Next Article in Journal
A Review on the Roles of Extracellular Polymeric Substances (EPSs) in Wastewater Treatment: Source, Mechanism Study, Bioproducts, Limitations, and Future Challenges
Previous Article in Journal
Use of Brushite as Adsorbent for the Removal of Anionic and Cationic Dyes Present in Aqueous Solutions
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Water
Volume 16
Issue 19
10.3390/w16192811
water-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The Hydrosocial Cycle and the Inequalities in Access to Water in Rural Areas of Metropolitan Region of Santiago, Chile

by
Carolina Rodríguez
1,*,
Jennyfer Serrano
2,
Rafael Sánchez
3 and
Eduardo Leiva
1,4,*
1
Departamento de Química Inorgánica, Facultad de Química, Pontificia Universidad Católica de Chile, Avenida Vicuña Mackenna 4860, Macul, Santiago 7820436, Chile
2
Escuela de Biotecnología, Universidad Mayor, Camino La Pirámide 5750, Huechuraba, Santiago 8580745, Chile
3
Instituto de Geografía, Pontificia Universidad Católica de Chile, Avenida Vicuña Mackenna 4860, Macul, Santiago 7820436, Chile
4
Departamento de Ingeniería Hidráulica y Ambiental, Pontificia Universidad Católica de Chile, Avenida Vicuña Mackenna 4860, Macul, Santiago 7820436, Chile
*
Authors to whom correspondence should be addressed.
Water 2024, 16(19), 2811; https://doi.org/10.3390/w16192811
Submission received: 2 September 2024 / Revised: 13 September 2024 / Accepted: 20 September 2024 / Published: 2 October 2024
(This article belongs to the Section Hydrology)
Browse Figures
Versions Notes

Abstract

:
Water scarcity in Chile has been increasing in recent years, particularly in the central-northern region, associated with a sustained decrease in rainfall and the effects of climate change. This study characterizes the hydrosocial cycle in the Metropolitan Region of Santiago, Chile, with a focus on rural areas, examining the relationship between water availability and socioeconomic factors. For this, demographic data and data related to water demand and use, obtained from government databases, were used. In addition, geographic information systems (GIS) were used for spatial analysis and map creation. Finally, surveys were conducted in rural schools and households to obtain information on water use perceptions and practices. The results show inequalities in access to water with a moderate negative correlation between poverty and water connection/consumption. Rural areas exhibited stronger negative correlations, indicating a greater impact of poverty on water access. Water-saving practices, such as reusing washing water for irrigation, were prevalent in rural households. These results highlight the importance of the hydrosocial cycle to understand the dynamics and factors that shape water demand and consumption in a highly complex region.

