Multiple causes of nonstationarity in the Weihe  annual low-flow series

Abstract. Under the background of global climate change and local anthropogenic activities, multiple driving forces have introduced various nonstationary components into low-flow series. This has led to a high demand on low-flow frequency analysis that considers nonstationary conditions for modeling. In this study, through a nonstationary frequency analysis framework with the generalized linear model (GLM) to consider time-varying distribution parameters, the multiple explanatory variables were incorporated to explain the variation in low-flow distribution parameters. These variables are comprised of the three indices of human activities (HAs; i.e., population, POP; irrigation area, IAR; and gross domestic product, GDP) and the eight measuring indices of the climate and catchment conditions (i.e., total precipitation P, mean frequency of precipitation events λ, temperature T, potential evapotranspiration (EP), climate aridity index AIEP, base-flow index (BFI), recession constant K and the recession-related aridity index AIK). This framework was applied to model the annual minimum flow series of both Huaxian and Xianyang gauging stations in the Weihe River, China (also known as the Wei He River). The results from stepwise regression for the optimal explanatory variables show that the variables related to irrigation, recession, temperature and precipitation play an important role in modeling. Specifically, analysis of annual minimum 30-day flow in Huaxian shows that the nonstationary distribution model with any one of all explanatory variables is better than the one without explanatory variables, the nonstationary gamma distribution model with four optimal variables is the best model and AIK is of the highest relative importance among these four variables, followed by IAR, BFI and AIEP. We conclude that the incorporation of multiple indices related to low-flow generation permits tracing various driving forces. The established link in nonstationary analysis will be beneficial to analyze future occurrences of low-flow extremes in similar areas.

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Multiple Causes of Nonstationarity in the Weihe Annual Low Flow Series

10.5194/hess-2017-259 ◽

2017 ◽

Author(s):

Bin Xiong ◽

Lihua Xiong ◽

Jie Chen ◽

Chong-Yu Xu ◽

Lingqi Li

Keyword(s):

Frequency Analysis ◽

Driving Forces ◽

Aridity Index ◽

Base Flow ◽

Low Flow ◽

Flow Index ◽

Time Varying ◽

Explanatory Variables ◽

Flow Generation ◽

Flow Frequency

Abstract. Under the background of global climate change and local anthropogenic activities, multiple driving forces have introduced a variety of non-stationary components into low-flow series. This has led to a high demand on low-flow frequency analysis that considers nonstationary conditions for modeling. In this study, a nonstationary framework of low-flow frequency analysis has been developed on basis of the Generalized Linear Model (GLM) to consider time-varying distribution parameters. In GLMs, the candidate explanatory variables to explain the time-varying parameters are comprised of the eight measuring indices of the climate and catchment conditions in low flow generation, i.e., total precipitation (P), mean frequency of precipitation events (λ), temperature (T), potential evapotranspiration (ET), climate aridity index (AIET), base-flow index (BFI), recession constant (K) and the recession-related aridity index (AIK). This framework was applied to the annual minimum flow series of both Huaxian and Xianyang gauging stations in the Weihe River, China. Stepwise regression analysis was performed to obtain the best subset of those candidate explanatory variables for the final optimum model. The results show that the inter-annual variability in the variables of those selected best subsets plays an important role in modeling annual low flow series. Specifically, analysis of annual minimum 30-day flow in Huaxian shows that AIK is of the highest relative importance among the best subset of eight candidates, followed by BFI and AIET. The incorporation of multiple indices related to low-flow generation permits tracing various driving forces. The established link in nonstationary analysis will be beneficial to predict future occurrences of low-flow extremes in similar areas.

