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WATER POVERTY INDEX IN SUBTROPICAL ZONES: THE CASE OF
HUASTECA POTOSINA, MEXICO
Briseida LÓPEZ ÁLVAREZ
1
*, Germán SANTACRUZ DE LEÓN
1
, José Alfredo RAMOS LEAL
2
and
Janete MORÁN RAMÍREZ
2
1
El Colegio de San Luis, A. C. (COLSAN). Parque de Macul 155, Frac. Colinas del Parque, San Luis Potosí,
S.L.P., C.P. 78299
2
Instituto Potosino de Investigación Científco y Tecnológico (IPICYT). Camino a La Presa de San José 2005,
Col. Lomas 4ta Sección, San Luis Potosí, S.L.P., C. P. 78216
* Autor para correspondencia: blopez@colsan.edu.mx
(Recibido mayo 2014; aceptado febrero 2015)
Key words: water access, water quality, water availability, human development, hydric resources, Valles River
ABSTRACT
Tools are needed in order to evaluate an integrated water resource management, and
to encourage the management and coordinated usage oF water resources along with
the environmental and socioeconomic Factors. One oF those tools is the Water Poverty
Index (WPI), which enables the evaluation oF water poverty in terms oF the physical
and socioeconomic Factors related to water availability. The WPI, as calculated in this
study, is derived From the weighted sum oF six key components –resources, access,
usage, capacity, quality and environment– on a scale oF 0 to 100. The objective oF this
work was to calculate the Río Valles Basin WPI For 2010. This region is a semi-tropical
area with abundant water resources, such as large springs. Its annual mean precipita-
tion is 1100 mm. In the Río Valles Basin, the volume oF surFace water used per year is
81.33 Mm
3
, which represents 91 % oF the total resource. The volume oF groundwater
used per year is 8.17 Mm
3
, representing the remaining 9 %. Usually 45 Mm
3
/year is
stored in La Lajilla dam. These data indicate that surFace water is the main source oF
supply For uses such as agriculture, which is the activity with the largest water demand.
A WPI score oF 59 was obtained For the Río Valles Basin.
Palabras clave: acceso al agua, calidad de agua, disponibilidad de agua, desarrollo humano, recursos hídricos,
Río Valles
RESUMEN
Para evaluar la gestión integrada de los recursos hídricos se necesitan herramientas para Fo-
mentar su administración y uso coordinado con el ambiente y los Factores socioeconómicos.
Una de estas herramientas es el Índice de Pobreza del Agua (IPA), que permite evaluar la
pobreza del agua en términos de los Factores Físicos y socioeconómicos relacionados con
su disponibilidad. El IPA, como se calculó en este estudio, se deriva de la suma ponderada
de seis componentes clave: el acceso, el uso, la capacidad, la calidad y el ambiente, en
una escala de 0 a 100. El objetivo de este trabajo Fue calcular el IPA de la cuenca del Río
Valles para el año 2010. Esta región es semitropical, con abundantes recursos hídricos,
Rev. Int. Contam. Ambie. 31 (2) 173-184, 2015
B. López Álvarez
et al.
174
como grandes manantiales y una precipitación media anual de 1100 mm. En la cuenca del
Río Valles el volumen de agua superfcial utilizada es de 81.33 Mm
3
/año, lo que representa
el 91 % del total del recurso utilizado. El volumen de agua subterránea utilizada es de
8.17 Mm
3
/año, lo que representa el 9 % restante, normalmente se almacenan 45 Mm
3
/año
en la presa de La Lajilla. Estos datos indican que el agua superfcial es la principal Fuente
de abasto para diversos usos como la agricultura que es la actividad con la mayor demanda
de agua. El IPA que se obtuvo para la cuenca del Río Valles fue de 59 puntos.
INTRODUCTION
IntegratedWater Resources Management (IWRM)
is a process to Foster the management and coordinated
usage oF water resources, as well as the environmen-
tal and socioeconomic factors in order to maximize
social and economic benefts in an equitable manner
without compromising the sustainability oF vital
ecosystems (IWRM-UNESCO 2009). To evaluate
IWRM, tools are needed and those should take into
account these elements. One oF those tools is the
Water Poverty Index (WPI), which makes it possible
to evaluate water poverty in diFFerent study scales
–countries, regions or communities– taking into
account physical and socioeconomic Factors related
to the availability oF water (Lawrence
et al
. 2002).
The WPI is evaluated based on fve components:
water resources, access, capacity, usage and envi-
ronment. These components enable establishing
connections between poverty, social marginalization,
environmental integrity, water availability and health.
