Identification of appropriate lags and temporal resolutions for low flow indicators in the River Rhine to forecast low flows with different lead times

2012 ◽  
Vol 27 (19) ◽  
pp. 2742-2758 ◽  
Author(s):  
Mehmet C. Demirel ◽  
Martijn J. Booij ◽  
Arjen Y. Hoekstra
Keyword(s):  
Low Flow ◽  
Lead Times ◽  
River Rhine ◽  
Low Flows

scholarly journals Impacts of climate change on the seasonality of low flows in 134 catchments in the River Rhine basin using an ensemble of bias-corrected regional climate simulations

2013 ◽  
Vol 10 (5) ◽  
pp. 6807-6845
Author(s):  
M. C. Demirel ◽  
M. J. Booij ◽  
A. Y. Hoekstra
Keyword(s):  
Climate Models ◽  
Regional Climate ◽  
Future Climate ◽  
Low Flow ◽  
River Rhine ◽  
Emission Scenarios ◽  
Climate Scenarios ◽  
Low Flows ◽  
Current Climate ◽  
The Future

Abstract. The impacts of climate change on the seasonality of low flows are analysed for 134 sub-catchments covering the River Rhine basin upstream of the Dutch–German border. Three seasonality indices for low flows are estimated, namely seasonality ratio (SR), weighted mean occurrence day (WMOD) and weighted persistence (WP). These indices are related to the discharge regime, timing and variability in timing of low flow events respectively. The three indices are estimated from: (1) observed low flows; (2) simulated low flows by the semi distributed HBV model using observed climate; (3) simulated low flows using simulated inputs from seven climate scenarios for the current climate (1964–2007); (4) simulated low flows using simulated inputs from seven climate scenarios for the future climate (2063–2098) including different emission scenarios. These four cases are compared to assess the effects of the hydrological model, forcing by different climate models and different emission scenarios on the three indices. The seven climate scenarios are based on different combinations of four General Circulation Models (GCMs), four Regional Climate Models (RCMs) and three greenhouse gas emission scenarios. Significant differences are found between cases 1 and 2. For instance, the HBV model is prone to overestimate SR and to underestimate WP and simulates very late WMODs compared to the estimated WMODs using observed discharges. Comparing the results of cases 2 and 3, the smallest difference is found in the SR index, whereas large differences are found in the WMOD and WP indices for the current climate. Finally, comparing the results of cases 3 and 4, we found that SR has decreased substantially by 2063–2098 in all seven subbasins of the River Rhine. The lower values of SR for the future climate indicate a shift from winter low flows (SR > 1) to summer low flows (SR < 1) in the two Alpine subbasins. The WMODs of low flows tend to be earlier than for the current climate in all subbasins except for the Middle Rhine and Lower Rhine subbasins. The WP values are slightly larger, showing that the predictability of low flow events increases as the variability in timing decreases for the future climate. From comparison of the uncertainty sources evaluated in this study, it is obvious that the RCM/GCM uncertainty has the largest influence on the variability in timing of low flows for future climate.

scholarly journals The skill of seasonal ensemble low flow forecasts for four different hydrological models

2014 ◽  
Vol 11 (5) ◽  
pp. 5377-5420 ◽  
Author(s):  
M. C. Demirel ◽  
M. J. Booij ◽  
A. Y. Hoekstra
Keyword(s):  
Conceptual Models ◽  
Potential Evapotranspiration ◽  
The Other ◽  
Data Driven ◽  
Low Flow ◽  
Lead Times ◽  
Hydrological Models ◽  
Meteorological Forcing ◽  
Low Flows ◽  
Better Than

Abstract. This paper investigates the skill of 90 day low flow forecasts using two conceptual hydrological models and two data-driven models based on Artificial Neural Networks (ANNs) for the Moselle River. One data-driven model, ANN-Indicator (ANN-I), requires historical inputs on precipitation (P), potential evapotranspiration (PET), groundwater (G) and observed discharge (Q), whereas the other data-driven model, ANN-Ensemble (ANN-E), and the two conceptual models, HBV and GR4J, use forecasted meteorological inputs (P and PET), whereby we employ ensemble seasonal meteorological forecasts. We compared low flow forecasts without any meteorological forecasts as input (ANN-I) and five different cases of seasonal meteorological forcing: (1) ensemble P and PET forecasts; (2) ensemble P forecasts and observed climate mean PET; (3) observed climate mean P and ensemble PET forecasts; (4) observed climate mean P and PET and (5) zero P and ensemble PET forecasts as input for the other three models (GR4J, HBV and ANN-E). The ensemble P and PET forecasts, each consisting of 40 members, reveal the forecast ranges due to the model inputs. The five cases are compared for a lead time of 90 days based on model output ranges, whereas the four models are compared based on their skill of low flow forecasts for varying lead times up to 90 days. Before forecasting, the hydrological models are calibrated and validated for a period of 30 and 20 years respectively. The smallest difference between calibration and validation performance is found for HBV, whereas the largest difference is found for ANN-E. From the results, it appears that all models are prone to over-predict low flows using ensemble seasonal meteorological forcing. The largest range for 90 day low flow forecasts is found for the GR4J model when using ensemble seasonal meteorological forecasts as input. GR4J, HBV and ANN-E under-predicted 90 day ahead low flows in the very dry year 2003 without precipitation data, whereas ANN-I predicted the magnitude of the low flows better than the other three models. The results of the comparison of forecast skills with varying lead times show that GR4J is less skilful than ANN-E and HBV. Furthermore, the hit rate of ANN-E is higher than the two conceptual models for most lead times. However, ANN-I is not successful in distinguishing between low flow events and non-low flow events. Overall, the uncertainty from ensemble P forecasts has a larger effect on seasonal low flow forecasts than the uncertainty from ensemble PET forecasts and initial model conditions.

