Decorrelation is not dissociation: There is no means to entirely decouple the Brutsaert-Nieber parameters in streamflow recession analysis

2021 ◽  
Vol 147 ◽  
pp. 103822
Author(s):  
Basudev Biswal
Keyword(s):  
2013 ◽  
Vol 17 (2) ◽  
pp. 817-828 ◽  
Author(s):  
M. Stoelzle ◽  
K. Stahl ◽  
M. Weiler

Abstract. Streamflow recession has been investigated by a variety of methods, often involving the fit of a model to empirical recession plots to parameterize a non-linear storage–outflow relationship based on the dQ/dt−Q method. Such recession analysis methods (RAMs) are used to estimate hydraulic conductivity, storage capacity, or aquifer thickness and to model streamflow recession curves for regionalization and prediction at the catchment scale. Numerous RAMs have been published, but little is known about how comparably the resulting recession models distinguish characteristic catchment behavior. In this study we combined three established recession extraction methods with three different parameter-fitting methods to the power-law storage–outflow model to compare the range of recession characteristics that result from the application of these different RAMs. Resulting recession characteristics including recession time and corresponding storage depletion were evaluated for 20 meso-scale catchments in Germany. We found plausible ranges for model parameterization; however, calculated recession characteristics varied over two orders of magnitude. While recession characteristics of the 20 catchments derived with the different methods correlate strongly, particularly for the RAMs that use the same extraction method, not all rank the catchments consistently, and the differences among some of the methods are larger than among the catchments. To elucidate this variability we discuss the ambiguous roles of recession extraction procedures and the parameterization of the storage–outflow model and the limitations of the presented recession plots. The results suggest strong limitations to the comparability of recession characteristics derived with different methods, not only in the model parameters but also in the relative characterization of different catchments. A multiple-methods approach to investigating streamflow recession characteristics should be considered for applications whenever possible.


2015 ◽  
Vol 525 ◽  
pp. 102-112 ◽  
Author(s):  
Brian F. Thomas ◽  
Richard M. Vogel ◽  
James S. Famiglietti
Keyword(s):  

2021 ◽  
Author(s):  
Hoori Ajami ◽  
Adam Schreiner-McGraw

<p>Mountain System Recharge (MSR) is one of the main components of recharge in many arid and semi-arid aquifers, yet the mechanisms of MSR in high-elevation mountain ranges are poorly understood. The complexity of recharge processes and the lack of groundwater observations in mountain catchments contribute to this problem. MSR consists of two distinct pathways: 1) mountain bedrock aquifer recharge (MAR) consists of snowmelt or rainfall derived infiltration into the mountain bedrock, which either discharges to streams as baseflow or reaches an alluvial aquifer in an adjacent valley via lateral subsurface flow referred to as mountain block recharge (MBR), and 2) Mountain front recharge (MFR) consists of streamflow infiltration at the mountain front. Here, we apply streamflow recession analysis across 11 anthropogenically unaffected catchments in the Sierra Nevada to derive seasonally distinct storage-discharge functions and quantify MAR in response to changes in precipitation. Median annual recharge efficiencies (ratio of annual MAR to precipitation) range from 4 to 28% and can reach up to 60% during the wettest years on record. We implement a global sensitivity analysis to identify parameters that significantly impact MAR rates. Results illustrate that MAR estimates are mostly sensitive to the filter parameters for streamflow data selection used during the recession analysis, and the number of dry days after a rain event where streamflow data are excluded has the greatest impact. Our results demonstrate that storage-discharge functions are useful for quantifying groundwater recharge in mountainous catchments under perennial flow conditions. However, estimated MAR rates are impacted by the uncertainty in streamflow data, filtering of streamflow time series and model structure. Future work will be focused on quantifying uncertainty in MAR estimates caused from various sources.</p><p> </p>


2019 ◽  
Vol 33 (10) ◽  
pp. 1434-1447 ◽  
Author(s):  
Hsin‐Fu Yeh ◽  
Chia‐Chi Huang
Keyword(s):  
Low Flow ◽  

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