A simple model for water table fluctuations in response to precipitation

Park, Eungyu; Parker, J. C.

doi:10.1016/j.jhydrol.2008.04.022

Cited by 95 publications

(64 citation statements)

References 13 publications

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“…Park and Parker [41] developed a physically based lumped model to simulate groundwater fluctuations in response to precipitation. This model is applicable to estimate groundwater recharge from the observed groundwater level fluctuations as well as groundwater discharge or underflow.…”

Section: Conclusion and Future Improvementsmentioning

confidence: 99%

Groundwater Level Dynamics in Bengaluru City, India

Sekhar

Tomer²,

Thiyaku³

et al. 2017

Sustainability

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Abstract:Groundwater accounts for half of Indian urban water use. However, little is known about its sustainability, because of inadequate monitoring and evaluation. We deployed a dense monitoring network in 154 locations in Bengaluru, India between 2015 and 2017. Groundwater levels collected at these locations were analyzed to understand the behavior of the city's groundwater system. At a local scale, groundwater behavior is non-classical, with valleys showing deeper groundwater than ridge-tops. We hypothesize that this is due to relatively less pumping compared to artificial recharge from leaking pipes and wastewater in the higher, city core areas, than in the rapidly growing, lower peripheral areas, where the converse is true. In the drought year of 2016, groundwater depletion was estimated at 27 mm, or 19 Mm 3 over the study area. The data show that rainfall has the potential to replenish the aquifer. High rainfall during August-September 2017 led to a mean recharge of 67 mm, or 47 Mm 3 for the study area. A rainfall recharge factor of 13.5% was estimated from the data for 2016. Sustainable groundwater management in Bengaluru must account for substantial spatial socio-hydrological heterogeneity. Continuous monitoring at high spatial density will be needed to inform evidence-based policy.

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Section: Conclusion and Future Improvementsmentioning

confidence: 99%

Groundwater Level Dynamics in Bengaluru City, India

Sekhar

Tomer²,

Thiyaku³

et al. 2017

Sustainability

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show abstract

“…Daily precipitation is important at a river basin scale because it is (1) the main driver of runoff generation in river basins (Chen et al 2010;Chiew et al 2009;Kim and Pachepsky 2010;Piani et al 2010); (2) used in the evaluation of flood frequency for flood safety, which is of utmost concern for water resource management agencies for operating and maintaining reservoir systems (Raff et al 2009), and for risk evaluations to guide design of infrastructure alterations or potential changes in reservoir operations (Raff et al 2009); (3) used to study the impact produced by a precipitation pattern change in the erosion process in a river basin (Abaurrea and Asín 2005); (4) important in irrigation water management (García-Garizábal and Causapé 2010); (5) used in the estimation of water budget (Guo et al 2004), precipitation erossivity (Angulo-Martínez and Beguería 2009;Vrieling et al 2010), and groundwater recharge (Nolan et al 2007; Toews and Allen 2009); (6) used to study the effect of its changes on loads of NO 3 -N and sediment from watersheds (Chaplot 2007) and forest ecosystems (Johnson et al 2000); and (7) used to study water table fluctuations (Park and Parker 2008), atmospheric circulation, and temperature (Brandsma and Buishand 1997). Hence, the performance of daily precipitation simulated by GCMs should be evaluated at finer spatial scales.…”

Section: Introductionmentioning

confidence: 99%

Performance evaluation of AR4 Climate Models in simulating daily precipitation over the Indian region using skill scores

Anandhi

Nanjundiah

2014

Theor Appl Climatol

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The ability of Coupled General Circulation Models (CGCMs) participating in the Intergovernmental Panel for Climate Change's fourth assessment report (IPCC AR4) for the 20th century climate (20C3M scenario) to simulate the daily precipitation over the Indian region is explored. The skill is evaluated on a 2.5°×2.5°grid square compared with the Indian Meteorological Department's (IMD) gridded dataset, and every GCM is ranked for each of these grids based on its skill score. Skill scores (SSs) are estimated from the probability density functions (PDFs) obtained from observed IMD datasets and GCM simulations. The methodology takes into account (high) extreme precipitation events simulated by GCMs. The results are analyzed and presented for three categories and six zones. The three categories are the monsoon season (JJASO -June to October), non-monsoon season (JFMAMND -January to May, November, December) and for the entire year ("Annual"). The six precipitation zones are peninsular, west central, northwest, northeast, central northeast India, and the hilly region. Sensitivity analysis was performed for three spatial scales, 2.5°grid square, zones, and all of India, in the three categories. The models were ranked based on the SS. The category JFMAMND had a higher SS than the JJASO category. The northwest zone had higher SSs, whereas the peninsular and hilly regions had lower SS. No single GCM can be identified as the best for all categories and zones. Some models consistently outperformed the model ensemble, and one model had particularly poor performance. Results show that most models underestimated the daily precipitation rates in the 0-1 mm/day range and overestimated it in the 1-15 mm/day range.

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“…Interestingly, for three of the study sites, the act of removing the unsaturated zone component, thereby simplifying the structure of the model, had a small impact on the model efficiencies. It may also be beneficial to use simpler functions that describe the relationship between groundwater storage, level and discharge that require fewer parameters such as the cubic function employed by Moore and Bell (2002), or even simpler approaches such as the semi-analytical solution presented by (Park and Parker, 2008) who assume recharge is a fixed proportion of rainfall, and lump the flow, storage and hydraulic gradient variables into a single parameter assumed constant over space and time. This of course deviates from the layered saturated zone structure used in AquiMod, and most physically based models, due to the discrete step-wise layering in flow and storage properties often observed in groundwater aquifers (Cross et al, 1995;Rushton and Rao, 1988).…”

Section: Identification Of Suitable Model Parameters and Structuresmentioning

confidence: 99%