The WPI has been applied at an international level
by Lawrence
et al.
(2002) and recently in a semi-arid
region such as the San Luis Potosí Valley (SLPV) by
López-Álvarez
et al.
(2013).
The objective oF this work was to calculate the
WPI in a semi-tropical region with abundant water
resources, specifcally at the Río Valles Basin (RVB).
This region is located in eastern Mexico on the bound-
ary oF the Eastern Sierra Madre (
Fig. 1
), in the states
oF Tamaulipas and San Luis Potosí (SLP). The latter
is Facing serious problems regarding the availability
oF water resources. The study was conducted in the
specifc region known as Huasteca Potosina where
rainFall is higher than the national mean (Santacruz
2007). In 2010 the RVB had a population oF 255452
inhabitants (INEGI 2010) with 91 % dependence on
surFace water.
The RVB comprises the Following cities and
municipalities: municipality oF Aquismón, Cities oF
Maíz, Ciudad Valles, El Naranjo and Tamasopo in
San Luis Potosí and the municipalities oF Antiguo
Morelos, Nuevo Morelos, Ocampo and Tula in Ta
-
maulipas (
Fig. 1
).
Development of the WPI for Huasteca Potosina
The WPI is based on the structure and meth-
odologies proposed by UNESCO in the Human
Development Index as part oF the United Nations
Development Programme (2002).
The methodology proposed by Lawrence
et al.
(2002) includes fve key components. Nevertheless,
the application oF the WPI to the RVB included water
quality as an additional component (
Table I
) since
Mexico’s surFace and groundwater have serious levels
oF natural and/or anthropic pollution, thereby limiting
its use (Santacruz 2007, Carranco-Lozada 2013).
Although this methodology includes six basic
components, depending on different scenarios,
subcomponents could be also considered. For in
-
stance, in the Resource component where ground-
water is included, the aquiFers in the system could
be the subcomponents (López-Álvarez
et al.
2013).
In terms oF the subcomponents oF surFace water
these could be represented by diFFerent water bodies
(reservoirs and rivers) in the study area. In addition,
For the Quality oF the resource both, groundwater
or surFace water subcomponent has its own qual-
ity value (López-Álvarez
et al.
2013). Regarding
the Usage component this could be subdivided
into urban, agricultural and industrial usage as
subcomponents. Socioeconomic data related to a
population can be used as subcomponent of Access
and Capacity. ±or the component oF Environment,
data such as land use, erosion rate, ²ood zones,
natural protected areas, vegetation types, and en-
dangered and protected animal spatial distribution
could be used as subcomponents. In general the
evaluation oF each component can be as complex
as the amount and quality oF inFormation available.
The mathematical structure on which the WPI is
based is expressed as:
=
=
=
N
i
Xi
N
i
i
Xi
i
w
X
w
WPI
1
1
(1)
where
WPI
i
is the Water Poverty Index For a particular
region,
w
Xi
is the weighted Factor and
X
i
is the value
WATER POVERTY INDEX IN SUBTROPICAL ZONES
175
of component
i
. The WPI is the result of the weighted
sum of the components: Resources (R), Access (A),
Usage (U), Capacity (C), Environment (E) and Water
Quality (Q).
Equation (1) can also be expressed in a further
developed form (equation 2). To standardize the re-
sults and produce a WPI value between 0 and 1, the
sum needs to be divided by the sum of the weights,
as shown:
q
e
u
c
a
r
q
e
u
c
a
r
i
w
w
w
w
w
w
Q
w
E
w
U
w
C
w
A
w
R
w
WPI
+
+
+
+
+
+
+
+
+
+
=
(2)
For most components a weight analysis is ap-
plied to de±ne the importance of each subcomponent
(Ramos 2002). The weight analysis is expressed as
(equation 3):
=
=
N
i
i
i
i
i
W
Xw
Xr
Wx
1
*
(3)
where
Xr
i
and
Xw
i
are the scores for each X
i
compo
-
nent and their theoretical weights and
W
i
is the sum
of the theoretical weights.
Since each component can be formed by more
than one subcomponent, the weight
w
applied to
each subcomponent (Xa
i
) in the WPI structure can
be obtained from the values associated with the
subcomponents. For example, in the case of the
Resource component percentages related to the
management of the different supply sources can be
used as weights. For theAccess component, percent-
ages of the population with access to drinking water
or with water treatment systems and percentages of
agricultural lands with access to irrigation can be
considered as weights for these subcomponents. For
the Capacity component socioeconomic conditions,
population income data, mortality rates of children
under 5 years of age, the education index and the
Gini coef±cient can be used as weight elements.
