Conductivity Mass Balance Method Research Articles

The age and sources of stream water in a boreal forest watershed in the permafrost region: a case study of a watershed in northeast China

Determining the age and sources of stream water is critical for understanding the watershed hydrological processes and biogeochemical cycle. In this study, daily isotope data of rainfall and runoff, as well as continuously monitored conductivity data from June to October in 2019 in-Laoyeling(LYL) watershed located in permafrost region of northeastern China were used to separate streamflow components through the application of two independent methods: isotope-based hydrograph separations (IHS) and the conductivity mass balance (CMB) methods. The results showed that stream water in a boreal forest watershed with permafrost of the Daxing’an Mountains is mainly composed of pre-event water. Although the IHS method is more sensitive and provides more details than the CMB method, the results of both methods show a similar trend. The average value of the young water fractions (Fyw) for those aged less than 65 days is 5.6%, while the mean transit time (MTT) was calculated to be 3.33 years. These findings enhance our understanding of the fundamental characteristics of runoff generation mechanisms and changes in runoff components in permafrost regions. Such knowledge is crucial for effective regional water resource management under the context of climate change, such as construction of water conservancy facilities and prediction of flood and drought disasters.

Can the two-parameter recursive digital filter baseflow separation method really be calibrated by the conductivity mass balance method?

Abstract. The two-parameter recursive digital filter method (Eckhardt) and the conductivity mass balance (CMB) method are two widely used baseflow separation methods favored by hydrologists. Some divergences in the application of these two methods have emerged in recent years. Some scholars believe that deviation of baseflow separation results of the two methods is due to uncertainty of the parameters of the Eckhardt method and that the Eckhardt method should be corrected by reference to the CMB method. However, other scholars attribute the deviation to the fact that they contain different transient water components. This study aimed to resolve this disagreement by analyzing the effectiveness of the CMB method for correcting the Eckhardt method through application of the methods to 26 basins in the United States by comparison of the biases between the generated daily baseflow series. The results showed that the approach of calibrating the Eckhardt method against the CMB method provides a “false” calibration of total baseflow by offsetting the inherent biases in the baseflow sequences generated by the two methods. The baseflow sequence generated by the Eckhardt method usually includes slow interflow and bank storage return flow, whereas that of the CMB method usually includes high-conductivity water flushed from swamps and depressions by rainfall, but not low-conductivity interflow and bank storage return flow. This difference results in obvious peak misalignment and periodic deviation between the baseflow sequences obtained by the two methods, thereby preventing calibration. However, multi-component separation of streamflow can be achieved through comparison. Future research should recognize the deviations between the separation results obtained by the different methods, identify the reasons for these differences, and explore the hydrological information contained therein.

Key challenges facing the application of the conductivity mass balance method: a case study of the Mississippi River basin

Abstract. The conductivity mass balance (CMB) method has a long history of application to baseflow separation studies. The CMB method uses site-specific and widely available discharge and specific conductance data. However, certain aspects of the method remain unstandardized, including the determination of the applicability of this method for a specific area, minimum data requirements for baseflow separation and the most accurate parameter calculation method. This study collected and analyzed stream discharge and water conductivity data for over 200 stream sites at large spatial (2.77 to 2 915 834 km2 watersheds) and temporal (up to 56 years) scales in the Mississippi River basin. The suitability criteria and key factors influencing the applicability of the CMB method were identified based on an analysis of the spatial distribution of the inverse correlation coefficient between stream discharge and conductivity and the rationality of baseflow separation results. Sensitivity analysis, uncertainty assessment and T test were used to identify the parameter the method was most sensitive to, and the uncertainties of baseflow separation results obtained from different parameter determination methods and various sampling durations were compared. The results indicated that the inverse correlation coefficient between discharge and conductivity can be used to quantitatively determine the applicability of the CMB method, while the CMB method is more applicable in tributaries, headwater reaches, high altitudes and regions with little influence from anthropogenic activities. A minimum of 6-month discharge and conductivity data was found to provide reliable parameters for the CMB method with acceptable errors, and it is recommended that the parameters SCRO and SCBF be determined by the 1st percentile and dynamic 99th percentile methods, respectively. The results of this study can provide an important basis for the standardized treatment of key problems in the application of the CMB.

Comparative Analysis of Four Baseflow Separation Methods in the South Atlantic-Gulf Region of the U.S.