1. Introduction

Water scarcity in Chile has reached critical levels in recent years, especially in the northern and central regions, where much of the population and agricultural activity are concentrated. Since 2010, Chile has experienced a sustained decrease in rainfall, with a reduction of up to 30% in the central zone during the last decades [1]. This megadrought has led to a marked decrease in the flows of key rivers such as the Maipo, Aconcagua and Mapocho, severely affecting the supply of water for human consumption and agricultural irrigation [2,3]. For instance, the flow of the Maipo River has significantly decreased, compromising the supply of drinking water for Santiago [4]. Furthermore, storage in key reservoirs, such as El Yeso and Peñuelas, has decreased dramatically, registering critically low levels in recent years [5]. These effects have been further exacerbated by climate change, which has intensified the pressure on the country’s water resources due to increasing evaporation and water demand [6].
The Maipo River basin, located in central Chile, is one of the most important in the country, both from a hydrographic and socioeconomic perspective. This basin covers an area of approximately 15,304 km² and extends from the Andes mountain range to its mouth in the Pacific Ocean, crossing the Metropolitan Region of Santiago [7]. The Maipo River, with a length of approximately 250 km, is the main source of water for Santiago, supplying nearly 7 million people and supporting much of the agricultural activity in the region, especially the cultivation of fruit trees and vineyards [8,9,10]. The basin is characterized by a snow-based hydrological regime, where most of the flow is caused by the melting of snow accumulated in the mountain range during the spring and summer months [2]. However, climate change has had a significant impact on water availability in the basin, reducing snowfall and altering snowmelt patterns, which has exacerbated the region’s vulnerability to drought [11]. In addition, the basin faces pressures from intensive water use for agricultural irrigation and urban growth, which has generated conflicts between different users and challenges for the sustainable management of the resource.
In recent decades, the Metropolitan Region (MR) of Santiago has experienced significant population growth, becoming the most densely populated region in Chile. From 1990 to 2020, the population increased from approximately 5.4 million to more than 7 million inhabitants, driven by both natural growth and migration, particularly from rural areas and other Latin American countries [12]. This growth has strengthened the MR as the main economic center of the country, contributing about 40% of the national Gross Domestic Product (GDP). The predominant economic activities include commerce, financial services, construction, and manufacturing, establishing Santiago as a hub for development and investment [13,14,15]. However, this economic development has been accompanied by growing economic inequality. Although the region generates a high concentration of wealth, its distribution is extremely unequal, which is reflected in socio-spatial segregation and significant differences in access to basic services such as education, health, and housing [16,17,18].
In the Metropolitan Region of Santiago, population growth, intense economic activities, and socioeconomic inequality have profoundly reconfigured water dynamics, highlighting the relevance of the hydrosocial cycle in the management of this vital resource. The hydrosocial cycle recognizes that water circulates not only through natural processes but also through networks of power, policies, and social decisions that determine its access and distribution [19]. In a region where pressure on water resources is increasing due to urban expansion and demand from industry and agriculture, understanding how these social interactions influence the water cycle is essential for addressing issues of inequity and sustainability. The application of the hydrosocial cycle in the Metropolitan Region enables the identification of how political and economic decisions have perpetuated inequality in access to water, exacerbating the disparities between different urban and rural areas [20]. This approach is therefore crucial to developing integrated water management policies that not only focus on the physical aspects of the hydrological cycle but also incorporate complex social interactions, ensuring more equitable and sustainable access to water in the region.
The objectives of this study are centered on the characterization of the hydrosocial cycle in the Metropolitan Region, with an emphasis on the differences in and characteristics of the rural areas within the region. Additionally, the study seeks to establish a relationship between water availability and socioeconomic aspects. Finally, an analysis of surveys applied to individuals in rural areas affected by drinking water availability is conducted, aiming to determine perceptions about water use and demand.

