scholarly journals Rainfall-Runoff Modelling Considerations to Predict Streamflow Characteristics in Ungauged Catchments and under Climate Change

Water ◽  
2018 ◽  
Vol 10 (10) ◽  
pp. 1319 ◽  
Author(s):  
Francis Chiew ◽  
Hongxing Zheng ◽  
Nicholas Potter
Keyword(s):  
Climate Change ◽  
Flow Characteristics ◽  
Large Data ◽  
Low Flow ◽  
Rainfall Runoff ◽  
Ungauged Catchments ◽  
Objective Criterion ◽  
Data Set ◽  
Daily Streamflow ◽  
Parameter Values

This paper investigates the prediction of different streamflow characteristics in ungauged catchments and under climate change, with three rainfall-runoff models calibrated against three different objective criteria, using a large data set from 780 catchments across Australia. The results indicate that medium and high flows are relatively easier to predict, suggesting that using a single unique set of parameter values from model calibration against an objective criterion like the Nash–Sutcliffe efficiency is generally adequate and desirable to provide a consistent simulation and interpretation of daily streamflow series and the different medium and high flow characteristics. However, the low flow characteristics are considerably more difficult to predict and will require careful modelling consideration to specifically target the low flow characteristic of interest. The modelling results also show that different rainfall-runoff models and different calibration approaches can give significantly different predictions of climate change impact on streamflow characteristics, particularly for characteristics beyond the long-term averages. Predicting the hydrological impact from climate change, therefore, requires careful modelling consideration and calibration against appropriate objective criteria that specifically target the streamflow characteristic that is being assessed.

Estimating low flow characteristics in ungauged catchments

1992 ◽  
Vol 6 (2) ◽  
pp. 85-100 ◽  
Author(s):  
Rory J. Nathan ◽  
Tom A. McMahon
Keyword(s):  
Flow Characteristics ◽  
Low Flow ◽  
Ungauged Catchments

scholarly journals Estimating the Relative Uncertainties Sourced from GCMs and Hydrological Models in Modeling Climate Change Impact on Runoff

2012 ◽  
Vol 13 (1) ◽  
pp. 122-139 ◽  
Author(s):  
Jin Teng ◽  
Jai Vaze ◽  
Francis H. S. Chiew ◽  
Biao Wang ◽  
Jean-Michel Perraud
Keyword(s):  
Climate Change ◽  
Climate Change Impact ◽  
Daily Rainfall ◽  
Low Flow ◽  
Hydrological Models ◽  
Rainfall Runoff ◽  
Runoff Modeling ◽  
Change Impact ◽  
The Difference ◽  
Climate Series

Abstract This paper assesses the relative uncertainties from GCMs and from hydrological models in modeling climate change impact on runoff across southeast Australia. Five lumped conceptual daily rainfall–runoff models are used to model runoff using historical daily climate series and using future climate series obtained by empirically scaling the historical climate series informed by simulations from 15 GCMs. The majority of the GCMs project a drier future for this region, particularly in the southern parts, and this is amplified as a bigger reduction in the runoff. The results indicate that the uncertainty sourced from the GCMs is much larger than the uncertainty in the rainfall–runoff models. The variability in the climate change impact on runoff results for one rainfall–runoff model informed by 15 GCMs (an about 28%–35% difference between the minimum and maximum results for mean annual, mean seasonal, and high runoff) is considerably larger than the variability in the results between the five rainfall–runoff models informed by 1 GCM (a less than 7% difference between the minimum and maximum results). The difference between the rainfall–runoff modeling results is larger in the drier regions for scenarios of big declines in future rainfall and in the low-flow characteristics. The rainfall–runoff modeling here considers only the runoff sensitivity to changes in the input climate data (primarily daily rainfall), and the difference between the hydrological modeling results is likely to be greater if potential changes in the climate–runoff relationship in a warmer and higher CO2 environment are modeled.

scholarly journals Transition near the edge of a rotating disk

2013 ◽  
Vol 737 ◽  
Author(s):  
Benoît Pier
Keyword(s):  
Boundary Layer ◽  
Boundary Condition ◽  
Large Data ◽  
Rotating Disk ◽  
Finite Radius ◽  
Objective Criterion ◽  
Data Set ◽  
Wide Range ◽  
Stabilizing Effect ◽  
Strong Source

