scholarly journals Stochastic or statistic? Comparing flow duration curve models in ungauged basins and changing climates

2015 ◽  
Vol 12 (9) ◽  
pp. 9765-9811 ◽  
Author(s):  
M. F. Müller ◽  
S. E. Thompson
Keyword(s):  
Statistical Method ◽  
Monte Carlo Analysis ◽  
Model Parameters ◽  
Ungauged Basins ◽  
Wet Season ◽  
Flow Duration ◽  
Infrastructure Design ◽  
Streamflow Variability ◽  
Flow Duration Curves ◽  
Rainfall Statistics

Abstract. The prediction of flow duration curves (FDCs) in ungauged basins remains an important task for hydrologists given the practical relevance of FDCs for water management and infrastructure design. Predicting FDCs in ungauged basins typically requires spatial interpolation of statistical or model parameters. This task is complicated if climate becomes non-stationary, as the prediction challenge now also requires extrapolation through time. In this context, process-based models for FDCs that mechanistically link the streamflow distribution to climate and landscape factors may have an advantage over purely statistical methods to predict FDCs. This study compares a stochastic (process-based) and statistical method for FDC prediction in both stationary and non-stationary contexts, using Nepal as a case study. Under contemporary conditions, both models perform well in predicting FDCs, with Nash–Sutcliffe coefficients above 0.80 in 75 % of the tested catchments. The main drives of uncertainty differ between the models: parameter interpolation was the main source of error for the statistical model, while violations of the assumptions of the process-based model represented the main source of its error. The process-based approach performed better than the statistical approach in numerical simulations with non-stationary climate drivers. The predictions of the statistical method under non-stationary rainfall conditions were poor if (i) local runoff coefficients were not accurately determined from the gauge network, or (ii) streamflow variability was strongly affected by changes in rainfall. A Monte Carlo analysis shows that the streamflow regimes in catchments characterized by a strong wet-season runoff and a rapid, strongly non-linear hydrologic response are particularly sensitive to changes in rainfall statistics. In these cases, process-based prediction approaches are strongly favored over statistical models.

scholarly journals Comparing statistical and process-based flow duration curve models in ungauged basins and changing rain regimes

2016 ◽  
Vol 20 (2) ◽  
pp. 669-683 ◽  
Author(s):  
M. F. Müller ◽  
S. E. Thompson
Keyword(s):  
Statistical Method ◽  
Monte Carlo Analysis ◽  
Model Parameters ◽  
Ungauged Basins ◽  
Wet Season ◽  
Flow Duration ◽  
Infrastructure Design ◽  
Streamflow Variability ◽  
Flow Duration Curves ◽  
Rainfall Statistics

Abstract. The prediction of flow duration curves (FDCs) in ungauged basins remains an important task for hydrologists given the practical relevance of FDCs for water management and infrastructure design. Predicting FDCs in ungauged basins typically requires spatial interpolation of statistical or model parameters. This task is complicated if climate becomes non-stationary, as the prediction challenge now also requires extrapolation through time. In this context, process-based models for FDCs that mechanistically link the streamflow distribution to climate and landscape factors may have an advantage over purely statistical methods to predict FDCs. This study compares a stochastic (process-based) and statistical method for FDC prediction in both stationary and non-stationary contexts, using Nepal as a case study. Under contemporary conditions, both models perform well in predicting FDCs, with Nash–Sutcliffe coefficients above 0.80 in 75 % of the tested catchments. The main drivers of uncertainty differ between the models: parameter interpolation was the main source of error for the statistical model, while violations of the assumptions of the process-based model represented the main source of its error. The process-based approach performed better than the statistical approach in numerical simulations with non-stationary climate drivers. The predictions of the statistical method under non-stationary rainfall conditions were poor if (i) local runoff coefficients were not accurately determined from the gauge network, or (ii) streamflow variability was strongly affected by changes in rainfall. A Monte Carlo analysis shows that the streamflow regimes in catchments characterized by frequent wet-season runoff and a rapid, strongly non-linear hydrologic response are particularly sensitive to changes in rainfall statistics. In these cases, process-based prediction approaches are favored over statistical models.