Percentage of water used for domestic, agricultural
102º0'0''
100º0'0''
98º0'0''
92º20'0''
99º0'0''
92º20'0''
99º0'0''
102º0'0''
22º0'0''
24º0'0''
26º0'0''
22º0'0''
22º0'0''
22º20'0''
22º40'0''
22º0'0''
22º20'0''
22º40'0''
24º0'0''
26º0'0''
Latitude North
Latitude North
Longitude West
Longitude West
Municipal Head
Legend
Perenial stream
Intermittent stream
La Lajilla dam
State dorder
Ciudad Valles
Aquismón
Antiguo Morelos
Ciudad del Maíz
El Naranjo
Tula
Nuevo Morelos
Tamasopo
Ocampo
EE.UU.
100º0'0''
Tamaulipas
San Luis Potosí
Gulf of
Mexico
Gulf of
Mexico
Pacific Ocean
EE.UU.
98º0'0''
El Naranjo
Nuevo Morelos
Ciudad Valles
El Salto river
Los Gatos river
Mesillas river
Va
l
les rive
r
Fig. 1.
Location of the Río Valles Basin
B. López Álvarez
et al.
176
and industrial purposes can be used as weights for
the Usage component. Whereas percentages in land
use changes in natural protected areas can be con-
sidered weights for the component of Environment.
Finally for the Quality component the management
of different supply sources can be used as weight
for indices to evaluate water quality.
For each component, the sum of the subcompo-
nents multiplied by a weight factor must equal 1. To
obtain the ±nal value, the WPI needs to be normal-
ized by weighting once more the subcomponents
and the sum should equal 1. The assigned weights
depend on the degree of importance or in²uence
of each component in each region. The weight
wi
is assigned to each component (X
i
) in the WPI
structure for that region. It is worth mentioning
that the results can be expressed as a score ranging
from 0 to 100.
The results for each component in this methodol-
ogy can be graphed as a polygon whose edges rep-
resent 100 % of each component. When normalized,
the maximum is 1 and the center of the polygon is 0.
The ideal polygon is that in which all the WPI com-
ponents have values of 1 and form a hexagon. As
more values with less than 1 are present, they move
further away from the hexagon and form an irregular
polygon.
Resources (R)
The RVB is in Hydrological Region 26. It has an
approximate area of 3216 km
2
and is divided into
four subbasins: “Río Los Gatos”, “Río El Salto”, “Río
Mesillas” and “Río Valles”. It is located in the drain-
age area of the Eastern Sierra Madre as evidenced
by the large springs found in the Huasteca Potosina
region (
Fig. 1
).
The climates are sub-humid with medium
andhighhumidityandsummerrains,andsemi-hotand
sub-humid with summer rains. The annual mean
precipitation is 1100 mm –higher than the national
mean of 772 mm (Santacruz 2008). The volume
of water used in the RVB is 81.33 Mm
3
/year for
surface water, which represents 91 % of the total
resource used and 8.17 Mm
3
/year for groundwater,
representing the remaining 9 %. Usually 45 Mm
3
/
year are stored in La Lajilla dam. These data indi-
cate that surface water is the primary resource in
the studied basin.
The weights assigned to the Resource subcompo-
nents were derived from the percentages of surface
and groundwater sources used as seen in equation 4
in the following mathematical expression (López-
Álvarez
et al.
2013):
Asub
A
R
09
.
0
sup
91
.
0
+
=
(4)
TABLE I.
KEY COMPONENTS IN THE WATER POVERTY INDEX (Adapted from Lawrence
et al.
2002)
Water Poverty Index
Component
De±nition
Sub-components
Resource (R)
Physical availability of surface and groundwater,
considering its use and water balance
• Surface water
• Groundwater
Volume used
Access (A)
Level of access to clean water for human use
• % of the population with access to drink-
ing water
• % of population with access to water
treatment.
