ18O values in the snowpack is affected by many natural factors, but 1989/90 winter air temperatures were reflected in the snow which remained on Austre Okstindbreen at 1350 m a.s.l. in July 1990. There were many variations of δ18O values in the 4.1m of snow above the 1989 summer surface, but variations in the underlying firn were relatively small. Meltwater percolation modifies the initial variations of δ18O values in the snowpack. At a site below the mean equilibrium-line altitude on Austre Okstindbreen, increased isotopic homogenization within a 10 day period in July accompanied an increase of the mean δ18O value. Although the isotopic record at a temperate glacier is likely to be influenced by more factors than is that at polar glaciers, it can provide an estimate of the approximate trend of local temperature variations.


2012 ◽  
Vol 9 (6) ◽  
pp. 7591-7611 ◽  
Author(s):  
A. C. V. Getirana ◽  
C. Peters-Lidard

Abstract. In this study, we evaluate the use of a large radar altimetry dataset as a complementary gauging network capable of providing water discharge in ungauged regions within the Amazon basin. A rating-curve-based methodology is adopted to derive water discharge from altimetric data provided by Envisat at 444 virtual stations (VS). The stage-discharge relations at VS are built based on radar altimetry and outputs from a global flow routing scheme. In order to quantify the impact of modeling uncertainties on rating-curve based discharges, another experiment is performed using simulated discharges derived from a simplified data assimilation procedure. Discharge estimates at 90 VS are evaluated against observations during the curve fitting calibration (2002–2005) and evaluation (2006–2008) periods, resulting in mean relative RMS errors as high as 52% and 12% for experiments without and with assimilation, respectively. Without data assimilation, uncertainty of discharge estimates can be mostly attributed to forcing errors at smaller scales, generating a positive correlation between performance and drainage area. Mean relative errors (RE) of altimetry-based discharges varied from 15% to 92% for large and small drainage areas, respectively. Rating curves produced a mean RE of 54% versus 68% from model outputs. Assimilating discharge data decreases the mean RE from 68% to 12%. These results demonstrate the feasibility of applying the proposed methodology to the regional or global scales. Also, it is shown the potential of satellite altimetry for predicting water discharge in poorly-gauged and ungauged river basins.


2021 ◽  
Author(s):  
Tyler Wizenberg ◽  
Kimberly Strong ◽  
Kaley Walker ◽  
Erik Lutsch ◽  
Tobias Borsdorff ◽  
...  