scholarly journals Impacts of climate change on the seasonality of low flows in 134 catchments in the River Rhine basin using an ensemble of bias-corrected regional climate simulations

2013 ◽  
Vol 17 (10) ◽  
pp. 4241-4257 ◽  
Author(s):  
M. C. Demirel ◽  
M. J. Booij ◽  
A. Y. Hoekstra
Keyword(s):  
Climate Change ◽  
Climate Models ◽  
Regional Climate ◽  
Future Climate ◽  
Low Flow ◽  
River Rhine ◽  
Emission Scenarios ◽  
Low Flows ◽  
Current Climate ◽  
The Future

Abstract. The impacts of climate change on the seasonality of low flows were analysed for 134 sub-catchments covering the River Rhine basin upstream of the Dutch-German border. Three seasonality indices for low flows were estimated, namely the seasonality ratio (SR), weighted mean occurrence day (WMOD) and weighted persistence (WP). These indices are related to the discharge regime, timing and variability in timing of low flow events respectively. The three indices were estimated from: (1) observed low flows; (2) simulated low flows by the semi-distributed HBV model using observed climate as input; (3) simulated low flows using simulated inputs from seven combinations of General Circulation Models (GCMs) and Regional Climate Models (RCMs) for the current climate (1964–2007); (4) simulated low flows using simulated inputs from seven combinations of GCMs and RCMs for the future climate (2063–2098) including three different greenhouse gas emission scenarios. These four cases were compared to assess the effects of the hydrological model, forcing by different climate models and different emission scenarios on the three indices. Significant differences were found between cases 1 and 2. For instance, the HBV model is prone to overestimate SR and to underestimate WP and simulates very late WMODs compared to the estimated WMODs using observed discharges. Comparing the results of cases 2 and 3, the smallest difference was found for the SR index, whereas large differences were found for the WMOD and WP indices for the current climate. Finally, comparing the results of cases 3 and 4, we found that SR decreases substantially by 2063–2098 in all seven sub-basins of the River Rhine. The lower values of SR for the future climate indicate a shift from winter low flows (SR > 1) to summer low flows (SR < 1) in the two Alpine sub-basins. The WMODs of low flows tend to be earlier than for the current climate in all sub-basins except for the Middle Rhine and Lower Rhine sub-basins. The WP values are slightly larger, showing that the predictability of low flow events increases as the variability in timing decreases for the future climate. From comparison of the error sources evaluated in this study, it is obvious that different RCMs/GCMs have a larger influence on the timing of low flows than different emission scenarios. Finally, this study complements recent analyses of an international project (Rhineblick) by analysing the seasonality aspects of low flows and extends the scope further to understand the effects of hydrological model errors and climate change on three important low flow seasonality properties: regime, timing and persistence.

scholarly journals Análise de Componente do Regime Hidrológico da Bacia do Rio Amazonas em Anos de Eventos Climáticos

2019 ◽  
Vol 12 (3) ◽  
pp. 988
Author(s):  
Rogério Souza Aguiar ◽  
Edson José Paulino da Rocha ◽  
José Augusto de Souza Junior ◽  
Joyse Tatiane Souza dos Santos ◽  
Josiane Sarmento Dos Santos
Keyword(s):  
Flow Rate ◽  
El Niño ◽  
El Nino ◽  
La Niña ◽  
Low Flow ◽  
Amazon River ◽  
Low Flows ◽  
La Nina ◽  
Basin Scale ◽  
Historical Series

