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Development of a GIS Based Procedure
(BIGBANG 1.0) for Evaluating
Groundwater Balances at National Scale
and Comparison with Groundwater
Resources Evaluation at Local Scale
G. Braca and D. Ducci
1 Introduction
In the last years water scarcity and drought problems in Italy have become of
growing concern (Ducci and Tranfaglia 2008; Fiorillo and Guadagno 2012). These
problems seem to be worsened in the near future, both for the increase of water
demand, often exceeding the available sustainable water resources, and for the
temperature increase and the variation of the quantity and the distribution of precipitation even if in different ways from north to south of Italy (Toreti et al. 2009).
Moreover, the Water Framework Directive (WFD) (2000/60/EC) has introduced
a legal framework for sustainable management of water resources across Europe,
even though it does not explicitly mention the evaluation of changes in temperature
and precipitation and its effects on groundwater resources.
In this context, the Italian National Institute for Environmental Protection and
Research (ISPRA) has developed an automatic GIS-based procedure named
BIGBANG (acronym of the Italian sentence “Bilancio Idrologico GIS BAsed a
scala Nazionale su Griglia regolare” which means “Nationwide GIS-based hydrological budget on a regular grid”) version 1.0, in order to evaluate the water budget
components at monthly temporal scale for the whole National territory.
This paper, after a description of the structure of the spatially distributed water
balance models, presents and discusses some results obtained in the whole
Campania region (southern Italy) during the period 1996–2015. The results have
been discretized for each groundwater bodies (GWBs).
G. Braca
ISPRA—Italian National Institute for Environmental Protection and Research, Rome, Italy
D. Ducci (&)
Department of Civil, Architectural and Environmental Engineering, University of Naples
Federico II, Naples, Italy
© Springer International Publishing AG 2018
M. L. Calvache et al. (eds.), Groundwater and Global Change in the Western
Mediterranean Area, Environmental Earth Sciences,
G. Braca and D. Ducci
These results have been compared with groundwater balances carried out at local
scale, in a carbonate hydrogeological system, for the period 2000–2015.
2 Materials and Methods
The BIGBANG 1.0 Procedure
The Italian National Institute for Environmental Protection and Research (ISPRA)
has developed a GIS based procedure (BIGBANG 1.0—“Nationwide GIS-Based
hydrological budget on a regular grid” version 1.0) for evaluating all the factors of
the monthly water balance at National scale in a spatially distributed way, using
Python programming language, at moment implemented in a proprietary GIS
platform (ESRI ArcGIS 10.1, ESRI 2012)
The procedure is based on the spatial environmental information at very high
resolution, also available on the WEB, in formats understandable by the main
Geographic Information Systems. This model allows the estimate of the spatially
distributed hydrological factors, such as total precipitation, potential and actual
evapotranspiration, surface runoff and groundwater recharge. The hydrological
factors of total precipitation, actual evapotranspiration, surface runoff and
groundwater recharge are evaluated for a 1 km resolution grid, in the ETRS89
Datum, using a LAEA (Lambert Azimuthal Equal Area) projection (Fig. 1). The
grid is based on the recommendation at the 1st European Workshop on Reference
Grids in 2003 and later INSPIRE geographical grid systems (EEA, European
Environmental Agency) and each cell is univocally identified by an ID. The 1 km
Fig. 1 BIGBANG calculation scheme. The hydrological factors are evaluated for a 1 km
resolution grid covering the whole National territory
Development of a GIS Based Procedure …
Fig. 2 European
environmental agency
reference grids for Italy
(100 km in gray, and 10 km,
in red, resolution)
resolution grid is not shown because too much small, but it is nested in the 10 km
resolution one (Fig. 2).
The water budget model used in BIGBANG follows the approach suggested by
Thornthwaite and Mather (1955) and it simulates on each grid cells: soil moisture
variations, actual evapotranspiration, groundwater recharge and surface runoff,
using a set of climatic data, as precipitation and temperature, soil and land-use data,
hydraulic and geological properties, etc.