Predicting annual and long-term flow-duration curves in ungauged basins

2007 ◽  
Vol 30 (4) ◽  
pp. 937-953 ◽  
Author(s):  
Attilio Castellarin ◽  
Giorgio Camorani ◽  
Armando Brath
Keyword(s):  
Ungauged Basins ◽  
Flow Duration ◽  
Flow Duration Curves

Regional flow-duration curves: reliability for ungauged basins

2004 ◽  
Vol 27 (10) ◽  
pp. 953-965 ◽  
Author(s):  
Attilio Castellarin ◽  
Giorgio Galeati ◽  
Luigia Brandimarte ◽  
Alberto Montanari ◽  
Armando Brath
Keyword(s):  
Ungauged Basins ◽  
Flow Duration ◽  
Regional Flow ◽  
Flow Duration Curves

scholarly journals Process-based karst modelling to relate hydrodynamic and hydrochemical characteristics to system properties

2013 ◽  
Vol 10 (3) ◽  
pp. 2835-2878
Author(s):  
A. Hartmann ◽  
M. Weiler ◽  
T. Wagener ◽  
J. Lange ◽  
M. Kralik ◽  
...  
Keyword(s):  
Sensitivity Analysis ◽  
Large Scale ◽  
Model Parameters ◽  
Karst Water ◽  
Flow Duration ◽  
Karst Areas ◽  
Flow Duration Curves ◽  
System Properties ◽  
Karst Systems ◽  
Sensitive Parameters

Abstract. More than 30% of Europe's land surface is made up of karst exposures. In some countries, water from karst aquifers constitutes almost half of the drinking water supply. Hydrological simulation models can predict the large-scale impact of future environmental change on hydrological variables. However, the information needed to obtain model parameters is not available everywhere and regionalisation methods have to be applied. The responsive behaviour of hydrological systems can be quantified by individual metrics, so-called system signatures. This study explores their value for distinguishing the dominant processes and properties of five different karst systems in Europe and the Middle East with the overall aim of regionalising system signatures and model parameters to ungauged karst areas. By defining ten system signatures derived from hydrodynamic and hydrochemical observations, a process-based karst model is applied to the five karst systems. In a stepwise model evaluation strategy, optimum parameters and their sensitivity are identified using automatic calibration and global variance-based sensitivity analysis. System signatures and sensitive parameters serve as proxies for dominant processes and optimised parameters are used to determine system properties. To test the transferability of the signatures, they are compared with the optimised model parameters and simple climatic and topographic descriptors of the five karst systems. By sensitivity analysis, the set of system signatures was able to distinguish the karst systems from one another by providing separate information about dominant soil, epikarst, and fast and slow groundwater flow processes. Comparing sensitive parameters to the system signatures revealed that annual discharge can serve as a proxy for the recharge area, that the slopes of the high flow parts of the flow duration curves correlate with the fast flow storage constant, and that the dampening of the isotopic signal of the rain as well as the medium flow parts of the flow duration curves have a non-linear relation to the distribution of groundwater dynamics. Even though, only weak correlations between system signatures and climatic and topographic factors could be found, our approach enabled us to identify dominant processes of the different systems and to provide directions for future large-scale simulation of karst areas to predict the impact of future change on karst water resources.