AbstractThe rotating-disk boundary layer is generally considered as an example of a flow that displays a robust transition from laminar to turbulent régimes. By taking into account disks of finite radius, Healey (J. Fluid Mech., vol. 663, 2010, pp. 148–159) has predicted a stabilizing effect of the boundary condition, but Imayama et al. (J. Fluid Mech., vol. 716, 2013, pp. 638–657) were unable to confirm this prediction experimentally. Following these contradictory results, the present experimental investigation revisits the rotating-disk boundary layer, without any artificially imposed excitation, and studies in further detail the dynamics prevailing in the region closely surrounding the edge of the disk, as well as the flow beyond the disk. Azimuthal mean velocities and fluctuation amplitudes are recorded with small steps in radial and axial directions for a wide range of disk sizes. An objective criterion is used to define the onset of fluctuations consistently over a large data set. Two distinct mechanisms for the onset of fluctuations are identified. In particular, it is found that the flow over the edge of the disk acts as a strong source of fluctuations. Explanations and suggestions for a possible reconciliation of previous studies are given.

scholarly journals Geostatistical prediction of flow-duration curves

2013 ◽  
Vol 10 (11) ◽  
pp. 13053-13091 ◽  
Author(s):  
A. Pugliese ◽  
A. Castellarin ◽  
A. Brath
Keyword(s):  
Cross Validation ◽  
Central Italy ◽  
Weighted Average ◽  
Low Flow ◽  
Mean Annual Precipitation ◽  
Ungauged Catchments ◽  
Study Region ◽  
Daily Streamflow ◽  
Flow Duration ◽  
Flow Duration Curves

Abstract. We present in this study an adaptation of Topological kriging (or Top-kriging), which makes the geostatistical procedure capable of predicting flow-duration curves (FDCs) in ungauged catchments. Previous applications of Top-kriging mainly focused on the prediction of point streamflow indices (e.g. flood quantiles, low-flow indices, etc.). In this study Top-kriging is used to predict FDCs in ungauged sites as a weighted average of standardised empirical FDCs through the traditional linear-weighting scheme of kriging methods. Our study focuses on the prediction of period-of-record FDCs for 18 unregulated catchments located in Central Italy, for which daily streamflow series with length from 5 to 40 yr are available, together with information on climate referring to the same time-span of each daily streamflow sequence. Empirical FDCs are standardised by a reference streamflow value (i.e. mean annual flow, or mean annual precipitation times the catchment drainage area) and the overall deviation of the curves from this reference value is then used for expressing the hydrological similarity between catchments and for deriving the geostatistical weights. We performed an extensive leave-one-out cross-validation to quantify the accuracy of the proposed technique, and to compare it to traditional regionalisation models that were recently developed for the same study region. The cross-validation points out that Top-kriging is a reliable approach for predicting FDCs, which can significantly outperform traditional regional models in ungauged basins.

scholarly journals Examining differences in streamflow estimation for gauged and ungauged catchments using evolutionary data assimilation

2013 ◽  
Vol 16 (2) ◽  
pp. 392-406 ◽  
Author(s):  
Gift Dumedah ◽  
Paulin Coulibaly
Keyword(s):  
Data Assimilation ◽  
Estimation Accuracy ◽  
Model Parameters ◽  
Ungauged Catchments ◽  
Model Parameter ◽  
Soil Moisture Accounting ◽  
Measurement Models ◽  
Daily Streamflow ◽  
Parameter Values ◽  
Ungauged Watersheds

Data assimilation has allowed hydrologists to account for imperfections in observations and uncertainties in model estimates. Typically, updated members are determined as a compromised merger between observations and model predictions. The merging procedure is conducted in decision space before model parameters are updated to reflect the assimilation. However, given the dynamics between states and model parameters, there is limited guarantee that when updated parameters are applied into measurement models, the resulting estimate will be the same as the updated estimate. To account for these challenges, this study uses evolutionary data assimilation (EDA) to estimate streamflow in gauged and ungauged watersheds. EDA assimilates daily streamflow into a Sacramento soil moisture accounting model to determine updated members for eight watersheds in southern Ontario, Canada. The updated members are combined to estimate streamflow in ungauged watersheds where the results show high estimation accuracy for gauged and ungauged watersheds. An evaluation of the commonalities in model parameter values across and between gauged and ungauged watersheds underscore the critical contributions of consistent model parameter values. The findings show a high degree of commonality in model parameter values such that members of a given gauged/ungauged watershed can be estimated using members from another watershed.

