A model to simulate recharge processes of karst massifs

Fiorillo, Francesco; Pagnozzi, Mauro; Ventafridda, Gerardo

doi:10.1002/hyp.10353

Cited by 43 publications

(48 citation statements)

References 23 publications

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“…How to accurately estimate recharge has remained a persistent challenge and an active research topic in the hydrological science community over many decades (Gee and Hillel, 1988;Scanlon, 2013;Sanford, 2002). It is generally accepted that recharge is correlated with precipitation in some fashions, and many studies adopt the concept of a recharge coefficient (Turkeltaub et al, 2015;Kalbus et al, 2006;Allocca et al, 2014), which is the ratio of the actual recharge to the precipitation, to estimate the recharge (Fiorillo et al, 2015;Allocca et al, 2014). The magnitude of such a recharge coefficient is controlled by a complex interplay of multiple factors such as moisture dynamics in the vadose zone (Schymanski et al, 2008), depth to water table, vegetation, etc., and the recharge coefficient is often regarded as a temporally invariant value at a given location (Fiorillo et al, 2015;Min et al, 2017;Vauclin et al, 1979).…”

Section: Introductionmentioning

confidence: 99%

“…It is generally accepted that recharge is correlated with precipitation in some fashions, and many studies adopt the concept of a recharge coefficient (Turkeltaub et al, 2015;Kalbus et al, 2006;Allocca et al, 2014), which is the ratio of the actual recharge to the precipitation, to estimate the recharge (Fiorillo et al, 2015;Allocca et al, 2014). The magnitude of such a recharge coefficient is controlled by a complex interplay of multiple factors such as moisture dynamics in the vadose zone (Schymanski et al, 2008), depth to water table, vegetation, etc., and the recharge coefficient is often regarded as a temporally invariant value at a given location (Fiorillo et al, 2015;Min et al, 2017;Vauclin et al, 1979). Specifically, it is assumed to be primarily controlled by the total precipitation and not too much by the temporal fluctuation of precipitation events (Hickel and Zhang, 2006;Acworth et al, 2016).…”

Section: Introductionmentioning

confidence: 99%

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Is annual recharge coefficient a valid concept in arid and semi-arid regions?

Cheng

Zhan

Yang

et al. 2017

Hydrol. Earth Syst. Sci.

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Abstract. Deep soil recharge (DSR) (at depth greater than 200 cm) is an important part of water circulation in arid and semi-arid regions. Quantitative monitoring of DSR is of great importance to assess water resources and to study water balance in arid and semi-arid regions. This study used a typical bare land on the eastern margin of Mu Us Sandy Land in the Ordos Basin of China as an example to illustrate a new lysimeter method of measuring DSR to examine if the annual recharge coefficient is valid or not in the study site, where the annual recharge efficient is the ratio of annual DSR over annual total precipitation. Positioning monitoring was done on precipitation and DSR measurements underneath mobile sand dunes from 2013 to 2015 in the study area. Results showed that use of an annual recharge coefficient for estimating DSR in bare sand land in arid and semi-arid regions is questionable and could lead to considerable errors. It appeared that DSR in those regions was influenced by precipitation pattern and was closely correlated with spontaneous strong precipitation events (with precipitation greater than 10 mm) other than the total precipitation. This study showed that as much as 42 % of precipitation in a single strong precipitation event can be transformed into DSR. During the observation period, the maximum annual DSR could make up 24.33 % of the annual precipitation. This study provided a reliable method of estimating DSR in sandy areas of arid and semi-arid regions, which is valuable for managing groundwater resources and ecological restoration in those regions. It also provided strong evidence that the annual recharge coefficient was invalid for calculating DSR in arid and semi-arid regions. This study shows that DSR is closely related to the strong precipitation events, rather than to the average annual precipitation, as well as the precipitation patterns.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Is annual recharge coefficient a valid concept in arid and semi-arid regions?

Cheng

Zhan

Yang

et al. 2017

Hydrol. Earth Syst. Sci.

View full text Add to dashboard Cite

show abstract

“…Therefore, it can be noticed and expected that higher recharge in limestone dominated by conduits is due to heavy rainfall. However, it should be mentioned that an accurate and reliable estimation of recharge into karst aquifers is difficult because of their heterogeneous local structures (Bonacci, 2001;De Waele and Parise, 2013;Fiorillo et al, 2015a;Bakalowicz, 2015).…”

Section: Introductionmentioning

confidence: 99%

Classification of karst springs for flash-flood-prone areas in western Turkey

Demiroğlu

2016

Nat. Hazards Earth Syst. Sci.

