Atmospheric chloride deposition in continental Spain

Alcalá, Francisco; Custódio, Emílio

doi:10.1002/hyp.6965

Cited by 59 publications

(61 citation statements)

References 24 publications

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“…The isotopic composition of groundwater is clearly different from the sea water composition analysed in the Strait of Bonifacio (1.07 for δ 18 O and 4.78 for δ 2 H). The Cl -and Na + concentrations and the high EC of the groundwater is more in agreement with a coastal situation influenced by the seas sprays as for Spanish and Portuguese coastal aquifers (Alcala and Custodio, 2008;Cruz et al, 2011) and many others Mediterranean coastal aquifers (Bouzourra et al, 2015;Dazy et al, 1997;Ghabayen et al, 2006;Manca et al, 2015).…”

Section: Groundwater Originsupporting

confidence: 73%

Residence time, mineralization processes and groundwater origin within a carbonate coastal aquifer with a thick unsaturated zone

Santoni

Huneau

Garel

et al. 2016

Journal of Hydrology

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Section: Groundwater Originsupporting

confidence: 73%

Residence time, mineralization processes and groundwater origin within a carbonate coastal aquifer with a thick unsaturated zone

Santoni

Huneau

Garel

et al. 2016

Journal of Hydrology

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“…The origins of groundwater salinization are diverse such as (1) seawater intrusion (Park et al 2005;Bouchaou et al 2008;Custodio 2010;Cruz et al 2011); (2) evapo-concentration (concentration by evapotranspiration) of airborne salts (Alcalá and Custodio 2008;Guan et al 2010); (3) hydrogeological characteristics of the aquifer (Ben Moussa et al 2011;Farber et al 2007); (4) water-rock interaction, such as dissolution, leaching and hydrolysis of minerals (Van der Weijden and Pacheco 2003; Abid et al 2011;Jalali 2007) and (5) human influence, such as return flows from irrigated agricultural activities (Oren et al 2004;Almasri 2007;García-Garizabal and Causape 2011).…”

Section: Introductionmentioning

confidence: 99%

Combining the advantages of neural networks using the concept of committee machine in the groundwater salinity prediction

Barzegar

Moghaddam

2016

Model. Earth Syst. Environ.

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Salinity is one of the main factors in groundwater quality monitoring. The main objectives of this study are to investigate and compare the accuracy of three different neural computing techniques, multi-layer perceptron neural network (MLP), radial basis function neural network (RBFNN), and generalized regression neural network (GRNN), in prediction of groundwater salinity of the Tabriz plain confined aquifer, expressed by electrical conductivity [EC (lS/cm)], and to employ an integrated method to combine the advantages of neural network models utilizing the concept of committee machine. To develop the models, 93 data records of groundwater samples were collected from East Azarbaijan regional water company. The data set including Ca 2? , Mg 2? , Na ? , SO 4 2-and Cl -concentrations as the inputs and salinity [EC (lS/ cm)] as an output were divided into two subsets; training and testing based on cross validation approach. After training and testing of the models, the performance of the models were evaluated using root mean square errors (RMSE), determination coefficient (R 2 ) and mean absolute error (MAE). The performance criteria of the constructed neural network models showed that RBFNN model has the best performance in predicting salinity. The committee neural network (CNN) combined the results of salinity predicted from MLP, RBFNN and GRNN, each of them has a weight factor showing its contribution in overall prediction. The optimal weights were derived by a genetic algorithm (GA). The results of salinity prediction derived from CNN showed that the CNN performs better than any one of the individual ANNs acting alone for predicting groundwater salinity.

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“…One estimate of average chloride deposition, either directly measured from bulk precipitation sampling, or indirectly inferred from the ratio of 36 Cl/Cl which has a 30% uncertainty (Scanlon, 2000), is often used in the CMB calculation. In the coastal area, however, large spatial variability of chloride deposition is observed (Blackburn and McLeod, 1983;Keywood et al, 1997;Kayaalp, 2001;Biggs, 2006;Alcala and Custodio, 2008a). A detailed map of atmospheric chloride deposition in the coastal area is thus needed to apply the CMB method for estimating groundwater recharge.…”

mentioning

confidence: 99%

“…First, the coastal distance-dependence reflects the efficiency of atmospheric chloride transport and how quickly it falls out or precipitates out. Therefore its parameterization may vary from place to place (Alcala et al, 2008a), which we term as the difficulty of function parameterization. Second, it is difficult to determine the coastal distance for each mapping pixel because this distance should be calculated from the coastal point that is upwind from the pixel.…”

mentioning

confidence: 99%

Factors influencing chloride deposition in a coastal hilly area and application to chloride deposition mapping

Guan

Love

Simmons

et al. 2010

Hydrol. Earth Syst. Sci.

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Abstract. Chloride is commonly used as an environmental tracer for studying water flow and solute transport in the environment. It is especially useful for estimating groundwater recharge based on the commonly used chloride mass balance (CMB) method. Strong spatial variability in chloride deposition in coastal areas is one difficulty encountered in appropriately applying the method. A high-resolution bulk chloride deposition map in the coastal region is thus needed. The aim of this study is to construct a chloride deposition map in the Mount Lofty Ranges (MLR), a coastal hilly area of approximately 9000 km 2 spatial extent in South Australia. We examined geographic (related to coastal distance), orographic, and atmospheric factors that may influence chloride deposition, using partial correlation and regression analyses. The results indicate that coastal distance, elevation, as well as terrain aspect and slope, appear to be significant factors controlling chloride deposition in the study area. Coastal distance accounts for 70% of spatial variability in bulk chloride deposition, with elevation, terrain aspect and slope an additional 15%. The results are incorporated into a de-trended residual kriging model (ASOADeK) to produce a 1 km×1 km resolution bulk chloride deposition and concentration maps. The average uncertainty of the deposition map is about 20-30% in the western MLR, and 40-50% in the eastern MLR. The maps will form a useful basis for examining catchment chloride balance for the CMB application in the study area.

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Atmospheric chloride deposition in continental Spain

Cited by 59 publications

References 24 publications

Residence time, mineralization processes and groundwater origin within a carbonate coastal aquifer with a thick unsaturated zone

Residence time, mineralization processes and groundwater origin within a carbonate coastal aquifer with a thick unsaturated zone

Combining the advantages of neural networks using the concept of committee machine in the groundwater salinity prediction

Factors influencing chloride deposition in a coastal hilly area and application to chloride deposition mapping

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