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Controls on hydrologic drought duration in near-natural streamflow in Europe and the USA

Hydrology and Earth System Sciences ◽

10.5194/hess-20-4043-2016 ◽

2016 ◽

Vol 20 (10) ◽

pp. 4043-4059 ◽

Cited By ~ 5

Author(s):

Erik Tijdeman ◽

Sophie Bachmair ◽

Kerstin Stahl

Keyword(s):

Large Scale ◽

Aridity Index ◽

Base Flow ◽

Classification Systems ◽

Flow Index ◽

Climate Classification ◽

Drought Duration ◽

Base Flow Index ◽

The Usa ◽

Hydrologic Drought

Abstract. Climate classification systems, such as Köppen–Geiger and the aridity index, are used in large-scale drought studies to stratify regions with similar hydro-climatic drought properties. What is currently lacking is a large-scale evaluation of the relation between climate and observed streamflow drought characteristics. In this study we explored how suitable common climate classifications are for differentiating catchments according to their characteristic hydrologic drought duration and whether drought durations within the same climate classes are comparable between different regions. This study uses a dataset of 808 near-natural streamflow records from Europe and the USA to answer these questions. First, we grouped drought duration distributions of each record over different classes of four climate classification systems and five individual climate and catchment controls. Then, we compared these drought duration distributions of all classes within each climate classification system or classification based on individual controls. Results showed that climate classification systems that include absolute precipitation in their classification scheme (e.g., the aridity index) are most suitable for differentiating catchments according to drought duration. However, differences in duration distributions were found for the same climate classes in Europe and the USA. These differences are likely caused by differences in precipitation, in catchment controls as expressed by the base flow index and in differences in climate beyond the total water balance (e.g., seasonality in precipitation), which have been shown to exert a control on drought duration as well. Climate classification systems that include an absolute precipitation control can be tailored to drought monitoring and early warning systems for Europe and the USA to define regions with different sensitivities to hydrologic droughts, which, for example, have been found to be higher in catchments with a low aridity index. However, stratification of catchments according to these climate classification systems is likely to be complemented with information of other climate classification systems (Köppen–Geiger) and individual climate and catchment controls (precipitation and the base flow index), especially in a comparative study between Europe and the USA.

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A method for low-flow estimation at ungauged sites: a case study in Wallonia (Belgium)

Hydrology and Earth System Sciences ◽

10.5194/hess-17-1319-2013 ◽

2013 ◽

Vol 17 (4) ◽

pp. 1319-1330 ◽

Cited By ~ 10

Author(s):

M. Grandry ◽

S. Gailliez ◽

C. Sohier ◽

A. Verstraete ◽

A. Degré

Keyword(s):

Return Period ◽

Management Practice ◽

Global Model ◽

Low Flow ◽

Quality Analysis ◽

Flow Index ◽

Physical Parameters ◽

Integrated Water Management ◽

Explanatory Variables ◽

Ungauged Sites

Abstract. Well-integrated water management can notably require estimating low flows at any point of a river. Depending on the management practice, it can be needed for various return periods. This is seldom addressed in the literature. This paper shows the development of a full analysis chain including quality analysis of gauging stations, low-flow frequency analysis, and building of a global model to assess low-flow indices on the basis of catchment physical parameters. The most common distributions that fit low-flow data in Wallonia were two-parameter lognormal and gamma. The recession coefficient and percolation were the most explanatory variables, regardless of the return period. The determination coefficients of the models ranged from 0.51 to 0.67 for calibration and from 0.61 to 0.80 for validation. The regression coefficients were found to be linked to the return period. This was used to design a complete equation that gives the low-flow index based on physical parameters and the desired return period (in a 5 to 50 yr range). The interest of regionalisation and the development of regional models are also discussed. Four homogeneous regions are identified, but to date the global model remains more robust due to the limited number of 20-yr-long gauging stations. This should be reconsidered in the future when enough data will be available.

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Comparison and regionalization of hydrologically based instream flow techniques in Atlantic Canada

Canadian Journal of Civil Engineering ◽

10.1139/l95-033 ◽

1995 ◽

Vol 22 (2) ◽

pp. 235-246 ◽

Cited By ~ 25

Author(s):

Daniel Caissie ◽

Nassir El-Jabi

Keyword(s):