The governing equation is based on mass balance:
P E ¼ R þ G þ DV
where P is the total precipitation, E is the actual evapotranspiration, R is the surface
runoff, G is the groundwater recharge and DV is the change in soil moisture storage
All the factors have been evaluated in millimeters per month.
The factor ðP EÞ is also defined as “internal flow” and it represents the total
volume of river runoff (R) and groundwater (G) in a territory (Eurostat/OECD
2014). The quantity ðR þ GÞ is also defined as “surplus” as the water which does
not evaporate or remain in soil storage and it is available to generate surface and
subsurface runoff and groundwater storage (Westenbroek et al. 2010). The difference between potential and actual evapotranspiration is also indicated as the water
“deficit” that represents the amount of water that should be supplied to the vegetation as irrigation (Westenbroek et al. 2010). Actual evapotranspiration is one of
the main water balance components, and its value is very difficult to measure
G. Braca and D. Ducci
Fig. 3 Hypothetical
relationship between the
actual evapotranspiration
(AET) and the water storage
directly. Therefore, the choice of reliable models capable of predicting spatially
distributed actual evapotranspiration represents a critical aspect for groundwater
budget evaluation.
The BIGBANG procedure takes also into account in each cell the effect of the
soil sealing rate (Munafò et al. 2013) obtained by lumping together the ISPRA
20 m resolution grid map resulting from Copernicus earth observation program
satellite products.
Equation (1) is used for each 1 km grid cell without consider the horizontal
motion of water on the ground-surface, or in the soil. The BIGBANG procedure
schematizes as a reservoir a volume of soil of 1 km grid for 1 m deep, whose
maximum capacity is given by the available water storage (AWS) depending on soil
texture. The variable representing the soil moisture at the end of the month is the
water storage (WS).
In the soil model, rainfall is assumed to infiltrate into the soil from which
moisture is depleted by the actual evapotranspiration (AET). When the soil storage
is full, it is assumed to be saturated and the exceeding rainfall becomes surface
runoff and recharge, according to the recharge scheme. Evapotranspiration is
assumed to continue at its potential rate (PET) until the soil water storage reaches
the value of field capacity FC that we assume as half of AWS (Kandel et al. 2005).
Afterwards, evapotranspiration (AET) decreases linearly to zero until the storage is
empty, reaching the water quantity known as wilting point (Fig. 3).
In the present version, the BIGBANG procedure uses the 1 km grid of AWS
from the LUCAS_TOPSOIL data grid (Toth et al. 2013) of the Joint Research
Center of UE (Fig. 4).
The BIGBANG Procedure Steps
The automatic GIS procedure consists in the following steps:
(1) Spatial interpolation of monthly time series of hydrological variables which
control water budget components: total precipitation, mean temperature, minimum temperature, maximum temperature, solar radiation, and others. Spatial
interpolation is performed on the reference grid covering Italy by using tools
Development of a GIS Based Procedure …
Fig. 4 AWS in mm for 1 km resolution grid derived from JRC LUCAS_TOPSOIL data grid and
location of the Monte Maggiore groundwater body
available in ESRI Spatial Analyst Package (kriging, IDW, etc.). Nevertheless,
BIGBANG can use grids available from reliable web sources. In BIGBANG
procedure, for example, monthly mean temperature grids are derived from
ISPRA SCIA System (Fioravanti et al. 2010), available from the web site, and
transformed in the ETRS89-LAEA coordinate system of the grid reference.
(2) Estimation of the grid of monthly snow precipitation, snow accumulation as
snow water equivalent, using a simple model based only on precipitation, mean
temperature and elevation derived from a DEM (McCabe and Markstrom
2007). Snow melt is estimate using a simple degree day model (DeWalle and
Rango 2008).