2. Methodology

To achieve the objectives of this study, various types of information were processed. The processed data included commune types, population, population density, access to potable water through public networks, income-based poverty, and daily water consumption per family. Demographic information was mainly acquired from data processing of the last census carried out in the country and its projections. Additionally, historical data on river flows and precipitation were used. Databases of the Superintendence of Sanitary Services and the General Directorate of Water were accessed to obtain data related to water availability and use, as well as climatological and fluviometric data, respectively. The data collected pertain to the study area, which corresponds to the Metropolitan Region of Santiago, Chile, as illustrated in Figure 1.
For the description and the spatial and socioeconomic analyses of the study region, maps were created using a geospatial approach based on Geographic Information Systems (GIS). QGIS was used to perform the spatial analysis and to generate the maps. Socioeconomic and demographic data were collected and processed for visualization, allowing for a precise spatial representation of key variables such as poverty, population density, and access to water. In parallel, a correlation analysis was conducted to quantify the relationships between the variables involved. This analysis was performed using correlation matrices, where Pearson correlation coefficients were calculated between pairs of variables. The objective was to identify and understand the interrelationships between the socioeconomic, demographic, and water access factors in different types of communes (urban, rural, and mixed).
To assess the availability and variability of water sources in the Metropolitan Region, an integrated approach was used that included the analysis of geospatial and temporal data. The distribution of surface and groundwater sources was mapped using Geographic Information Systems (GIS), considering the most relevant wells and sub-basins for regional supply. In parallel, precipitation time series from the last 20 years were analyzed. An isohyet map was generated to represent the spatial distribution of the average annual precipitation. The data used for this analysis were sourced from the General Directorate of Water (DGA)
Finally, to complement the hydrosocial analysis of the region, with an emphasis on rural areas, surveys were conducted in six schools and in the homes belonging to these educational communities, distributed across various rural communes in the Metropolitan Region (Area 1: 33°43′57.906″ S, 71°1′27.974″ W; Area 2: 33°52′11.371″ S, 70°43′42.030″ W; Area 2: 33°41′43.851″ S, 70°20′4.947″ W; Area 3: 33°41′43.851″ S, 70°20′4.947″ W; Area 4: 33°6′34.023″ S, 70°47′38.385″ W; Area 5: 33°10′6.296″ S, 70°53′30.078″ W; and Area 6: 33°43′18.948″ S, 70°32′59.256″ W), as shown in Appendix A, Figure A1. These surveys focused on determining both real data and perceptions regarding water use, as well as water-saving and reuse practices. The collected data were processed, and histograms and correlation analyses were constructed to analyze the findings. The surveys applied to schools and households are presented in Appendix B and Appendix C.
Based on the survey conducted in six rural schools in the region, information was gathered regarding perceptions of water use. This survey was completed by students and teachers from these establishments. A total of 124 students responded to the survey, with an age range of 13–19 years and an average age of 13.6 years. Of these, 34% were female, 63% male, and 3% did not identify with any gender. Additionally, 111 teachers participated in the survey, with an age range of 23 to 66 years and an average age of 43.3 years, with 87% being female and 13% male.
Figure 2 shows a methodological flowchart summarizing the methods used to carry out this work.

3. Spatial and Socioeconomic Analysis of Metropolitan Region

The Metropolitan Region of Santiago is the capital of Chile and the most populous region in the country. Despite its large urban center, some of the communes within this region exhibit rural characteristics. Figure 3a illustrates the classification of these communes according to their urban or rural statuses. Out of the 52 communes in the region, 41 are classified as urban, collectively housing 6.8 million inhabitants, which accounts for 95.8% of the regional population and occupies 35.9% of the region’s total area. In contrast, the six communes identified as rural are primarily located on the periphery of the region. These rural communes are home to slightly fewer than 100,000 inhabitants, representing 1.3% of the regional population, and cover an area that constitutes 52.8% of the regional total. Lastly, five communes are classified as mixed, with a population of approximately 200,000 inhabitants, equivalent to 2.9% of the regional population and 11.4% of the total area. These data are further illustrated in Figure 3b,c, which present a classification of the communes by population and population density, respectively. It is evident that the urban center is concentrated in the central communes of the region, which also have the largest populations and the highest population densities.
The Metropolitan Region exhibits a structure typical of large urban centers, characterized by peri-urban growth. This rural-urban expansion surrounding the cities creates a mosaic-like landscape [22]. Generally, this area is marked by a vulnerable population with high poverty rates and limited access to services and infrastructure [23,24]. Figure 4 illustrates part of this inequality. Chile has achieved nearly universal access to drinking water (99%) and sanitation (78.6%), positioning it as the country in Latin America and the Caribbean with the best access, with averages comparable to those of other OECD countries [25]. However, a portion of the population still lacks access to these services. Figure 4a shows the percentage of households at the communal level connected to the public water supply network. It is evident that the urban core is almost fully connected, while in the peri-urban areas with greater rurality, this percentage decreases. In rural and mixed areas, the percentage of the population not connected to the public network is supplied by the Rural Drinking Water Program (APR), water tanker trucks, and, to a lesser extent, wells or norias [26]. Additionally, it can be observed that the poverty rate increases in peri-urban areas and in the southwest zone of the urban core. Conversely, data on water consumption per client per day (Figure 4c) reveal an increase toward the northeast sector where the lowest poverty rates are located. Water consumption is also high in some rural or mixed communes, primarily due to the use of water for the irrigation of gardens.
The results shown in Figure 3 and Figure 4 provide relevant information about the spatial and social configuration of the Metropolitan Region. To further analyze this quantitatively, a correlation analysis was applied to the different variables involved.
The correlation analysis conducted for all the communes (Table 1) shows a moderate negative correlation between poverty and water connection (−0.48), as well as between poverty and water consumption (−0.36). This suggests that, in general, poorer communes tend to have reduced access to water connections and lower water consumption. Additionally, there is a positive correlation between water connection and population density (0.56), indicating that more densely populated areas tend to have better access to water.
When disaggregating the analysis by type of commune, urban communes exhibit weaker correlations compared to the general analysis. Here, poverty has a slight negative correlation with water connection (−0.20) and water consumption (−0.35). Population density has a moderate positive correlation with water connection (0.56), similar to the overall result. On the other hand, rural communes present more extreme patterns, with a strong negative correlation between poverty and water consumption (−0.99) and between poverty and population (−0.84). This suggests that in rural areas, poverty has a much more significant impact on access to and consumption of water, possibly due to the less-developed infrastructure available. Interestingly, there is a high positive correlation between water consumption and population (0.83) in these areas. Finally, in mixed communes, a strong negative correlation is observed between poverty and water consumption (−0.95) and a moderate positive correlation between poverty and water connection (0.62). These results indicate that in mixed areas, poverty significantly affects water consumption, while water connection seems to be better in these communes, although still negatively related to the available area (−0.17).