Abstract. ACE/TROPOMI Abstract for AMT submission The TROPOspheric Monitoring Instrument (TROPOMI) provides a daily, spatially-resolved (initially 7 × 7 km2, upgraded to 7 × 5.6 km2 in August 2019) global data set of CO columns, however, due to the relative sparseness of reliable ground-based data sources, it can be challenging to characterize the validity and accuracy of satellite data products in remote regions such as the high Arctic. In these regions, satellite inter-comparisons can supplement model- and ground-based validation efforts and serve to verify previously observed differences. In this paper, we compare the CO products from TROPOMI, the Atmospheric Chemistry Experiment (ACE) Fourier Transform Spectrometer (FTS), and a high-Arctic ground-based FTS located at the Polar Environment Atmospheric Research Laboratory (PEARL) in Eureka, Nunavut (80.05° N, 86.42° W). A global comparison of TROPOMI reference profiles scaled by the retrieved total column with ACE-FTS CO partial columns for the period from 10 November 2017 to 31 May 2020 displays excellent agreement between the two data sets (R = 0.93), and a small relative bias of −0.68 ± 0.25 % (bias ± standard error). Additional comparisons were performed within five latitude bands; the north Polar region (60° N to 90° N), northern Mid-latitudes (20° N to 60° N), the Equatorial region (20° S to 20° N), southern Mid-latitudes (60° S to 20° S), and the south Polar region (90° S to 60° S). Latitudinal comparisons of the TROPOMI and ACE-FTS CO datasets show strong correlations ranging from R = 0.93 (southern Mid-latitudes) to R = 0.85 (Equatorial region) between the CO products, but display a dependence of the mean differences on latitude. Positive mean biases of 7.92 ± 0.58 % and 7.98 ± 0.51 % were found in the northern and southern Polar regions, respectively, while a negative bias of −9.16 ± 0.55 % was observed in the Equatorial region. To investigate whether these differences are introduced by cloud contamination which is reflected in the TROPOMI averaging kernel shape, the latitudinal comparisons were repeated for cloud-covered pixels and clear-sky pixels only, and for the unsmoothed and smoothed cases. Clear-sky pixels were found to be biased higher with poorer correlations on average than clear+cloudy scenes and cloud-covered scenes only. Furthermore, the latitudinal dependence on the biases was observed in both the smoothed and unsmoothed cases. To provide additional context to the global comparisons of TROPOMI with ACE-FTS in the Arctic, both satellite data sets were compared against measurements from the ground-based PEARL-FTS. Comparisons of TROPOMI with smoothed PEARL-FTS total columns in the period of 3 March 2018 to 27 March 2020 display a strong correlation (R = 0.88), however a positive mean bias of 14.3 ± 0.16 % was also found. A partial column comparison of ACE-FTS with the PEARL-FTS in the period from 25 February 2007 to 18 March 2020 shows good agreement (R = 0.82), and a mean positive bias of 9.83 ± 0.22 % in the ACE-FTS product relative to the ground-based FTS. The magnitude and sign of the mean relative differences are consistent across all inter-comparisons in this work, as well as with recent ground-based validation efforts, suggesting that current TROPOMI CO product exhibits a positive bias in the high-Arctic region. However, the observed bias is within the TROPOMI mission accuracy requirement of ±15 %, providing further confirmation that the data quality in these remote high-latitude regions meets this specification.


1987 ◽  
Vol 24 (7) ◽  
pp. 1486-1489 ◽  
Author(s):  
Malcolm Drury ◽  
Alan Taylor

Borehole heat-flow measurements are reported from six new sites in the Superior Province of the Canadian Shield. Values adjusted for glaciation effects, but not for Holocene climatic variations, range from 42 to 56 mW/m2. When these new values are combined with 21 previously published borehole values the mean is 42 mW/m2 with a standard deviation of 11 mW/m2. The data for a site on the Lac du Bonnet batholith suggest that the batholith has a thin veneer, less than 3 km, of rock of high radiogenic heat production at the surface.


2014 ◽  
Vol 9 (No. 1) ◽  
pp. 25-30 ◽  
Author(s):  
M.R. Khaleghi ◽  
J. Ghodusi ◽  
H. Ahmadi

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.


1973 ◽  
Vol 53 (2) ◽  
pp. 177-183 ◽  
Author(s):  
W. STANEK

pH values were measured on peat samples taken from a water-logged peatland in Ontario, from April 1970 to April 1971, by 14 procedures: on fresh peat and groundwater, in their natural state; and on combinations of hand-squeezed, air-dried, and oven-dried peat, each rewetted to liquid limit with either distilled H2O, N/100 CaCl2∙2H2O, N/10 KCl, or N/10 CaCl2∙2H2O. Groundwater showed the highest mean pH (4.0), followed by hand-squeezed peat rewetted with distilled H2O (3.8), then fresh peat (3.6). In comparison with fresh peat, air and oven drying lowered the mean pH value by 0.1 and 0.2 units, rewetting with N/100 CaCl2∙2H2O, by 0.4; N/10 KCl, by 0.5; and N/10 CaCl2∙2H2O, by 0.6 units approximately. The coefficients of variation and the confidence limits showed, for practical application, that all methods were equally reliable and that pH determined at any time of the year validly characterized a site.