(3) Calculation of the grid of monthly potential evapotranspiration by selection of
different formulations: simplified Turc (1961) formula, Thornthwaite (1948)
formula and Hargreaves and Samani (1982) formula. The choice of the
appropriate formula depends mainly on the hydrological data availability.
(4) Calculation of the grid of monthly actual evapotranspiration on the basis of
potential evapotranspiration grid through a soil water balance.
G. Braca and D. Ducci
(5) Calculation of the grid of groundwater recharge estimated as a percentage of the
total volume of surface runoff (R) and groundwater (G) in function of the
permeability of the outcropping hydrogeological units. The shapefile of the
hydrogeological units is downloadable at the ISPRA website. Calculation of the
Surface Runoff by difference.
(6) Temporal aggregation of balance components grids (seasonal, yearly, etc.).
(7) Calculation of long term annual average of balance components grids.
(8) Clipping grids of spatial distribution of hydrological components over territory
(regions, hydrological basins and sub-basins, groundwater bodies, etc.).
(9) Calculation of spatial statistics using ESRI ArcGIS 10.1 Spatial Analyst
Package tools.
Definition of tables summarizing all the water budget terms for different
intervals of time step and different parts of the territory by queries.
Hydrogeological Features
The Campania region (13,500 km2) is located in the southern part of the Italian
peninsula and it shows at W a coastline along the Tyrrhenian Sea. The region
presents three main landscapes: the Apennine carbonate Mesozoic mountains,
reaching elevations of more than 2000 m (about 32%), the alluvial and pyroclastic
coastal plains of the rivers Garigliano, Volturno and Sele (about 18%) and finally
hills and valleys constituted by prevalently impervious sediments, while a small
part is represented by the Roccamonfina and Vesuvius volcanoes and pyroclastic
hills of the Phlegrean Fields. The main aquifers with copious springs are the carbonate mountains, which have a very high permeability due to a well-developed
karstic network.
The Campania Region is partitioned in 80 significant groundwater bodies: 10%
volcanic GWBs, 25% alluvial GWBs, 30% karstic GWBs and 35% mixed, at
low-moderate permeability. The carbonate GWB of Monte Maggiore (Fig. 3)
(180 km2) is composed prevalently by Cretacic limestone, and only in little part by
older dolomite. The GWB feeds two springs located at the foot Triflisco Springs
and Pila Springs (total mean discharge about 4.6 m3/s) toward south, while the
remaining part of the flow is directed toward another GWB.
3 Results
The yearly and monthly evaluations have been compared with groundwater balances carried out at local scale, in the carbonate groundwater body of Monte
Maggiore. The yearly comparison is shown in Table 1. The most evident difference
is in the area, due to the dimension of the cells at national scale that creates an error.
706 (1)
620 (2)
556 (3)
evapotranspiration (E)
Surface runoff
recharge (G)
106 m3/
Actual evapotranspiration evaluated by (1): Turc; (2) Hargreaves and Samani; (3) Thornthwaite and Mather. CIP = percentage of (P-E) that becomes
groundwater recharge (G) in function of the permeability of the outcropping hydrogeological units
Local scale
Monte Maggiore—period 2000–2015
Mean elevation
m a.s.l.
Table 1 Yearly water budget for Monte Maggiore groundwater body
Development of a GIS Based Procedure …
G. Braca and D. Ducci
At local scale T has been evaluated on the basis of the Digital Elevation Model
considering the equation: T = 16.8–0.0059 h. The difference in precipitation is due
to the different interpolation model used. At the end the differences among methods
and scale are low and all less than 15%. The monthly comparison also shows a
good accordance between the different scales, individuating the same periods for
deficit and exceedance.