Baseflow estimation and evaluation are two critical and essential tasks for water quality and quantity, drought management, water supply, and groundwater protection. Observed baseflows are rarely available and are limited to focused pilot studies. In this study, an exhaustive evaluation of four different baseflow separation methods (HYSEP, WHAT, BFLOW, and PART) using surrogates of observed baseflows estimated with the conductivity mass balance (CMB) method is carried out using data from several streamflow gauging sites from the South Atlantic-Gulf (SAG) region comprised of nine states in the Southeastern U.S. Daily discharge data from 75 streamflow gauging sites for the period 1970–2013, located in the least anthropogenically affected basins in the SAG region were used to estimate the baseflow index (BFI), which quantifies the contribution of baseflow from streamflows. The focus of this study is to compare the four different baseflow separation methods and calibrate and validate these methods using CMB method based estimates of baseflows to evaluate the variation of BFI values derived from these methods. Results from the study suggest that the PART and HYSEP methods provide the highest and lowest average BFI values of 0.62 and 0.52, respectively. Similarities in BFI values estimated from these methods are noted based on a strong correlation between WHAT and BFLOW. The highest BFI values were found in April in the eastern, western, and central parts of the SAG region, and the highest contribution of baseflow to the streamflow was noted in October in the southern region. However, the lowest BFI values were noted in the month of September in all regions of SAG. The calibrated WHAT method using data from the CMB method provides the highest correlation as noted by the coefficient of determination. This study documents an exhaustive and comprehensive evaluation of baseflow separation methods in the SAG region, and results from this work can aid in the selection of the best method based on different metrics reported in this study. The use of the best method can aid in the short and long term management of low flows at a regional level that supports a sustainable aquatic environment and mitigates the effects of droughts effectively.

Two baseflow separation methods based on daily average gage height and discharge

Abstract Hydrologists are urgently seeking to find a more universal and inexpensive tracer for baseflow separation, and gage height may form an appropriate choice. This study derives the gage height mass balance (GHMB) and gage height power function (GHPF) methods using a two-component mass balance equation based on the relationship between the gage height and streamflow. The GHMB and GHPF methods are corrected by comparing the results of the conductivity mass balance (CMB), conductivity power function (CMBPF), GHMB, and GHPF methods in 20 basins in the United States. Subsequently, the corrected GHMB and GHPF methods are applied to seven other basins. The results indicate that: (1) the baseflow index (BFI) values calculated from the GHMB and GHPF methods are in good agreement with those of conventional methods; (2) the daily baseflow calculated as per the GHMB and GHPF methods can be suitably fitted with the CMB method; (3) the baseflow is significantly suppressed when the flood peak is larger, and deviations between the GHMB, GHPF, and CMB results are mainly observed for flood events with a large flood peak. As a tracer, the gage height can reasonably separate the baseflow, and the results indicate the efficacy of the methods.

Analysis of the Performance of Base Flow Separation Methods Using Chemistry and Statistics in Sudano-Sahelian Watershed, Burkina Faso

This research aims to determine appropriate methods for base flow separation under Sudano-Sahelian climate in West Africa. Four Recursive Digital Filtering (RDF) methods and the Conductivity Mass Balance (CMB) method were used. Daily streamflow of the Mouhoun River (formerly Black Volta River) at Samendeni gauge station has been separated into base flow and runoff. The RDF methods are easy to use but cannot take into account the actual hydrological processes within the watershed, while CMB method does it well. But, given that regular discharge measurement is rarely coupled with Electrical Conductivity measurements, it is therefore not possible to apply CMB method over time at each outlet. The CMB method is frequently used on a short time as a reference to assess the performance or to calibrate RDF methods. In the present study, CMB method was used for the year 2017, especially during the rainy season (from July to October) to produce more realistic base flow values. Statistical analysis was used to compare RDF and CMB methods. It was found that all the four RDF methods used are significantly different from the CMB method in the study area. Among the RDF methods, the Eckhardt method which is two parameters filtering method was successfully calibrated using CMB method Base Flow Index (BFI) as constraint. With the calibration process, the parameter BFImax of the Eckhardt method was adjusted to 0.32 in the study area context. The achievements of this study can have several implications such as adequate base flow estimation over time at Samendeni gauge station and at other similar gauges of the Mouhoun watershed which will be particularly beneficial to the critical issue of assessment of climate change impact on base flow in the study area.