Regression Analysis ◽

Base Flow ◽

Low Flow ◽

Coefficient Of Determination ◽

Atlantic Canada ◽

Ungauged Basins ◽

Instream Flow ◽

Regional Study ◽

Explanatory Variables ◽

Tennant Method

Five hydrologically based instream flow assessment methods are compared for 70 rivers in Atlantic Canada; these methods included (i) Tennant method; (ii) 25% mean annual flow (25% MAF); (iii) median monthly flow (Q50) which includes the aquatic base flow (ABF); (iv) the flow equalled or exceeded 90% of time on a monthly flow duration curve (Q90); and (v) the statistical 7-day low flow frequency of a 10-year recurrence interval (7Q10). By comparing the different methods relative to the 25% MAF (the commonly used method in Atlantic Canada), we found that the Q90 and 7Q10 methods predicted extremely low instream flows during winter and summer months. Resource management decisions based on these extremely low flow predictions could have serious adverse consequences. The median monthly flow method (Q50) was recommended for gauged basins, whereas the Tennant method, the 25% MAF method, and the ABF methods were recommended for ungauged basins. For ungauged basins, we conducted a regional study to estimate the 25% MAF and the ABF using multiple regression analysis. Physiographic parameters were used as explanatory variables in the regression analysis. Based on the coefficient of determination, R2, the best regression results were obtained for the 25% MAF with R2 ranging from 0.957 to 0.999. Although the results for ABF were slightly lower than for the 25% MAF, R2 was still in the range of 0.868 to 0.979. Key words: environmental assessment, maintenance flow, low flow, aquatic resources.

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Continuous Modeling of the Mkurumudzi River Catchment in Kenya Using the HEC-HMS Conceptual Model: Calibration, Validation, Model Performance Evaluation and Sensitivity Analysis

Hydrology ◽

10.3390/hydrology5030044 ◽

2018 ◽

Vol 5 (3) ◽

pp. 44 ◽

Cited By ~ 8

Author(s):

Wendso Ouédraogo ◽

James Raude ◽

John Gathenya

Keyword(s):

Sensitivity Analysis ◽

Stream Flow ◽

Model Performance ◽

Base Flow ◽

Low Flow ◽

Coefficient Of Determination ◽

Flow Index ◽

Model Parameters ◽

Time Step ◽

Continuous Modeling

The Mkurumudzi River originates in the Shimba hills and runs through Kwale County on the Kenyan Coast. Study on this river has been informed by the many economic activities that the river supports, which include sugarcane plantations, mining, tourism and subsistence farming. The main objective of this study was to use the soil moisture accounting (SMA) model specified in the Hydrologic Engineering Center-Hydrologic Modeling System (HEC-HMS) settings for the continuous modeling of stream flow in the Mkurumudzi catchment. Data from past years were compared with observed stream flow data in order to evaluate whether the model can be used for further prediction. The calibration was performed using data from 1988 to 1991 and validation for the period from 1992 to 1995 at a daily time step. The model performance was evaluated based on computed statistical parameters and visual checking of plotted hydrographs. For the calibration period of the continuous modeling, the performance of the model was very good, with a coefficient of determination R2 = 0.80, Nash-Sutcliffe Efficiency NSE = 0.80, index of agreement d = 0.94, and a Root Mean Squared Error (RMSE)/observations’ standard deviation ratio—RSR = 0.46. Similarly, the continuous model performance for the validation period was good, with R2 = 0.67, NSE = 0.65, RSR = 0.62 and d = 0.88. Based on these performance results, the SMA model in the HEC-HMS was found to give a satisfactory prediction of stream flow in the Mkurumudzi Catchment. The sensitivity analysis of the model parameters was performed, and the different parameters were ranked according to their sensitivity in terms of percent change in simulated runoff volume, peaks, Nash-Efficiency, seven-day low flow and base flow index. Sensitivity analysis helped to understand the relationships between the key model parameters and the variables.