4. Water Sources and Precipitation Trends

Most of the Metropolitan Region is supplied with drinking water from surface water sources. The main sources are the Maipo River, which covers around 80% of the regional drinking water demand [27], and the Mapocho River and the Arrayan Estuary, which primarily supply the communes in the northeastern sector of the region. To a lesser extent, underground water sources are used for drinking water supply. Although not in significant quantities, the use of groundwater has been increasing in recent decades due to rising demand and periods of drought [28]. These points are summarized in Figure 5a. Furthermore, it is noteworthy that by the 1960s, only 6% of the rural population had access to drinking water, which led to the creation of the Rural Drinking Water Program (PAPR) [26,29]. Figure 5b shows the Rural Drinking Water (APR) systems in the Metropolitan Region, which are responsible for supplementing access to drinking water primarily for the populations of the rural and mixed communes of the region.
The Maipo and Mapocho Rivers and the Arrayan Estuary exhibit a nivo-pluvial regime, meaning that their flow patterns are influenced by both snowmelt and rainfall [32]. This is particularly evident in the Maipo River basin, where snowmelt from the Andes significantly contributes to the river’s flow during the summer months. As shown in Figure 5c, which presents the average monthly flows over the last 20 years, this pattern is most pronounced in the Maipo River. The flow increases mainly from October to March, coinciding with spring and summer in the region, highlighting the strong influence of snowmelt on water availability.
Figure 6 presents an analysis of precipitation in the Metropolitan Region. In Figure 6a, the isohyet map shows the spatial distribution of the average annual precipitation, revealing how it varies significantly across the region, with higher-altitude areas receiving more precipitation [33]. Precipitation in this area is concentrated during the winter months and is primarily caused by low-pressure fronts [33]. In Figure 6b, the average precipitation over the last 20 years is presented along with a regression line. This line suggests a decreasing trend in precipitation. In this context, numerous studies have reported a decrease in precipitation in central Chile in recent years. Some studies indicate precipitation deficits ranging from 25% to 45% over the past 15 years [34]. Additionally, the impact of anthropogenic contributions to this phenomenon has been documented [35].

