scholarly journals Base Flow Index of Way Seputih River at Buyut Udik

2020 ◽  
Vol 1 (2) ◽  
pp. 74
Author(s):  
Dyah Indriana Kusumastuti
Keyword(s):  
Water Conservation ◽  
River Flow ◽  
Dry Season ◽  
Base Flow ◽  
Flow Index ◽  
Discharge Data ◽  
Yearly Average ◽  
Base Flow Index ◽  
Flow Components ◽  
Over Time

One of river flow components considered in watershed management is baseflow, the main contributor to the river flow during dry season. Ratio between baseflow to total flow is called Base Flow Index (BFI). In fact, BFI can be used as an indcator how good the catchment hydrology is. The purpose of this study is to analyze BFI of Way Seputih river at Hydrometry Station Buyut Udik. The method includes Recursive Digital Filter (RDF) method, which utilizes constant recession of hydrographs in displaying the ratio of baseflow from continuous discharge during periods when there is no direct runoff. Daily discharge data from Way Seputih river at Buyut Udik recorded from 1973 to 2006 is used. The result shows that yearly BFI values range from 0.142 to 0.487 and there is a decrease trend of yearly BFI over time. This result is confirmed by yearly average discharges which tend to decrease over time. These are effected by land cover degradation in Way Seputih catchment and  this should be a concern for authorities to improve land and water conservation in Way Seputih catchment so that river flow could be maintained throughout the year. Keywords: base flow index, baseflow, dry season 

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

Water ◽  
2019 ◽  
Vol 11 (5) ◽  
pp. 901 ◽  
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.

scholarly journals Towards a hydrological classification of European soils: preliminary test of its predictive power for the base flow index using river discharge data

2007 ◽  
Vol 11 (4) ◽  
pp. 1501-1513 ◽  
Author(s):  
M. K. Schneider ◽  
F. Brunner ◽  
J. M. Hollis ◽  
C. Stamm
Keyword(s):  
Water Movement ◽  
Base Flow ◽  
Regression Coefficients ◽  
Northern Europe ◽  
Flow Index ◽  
Discharge Data ◽  
Base Flow Index ◽  
The Uk

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.

scholarly journals Towards a hydrological classification of European soils: preliminary test of its predictive power for the base flow index using river discharge data

2007 ◽  
Vol 4 (2) ◽  
pp. 831-861
Author(s):  
M. K. Schneider ◽  
F. Brunner ◽  
J. M. Hollis ◽  
C. Stamm
Keyword(s):  
Water Movement ◽  
Base Flow ◽  
Regression Coefficients ◽  
Northern Europe ◽  
Flow Index ◽  
Discharge Data ◽  
Base Flow Index ◽  
The Uk

Abstract. Predicting discharge in ungauged catchments requires knowledge on the distribution and spatial heterogeneity of hydrological soil properties. Because hydrological soil information is not available on a European scale, we reclassified the Soil Geographical Database of Europe (SGDBE) 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 the results, we draft a roadmap for a refined hydrological classification of European soils.

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

2009 ◽  
Vol 13 (6) ◽  
pp. 893-904 ◽  
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.

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

2016 ◽  
Vol 20 (10) ◽  
pp. 4043-4059 ◽  
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.

scholarly journals Studi Pemisahan Aliran Dasar Metode Local Minimum Method Daerah Aliran Sungai Miu

2021 ◽  
pp. 143-148
Author(s):  
S.R. Oktavia ◽  
O.A. Mantika ◽  
Rugaiyah Rugaiyah
Keyword(s):  
Local Minimum ◽  
River Flow ◽  
Statistical Tests ◽  
Flood Management ◽  
Statistical Test ◽  
Base Flow ◽  
Discharge Data ◽  
Permeability Characteristics ◽  
Measurement Results ◽  
Office Software

The two main elements of a river flow hydrograph are direct runoff and baseflow. Base flow is a flow that comes from groundwater and it is available during the rainy and dry seasons. Information of baseflow value of a watershed has an important meaning in efforts to develop and manage water resources, including the provision of clean water, irrigation systems, flood management and others. Miu watershed located in Sigi Regency often experiences natural disasters such as floods and droughts that occur almost every year, which is the research location with an area of 65,452.01 Ha. This study aims to determine the value of baseflow using the Local Minimum Method and to find out whether this method can be used for baseflow modeling in research watersheds. This study was conducted using Hydro Office software with input data in the form of daily discharge data from 2004 to 2013. The average baseflow value obtained was 5.43 m3/s. The process of calibrating the baseflow value by taking flow data in the dry season where there is no rainfall input. It is obtained that BFI have value an average of 0.89. This value indicates that the Miu watershed has high storage permeability characteristics, The Miu watershed has quite stable flow during dry periods, because the greater the BFI value, the better the water supply in a watershed. In the statistical test, the observed discharge is the discharge data from the measurement results for the period 2004-2013, while the calculated discharge is the result of the estimated base flow value obtained using the graphical method. From the results of the statistical test of RMSE and R2, the RMSE value was 0.147 and the R2 value was 0.751. Both statistical tests show that the local minimum method has a fairly good performance in modeling the base flow in the Miu watershed.

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

2009 ◽  
Vol 6 (2) ◽  
pp. 1907-1938 ◽  
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.

scholarly journals Characteristics of Duwet Karst Spring Based on Baseflow Index Assessment and its Potential in Fresh Water Supply

GeoEco ◽  
2021 ◽  
Vol 7 (1) ◽  
pp. 38
Author(s):  
Pipit Wijayanti ◽  
Rita Noviani
Keyword(s):  
Water Level ◽  
Fresh Water ◽  
Rainy Season ◽  
Dry Season ◽  
Base Flow ◽  
Spring Discharge ◽  
Discharge Data ◽  
Level Data ◽  
Water Level Data ◽  
Total Base

<p><em>This study aims to determine the potential of Duwet springs and their availability for supplying fresh water to the surrounding community. we use hydrographs to analyze aquifer characteristics. To analyze the hydrographs, we use water level and spring discharge data. Automatic Water Level Record (AWLR) records water level data for 1 dry season and 1 rainy season every 15 minutes. We use the volumetric method to measure the spring discharge 14 times. We compare the base flow and demand over a year to analyze the potential for fresh water. The results show that the Stage discharge rating curve y = 0.0002e5,453x with R² value of 0.87. Duwet Springs is a perennial spring that has a small discharge (class VI). The largest discharge ever recorded was 0.69 L/s (March 7, 2020) and the smallest recorded was 0.12 L/s (August 21, 2020). BFI value varied between 0.05 and 1 with mean 0.801. The total base flow is 2490675.734 L (rainy season) and 1563419.873 L (dry season). These springs are sufficient for 75% of the rainy season and 84% in the dry season. This indicates that the existence of Duwet springs is very important for the surrounding community.</em></p>

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