scholarly journals Spatially distributed groundwater recharge estimated using a water-budget model for the Island of Maui, Hawai`i, 1978–2007

Author(s):  
Adam G. Johnson ◽  
John A. Engott ◽  
Maoya Bassiouni ◽  
Kolja Rotzoll
2021 ◽  
Author(s):  
Emmanuel Dubois ◽  
Marie Larocque ◽  
Sylvain Gagné ◽  
Guillaume Meyzonnat

Abstract. Groundwater recharge (GWR) is recognized to be a strategic hydrologic variable, necessary to estimate when implementing sustainable groundwater management, especially within a global change context. However, its simulation at the regional scale and for long-term conditions is challenging, especially due to the limited availability of spatially-distributed calibration data and to the rather short observed time series. The use of a superficial water budget model to estimate recharge is appropriate for this task. A reliable regional-scale estimate of GWR that can be updated relatively easily using widely-available data is essential for the implementation of long-term water use policies and is clearly lacking in southern Quebec (Canada; 36 000 km2). This study aims to test the ability of a spatially-distributed water budget model, automatically calibrated with river flow rates and baseflow estimates, to simulate GWR at a regional-scale from 1961 to 2017 in southern Quebec (monthly time step, 500 m × 500 m spatial resolution). The novelty of this work lies in the simulation of the first regional-scale GWR estimate for southern Quebec and in the development of a robust approach to implement a superficial water budget model at the regional-scale and for a long period. The HydroBudget model was specifically developed by a team at Université du Québec à Montréal for regional-scale simulation and cold climate conditions, and uses parsimonious input data (distributed precipitation, temperature, and runoff curve numbers). The model was regionally calibrated with river flows and baseflows (recursive filter on river flow data), and the automatic calibration procedure of the R package caRamel allowed a satisfying calibration quality (KGE = 0.72) to be reached. Across the study area and based on the exceptionally long spatialized time series, the simulated water budget was divided into 41 % runoff (444 mm/yr), 47 % actual evapotranspiration (501 mm/yr), and 12 % potential groundwater recharge (139 mm/yr). This partitioning was influenced by precipitation, temperature, soil texture, land cover, and topography. Groundwater recharge peaked during spring (44 % of annual recharge) and winter (32 % of annual recharge). A novel and particularly useful result from this work was to show that the seasonality of recharge was driven by the regional temperature gradient, with decreasing temperatures from west to east, and that winter GWR presented a statistically significant increasing trend since 1961 due to increased precipitation and warming temperatures. Another original contribution of this work was to show that at the regional scale, water budget models, such as HydroBudget, can be easily calibrated with river flow measurements and baseflows, and therefore represent a good option with which to acquire knowledge about regional hydrological dynamics. Being accessible, they are a useful approach for scientists, modellers, and stakeholders alike to understand regional-scale groundwater renewal rates, especially if they can be easily adapted to specific study needs and environments.


2021 ◽  
Author(s):  
Emmanuel Dubois ◽  
Marie Larocque ◽  
Sylvain Gagné

<p>In cold and humid climates, rivers and superficial water bodies are often fed by groundwater with relatively constant inflows that are most visible during the summer (limited net precipitation) and the winter (limited runoff and infiltration). The harsh winter – short growing season succession could be drastically affected by climate change. Although water is abundant, extreme low flows are expected in the near future, most likely due to warmer summer temperatures, increased summer PET and possible lower summer precipitation. It is thus crucial to provide stakeholders with scenarios of future groundwater recharge (GWR) to anticipate the impacts of climate change on groundwater resources at the regional scale. This study aims to test the contributions of a superficial water budget model to estimate the impact of climate change on the regional GWR. The methodology is tested in a forested and agricultural region of southern Quebec, located between the St. Lawrence River and the Canada-USA border, and between the Quebec-Ontario border and Quebec City (36,000 km²). Scenarios of GWR for the region are simulated with the HydroBudget model, performing a transient-state spatialized superficial water budget, and 12 climate scenarios (RCP 4.5 and 8.5, 1951-2100 period). The model was previously calibrated in the study area for the 1961-2017 period and provides spatially distributed runoff, actual evapotranspiration, and GWR fluxes at a 500 x 500 m resolution with a monthly time step. Climate scenarios show warming of the annual temperature from +2 to +5°C and up to 20% increase of annual precipitation at the 2100 horizon compared to the 1981-2010 reference period. By the end of the century, the number of days above 0°C could double between November and April, dividing by almost two the quantity of snow during winter. The clear trends of warming temperature leads to a clear actual evapotranspiration (AET) increase while the increasing variability in annual precipitation translates into more variable annual runoff and GWR. Although no annual GWR decrease is simulated, an increase of winter GWR (up to x2) is expected, linked to warmer winters and unfrozen soils, followed by a decrease for the rest of the year, linked to a longer growing season producing higher AET rates. Although simple in its simulation process, the use of a superficial water budget model simulating soil frost provides new insights into the possible future trends in the different hydrologic variables based on a robust understanding of past condition. Aside from providing scenarios of spatialized GWR (also runoff and AET) at the 2100 horizon for a large region, this study shows that a simple water budget model is an appropriate and affordable tool to provide stakeholders with useful data for water management in a changing climate.</p>


2013 ◽  
Vol 17 (11) ◽  
pp. 4577-4588 ◽  
Author(s):  
M. Pan ◽  
E. F. Wood

Abstract. The process whereby the spatially distributed runoff (generated through saturation/infiltration excesses, subsurface flow, etc.) travels over the hillslope and river network and becomes streamflow is generally referred to as "routing". In short, routing is a runoff-to-streamflow process, and the streamflow in rivers is the response to runoff integrated in both time and space. Here we develop a methodology to invert the routing process, i.e., to derive the spatially distributed runoff from streamflow (e.g., measured at gauge stations) by inverting an arbitrary linear routing model using fixed interval smoothing. We refer to this streamflow-to-runoff process as "inverse routing". Inversion experiments are performed using both synthetically generated and real streamflow measurements over the Ohio River basin. Results show that inverse routing can effectively reproduce the spatial field of runoff and its temporal dynamics from sufficiently dense gauge measurements, and the inversion performance can also be strongly affected by low gauge density and poor data quality. The runoff field is the only component in the terrestrial water budget that cannot be directly measured, and all previous studies used streamflow measurements in its place. Consequently, such studies are limited to scales where the spatial and temporal difference between the two can be ignored. Inverse routing provides a more sophisticated tool than traditional methods to bridge this gap and infer fine-scale (in both time and space) details of runoff from aggregated measurements. Improved handling of this final gap in terrestrial water budget analysis may potentially help us to use space-borne altimetry-based surface water measurements for cross-validating, cross-correcting, and assimilation with other space-borne water cycle observations.


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