5. Results of Surveys on the Perception of Water Use and Management in Rural Areas

5.1. Rural Schools

The data collected from the surveys were converted into daily water consumption, expressed as liters per person per day (lppd), and are presented in Figure 7. A significant number of outliers was observed in the results, so the Robust Regression and Outlier Removal (ROUT) method was employed to identify and exclude outliers from the dataset. For this analysis, a Q value of 5% was selected to detect significant outliers without excessively excluding data that could be informative. The results of this analysis identified a total of 13 outliers, which were removed to construct the histogram and box plot presented in Figure 7a,b, respectively.
The histogram shown in Figure 7a exhibits a multimodal distribution with peaks at several intervals. The highest frequency value is observed in the bin centered at 20 L per day, with a frequency of approximately 0.16. The distribution shows some asymmetry, with a higher concentration of data in the lower value bins (0 to 60) and a gradual decrease in frequency as the bin values increase. This suggests that the data tend to be more clustered at lower water consumption values. Additionally, a lognormal model was fitted to the data, which presented an R² value of 0.74, indicating the best fit achieved. The median and mean of the data are relatively close with the mean being slightly higher, which is consistent with the right skewness. Additionally, the box plot shows a wide interquartile range, suggesting a broad variability in the data.
Another study conducted in a different area of Chile reported a perception of water use in schools averaging 45 lppd, a value slightly lower than that obtained in this study [36]. Additionally, another study carried out in student residences showed water use associated with washbasins and toilets ranging from 28 to 41 lppd [37], while in residential settings, water consumption related to washbasin taps varies between 7 and 21 lppd [38]. The results of this study show realistic, albeit slightly elevated, values as compared to those evidenced in other studies. This, along with the high number of outliers found in some survey responses, suggests a tendency for respondents to overestimate their own water consumption. This phenomenon is commonly observed in data collection methods associated with self-perception of water use [39].

5.2. Rural Households

A survey was conducted among 43 households associated with the schools mentioned in the previous section. Information on water consumption over the last 12 months was requested, but these data were only obtained from 10 of the surveyed households. Figure 8a shows a correlation graph between the number of household members and the average water consumption. The Pearson correlation analysis yielded a value of 0.63, indicating a moderate positive correlation between these two parameters. Additionally, the survey inquired about current water-saving and reuse practices (Figure 8b). From this analysis, it was determined that one of the most commonly used practices is the direct reuse of water from washing machines, with 44% of households practicing this, followed by the reuse of water from showers, with 26% practicing this method. In both cases, the repurposed water is primarily used for garden irrigation.
Water reuse practices in households, particularly in regions where water is scarce, have been adopted as a strategy to conserve water. An analysis of greywater reuse practices highlights the growing prevalence of reusing water from activities such as bathing, laundry, and dishwashing for purposes like irrigation and toilet flushing. However, despite the environmental benefits, barriers such as public perception, safety concerns, and regulatory challenges still limit its widespread adoption [40,41].

6. Conclusions

The analyses conducted in this study highlight significant inequalities in water access, particularly in rural and peri-urban areas, where infrastructure is less developed. There is a moderate negative correlation between poverty and water connection, as well as between poverty and water consumption. Additionally, the strong negative correlations found in rural areas suggest that poverty exacerbates limitations in water infrastructure, leading to significantly lower water consumption. Conversely, the positive correlation between population density and water connection indicates that densely populated areas tend to have better access to water services, although this is not uniform across all communes.
There is a significant role of surface water sources, particularly the Maipo River, in meeting the drinking water demands of the Metropolitan Region of Santiago. The analysis of hydrological patterns, such as the nivo-pluvial regime of the Maipo and Mapocho Rivers, demonstrates the critical influence of snowmelt on water availability during the summer months. The observed decrease in precipitation over the last 20 years, along with anthropogenic impacts, raises concerns about future water availability in the region. These findings underscore the urgent need for integrated water management strategies that address both natural and human-induced changes, ensuring sustainable and equitable water access across the region, especially in vulnerable rural and peri-urban areas.
The survey results indicate realistic, though slightly elevated, estimates of daily water consumption, reflecting a common tendency among respondents to overestimate their water use. Additionally, the study found a moderate positive correlation between household size and water consumption. The most common water-saving practice identified in rural households was the reuse of water from washing machines for garden irrigation. These findings underscore the importance of considering the hydrosocial cycle in water management strategies, particularly in rural and peri-urban areas. The hydrosocial cycle framework, which integrates social, economic, and environmental factors, is crucial for understanding the complex dynamics of water use and access.