As cheias e vazantes do rio Amazonas passaram a ser mais persistentes ao longo dos anos. Este estudo busca analisara influência da variabilidade temporal em escala de bacia hidrográfica sobre o regime do rio Amazonas, a partir das vazões da estação hidrológica da Agência Nacional de Águas – ANA, localizada em Óbidos, no Estado do Pará em uma série histórica de janeiro/1970 a dezembro/2013. Além do tempo, o estudo analisou a intensidade do El Niño e La Niña. Como esperado, o tempo influenciou na vazão média interanual encontrada de 98.723 m3/s para os 44 anos da série analisada. Porém com variabilidade anual do regime do rio Amazonas de intensas proporções temporais, com a vazão variando de ordem de 72.380 m3/s (como em 1997) no regime de vazante até uma ordem de 131.620 m3/s (como em 1974) no regime de cheia. Também foi identificado que fenômenos de El Niño e La Niña modularam eventos climáticos extremos sobre as vazões da Bacia Amazônica em cada ano. A análise interanual mostrou que os anos de baixas vazões, possuíam a característica de persistência de ocorrência em relação às altas vazões. A partir de 1989, houve um aumento em relação à amplitude média da vazão de 87.727 m3/s devido a fortes níveis mínimos registrados. Ao analisar a vazão normalizada percebeu-se que na maioria dos anos de baixa vazão foram também anos do fenômeno El Niño. Constatado esta persistência de baixas vazões, investigaram-se os fatores de armazenamento e disponibilidade do rio Amazonas.   Analysis of Hydrological Regime Componentof the Amazonas River Basin in Years of Climate Events. ABSTRACTThe floods and drains of the Amazon River have become more persistent over the years. This study seeks to analyze the influence of the temporal variability in the basin scale on the Amazon river regime, from the flows of the hydrological station of the National Water Agency - ANA, located in Óbidos, State of Pará, in a historical series from January/1970 to December /2013. Besides time, the study analyzed the intensity of El Niño and La Niña. As expected, time influenced the annual interannual flow rate of 98,723 m3/s for the 44 years of the analyzed series. However, with an annual variability of the Amazon river regime of intense flows, with an increase of 72,380 m3/s (as in 1997) in the effluent regime up to an order of 131,620 m3/s (as in 1974) in the flood regime. It was also identified that El Niño and La Niña phenomena modulated extreme climatic events on the Amazon Basin flows each year. The year-on-year analysis showed that the years of low flows had a persistence of occurrence in relation to high flows. As of 1989, there was an increase in relation to the average flow amplitude of 87,727 m3/s due to the strong minimum levels recorded. Analyzing the normalized flow rate, it was observed that in most of the years of low flow there were also years of the El Niño phenomenon. Considering this persistence of low flows, we investigated the storage and availability factors of the Amazon River.Keywords: Time flows. Ecological Maintenance.Amazonriver. 

scholarly journals Hydrological characterization of watersheds in the Blue Nile Basin, Ethiopia

2011 ◽  
Vol 15 (1) ◽  
pp. 11-20 ◽  
Author(s):  
S. G. Gebrehiwot ◽  
U. Ilstedt ◽  
A. I. Gärdenas ◽  
K. Bishop
Keyword(s):  
Land Use ◽  
Soil Type ◽  
Low Flow ◽  
Flow Index ◽  
Nile Basin ◽  
Grazing Land ◽  
Blue Nile ◽  
Low Flows ◽  
Blue Nile Basin ◽  
Low Flow Index

Abstract. Thirty-two watersheds (31–4350 km2), in the Blue Nile Basin, Ethiopia, were hydrologically characterized with data from a study of water and land resources by the US Department of Interior, Bureau of Reclamation (USBR) published in 1964. The USBR document contains data on flow, topography, geology, soil type, and land use for the period 1959 to 1963. The aim of the study was to identify watershed variables best explaining the variation in the hydrological regime, with a special focus on low flows. Moreover, this study aimed to identify variables that may be susceptible to management policies for developing and securing water resources in dry periods. Principal Component Analysis (PCA) and Partial Least Square (PLS) were used to analyze the relationship between five hydrologic response variables (total flow, high flow, low flow, runoff coefficient, low flow index) and 30 potential explanatory watershed variables. The explanatory watershed variables were classified into three groups: land use, climate and topography as well as geology and soil type. Each of the three groups had almost equal influence on the variation in hydrologic variables (R2 values ranging from 0.3 to 0.4). Specific variables from within each of the three groups of explanatory variables were better in explaining the variation. Low flow and low flow index were positively correlated to land use types woodland, dense wet forest and savannah grassland, whereas grazing land and bush land were negatively correlated. We concluded that extra care for preserving low flow should be taken on tuffs/basalts which comprise 52% of the Blue Nile Basin. Land use management plans should recognize that woodland, dense wet forest and savannah grassland can promote higher low flows, while grazing land diminishes low flows.