1998 ◽  
Vol 09 (06) ◽  
pp. 827-836 ◽  
Author(s):  
A. M. Vidales ◽  
E. Miranda ◽  
G. Zgrablich

Invasion percolation is studied on correlated square networks described through a site-bond model which has proven to be useful for the characterization of real heterogeneous media. It is shown how the correlation degree affects the mean front velocity, the number of islands of trapped defender fluid (which are completely surrounded by invaded elements), their size distribution and total number of steps to reach the final state. The correlation degree seems to affect the fractal dimension of the percolating cluster. A characteristic correlation length is found to exist which maximizes the mean invasion velocity.


2020 ◽  
Vol 48 (4) ◽  
pp. 030006052091727 ◽  
Author(s):  
Gaku Oshikubo ◽  
Akihisa Akahane ◽  
Aki Unno ◽  
Yukako Watanabe ◽  
Emi Ikebuchi ◽  
...  

Objective To investigate the utility of the voxel-based specific regional analysis system for Alzheimer’s disease (VSRAD). Methods Clinical data from patients who underwent screening for dementia using VSRAD and the Japanese version of COGNISTAT, the Neurobehavioral Cognitive Status Examination, were retrospectively investigated to specify the domains of cognitive function that correlate with the statistical mean value of positive Z-scores in the target volume-of-interest (VOI). A receiver operating characteristic (ROC) curve was constructed to assess the mean value of positive Z-scores in discriminating patients with AD. Results A total of 72 patients were included (18 male and 54 female; 15 patients with AD). The mean value of positive Z-scores in the target VOI was significantly correlated with standardized COGNISTAT scores for Orientation and Memory in all patients (r = –0.35 and –0.38, respectively). ROC curve analysis revealed that a cut-off of 1.57 for mean value of positive Z-scores in the target VOI provided 69.4% accuracy in discriminating patients with AD, with a sensitivity of 0.80 and specificity of 0.67. Conclusions The results evinced the value of VSRAD in diagnosing AD. The degree of atrophy represented by the target VOI may reflect impairments in Orientation and Memory, which are early stage symptoms observed in AD.


2018 ◽  
Vol 22 (12) ◽  
pp. 6591-6609 ◽  
Author(s):  
Diana Lucatero ◽  
Henrik Madsen ◽  
Jens C. Refsgaard ◽  
Jacob Kidmose ◽  
Karsten H. Jensen

Abstract. This study analyzes the quality of the raw and post-processed seasonal forecasts of the European Centre for Medium-Range Weather Forecasts (ECMWF) System 4. The focus is given to Denmark, located in a region where seasonal forecasting is of special difficulty. The extent to which there are improvements after post-processing is investigated. We make use of two techniques, namely linear scaling or delta change (LS) and quantile mapping (QM), to daily bias correct seasonal ensemble predictions of hydrologically relevant variables such as precipitation, temperature and reference evapotranspiration (ET0). Qualities of importance in this study are the reduction of bias and the improvement in accuracy and sharpness over ensemble climatology. Statistical consistency and its improvement is also examined. Raw forecasts exhibit biases in the mean that have a spatiotemporal variability more pronounced for precipitation and temperature. This variability is more stable for ET0 with a consistent positive bias. Accuracy is higher than ensemble climatology for some months at the first month lead time only and, in general, ECMWF System 4 forecasts tend to be sharper. ET0 also exhibits an underdispersion issue, i.e., forecasts are narrower than their true uncertainty level. After correction, reductions in the mean are seen. This, however, is not enough to ensure an overall higher level of skill in terms of accuracy, although modest improvements are seen for temperature and ET0, mainly at the first month lead time. QM is better suited to improve statistical consistency of forecasts that exhibit dispersion issues, i.e., when forecasts are consistently overconfident. Furthermore, it also enhances the accuracy of the monthly number of dry days to a higher extent than LS. Caution is advised when applying a multiplicative factor to bias correct variables such as precipitation. It may overestimate the ability that LS has in improving sharpness when a positive bias in the mean exists.


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