Author Contributions

The writing—original draft preparation was made by C.R., but all the authors contributed to its preparation and review. Conceptualization, methodology, and data analyses were carried out by C.R. in discussion with E.L.; the validation of results was performed by C.R.; and the manuscript was edited and reviewed by C.R., R.S., J.S. and E.L. Supervision, project administration, and funding acquisition was performed by E.L., J.S., R.S. and C.R. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by FIC-R Fondo de Innovación para la Competitividad Gore Santiago BIP Nos. 40037328-0, FONDECYT REGULAR 1241833 (2024–2028) and Puente 2023-17 grants.

Data Availability Statement

The raw data supporting the conclusions of this article will be made available by the authors upon request.

Acknowledgments

Our gratitude is also extended to the reviewers for their corrections and suggestions, which contributed significantly to the improvement of the quality of this manuscript.

Conflicts of Interest

The authors declare no conflicts of interest.

Appendix A

Water 16 02811 g0a1
Figure A1. Survey application areas in rural sectors.
Figure A1. Survey application areas in rural sectors.
Water 16 02811 g0a1

Appendix B

  • Survey Applied to Schools (Translation from Spanish to English)
  • Personal data
  • Age: _____years
  • Gender: ☐ Male ☐ Female ☐ Other
  • Water consumption in the establishment
  • How many times a day do you use the sink faucet in the establishment?________
  • How long do you leave the faucet open each time you use it?________seconds
  • How many times a day do you use the toilet in the establishment?___________
  • How many times a day do you use the urinal at the establishment?__________

Appendix C

Survey Applied to Households (Translation from Spanish to English)
  • Characterization of the home
People in the householdNumber of womenNumber of men
Adults
Minors
2.
Origin and use of water
  • Mark with an X where appropriate
UseOrigin
Public supply networkRural drinking water (APR)WellWater tanker truckRecycled or treated waterIrrigation canalUnknown
Bathroon
Kitchen
Home cleaning
Irrigation
Others
3.
Quantifying consumption
  • If your home has a meter or can estimate the amount of drinking water you consume monthly, what was your water consumption in cubic meters (m3) over the last 12 months?
October 2022m3April 2023m3
November 2022m3May 2023m3
Dicember 2022m3June 2023m3
January 2023m3July 2023m3
February 2023m3August 2023m3
March 2023m3September 2023m3
4.
Reusing water or saving water at home
  • Does your home have any of the following water saving or reuse systems?
YesNo
Dual-flush toilet systems
Placing a bottle or other objects in the toilet tank
Aeration of faucet taps (sink or kitchen sink)
Water-saving faucet taps (programmed shut-off)
Reusing water from washing machines
Reusing water from showers
Drip irrigation (garden, crops)
Other: ________________________________