Low flow frequency analysis for stream with mixed populations

2015 ◽  
Vol 42 (8) ◽  
pp. 503-509 ◽  
Author(s):  
Mike Hulley ◽  
Colin Clarke ◽  
Ed Watt
Keyword(s):  
Frequency Analysis ◽  
Worked Examples ◽  
Low Flow ◽  
Flow Estimation ◽  
Low Flows ◽  
Record Length ◽  
Mixed Populations ◽  
Flow Frequency ◽  
Recommendations For Assessment

A methodology is developed for the estimation of annual low-flow quantiles for streams with annual low flows occurring in both the summer and winter. Since the low flow generating processes are different in summer and winter, independent seasonal analyses are required. The methodology provides recommendations for assessment of record length, randomness, homogeneity, independence and stationarity, as well as guidelines for distribution selection and fitting for seasonal distributions. The seasonal distributions are then used to develop the combined distribution for annual low flow estimation. Four worked examples of long-term Canadian hydrometric stations are provided.

scholarly journals Contrasting Differences in Responses of Streamflow Regimes between Reforestation and Fruit Tree Planting in a Subtropical Watershed of China

Forests ◽  
2019 ◽  
Vol 10 (3) ◽  
pp. 212 ◽  
Author(s):  
Zhipeng Xu ◽  
Wenfei Liu ◽  
Xiaohua Wei ◽  
Houbao Fan ◽  
Yizao Ge ◽  
...  
Keyword(s):  
Flow Regime ◽  
Fruit Tree ◽  
High Flow ◽  
Tree Planting ◽  
Low Flow ◽  
Jiangxi Province ◽  
Negative Effects ◽  
Flow Duration ◽  
Low Flows ◽  
High Flows

Fruit tree planting is a common practice for alleviating poverty and restoring degraded environment in developing countries. Yet, its environmental effects are rarely assessed. The Jiujushui watershed (261.4 km2), located in the subtropical Jiangxi Province of China, was selected to assess responses of several flow regime components on both reforestation and fruit tree planting. Three periods of forest changes, including a reference (1961 to 1985), reforestation (1986 to 2000) and fruit tree planting (2001 to 2016) were identified for assessment. Results suggest that the reforestation significantly decreased the average magnitude of high flow by 8.78%, and shortened high flow duration by 2.2 days compared with the reference. In contrast, fruit tree planting significantly increased the average magnitude of high flow by 27.43%. For low flows, reforestation significantly increased the average magnitude by 46.38%, and shortened low flow duration by 8.8 days, while the fruit tree planting had no significant impact on any flow regime components of low flows. We conclude that reforestation had positive impacts on high and low flows, while to our surprise, fruit tree planting had negative effects on high flows, suggesting that large areas of fruit tree planting may potentially become an important driver for some negative hydrological effects in our study area.

scholarly journals Smooth regional estimation of low-flow indices: physiographical space based interpolation and top-kriging

2011 ◽  
Vol 15 (3) ◽  
pp. 715-727 ◽  
Author(s):  
S. Castiglioni ◽  
A. Castellarin ◽  
A. Montanari ◽  
J. O. Skøien ◽  
G. Laaha ◽  
...  
Keyword(s):  
Spatial Interpolation ◽  
Central Italy ◽  
Low Flow ◽  
Flow Index ◽  
Ungauged Basins ◽  
Low Flows ◽  
Interpolation Techniques ◽  
Point Data ◽  
Leave One Out ◽  
Low Flow Index

Abstract. Recent studies highlight that spatial interpolation techniques of point data can be effectively applied to the problem of regionalization of hydrometric information. This study compares two innovative interpolation techniques for the prediction of low-flows in ungauged basins. The first one, named Physiographical-Space Based Interpolation (PSBI), performs the spatial interpolation of the desired streamflow index (e.g., annual streamflow, low-flow index, flood quantile, etc.) in the space of catchment descriptors. The second technique, named Topological kriging or Top-kriging, predicts the variable of interest along river networks taking both the area and nested nature of catchments into account. PSBI and Top-kriging are applied for the regionalization of Q355 (i.e., a low-flow index that indicates the streamflow that is equalled or exceeded 355 days in a year, on average) over a broad geographical region in central Italy, which contains 51 gauged catchments. The two techniques are cross-validated through a leave-one-out procedure at all available gauges and applied to a subregion to produce a continuous estimation of Q355 along the river network extracted from a 90m elevation model. The results of the study show that Top-kriging and PSBI present complementary features. Top-kriging outperforms PSBI at larger river branches while PSBI outperforms Top-kriging for headwater catchments. Overall, they have comparable performances (Nash-Sutcliffe efficiencies in cross-validation of 0.89 and 0.83, respectively). Both techniques provide plausible and accurate predictions of Q355 in ungauged basins and represent promising opportunities for regionalization of low-flows.

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