Attributes for MRB_E2RF1 Catchments by Major River Basins in the Conterminous United States: Base-Flow Index, 2002

Abstract. Predicting discharge in ungauged catchments or contaminant movement through soil requires knowledge of the distribution and spatial heterogeneity of hydrological soil properties. Because hydrological soil information is not available at a European scale, we reclassified the Soil Geographical Database of Europe (SGDBE) at 1:1 million in a hydrological manner by adopting the Hydrology Of Soil Types (HOST) system developed in the UK. The HOST classification describes dominant pathways of water movement through soil and was related to the base flow index (BFI) of a catchment (the long-term proportion of base flow on total stream flow). In the original UK study, a linear regression of the coverage of HOST classes in a catchment explained 79% of BFI variability. We found that a hydrological soil classification can be built based on the information present in the SGDBE. The reclassified SGDBE and the regression coefficients from the original UK study were used to predict BFIs for 103 catchments spread throughout Europe. The predicted BFI explained around 65% of the variability in measured BFI in catchments in Northern Europe, but the explained variance decreased from North to South. We therefore estimated new regression coefficients from the European discharge data and found that these were qualitatively similar to the original estimates from the UK. This suggests little variation across Europe in the hydrological effect of particular HOST classes, but decreasing influence of soil on BFI towards Southern Europe. Our preliminary study showed that pedological information is useful for characterising soil hydrology within Europe and the long-term discharge regime of catchments in Northern Europe. Based on these results, we draft a roadmap for a refined hydrological classification of European soils.

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Conditioning rainfall-runoff model parameters for ungauged catchments and land management impacts analysis

Hydrology and Earth System Sciences ◽

10.5194/hess-13-893-2009 ◽

2009 ◽

Vol 13 (6) ◽

pp. 893-904 ◽

Cited By ~ 68

Author(s):

N. Bulygina ◽

N. McIntyre ◽

H. Wheater

Keyword(s):

Parameter Space ◽

Land Management ◽

Base Flow ◽

Distributed Model ◽

Flow Index ◽

Model Parameters ◽

Ungauged Catchments ◽

Management Interventions ◽

Simulated Event ◽

Base Flow Index

Abstract. Data scarcity and model over-parameterisation, leading to model equifinality and large prediction uncertainty, are common barriers to effective hydrological modelling. The problem can be alleviated by constraining the prior parameter space using parameter regionalisation. A common basis for regionalisation in the UK is the HOST database which provides estimates of hydrological indices for different soil classifications. In our study, Base Flow Index is estimated from the HOST database and the power of this index for constraining the parameter space is explored. The method is applied to a highly discretised distributed model of a 12.5 km2 upland catchment in Wales. To assess probabilistic predictions against flow observations, a probabilistic version of the Nash-Sutcliffe efficiency is derived. For six flow gauges with reliable data, this efficiency ranged between 0.70 and 0.81, and inspection of the results shows that the model explains the data well. Knowledge of how Base Flow Index and interception losses may change under future land use management interventions was then used to further condition the model. Two interventions are considered: afforestation of grazed areas, and soil degradation associated with increased grazing intensity. Afforestation leads to median reduction in modelled runoff volume of 24% over the simulated 3 month period; and a median peak flow reduction ranging from 12 to 15% over the six gauges for the largest simulated event. Uncertainty in all results is low compared to prior uncertainty and it is concluded that using Base Flow Index estimated from HOST is a simple and potentially powerful method of conditioning the parameter space under current and future land management.