The cumulative effects of forest disturbance and climate variability on streamflow components in a large forest-dominated watershed

Assessing how forest disturbance and climate variability affect streamflow components is critical for watershed management, ecosystem protection, and engineering design. Previous studies have mainly evaluated the effects of forest disturbance on total streamflow, rarely with attention given to its components (e.g., base flow and surface runoff), particularly in large watersheds (>1000 km2). In this study, the Upper Similkameen River watershed (1810 km2), an international watershed situated between Canada and the USA, was selected to examine how forest disturbance and climate variability interactively affect total streamflow, baseflow, and surface runoff. Baseflow was separated using a combination of the recursive digital filter method and conductivity mass balance method. Time series analysis and modified double mass curves were then employed to quantitatively separate the relative contributions of forest disturbance and climate variability to each streamflow component. Our results showed that average annual baseflow and baseflow index (baseflow/streamflow) were 113.3 ± 35.6 mm year−1 and 0.27 for 1954–2013, respectively. Forest disturbance increased annual streamflow, baseflow, and surface runoff of 27.7 ± 13.7 mm, 7.4 ± 3.6 mm, and 18.4 ± 12.9 mm, respectively, with its relative contributions to the changes in respective streamflow components being 27.0 ± 23.0%, 29.2 ± 23.1%, and 25.7 ± 23.4%, respectively. In contrast, climate variability decreased them by 74.9 ± 13.7 mm, 17.9 ± 3.6 mm, and 53.3 ± 12.9 mm, respectively, with its relative contributions to the changes in respective streamflow components being 73.0 ± 23.0%, 70.8 ± 23.1% and 73.1 ± 23.4%, respectively. Despite working in opposite ways, the impacts of climate variability on annual streamflow, baseflow, and surface runoff were of a much greater magnitude than forest disturbance impacts. This study has important implications for the protection of aquatic habitat, engineering design, and watershed planning in the context of future forest disturbance and climate change.

Base flow separation: A comparison of analytical and mass balance methods

Summary Base flow is the ground water contribution to stream flow. Many activities, such as water resource management, calibrating hydrological and climate models, and studies of basin hydrology, require good estimates of base flow. The base flow component of stream flow is usually determined by separating a stream hydrograph into two components, base flow and runoff. Analytical methods, mathematical functions or algorithms used to calculate base flow directly from discharge, are the most widely used base flow separation methods and are often used without calibration to basin or gage-specific parameters other than basin area. In this study, six analytical methods are compared to a mass balance method, the conductivity mass-balance (CMB) method. The base flow index (BFI) values for 35 stream gages are obtained from each of the seven methods with each gage having at least two consecutive years of specific conductance data and 30 years of continuous discharge data. BFI is cumulative base flow divided by cumulative total discharge over the period of record of analysis. The BFI value is dimensionless, and always varies from 0 to 1. Areas of basins used in this study range from 27 km 2 to 68,117 km 2 . BFI was first determined for the uncalibrated analytical methods. The parameters of each analytical method were then calibrated to produce BFI values as close to the CMB derived BFI values as possible. One of the methods, the power function ( aQ b + cQ ) method, is inherently calibrated and was not recalibrated. The uncalibrated analytical methods have an average correlation coefficient of 0.43 when compared to CMB-derived values, and an average correlation coefficient of 0.93 when calibrated with the CMB method. Once calibrated, the analytical methods can closely reproduce the base flow values of a mass balance method. Therefore, it is recommended that analytical methods be calibrated against tracer or mass balance methods.

A new approach for continuous estimation of baseflow using discrete water quality data: Method description and comparison with baseflow estimates from two existing approaches

Understanding how watershed characteristics and climate influence the baseflow component of stream discharge is a topic of interest to both the scientific and water management communities. Therefore, the development of baseflow estimation methods is a topic of active research. Previous studies have demonstrated that graphical hydrograph separation (GHS) and conductivity mass balance (CMB) methods can be applied to stream discharge data to estimate daily baseflow. While CMB is generally considered to be a more objective approach than GHS, its application across broad spatial scales is limited by a lack of high frequency specific conductance (SC) data. We propose a new method that uses discrete SC data, which are widely available, to estimate baseflow at a daily time step using the CMB method. The proposed approach involves the development of regression models that relate discrete SC concentrations to stream discharge and time. Regression-derived CMB baseflow estimates were more similar to baseflow estimates obtained using a CMB approach with measured high frequency SC data than were the GHS baseflow estimates at twelve snowmelt dominated streams and rivers. There was a near perfect fit between the regression-derived and measured CMB baseflow estimates at sites where the regression models were able to accurately predict daily SC concentrations. We propose that the regression-derived approach could be applied to estimate baseflow at large numbers of sites, thereby enabling future investigations of watershed and climatic characteristics that influence the baseflow component of stream discharge across large spatial scales.