4 Conclusions
The comparison between a groundwater balance carried out at National scale and at
local scale shows that the lithological and hydrogeological features, much more
detailed at local scale, can influence some factors of the balance, but the final
amount of the recharge is comparable
Future developments of the proposed procedure BIGBANG (that is only at
version 1.0) will regard improvements especially about spatial interpolation method
of precipitation that should be taken into account the auxiliary variables as topographic elevation, coastal proximity, facet orientation, and others like PRISM
method (Parameter-elevation Relationships on Independent Slopes Model, Daly
et al. 1997), hydraulic soil properties, evapotranspiration model and the parameters
calibration. Moreover the water balance performed by BIGBANG should be
improved with the introduction of the water surface volumes stored in the natural
lakes and artificial reservoirs.
As historic time series of monthly precipitation and temperature data are
retrieved from hydrological year books, another application of BIGBANG procedure will be to reconstruct historic monthly water balance in Italy in order to
analyze the long time series (more than fifty years) of water budget terms and their
variability throughout the time.
Finally in the future it will be very helpful that BIGBANG produced dataset,
maps and tables, could be available to users through a dedicated web site.
Daly C, Taylor G, Gibson W (1997) The PRISM approach to mapping precipitation and
temperature. In: 10th AMS Conference on Applied Climatology, Reno, NV, pp 10–12
DeWalle DR, Rango A (2008) Principles of snow hydrology. Cambridge University Press
Ducci D, Tranfaglia G (2008) Effects of climate change on groundwater resources in Campania
(Southern Italy). Geol Soc Sp Publ 288:25–38
ESRI Environmental Systems Research Institute Inc. (2012) ArcGIS Desktop: Release 10.1
Redlands, CA
Eurostat/OECD (2014) Data collection manual for the OECD/Eurostat Joint Questionnaire on
Inland Waters Version 3.0—Sept 2014
Development of a GIS Based Procedure …
Fioravanti G, Toreti A, Fraschetti P, Perconti W, Desiato F (2010) Gridded monthly temperatures
over Italy. EMS Annual Meeting Abstracts, 7, EMS2010-306, ECAC Conference, Zurich, 13–
17 Sept 2010
Fiorillo F, Guadagno F (2012) Long karst spring discharge time series and droughts occurrence in
Southern Italy. Environ Earth Sci 65(8):2273–2283
Hargreaves GH, Samani ZA (1982) Estimating potential evapotranspiration. J Irrig Drain Eng
Kandel D, Chiew F, Grayson R (2005) A tool for mapping and forecasting soil moisture deficit
over Australia. Technical Report 05/2 Mar 2005
McCabe GJ, Markstrom SL (2007) A monthly water-balance model driven by a graphical user
interface. U.S. geological survey open-file report 2007-1088, 6 p
Munafò M, Salvati L, Zitti M (2013) Estimating soil sealing rate at national level—Italy as a case
study. Ecol Ind 26:137–140
Thornthwaite CW (1948) An approach towards a rational classification of climate. Geogr Rev
Thornthwaite CW, Mather JR (1955) The water balance. Laboratory of climatology, 8, Centerton
Toreti A, Fioravanti G, Percontia W, Desiato F (2009) Annual, seasonal precipitation over Italy
from 1961 to 2006. Int J Climatol 29:1976–1987
Turc L (1961) Estimation of irrigation water requirements, potential evapotranspiration: a simple
climatic formula evolved up to date. J Ann Agron 12:13–14
Toth G, Jones A, Montanarella L (eds) (2013) LUCAS topsoil survey. Methodology, data, results.
JRC Technical Reports. Luxembourg. Publications office of the European Union, EUR
26102—scientific, technical research series—ISSN 1831-9424 (online); ISBN 978-92-7932542-7; doi:10.2788/97922
Westenbroek SM, Kelson VA, Dripps WR, Hunt RJ, Bradbury KR (2010) SWB—a modified
Thornthwaite-Mather soil-water-balance code for estimating groundwater recharge. U.S.
geological survey techniques, Methods 6–A31, 60 p
Copernicus earth observation program satellite products,
EEA, European Environmental Agency,
ISPRA website,
ISPRA website hydrogeology,
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