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Streamflow contributions from tribal lands to major river basins of the United States

PLoS ONE ◽

10.1371/journal.pone.0203872 ◽

2018 ◽

Vol 13 (9) ◽

pp. e0203872

Author(s):

Kyle Blasch ◽

Stephen Hundt ◽

Patrick Wurster ◽

Roy Sando ◽

Antony Berthelote

Keyword(s):

United States ◽

River Basins ◽

The United States ◽

Major River ◽

Tribal Lands

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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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Quantification of Temporal Variations in Base Flow Index Using Sporadic River Data: Application to the Bua Catchment, Malawi

Water ◽

10.3390/w11050901 ◽

2019 ◽

Vol 11 (5) ◽

pp. 901 ◽

Cited By ~ 10

Author(s):

Laura Kelly ◽

Robert M. Kalin ◽

Douglas Bertram ◽

Modesta Kanjaye ◽

Macpherson Nkhata ◽

...

Keyword(s):

Water Resources ◽

River Flow ◽

Temporal Variations ◽

Dry Season ◽

Base Flow ◽

Flow Index ◽

Wet Season ◽

Data Application ◽

Base Flow Index ◽

Long Term Trends

This study investigated how sporadic river datasets could be used to quantify temporal variations in the base flow index (BFI). The BFI represents the baseflow component of river flow which is often used as a proxy indicator for groundwater discharge to a river. The Bua catchment in Malawi was used as a case study, whereby the smoothed minima method was applied to river flow data from six gauges (ranging from 1953 to 2009) and the Mann-Kendall (MK) statistical test was used to identify trends in BFI. The results showed that baseflow plays an important role within the catchment. Average annual BFIs > 0.74 were found for gauges in the lower reaches of the catchment, in contrast to lower BFIs < 0.54 which were found for gauges in the higher reaches. Minimal difference between annual and wet season BFI was observed, however dry season BFI was >0.94 across all gauges indicating the importance of baseflow in maintaining any dry season flows. Long term trends were identified in the annual and wet season BFI, but no evidence of a trend was found in the dry season BFI. Sustainable management of the investigated catchment should, therefore, account for the temporal variations in baseflow, with special regard to water resources allocation within the region and consideration in future scheme appraisals aimed at developing water resources. Further, this demonstration of how to work with sporadic river data to investigate baseflow serves as an important example for other catchments faced with similar challenges.

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Conditioning rainfall-runoff model parameters for ungauged catchments and land management impacts analysis

Hydrology and Earth System Sciences Discussions ◽

10.5194/hessd-6-1907-2009 ◽

2009 ◽

Vol 6 (2) ◽

pp. 1907-1938 ◽

Cited By ~ 2

Author(s):

N. Bulygina ◽

N. McIntyre ◽

H. Wheater

Keyword(s):

Parameter Space ◽

Land Management ◽

Base Flow ◽

Distributed Model ◽

Flow Index ◽

Model Parameters ◽

Ungauged Catchments ◽

Management Interventions ◽

Simulated Event ◽

Base Flow Index

Abstract. Data scarcity and model over-parameterisation, leading to model equifinality and large prediction uncertainty, are common barriers to effective hydrological modelling. The problem can be alleviated by constraining the prior parameter space using parameter regionalization. A common basis for regionalization in the UK is the HOST database which provides estimates of hydrological indices for different soil classifications. In our study, Base Flow Index is estimated from the HOST database and the power of this index for constraining the parameter space is explored. The method is applied to a highly discretized distributed model of a 12.5 km2 upland catchment in Wales. To assess probabilistic predictions against flow observations, a probabilistic version of the Nash-Sutcliffe efficiency is derived. For six flow gauges with reliable data, this efficiency ranged between 0.70 and 0.81, and inspection of the results shows that the model explains the data well. Knowledge of how Base Flow Index and interception losses may change under future land use management interventions was then used to further condition the model. Two interventions are considered: afforestation of grazed areas, and soil degradation associated with increased grazing intensity. Afforestation leads to median reduction in modelled runoff volume of 24% over the simulated 3 month period; and a median peak flow reduction ranging from 12–15% over the six gauges for the largest simulated event. Uncertainty in all results is suprisingly low and it is concluded that using Base Flow Index estimated from HOST is a simple and potentially powerful method of conditioning the parameter space under current and future land management.

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