scholarly journals Flood Frequency Analysis at Ungauged Sites Based on Regionally Estimated Streamflows

2017 ◽  
Vol 18 (9) ◽  
pp. 2521-2539 ◽  
Author(s):  
Ana I. Requena ◽  
Taha B. M. J. Ouarda ◽  
Fateh Chebana
Keyword(s):  
Frequency Analysis ◽  
Regional Analysis ◽  
Flow Characteristics ◽  
Flood Frequency ◽  
Low Flow ◽  
Flood Frequency Analysis ◽  
Daily Streamflow ◽  
Ungauged Sites ◽  
Regional Flow ◽  
Regional Flood Frequency Analysis

Abstract Estimation of flood events at ungauged sites is often performed through regional flood frequency analysis (RFFA). RFFA uses the available information at gauged sites to estimate the desired design events at the ungauged site. These regional methods are based on a prior aggregation of the hydrological information at the gauged sites, which implies loss of information. In the present study, a different approach or path for conducting RFFA is presented. First, the daily streamflow series at the ungauged site is regionally estimated from daily information at the gauged sites through a regional flow duration curve approach. Then, a local flood frequency analysis is performed on the extracted maximum peak flow series. The proposed approach, referred to as regional streamflow-based frequency analysis (RSBFA), is applied to a case study in the province of Quebec, Canada. Results indicate that the performance of the RSBFA approach is comparable to traditional methods. However, the proposed method has the advantages of being simple, flexible, and of providing the whole daily streamflow series at the ungauged site, which allows the direct estimation of a large number of other flow characteristics, such as low-flow features. The RSBFA approach also avoids performing a complete at-site flood frequency analysis at each gauged site. The fact that all the regional information is included in the regionally estimated daily streamflow series implies a number of benefits: annual or seasonal, absolute or specific, stationary or nonstationary, and univariate or multivariate flood quantiles corresponding to any return period may then be obtained through the estimated series without reconducting a regional analysis.

scholarly journals Climate change alters low flows in Europe under global warming of 1.5, 2, and 3 °C

2018 ◽  
Vol 22 (2) ◽  
pp. 1017-1032 ◽  
Author(s):  
Andreas Marx ◽  
Rohini Kumar ◽  
Stephan Thober ◽  
Oldrich Rakovec ◽  
Niko Wanders ◽  
...  
Keyword(s):  
Climate Change ◽  
Global Warming ◽  
General Circulation ◽  
Snow Accumulation ◽  
Low Flow ◽  
Model Ensemble ◽  
Daily Streamflow ◽  
Low Flows ◽  
Future Global Warming ◽  
The Mediterranean