Data requirements for using combined conductivity mass balance and recursive digital filter method to estimate groundwater recharge in a small watershed, New Brunswick, Canada

Summary Estimation of baseflow and groundwater recharge rates is important for hydrological analysis and modelling. A new approach which combines recursive digital filter (RDF) model with conductivity mass balance (CMB) method was considered to be reliable for baseflow separation because the combined method takes advantages of the reduced data requirement for RDF method and the reliability of CMB method. However, it is not clear what the minimum data requirements for producing acceptable estimates of the RDF model parameters are. In this study, 19-year record of stream discharge and water conductivity collected from the Black Brook Watershed (BBW), NB, Canada were used to test the combined baseflow separation method and assess the variability of parameters in the model over seasons. The data requirements and potential bias in estimated baseflow index (BFI) were evaluated using conductivity data for different seasons and/or resampled data segments at various sampling durations. Results indicated that the data collected during ground-frozen season are more suitable to estimate baseflow conductivity ( C bf ) and data during snow-melting period are more suitable to estimate runoff conductivity ( C ro ). Relative errors of baseflow estimation were inversely proportional to the number of conductivity data records. A minimum of six-month discharge and conductivity data is required to obtain reliable parameters for current method with acceptable errors. We further found that the average annual recharge rate for the BBW was 322 mm in the past twenty years.

Baseflow separation in a small watershed in New Brunswick, Canada, using a recursive digital filter calibrated with the conductivity mass balance method

AbstractBaseflow separation is important for obtaining critical parameters for hydrological models. As measuring the baseflow component directly is difficult, various analytical and empirical baseflow separation methods have been developed and tested. The recursive digital filter (RDF) method is commonly used for baseflow separation due to its simplicity and low data requirement. However, parameters used in the RDF method are often determined arbitrarily, resulting in high uncertainty of the estimated baseflow rate. A more accurate method is the conductivity mass balance (CMB) method, which is established based on the differences in physical processes between baseflow and surface runoff. In this research, the output of the CMB method was used to calibrate the parameters of an RDF model, and the calibrated RDF model was used to estimate monthly, seasonal and annual baseflow rate and baseflow index for the past 19 years using streamflow discharge records. The characteristics of the baseflow hydrographs were found to be consistent with the hydrological and hydrogeological conditions of the research area. Research results indicated that the accuracy of the RDF model has been greatly enhanced after being calibrated with the CMB method so that the RDF model can provide more reliable baseflow separation results for a long‐term study. Copyright © 2012 John Wiley & Sons, Ltd.

Calibration of Base Flow Separation Methods with Streamflow Conductivity

The conductivity mass-balance (CMB) method can be used to calibrate analytical base flow separation methods. The principal CMB assumptions are base flow conductivity is equal to streamflow conductivity at lowest flows, runoff conductivity is equal to streamflow conductivity at highest flows, and base flow and runoff conductivities are assumed to be constants over the period of record. To test the CMB assumptions, fluid conductivities of ground water, surface runoff, and streamflow were measured during wet and dry conditions in a 12-km(2) stream basin. Ground water conductivities at wells varied an average of 6% from dry to wet conditions, while stream conductivities varied 58%. Shallow ground water conductivity varied significantly with distance from the stream, with lowest conductivities of 87 microS/cm near the divide, a maximum of 520 microS/cm 59 m from the stream, and 215 microS/cm 22 m from the stream. Runoff conductivities measured in three rain events remained nearly constant, with lower conductivities of 35 microS/cm near the divide and 50 microS/cm near the stream. The CMB method was applied to the records from 10 USGS stream-gauging stations in Texas, Kentucky, Georgia, and Florida to calibrate the USGS base flow separation technique, HYSEP, by varying the time parameter 2N*. There is a statistically significant relationship between basin areas and calibrated values of 2N*, expressed as N = 0.46A(0.44), with N in days and A in km(2). The widely accepted relationship N = 0.83A(0.2) is not valid for these basins. Other analytic methods can also be calibrated with the CMB method.