scholarly journals U.S. Geological Survey groundwater toolbox, a graphical and mapping interface for analysis of hydrologic data (version 1.0): user guide for estimation of base flow, runoff, and groundwater recharge from streamflow data

2015 ◽  
Author(s):  
Paul M. Barlow ◽  
William L. Cunningham ◽  
Tong Zhai ◽  
Mark Gray
Keyword(s):  
Groundwater Recharge ◽  
Base Flow ◽  
Geological Survey ◽  
Hydrologic Data ◽  
Streamflow Data

scholarly journals Long-term groundwater recharge rates across India by in situ measurements

2018 ◽  
Author(s):  
Soumendra N. Bhanja ◽  
Abhijit Mukherjee ◽  
Rangarajan Ramaswamy ◽  
Bridget R. Scanlon ◽  
Pragnaditya Malakar ◽  
...  
Keyword(s):  
Groundwater Recharge ◽  
River Basins ◽  
Base Flow ◽  
Groundwater Abstraction ◽  
Pumping Wells ◽  
Anthropogenic Discharge ◽  
Stressed Region ◽  
Recharge Rates ◽  
Using Data

Abstract. Groundwater recharge sustains groundwater discharge, including natural discharge through springs and base flow to surface water as well as anthropogenic discharge through pumping wells. Here, for the first time, we compute long-term (1996–2015) groundwater recharge rates using data retrieved from several groundwater level monitoring locations across India (3.3 million km2 area), the most groundwater-stressed region globally. Spatial variations in groundwater recharge rates (basin-wide mean: 17 to 960 mm/yr) were estimated in the 22 major river basins across India. The extensive plains of the Indus–Ganges–Brahmaputra (IGB) river basins are subjected to prevalence of comparatively higher recharge. This is mainly attributed to occurrence of coarse sediments, higher rainfall, and intensive irrigation-linked groundwater abstraction inducing recharge by increasing available groundwater storage and return flows. Lower recharge rates (

scholarly journals Assessment of surface water resources availability using catchment modeling and the results of tracer studies in the meso-scale Migina Catchment, Rwanda

2013 ◽  
Vol 10 (12) ◽  
pp. 15375-15408 ◽  
Author(s):  
O. Munyaneza ◽  
A. Mukubwa ◽  
S. Maskey ◽  
J. Wenninger ◽  
S. Uhlenbrook
Keyword(s):  
Decision Making ◽  
Water Resources ◽  
Hydrological Model ◽  
Base Flow ◽  
Hydrological Processes ◽  
Model Parameters ◽  
Water Resources Planning ◽  
Catchment Scale ◽  
Streamflow Data ◽  
Resources Planning

Abstract. In the last couple of years, different hydrological research projects were undertaken in the Migina catchment (243.2 km2), a tributary of the Kagera river in Southern Rwanda. These projects were aimed to understand hydrological processes of the catchment using analytical and experimental approaches and to build a pilot case whose experience can be extended to other catchments in Rwanda. In the present study, we developed a hydrological model of the catchment, which can be used to inform water resources planning and decision making. The semi-distributed hydrological model HEC-HMS (version 3.5) was used with its soil moisture accounting, unit hydrograph, liner reservoir (for base flow) and Muskingum-Cunge (river routing) methods. We used rainfall data from 12 stations and streamflow data from 5 stations, which were collected as part of this study over a period of two years (May 2009 and June 2011). The catchment was divided into five sub-catchments each represented by one of the five observed streamflow gauges. The model parameters were calibrated separately for each sub-catchment using the observed streamflow data. Calibration results obtained were found acceptable at four stations with a Nash–Sutcliffe Model Efficiency of 0.65 on daily runoff at the catchment outlet. Due to the lack of sufficient and reliable data for longer periods, a model validation (split sample test) was not undertaken. However, we used results from tracer based hydrograph separation from a previous study to compare our model results in terms of the runoff components. It was shown that the model performed well in simulating the total flow volume, peak flow and timing as well as the portion of direct runoff and base flow. We observed considerable disparities in the parameters (e.g. groundwater storage) and runoff components across the five sub-catchments, that provided insights into the different hydrological processes at sub-catchment scale. We conclude that such disparities justify the need to consider catchment subdivisions, if such parameters and components of the water cycle are to form the base for decision making in water resources planning in the Migina catchment.

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