Abstract. There is growing evidence that climate change will alter water availability in Europe. Here, we investigate how hydrological low flows are affected under different levels of future global warming (i.e. 1.5, 2, and 3 K with respect to the pre-industrial period) in rivers with a contributing area of more than 1000 km2. The analysis is based on a multi-model ensemble of 45 hydrological simulations based on three representative concentration pathways (RCP2.6, RCP6.0, RCP8.5), five Coupled Model Intercomparison Project Phase 5 (CMIP5) general circulation models (GCMs: GFDL-ESM2M, HadGEM2-ES, IPSL-CM5A-LR, MIROC-ESM-CHEM, NorESM1-M) and three state-of-the-art hydrological models (HMs: mHM, Noah-MP, and PCR-GLOBWB). High-resolution model results are available at a spatial resolution of 5 km across the pan-European domain at a daily temporal resolution. Low river flow is described as the percentile of daily streamflow that is exceeded 90 % of the time. It is determined separately for each GCM/HM combination and warming scenario. The results show that the low-flow change signal amplifies with increasing warming levels. Low flows decrease in the Mediterranean region, while they increase in the Alpine and Northern regions. In the Mediterranean, the level of warming amplifies the signal from −12 % under 1.5 K, compared to the baseline period 1971–2000, to −35 % under global warming of 3 K, largely due to the projected decreases in annual precipitation. In contrast, the signal is amplified from +22 (1.5 K) to +45 % (3 K) in the Alpine region due to changes in snow accumulation. The changes in low flows are significant for regions with relatively large change signals and under higher levels of warming. However, it is not possible to distinguish climate-induced differences in low flows between 1.5 and 2 K warming because of (1) the large inter-annual variability which prevents distinguishing statistical estimates of period-averaged changes for a given GCM/HM combination, and (2) the uncertainty in the multi-model ensemble expressed by the signal-to-noise ratio. The contribution by the GCMs to the uncertainty in the model results is generally higher than the one by the HMs. However, the uncertainty due to HMs cannot be neglected. In the Alpine, Northern, and Mediterranean regions, the uncertainty contribution by the HMs is partly higher than those by the GCMs due to different representations of processes such as snow, soil moisture and evapotranspiration. Based on the analysis results, it is recommended (1) to use multiple HMs in climate impact studies and (2) to embrace uncertainty information on the multi-model ensemble as well as its single members in the adaptation process.

scholarly journals Top-kriging - geostatistics on stream networks

2006 ◽  
Vol 10 (2) ◽  
pp. 277-287 ◽  
Author(s):  
J. O. Skøien ◽  
R. Merz ◽  
G. Blöschl
Keyword(s):  
Unbiased Estimator ◽  
Flow Characteristics ◽  
Low Flow ◽  
Main Stream ◽  
Best Linear Unbiased Estimator ◽  
Stream Networks ◽  
Ungauged Catchments ◽  
Best Linear Unbiased ◽  
Flood Characteristics ◽  
Annual Discharge

Abstract. We present Top-kriging, or topological kriging, as a method for estimating streamflow-related variables in ungauged catchments. It takes both the area and the nested nature of catchments into account. The main appeal of the method is that it is a best linear unbiased estimator (BLUE) adapted for the case of stream networks without any additional assumptions. The concept is built on the work of Sauquet et al. (2000) and extends it in a number of ways. We test the method for the case of the specific 100-year flood for two Austrian regions. The method provides more plausible and, indeed, more accurate estimates than Ordinary Kriging. For the variable of interest, Top-kriging also provides estimates of the uncertainty. On the main stream the estimated uncertainties are smallest and they gradually increase as one moves towards the headwaters. The method as presented here is able to exploit the information contained in short records by accounting for the uncertainty of each gauge. We suggest that Top-kriging can be used for spatially interpolating a range of streamflow-related variables including mean annual discharge, flood characteristics, low flow characteristics, concentrations, turbidity and stream temperature.

scholarly journals Analysis of Counting Bloom Filters Used for Count Thresholding

Electronics ◽  
2019 ◽  
Vol 8 (7) ◽  
pp. 779
Author(s):  
Kibeom Kim ◽  
Yongjo Jeong ◽  
Youngjoo Lee ◽  
Sunggu Lee
Keyword(s):  
Large Data ◽  
Bloom Filter ◽  
Bloom Filters ◽  
Data Sets ◽  
Approximate Counting ◽  
Data Set ◽  
Typical Parameter ◽  
Parameter Values ◽  
Counting Bloom Filter ◽  
Counting Bloom Filters

A bloom filter is an extremely useful tool applicable to various fields of electronics and computers; it enables highly efficient search of extremely large data sets with no false negatives but a possibly small number of false positives. A counting bloom filter is a variant of a bloom filter that is typically used to permit deletions as well as additions of elements to a target data set. However, it is also sometimes useful to use a counting bloom filter as an approximate counting mechanism that can be used, for example, to determine when a specific web page has been referenced more than a specific number of times or when a memory address is a “hot” address. This paper derives, for the first time, highly accurate approximate false positive probabilities and optimal numbers of hash functions for counting bloom filters used in count thresholding applications. The analysis is confirmed by comparisons to existing theoretical results, which show an error, with respect to exact analysis, of less than 0.48% for typical parameter values.

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