Patterns and Implications of Hydrologic Regime Change in Chongwe River, Zambia

2016 ◽  
Vol 8 (3) ◽  
pp. 1 ◽  
Author(s):  
Moses Ngongo Chisola ◽  
Michal Kuráž
Keyword(s):  
Water Use ◽  
Dry Season ◽  
Significant Trend ◽  
Series Data ◽  
Hydrologic Regime ◽  
Wet Season ◽  
Significance Level ◽  
Flow Duration ◽  
Flow Duration Curves ◽  
Gauging Station

Conflicts regarding water use have emerged in some small irrigation dominated peri-urban catchments in Zambia; Chongwe being one such catchment. Despite these conflicts suggesting a change in hydrologic regime, the nature of the changes and their drivers has not been adequately investigated. The Mann Kendall trend test and Flow Duration Curves were used to investigate changes in hydro-climatic time series data in Chongwe upper catchment for the period 1955-2006. Although the results reviewed a significant upward trend in temperature at 0.05 significance level, there is no significant trend in rainfall. Annual and seasonal runoff at the upstream located Ngwerere weir reviewed significant upward trends at 0.05 significance level. This increased runoff which is attributed to sewer water discharge and increased imperviousness is abstracted for agricultural activities upstream. In this regard, results reviewed no significant trend in runoff at the outlet gauging station (Chongwe 5025). However, analysis of the Flow Duration Curves at this outlet gauging station indicated an increase in wet season flows and a reduction in dry season flows for the 1990-2006 period. These results suggest that human activities in the upstream parts of the catchments could be the major contributing factors to the changes in flow regime, hence the ensuing upstream vs downstream water use conflicts. However, there is still excess runoff in the wet season that could be harvested by downstream water users in order to offset the deficit in downstream dry season flows.

scholarly journals Regional water balance modelling using flow-duration curves with observational uncertainties

2014 ◽  
Vol 18 (8) ◽  
pp. 2993-3013 ◽  
Author(s):  
I. K. Westerberg ◽  
L. Gong ◽  
K. J. Beven ◽  
J. Seibert ◽  
A. Semedo ◽  
...  
Keyword(s):  
Water Balance ◽  
Model Calibration ◽  
Hydrologic Model ◽  
Local Model ◽  
Screening Methods ◽  
Ungauged Basins ◽  
Data Set ◽  
Discharge Data ◽  
Flow Duration ◽  
Flow Duration Curves

Abstract. Robust and reliable water-resource mapping in ungauged basins requires estimation of the uncertainties in the hydrologic model, the regionalisation method, and the observational data. In this study we investigated the use of regionalised flow-duration curves (FDCs) for constraining model predictive uncertainty, while accounting for all these uncertainty sources. A water balance model was applied to 36 basins in Central America using regionally and globally available precipitation, climate and discharge data that were screened for inconsistencies. A rating-curve analysis for 35 Honduran discharge stations was used to estimate discharge uncertainty for the region, and the consistency of the model forcing and evaluation data was analysed using two different screening methods. FDCs with uncertainty bounds were calculated for each basin, accounting for both discharge uncertainty and, in many cases, uncertainty stemming from the use of short time series, potentially not representative for the modelling period. These uncertain FDCs were then used to regionalise a FDC for each basin, treating it as ungauged in a cross-evaluation, and this regionalised FDC was used to constrain the uncertainty in the model predictions for the basin. There was a clear relationship between the performance of the local model calibration and the degree of data set consistency – with many basins with inconsistent data lacking behavioural simulations (i.e. simulations within predefined limits around the observed FDC) and the basins with the highest data set consistency also having the highest simulation reliability. For the basins where the regionalisation of the FDCs worked best, the uncertainty bounds for the regionalised simulations were only slightly wider than those for a local model calibration. The predicted uncertainty was greater for basins where the result of the FDC regionalisation was more uncertain, but the regionalised simulations still had a high reliability compared to the locally calibrated simulations and often encompassed them. The regionalised FDCs were found to be useful on their own as a basic signature constraint; however, additional regionalised signatures could further constrain the uncertainty in the predictions and may increase the robustness to severe data inconsistencies, which are difficult to detect for ungauged basins.

An approach to estimate nonparametric flow duration curves in ungauged basins

2009 ◽  
Vol 45 (10) ◽  
Author(s):  
D. Ganora ◽  
P. Claps ◽  
F. Laio ◽  
A. Viglione
Keyword(s):  
Ungauged Basins ◽  
Flow Duration ◽  
Flow Duration Curves
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