References

  1. Garreaud, R.D.; Alvarez-Garreton, C.; Barichivich, J.; Pablo Boisier, J.; Christie, D.; Galleguillos, M.; LeQuesne, C.; McPhee, J.; Zambrano-Bigiarini, M. The 2010–2015 Megadrought in Central Chile: Impacts on Regional Hydroclimate and Vegetation. Hydrol. Earth Syst. Sci. 2017, 21, 6307–6327. [Google Scholar] [CrossRef]
  2. Vicuña, S.; Garreaud, R.D.; McPhee, J. Climate Change Impacts on the Hydrology of a Snowmelt Driven Basin in Semiarid Chile. Clim. Chang. 2011, 105, 469–488. [Google Scholar] [CrossRef]
  3. Peña, H. Integrated Water Resources Management in Chile: Advances and Challenges. Glob. Issues Water Policy 2018, 21, 197–207. [Google Scholar] [CrossRef]
  4. Meza, F.J.; Silva, D.; Vigil, H. Climate Change Impacts on Irrigated Maize in Mediterranean Climates: Evaluation of Double Cropping as an Emerging Adaptation Alternative. Agric. Syst. 2008, 98, 21–30. [Google Scholar] [CrossRef]
  5. Valdés-Pineda, R.; Garcia-Chevesich, P.A.; Alaniz, A.J.; Venegas-Quiñonez, H.; Valdés, J.B.; Pizarro, R. The Impact of a Lack of Government Strategies for Sustainable Water Management and Land Use Planning on the Hydrology of Water Bodies: Lessons Learned from the Disappearance of the Aculeo Lagoon in Central Chile. Sustainability 2021, 14, 413. [Google Scholar] [CrossRef]
  6. Cai, W.; McPhaden, M.J.; Grimm, A.M.; Rodrigues, R.R.; Taschetto, A.S.; Garreaud, R.D.; Dewitte, B.; Poveda, G.; Ham, Y.G.; Santoso, A.; et al. Climate Impacts of the El Niño–Southern Oscillation on South America. Nat. Rev. Earth Environ. 2020, 1, 215–231. [Google Scholar] [CrossRef]
  7. Ibañez, M.; Gironás, J.; Oberli, C.; Chadwick, C.; Garreaud Salazar, R.D. Daily and Seasonal Variation of the Surface Temperature Lapse Rate and 0°C Isotherm Height in the Western Subtropical Andes. Int. J. Climatol. 2020, 41, E980–E999. [Google Scholar] [CrossRef]
  8. Piñones, A.; Valle-Levinson, A.; Narváez, D.A.; Vargas, C.A.; Navarrete, S.A.; Yuras, G.; Castilla, J.C. Wind-Induced Diurnal Variability in River Plume Motion. Estuar. Coast. Shelf Sci. 2005, 65, 513–525. [Google Scholar] [CrossRef]
  9. Borgias, S.; Bauer, C.J. Trajectory of a Divided River Basin: Law, Conflict, and Cooperation along Chile’s Maipo River. Water Policy 2018, 20, 127–145. [Google Scholar] [CrossRef]
  10. Arróspide, F.; Mao, L.; Escauriaza, C. Morphological Evolution of the Maipo River in Central Chile: Influence of Instream Gravel Mining. Geomorphology 2018, 306, 182–197. [Google Scholar] [CrossRef]
  11. Masiokas, M.H.; Villalba, R.; Luckman, B.H.; Le Quesne, C.; Aravena, J.C. Snowpack Variations in the Central Andes of Argentina and Chile, 1951–2005: Large-Scale Atmospheric Influences and Implications for Water Resources in the Region. J. Clim. 2006, 19, 6334–6352. [Google Scholar] [CrossRef]
  12. INE. Resultados CENSO 2017. Available online: https://censoagro2017.ibge.gov.br/resultados-censo-agro-2017.html (accessed on 19 August 2024).
  13. Zegras, C.; Gakenheimer, R. Urban Growth Management for Mobility: The Case of the Santiago, Chile Metropolitan Region; Lincoln Institute of Land Policy: Washington, DC, USA, 2000; p. 172. Available online: http://web.mit.edu/czegras/www/Zegras_Gakenheimer_Stgo_growth_mgmt.pdf (accessed on 10 August 2024).
  14. Krellenberg, K.; Müller, A.; Schwarz, A.; Höfer, R.; Welz, J. Flood and Heat Hazards in the Metropolitan Region of Santiago de Chile and the Socio-Economics of Exposure. Appl. Geogr. 2013, 38, 86–95. [Google Scholar] [CrossRef]