• % of agricultural land with access to
irrigation
Capacity (C)
Ef±cacy of the human population’s capacity to
manage water
Income
• Mortality rate of children under 5 years
Education index
• Gini coef±cient
Usage (U)
Ways in which water is used for different
purposes, including domestic, agricultural and
industrial uses
• Domestic water use (L/day)
• Adjusted % of water used for agriculture
and industry, based on the sector’s contri-
bution to the GDP
Environment (A)
Evaluation of environmental integrity related to
water
Land use
Natural Protected Areas
Water quality (Q)
Evaluation of water quality for human use
• Surface and groundwater quality data
WATER POVERTY INDEX IN SUBTROPICAL ZONES
177
()
Vol
.
annual precipitation
Stored volu
me
Mm
Asur
3
=
(4.1)
Extraction
Extraction
Mm
Agrn
2
Recharg
)
(
3
-
=
(4.2)
Access (A)
Seventy-fve percent oF the population in the
RVB lives in Ciudad Valles, El Naranjo and Nuevo
Morelos. These three population centers contain most
oF the drinking water (90 % coverage) and water
treatment (30 % coverage) services (
Fig. 2
). The
rest oF the population (38 694 inhabitants) lives in
small and dispersed localities lacking public services
(INEGI 2010a).
A total oF 81.2 % oF the Economically Active
Population (EAP) works in the three population
centers mentioned, perForming secondary and tertiary
activities. The remaining percentage works in the
primary sector (agriculture and livestock). ±or this
sector there are 84 405 ha oF agricultural land, 12
399 oF which have some kind oF irrigation system
(INEGI 2007).
The Access (A) component includes the percent-
age oF the population with access to piped water
(
A
ap
) For their basic needs, the percentage oF water
that is treated (
A
t
), and the relationship oF agricultural
land with and without access to irrigation (
A
i
). The
expression (equation 5) that defnes this component
is (López-Álvarez
et al.
2013):
i
A
A
A
A
t
ap
1
.
0
3
.
0
6
.
0
+
+
=
(5)
The subcomponents were weighted using a weight
analysis (Ramos 2002, López-Álvarez
et al.
2013)
which shows subcomponent
A
ap
as the most signif-
cant and
A
i
as the least signifcant.
Capacity (C)
In Mexico, the Human Development Index
(HDI) is evaluated at municipal level.Although the
RVB covers several municipalities, only three have
notable social and economic in²uence (Santacruz
2007): Nuevo Morelos, El Naranjo and Ciudad
Valles. The municipality oF Nuevo Morelos, Tam-
aulipas, had a HDI oF 0.753 (placing it at 35 out
oF 43) in 2005, which was below the state mean
(0.85) For that year. El Naranjo and Ciudad Valles,
in San Luis Potosí, had an HDI oF 0.810 (9 out oF
58) and 0.838 (4 out oF 58), respectively. OF these
municipalities only Ciudad Valles was above the
state mean oF 0.816.
The (C) component was evaluated based on the
HDI. It evaluates the socioeconomic variables that
can aFFect access to water or re²ect access as well as
its the quality. The Gini coeFfcient is introduced to
adjust the capacity to access clean water according
to a measurement oF the unequal distribution oF in-
come (Lawrence
et al.
2002).
The subcomponents are: income index (
I
i
), mor
-
tality rate For children under 5 years oF age (
M
i
),
education index (
I
e
) and the Gini coeFfcient (
C
G
).
Capacity is evaluated by the equation 6 (López-
Álvarez
et al.
2013):
G
e
i
i
C
I
M
I
C
2
.
0
2
.
0
1
.
0
5
.
0
+
+
+
=
(6)
Weights were assigned to the subcomponents us-
ing a weight analysis (Ramos 2002, López-Álvarez
et
al.
2013), which indicates that subcomponent
I
i
is the
most signifcant,
I
e
and
C
G
have medium signifcance
and
M
i
is the least signifcant.
Usage (U)
The RVB presents biophysical conditions that
Favor certain water uses. Its subbasins have particular
conditions that make them more or less “suitable”
For a specifc use. Since the last decades oF the 19
th
century and the early decades oF the 20
th
century, the
22º0'0''
22º20'0''
22º40'0''
22º0'0''
22º20'0''
22º40'0''
Latitude North
Longitude West
99º30'0'
'9
9º15'0''
99º0'0''
99º30'0'
'9
9º15'0''
99º0'0''
Population ≤ than 100 inhabitants
Population ≥ than 100 inhabitants
Population between 100 and 500 inhabitants
Population between 500 and 1000 inhabitants
State border
Urban settlement
Perenial stream
Intermittent stream
Legend
Fig. 2.
Distribution oF the human population in the Río Valles
Basin
B. López Álvarez
et al.
178
water usage has refected the advances in technology
oF the period. The volume oF water used and extracted
From diFFerent water bodies, primarily the Valles
River is 89.85 Mm
3
/year, according to the Comisión
Nacional del Agua (National Water Commission,
CONAGUA, Spanish acronym) and the Registro
Público de Derechos del Agua (Public Water Rights
Record, REPDA, Spanish acronym). ±rom this
89.85 Mm
3
/year, 89.2 % is used in agriculture For
irrigating crops, such as sugar cane (
Saccharum of-
fcinarum)
.Atotal oF 81.06 % oF the volume oF water
used in agriculture comes from surface sources and
the rest From groundwater (
Fig. 3
).