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Hydrological modelling of the karst Ljubljanica River catchment using lumped conceptual model

Acta hydrotechnica ◽

10.15292/acta.hydro.2018.06 ◽

2018 ◽

pp. 87-100 ◽

Cited By ~ 6

Author(s):

Cenk Sezen ◽

Nejc Bezak ◽

Mojca Šraj

Keyword(s):

Water System ◽

Flow Simulation ◽

Resource Planning ◽

Base Flow ◽

Low Flow ◽

Flow Index ◽

Rainfall Runoff ◽

River Catchment ◽

Simulation Performance

Modelling rainfall runoff is important for several human activities. For example, rainfall runoff models are needed for water resource planning and water system design. In this regard, the daily runoff was modelled using the Genie Rural, a 4-parameter Journalier (GR4J), Genie Rural, a 6-parameter Journalier (GR6J), and the CemaNeige GR6J lumped conceptual models that were developed by the IRSTEA Hydrology Group. The main difference among the tested models is in the complexity and processes that are considered in the various model versions. As a case study, the non-homogeneous mostly karst Ljubljanica River catchment down to the Moste discharge gauging station was selected. Models were evaluated using various efficiency criteria. For example, base flow index (BFI) was calculated for the results of all tested models and observed discharges in order to compare low flow simulation performance. Based on the presented results we can conclude that in case of the non-homogeneous and karst Ljubljanica catchment the CemaNeige GR6J yields better modelling results compared to the GR4J and GR6J models. Compared to the GR6J and GR4J model versions, the CemaNeige CR6J also includes the snow module and improved methodology for the low-flow simulations that are also included in the GR6J model version.

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Applicability of Lindley Distribution for Hydroelectric Dam Operations in the Dry Season

Korean Society of Hazard Mitigation ◽

10.9798/kosham.2020.20.6.291 ◽

2020 ◽

Vol 20 (6) ◽

pp. 291-299

Author(s):

Hongjoon Shin ◽

Hyunjun Ahn ◽

Changsam Jeong

Keyword(s):

Frequency Analysis ◽

Estimation Method ◽

Low Flow ◽

Distribution Model ◽

Distribution Models ◽

Recording Time ◽

Lindley Distribution ◽

Hydroelectric Dam ◽

Flow Frequency ◽

Dam Inflow

The long-term low-flow data are necessary for efficient planning of water resources and for estimating accurate quantiles via runoff data analysis at point. However, the short recording time period, low confidence, inconsistent distribution model, and parameter estimation method, make it difficult to estimate a proper low-flow quantile for each return period. In this study, the Lindley distribution model, which is a mix of the exponential and the gamma distribution models and has been verified as efficient by previous studies, was used to analyze the low-flow frequency using dam inflow data. We studied its applicability via comparison with statistics of observed data and other models already used for low-flow frequency analysis. For this, we carried out a performance analysis through a low-flow frequency analysis of inflow data from the hydroelectric dam and the reappearance capacity assessment of observed data at the Han river watershed. As a result, the hydrological applicability of the Lindley distribution model and its relative qualitative and quantitative excellence compared to the existing model were verified.

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Similarity of climate control on base flow and perennial stream density in the Budyko framework

Hydrology and Earth System Sciences ◽

10.5194/hess-17-315-2013 ◽

2013 ◽

Vol 17 (1) ◽

pp. 315-324 ◽

Cited By ~ 40

Author(s):

D. Wang ◽

L. Wu

Keyword(s):

Aridity Index ◽

Base Flow ◽

Low Flow ◽

Climate Control ◽

Stream Network ◽

Monotonic Trend ◽

Perennial Stream ◽

Stream Density ◽

The Mean ◽

Annual Scale

Abstract. Connection between perennial stream and base flow at the mean annual scale exists since one of the hydrologic functions of perennial stream is to deliver runoff even in low flow seasons. The partitioning of precipitation into runoff and evaporation at the mean annual scale, on the first order, is captured by the ratio of potential evaporation to precipitation (EP/P called climate aridity index) based on Budyko hypothesis. Perennial stream density (DP), which is obtained from the high resolution National Hydrography Dataset, for 185 watersheds declines monotonically with climate aridity index, and an inversely proportional function is proposed to model the relationship between DP and EP/P. The monotonic trend of perennial stream density reconciles with the Abrahams curve since perennial stream density is only a small portion of the total drainage density. The correlation coefficient between the ratio of base flow to precipitation (Qb/P), which follows a complementary Budyko type curve and perennial stream density is found to be 0.74. The similarity between Qb/P and DP reveals the co-evolution between water balance and perennial stream network.