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Abstract. Flash floods are caused by heavy rainfall that has become more frequent. They are more prominent in lowstorage karst regions, although karst terrain often acts as a natural flood control particularly when it is bare and dominated by conduits. A study using a hydrogeochemical approach and assessing data from several springs in different carbonate rock in western Turkey has made it possible to classify karst aquifers based on their response to heavy rainfall events. According to this aim, physico-chemical measurements in wet and dry seasons and discharge rates in springs are compared in order to explain aquifer characteristics. Groundwater samples have a pH ranging from 6.3 to 8.9, temperature (T ) varying from 7 to 35 • C and electrical conductivity (EC) ranging from 140 to 998 µs cm −1 . Groundwater samples with high EC, high T and low dissolved oxygen (DO) represent the deep circulating water, while low EC, low T and high DO are linked to the shallow circulating water. Lower variability between wet and dry seasons reveals that fracture permeability is predominantly controlled by diffuse groundwater flow with low or high storage, and conduit permeability with high storage. However, variability of the physico-chemical characteristics is higher in a conduit permeability with low storage. These types of aquifers with high transfer capability, predominantly controlled by turbulent groundwater flow, affect flash floods.

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“…Both VR and VP are expressed in L 3 or just L averaged over the catchment; thus RC is a dimensionless coefficient, theoretically ranging from 0 (when VR ¼ 0) to 1 (when VR ¼ VP). On a global scale, the reported RCs for karst aquifers cover the whole range, even approaching the two end members (see for example Ashjari and Raeisi, 2006;Allocca et al, 2014;Fiorillo et al, 2015;Martos-Rosillo et al, 2015). RC simply represents the percentage of total precipitation that reached the phreatic zone, reflecting the combined effects of all rechargeprohibiting processes such as water loss through surface runoff or evapotranspiration.…”

Section: Introductionmentioning

confidence: 99%

“…Instead, determination of RC during a hydrological year, RC Y , or even a shorter time scale (monthly RC M or daily RC D ) is of interest for practical applications (see Bonacci, 2001;Bonacci et al, 2006;Denić-Jukić, 2004, 2009;Jemcov and Petric, 2009;Fiorillo et al, 2015). However, at a short time scale of a year (or a month), the amount of change in groundwater storage is likely not negligible in comparison to the rest of the parameters in the RC calculation.…”

mentioning

confidence: 99%

A new method to estimate annual and event-based recharge coefficient in karst aquifers; case study: Sheshpeer karst aquifer, south-central Iran

Kavousi¹,

Raeisi²

2016

JCKS

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Quantification of recharge is a fundamental issue in evaluation and management of karst water resources. Recharge coefficient (RC), which is the ratio of aquifer recharged water (VR) to the total precipitation, has been widely used for recharge estimation in karst catchments. Though the RC definition is straightforward, in practice, its application on a fixed short time scale (e.g., monthly or annual) is challenging, because of the problems in determination of change in groundwater storage (DVS) that is included in VR. Some researchers have neglected DVS, estimated VR as equal to the net aquifer outflows; hence they have over-or under-estimated the RC, ignoring the aquifer's antecedent storage condition. In this study, a new method is proposed to estimate the actual event VR, and consequently, the event-based RC, utilizing the MRC displacement method of Kavousi and Raeisi (2015). Applying the method, VR due to a specific event or a combination of events during a hydrological year can be directly estimated by decomposition of the observed hydrograph to the individual hydrographs induced by different events. The method is applicable for karst aquifers with no-flow boundaries, draining by a spring. The calculated event VR takes DVS into account, enabling an accurate event-based RC estimation. The method was applied to the Sheshpeer karst aquifer in Iran. The estimated RCs reasonably matched up to the catchment properties and former field studies. Results showed that the annual RCs would be underestimated if the DVS was neglected, because DVS was positive during the study period.

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A model to simulate recharge processes of karst massifs

Cited by 43 publications

References 23 publications

Is annual recharge coefficient a valid concept in arid and semi-arid regions?

Is annual recharge coefficient a valid concept in arid and semi-arid regions?

Classification of karst springs for flash-flood-prone areas in western Turkey

A new method to estimate annual and event-based recharge coefficient in karst aquifers; case study: Sheshpeer karst aquifer, south-central Iran

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