In the RVB 7.53 % oF the water volume extracted
is For agro-industrial uses and 2.43 % For public-
urban uses.
This component includes three subcomponents:
water For domestic use (
U
d
), water For agro-industrial
use (
U
i
) and water For agricultural use (
U
a
). It is deter
-
mined From equation 7 (López-Álvarez
et al.
2013):
a
i
d
U
U
U
U
9
.
0
08
.
0
02
.
0
+
+
=
(7)
The weight assigned to the subcomponents is
based on the percentage oF water used in the RVB.
It is worth mentioning that For domestic use, the
amount oF drinking water used per inhabitant per day
must be taken into account. ±or the RVB the aver-
age amount oF drinking water used is 200 L/hab/day
(PHE 2000).
To determine agro-industrial water usage, a rela-
tionship was established between the proportion oF
the gross domestic product (GDP) generated From
this activity and the amount oF water used. This re-
lationship was applied to water For agricultural use
and provides an approximate measurement oF the
eF²ciency oF water usage (Lawrence
et al
. 2002).
Agro-industry and agriculture in the RVB represents
4 and 1 % oF the state GDP, respectively (INEGI
2010b).
Environment (E)
RainFed and irrigated agriculture in the RVB are
based on sugar cane crops. The increased area planted
with this crop had also led to a growing demand For
irrigation water and has expanded the agricultural
boundaries into areas that Formerly contained tropi-
cal forests.
This expansion oF the agricultural boundaries was
evaluated with inFormation related to land use and
vegetation type From the years 1970 to 2000 (
Table II
).
RainFed agriculture expanded during the study From
313.2 km
2
to 717.79 km
2
. While this activity is sig-
ni²cant in all Four subbasins, rainFed agriculture grew
177.66 km
2
in the “Río Los Gatos” and 92.55 km
2
in the “Río Valles” subbasins (
Fig. 4
).
The increase in rainFed agricultural area mostly
coincides with the decrease in the lowland deciduous
and sub-deciduous woodland during the study. Over
24 years the area oF the “Río Los Gatos” subbasin,
with lowland deciduous and sub-deciduous wood-
land, decreased From 546.63 km
2
to 351.00 km
2
. That
is a reduction oF 195.63 km
2
(35.78 %). The same
situation occurred in the “Río Mesillas” subbasin that
lost 173.97 km
2
oF deciduous woodland during the
same period oF time (Santacruz 2007).
Total volume
Surface water
Groundwater
Agriculture
Industry
Water uses
Urban-Public
Others
80
70
60
50
40
30
20
10
Volume (Mm
3
/year)
90
89.5
81.33
8.17
80
70
60
50
40
30
20
10
Volume (Mm
3
/year)
Total volume
used in the
basin Rio Valles
Surface
water
Groundwater
Source type
Fig. 3.
Volume oF water used and extracted From diFFerent water bodies, mainly in the Valles River.
Poner “mm” en minúscula las dos en ambas grá²cas
WATER POVERTY INDEX IN SUBTROPICAL ZONES
179
TABLE II.
RATE OF CHANGE (% AND km
2
) IN VEGETATION TYPE AND LAND USE IN THE RÍO
VALLES BASIN BETWEEN 1976 AND 2000
Land use and vegetation
Entire basin
1976
2000
Change
(km
2
)
(%)
Irrigated agriculture
82.32
135.19
52.86
64.22
Rainfed agriculture
313.02
717.79
404.78
129.31
Introduced and cultivated pastures
372.2
481.86
109.65
29.46
Jungle medium evergreen sub-evergreen
48.4
32.51
-15.88
–32.83
Lowland deciduous and sub-deciduous woodland
1857.5
1329.11
–528.38
–28.44
Palm forest
88.54
41.23
–47.31
–53.43
Human settlements
9.27
29.32
20.04
216.28
Water bodies
8.16
9.23
1.07
13.11
Oak forests
399.94
410.78
10.84
2.71
Mountain mesophytic forest
11.21
10.42
–0.79
7.04
Xeric shrublands
7.74
1.45
–6.28
81.13
Source: Santacruz (2007 and 2012).