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Controls on hydrologic drought duration in near-natural streamflow in Europe and the USA

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-12-12877-2015 ◽

2015 ◽

Vol 12 (12) ◽

pp. 12877-12910 ◽

Cited By ~ 3

Author(s):

E. Tijdeman ◽

S. Bachmair ◽

K. Stahl

Keyword(s):

Large Scale ◽

Aridity Index ◽

Early Warning Systems ◽

Base Flow ◽

Classification Systems ◽

Flow Index ◽

Climate Classification ◽

Drought Duration ◽

The Usa ◽

Hydrologic Drought

Abstract. Climate classification systems, such as Köppen–Geiger and the aridity index, are often used in large-scale drought modeling studies and in drought monitoring and early warning systems to stratify regions with similar hydro-climatic drought properties. What is currently lacking is a large-scale evaluation of the relation between climate and hydrologic drought characteristics. In this study we explored how suitable common climate classifications are for differentiating river basins according to their characteristic hydrologic drought duration and whether drought durations within the same climate classes are comparable between different regions. This study uses a dataset of 808 near-natural streamflow records from Europe and the USA to answer these questions. First, we grouped drought duration distributions of each record over different classes of climate classification systems and individual climate and catchment controls. Then, we compared these drought duration distributions of all classes within each climate classification system or classification based on individual controls. Results showed that climate classification systems that include absolute precipitation in their classification scheme (e.g., the aridity index) are most suitable to differentiate basins according to drought duration within both the USA and Europe. However, differences in duration distributions were found for the same climate classes in Europe and the USA. These differences are likely caused by differences in precipitation, in catchment controls as expressed by the base flow index and in differences in climate beyond the total water balance (e.g., seasonality in precipitation), which have shown to exert a control on drought duration as well. Climate classification systems that include an absolute precipitation control can be tailored into drought monitoring and early warning systems for Europe and the USA to define regions with different sensitivities to hydrologic droughts, which, for example, have been found to be higher in basins with a low aridity index. However, stratification of basins according to these climate classification systems is likely to be complemented with information of other climate classification systems (Köppen–Geiger) and individual controls (precipitation and the base flow index), especially in a comparative study between Europe and the USA.

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Surface-groundwater interaction in unconfined sedimentary aquifer system in the Brazil’s tropical wet region

RBRH ◽

10.1590/2318-0331.241920180136 ◽

2019 ◽

Vol 24 ◽

Author(s):

Guilherme Henrique Cavazzana ◽

Giancarlo Lastoria ◽

Sandra Garcia Gabas

Keyword(s):

Water Resources ◽

Water Security ◽

Surface Flow ◽

Base Flow ◽

Low Flow ◽

Flow Index ◽

Monthly Precipitation ◽

Hydrograph Separation ◽

Aquifer System ◽

Sedimentary Aquifer

ABSTRACT Since groundwater and surface waters are important components of the hydrological system, determining their interaction is essential for the efficient management of water resources by predicting the consequences of interference, whether due to the growth of demand or due to climate change. However, integrated scientific studies on these water resources are scarce, including in the Guariroba’s Environmental Protection Area, responsible for supplying 31.3% of the Campo Grandem/MS’s population, representing a local water security element. Thus, this work had as objective to evaluate the interaction between surface-groundwater in an unconfined sedimentary aquifer system, based on hydrograph separation methodologies of base flow, Flow Duration Curve (FDC) analysis, Master Recession Curve (MRC) evaluation and verification of the relationship between the surface flow, piezometric levels (PL) of the wells and the monthly precipitation. The results indicates a proportional relationship between rainfall, superficial flow and PL variations; the FDC smooth slope suggests that the baseflow is sustained by the groundwater discharge, corresponding to 89% of the total flow; the low-flow index indicates that the groundwater’s storage capacity is about 80%; the Base-Flow Index (BFI) ranging from 0.804 to 0.921, indicates a stable flow regime, aquifer’s high permeability conditions, though not uniform, and low runoff.

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