1970
Longitude West
Legend
Land use and vegetation
Irrigation agriculture
Xeric shrublands
Palm grove
Induced and cultivated pasture
Lowland deciduous woodlandand sub-deciduous
High evergreen and sub-evergreen jungle
Scale 1:250 000
Perennial stream
Rainfed agriculture
Urban settlement
Broadleaf forest
Mesophyll mountain forest
Water
22º51'
22º00'
22º15'
22º30'
22º34'48''
99º34'12''
99º30'
99º15'
99º00'
98º55'48''
Latitude North
Longitude West
22º51'
22º00'
22º15'
22º30'
22º34'48''
99º34'12''
99º30'
99º15'
99º00'
98º55'48''
Latitude North
2000
Fig. 4.
Vegetation type and Land Use in the Río Valles Basin between 1970 and 2000. CAMBIAR “Low decidu-
ous jungle and sub-deciduous” POR “Lowland deciduous and sub-deciduous tropical forest” Y “High
evergreen jungle y sub-evergreen” POR “Highland evergreen and sub-evergreen tropical forest”
B. López Álvarez
et al.
180
Overall the RVB lost 544.26 km
2
of its jungles
and 10.84 km
2
of its forests between 1976 and 2000,
resulting in a deforestation rate of 1.18 % (Santacruz
2007). This value is slightly higher than the annual
0.65 and 0.76% at national level, with similar veg-
etation types during the same studied period (Reyes
et al.
2006).
The evaluation was carried out at a scale of 0 to
100 %, where the category of 0 to 20 represents very
small changes, 20 to 40 small changes, 40 to 60 me-
dium changes, 60 to 80 large changes and 80 to 100
very large changes. Therefore, the score of 0 to 20 %
would be the most favorable to the WPI, since it would
represent little change in the natural vegetation. On the
other hand, the score of 80 to 100 % would represent
nearly a total loss of natural vegetation in the basin.
Quality (Q)
Water is indispensable for human life. Both, its
quality and quantity are important and its degradation
impacts the environment and, in particular, human
health (Azqueta 2002, Soares 2003). Water pollution
can occur from natural or anthropogenic causes. The
improper management of water resources is one of
the main reasons for its deterioration. UNESCO
(1998) indicates that an evaluation of the quality and
quantity of available water is a prerequisite for the
development and management of water resources.
In the RVB, CONAGUA has different water
quality monitoring stations, primarily in the “Río El
Salto” and “Río Valles” subbasins. In terms of the
physical, chemical and bacteriological information
regarding water quality at these monitoring stations,
the temporal behavior of quality parameters were
determined and compared with the maximum al-
lowable limits according to the Mexican regulation
NOM-127-SSA1-1994. It is important to mention
that only Ciudad Valles has wastewater treatment
plants (whose operations and efFciency is question-
able). Domestic wastewater is discharged directly
into receptor water bodies, increasing the presence of
pollutants, especially those that are bacteriological.
The values for total and fecal coliforms (NMP/
100 mL) were over 0 (
Fig. 5
) in all the samples taken
in the “Río El Salto” subbasin.
The presence of bacteriological pollution in the
main water supply source reduces considerably the
availability of water for human use purposes in the
basin. At the monitoring stations named AADAPA
and Birmania by CONAGUA –the latter being
downstream from the former– the most probable
number (MPN) in the samples taken in the year
2005 varied from 47 000 to 700 000 MPN/100 mL.
Sánchez and Hernández (1996) found total coliform
1
Sampling date
Total coliforms
Fecal coliforms
NOM-127 (Zero CFU/100 mL)
07/08/1995
06/10/1995
01/03/1996
15/05/1996
15/08/1996
14/12/1996
26/02/1997
04/06/1997
22/12/1997
19/02/1998
20/05/1998
19/08/1998
18/11/1998
01/09/1999
27/10/1999
25/11/1999
10/02/2000
25/04/2000
15/06/2000
10/08/2000
04/10/2000
21/02/2001
25/04/2001
12/06/2001
14/08/2001
17/10/2001
20/02/2002
14/05/2002
05/08/2002
19/11/2002
18/09/1997
100 000
10 000
1000
100
Total anf fecal coliforms (MPN/100 mL)
10
Fig. 5.
Bacteriological analysis of water from the “Río Valles” and the “Río El Salto” sub-
basins.
Source: Santacruz (2007) and NOM-127-SSA1 (1994)
WATER POVERTY INDEX IN SUBTROPICAL ZONES
181
values of 2500 MPN/100 mLat different points located
throughout the main channel in this subbasin. They
also detected the presence of enterobacteria such as
Escherichia coli, Proteus, Klebsiella pneumoniae,
Shigella dysenteriae
and
Serratia marcescens
.
This component was evaluated using the Water
Quality Index (WQI) developed by Mcclelland
(1974). This index is a numerical representation of the
chemical parameter analyzed. The index is obtained
from adding and pondering the speciFc weights ob-
tained from a geometric mean (equation 8):
=
i
i
i
P
P
C
k
WQA
(8)
where
C
i
is the percentage value assigned to the param-
eters,
P
i
is the weight assigned to each parameter,
k
is
the constant which takes the value of 1 for clear water
with no apparent pollution, 0.75 for clear water with a
slight color, foam, and slight unnatural apparent turbid-
ity, 0.50 for water with a contaminated appearance and
0.25 for sewage with fermentations and odors.
To obtain the water quality component for the
surface and groundwater available in the study area,
the following expression is used (López-Álvarez
et
al.
2013, equation 9):
Agrn
Asur
Q
Q
Q
09
.
0
91
.
0
+
=
(9)
where
Q
Asur
and
Q
Agrn
are the WQI for surface and
groundwater from the aquifer, respectively. The
weight factors (0.91 and 0.09) used in this component
were assigned according to the percentage of usage
from these sources in the region.
On a scale of 0 to 100, the maximum value of
100 represents excellent quality and values under 50
represent serious pollution problems.
RESULTS AND DISCUSSION
The following results were obtained after analyz-
ing the information to evaluate each component for
the RVB.
Resources
Given the orographic and climatic conditions in
the RVB, during the rainy season large ±ows occur,
frequently causing ±ooding in the lower parts of the
basin. Consequently, surface water is abundant and
provides the main source (91 %) of water for different
activities in the region.
²rom a geological perspective, groundwater cir-
culates in highly fractured limestone with dissolution
cavities (karst area), resulting in large recharges of the
aquifer (Morán-Ramírez
et al.
2013). The abundant
surface water generates low demand for groundwater,
therefore, the amount of deep wells is low compared
to other regions in Mexico. Very little groundwater
is used, representing only 9 % of the total water use
in the RVB.
To evaluate the normalized R parameter, value 1
represents abundant water resources. This compo-
nent was evaluated with an equation that includes
extreme scenarios, in which the value 0.5 represents
a balance of the resource in the aquifers and values
less than 0.5 represent the depletion of the aquifer
(López-Álvarez
et al.
2013).
In the case of the RVB, a value of 0.97 was ob-
tained for this component, which is consistent with
the climatological conditions and the abundant water
resources in the study area.
Quality
Although surface water is abundant and serves as
the main source for a variety of economic activities,
its domestic use is limited because its quality is very
poor for human consumption. ²or example, water
from the Río Valles contains total coliform values of
as much as 273 000 C²U and fecal coliform values
of 170 000 C²U, causing gastrointestinal and der-
matological illnesses among the human population
(Gómez and Velarde 1996).
The WQI score was 51 for surface water and 66.7
for the aquifer (Santacruz and Ramos 2010). These
values were used in equation (9), based on which
the score of 0.52 for component
Q
was obtained.
While this limits its use for human consumption, it
is acceptable for agricultural irrigation (Santacruz
and Ramos 2010).
Usage
Regarding this component, agricultural activity
plays an important role and demands a high volume
of the resource for gravity irrigation systems, whose
maximum efFciency is estimated at 50 %. The value
of its production has little in±uence on the state’s
GDP and the regional economy.
Domestic use is deFcient because most of the
drinking water services are located in the municipal
capital of Ciudad Valles while the rest of the localities
lack these services.
The evaluation of this component resulted in a
normalized U value of 0.052, which re±ects the so-
cioeconomic conditions in the study zone.
B. López Álvarez
et al.
182
TABLE III.
VALUESOBTAINEDFOREACHCOMPONENT
OF THE WATER POVERTY INDEX OF RÍO
VALLES BASIN
Component
Score
Weight
Water Poverty Index
Resource
0.97
30
59
Quality
0.52
20
Use
0.05
10
Access
0.31
15
Capacity
0.35
15
Environment
0.90
10
Access
The rural population in the RVB is dispersed,
while most of the urban population is gathered in
three municipalities where drinking water services
are centralized, particularly wastewater treatment in
Ciudad Valles. The rest of the municipalities have
less and dispersed population, therefore, access to
these services is limited.
A normalized value of 0.31 was obtained due to
the centralization of drinking water and treatment
services in the main population centers and the lack
of those services in rural localities.
Capacity
In the city of San Luis Potosí, a notable concen-
tration of services and economic activity exists. This
situation polarizes the socioeconomic conditions in
the rest of the state, and therefore the HDI in the
study zone is low.
The mortality rate, income and Gini coef±cient
used to evaluate the Capacity component gave similar
values to those obtained in the SLP Valley (López-
Álvarez
et al.
2013), while the education indices
were lower than those obtained in the SLPV, which
is re²ected in the normalized score of 0.35 for this
component.
Environment
Land use changes in the RVB were considered to
evaluate the environment component. The modi±ed
natural area is approximately 588 km
2
, which rep-
resents 24 % of the total area of the RVB, a value of
0.9 was assigned to this component. This is consistent
with land use changes in the region, where tropical
rain forests have been converted into irrigated agri-
cultural land. This land use change has less impact
than in other regions of SLP where natural vegeta-
tion has been turned into urban use or deforestation
without recovery had occurred (López-Álvarez
et
al.
2013).
Water Poverty Index for the RVB
The resulting polygon for the RVB re²ects seri-
ous problems with usage, access and capacity. On
the other hand water quality, for instance, is the least
problematic in its evaluation, and the environmental
and resource components also have favorable condi-
tions (
Fig. 6
).
Table III
presents the scores obtained for each
component and their weights, as well as the overall
WPI for the RVB, with a score of 59.
If we compare this value with those obtained by
Lawrence
et al.
(2002), that are not normalized, it
is far from the scores of developed countries, such
as Finland with a WPI of 78. The WPI in the RVB
is higher than those in underdeveloped countries
with water poverty problems, such as Haiti with a
WPI of 35.1, and is even higher than the WPI for
Mexico and the SLPV, with values of 57.5 and 46,
respectively.
The WPI value for the RVB (59) is probably due
to the high availability of water and the low environ-
mental effects in this area. Nevertheless it indicates
that the rural population does not have access to the
resource, its socioeconomic situation is unequal and
the use of water is de±cient (
Fig. 6
).
Contrasts can be seen when comparing the WPI in
the SLPV with that of the RVB (
Fig. 7
). The resource
is abundant in the RVB while scarce in the SLPV.
In addition, access and the capacity components are
de±cient in the RVB whereas in the SLPV there is a
more ef±cient management of this resource.
0.97
Resource
Environment
Capacity
Access
Use
Quality
0.52
0.05
0.31
0.35
0.90
1.0
0.8
0.6
0.4
0.2
0.0
Fig.6.
Normalized Water Poverty Index Hexagon for the Río
Valles Basin
WATER POVERTY INDEX IN SUBTROPICAL ZONES
183
Throughout history, the environment in the
SLPV has undergone irreversible changes, such as
deforestation and depletion and pollution of surface
and groundwater resources. Nevertheless, the envi-
ronmental changes in the RVB are reversible and
deforested zones may be recovered in a short period
of time. In terms of the resource, recharge is high
and Fows are very dynamic because of the karstic
characteristic of the rock.
The above analysis shows that the abundance of
the resource does not ensure better socioeconomic
development in a region.
CONCLUSIONS
Geographic, geological, orographic and climatic
conditions are factors that enhance the abundance of
the resource (R), resulting in a value of 0.97.
Land use changes in the RVB have had little im-
pact on the environment because the loss of natural
vegetation cover was replaced by irrigated agricul-
ture, resulting in a value of 0.9 for the environmental
component (E).
In terms of the quality (Q) of water for human
consumption, treatment is required. Nevertheless, it
is adequate for agricultural uses and a value of 0.52
was obtained.
Regarding capacity (C), a value of 0.35 was
achieved, which reFects the centralization of the
economical activity in the area, that is focused mainly
in one municipality, while the rest of the localities
are left behind.
Seventy ±ve percent of the human population living
in the RVB is localized in CiudadValles, El Naranjo and
Nuevo Morelos. This population has access to clean
water, but there are de±cient wastewater treatment
services and adequate access to irrigation water. The
rest of the population (25 %) has de±cient or no access
(A) to the resource, as reFected by a score of 0.31.
The main use of water is for agriculture, which
is the largest activity in the region. Nonetheless, the
usage (U) does not signi±cantly contribute to the
state´s GDP, as reFected by a value of 0.05 for this
component. In addition, domestic use is centered
primarily in Ciudad Valles, whereas services for the
rest of the population in the RVB are de±cient.
The evaluation of the WPI for the RVB demon-
strates that water poverty levels in a region are not
determined by the quantity of the resource but rather
by its ef±cient management and use. Therefore, the
WPI could be a useful tool for integrated water re-
sources management.
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