  15. Estadísticas y Datos-Banco Central de Chile. Available online: https://www.bcentral.cl/web/banco-central/areas/estadisticas/ (accessed on 18 August 2024).
  16. Paredes, D.; Iturra, V.; Lufin, M. A Spatial Decomposition of Income Inequality in Chile. Reg. Stud. 2016, 50, 771–789. [Google Scholar] [CrossRef]
  17. Contreras, D.; Bhamidipati, S.; Wilkinson, S. Social Vulnerability and Spatial Inequality in Access to Healthcare Facilities: The Case of the Santiago Metropolitan Region (RMS), Chile. Socioecon. Plan. Sci. 2023, 90, 101735. [Google Scholar] [CrossRef]
  18. Boulant, J.; Brezzi, M.; Veneri, P. Income Levels and Inequality in Metropolitan Areas: A Comparative Approach in OECD Countries; OECD: Paris, France, 2016. [Google Scholar]
  19. Linton, J.; Budds, J. The Hydrosocial Cycle: Defining and Mobilizing a Relational-Dialectical Approach to Water. Geoforum 2014, 57, 170–180. [Google Scholar] [CrossRef]
  20. Boelens, R.; Hoogesteger, J.; Swyngedouw, E.; Vos, J.; Wester, P. Hydrosocial Territories: A Political Ecology Perspective. Water Int. 2016, 41, 1–14. [Google Scholar] [CrossRef]
  21. Oficina de Estudios y Políticas Agrarias ODEPA Región Metropolitana de Santiago. Available online: https://bibliotecadigital.odepa.gob.cl/bitstream/handle/20.500.12650/72862/Ficha-regional-Metropolitana.pdf (accessed on 27 August 2024).
  22. Sahana, M.; Ravetz, J.; Patel, P.P.; Dadashpoor, H.; Follmann, A. Where Is the Peri-Urban? A Systematic Review of Peri-Urban Research and Approaches for Its Identification and Demarcation Worldwide. Remote Sens. 2023, 15, 1316. [Google Scholar] [CrossRef]
  23. Delgado-Viñas, C.; Gómez-Moreno, M.L. The Interaction between Urban and Rural Areas: An Updated Paradigmatic, Methodological and Bibliographic Review. Land 2022, 11, 1298. [Google Scholar] [CrossRef]
  24. Hutchings, P.; Willcock, S.; Lynch, K.; Bundhoo, D.; Brewer, T.; Cooper, S.; Keech, D.; Mekala, S.; Mishra, P.P.; Parker, A.; et al. Understanding Rural–Urban Transitions in the Global South through Peri-Urban Turbulence. Nat. Sustain. 2022, 5, 924–930. [Google Scholar] [CrossRef]
  25. OECD. OECD Environmental Performance Reviews: Chile 2024; OECD Environmental Performance Reviews; OECD Publishing: Paris, France, 2024; ISBN 9789264379183. [Google Scholar]
  26. Fuster, R.; Donoso, G. Rural Water Management. Glob. Issues Water Policy 2018, 21, 151–163. [Google Scholar] [CrossRef]
  27. Peña-Guerrero, M.D.; Nauditt, A.; Muñoz-Robles, C.; Ribbe, L.; Meza, F. Drought Impacts on Water Quality and Potential Implications for Agricultural Production in the Maipo River Basin, Central Chile. Hydrol. Sci. J. 2020, 65, 1005–1021. [Google Scholar] [CrossRef]
  28. Munoz, J.F.; Fernández, B.; Escauriaza, C. Evaluation of Groundwater Availability and Sustainable Extraction Rate for the Upper Santiago Valley Aquifer, Chile. Hydrogeol. J. 2003, 11, 687–700. [Google Scholar] [CrossRef]
  29. Nelson-Nuñez, J.; Walters, J.P.; Charpentier, D. Exploring the Challenges to Sustainable Rural Drinking Water Services in Chile. Water Policy 2019, 21, 1251–1265. [Google Scholar] [CrossRef]
  30. Dirección General de Aguas (DGA) Servicios Hidrometeorológicos. Available online: https://dga.mop.gob.cl/Paginas/hidrolineasatel.aspx (accessed on 27 August 2024).
  31. Datos.gob Listado de Sistemas de Agua Potable Rural en Chile. Available online: https://datos.gob.cl/lv/dataset/listado-de-sistemas-de-agua-potable-rural-en-chile (accessed on 27 August 2024).
  32. Bocchiola, D.; Soncini, A.; Senese, A.; Diolaiuti, G. Modelling Hydrological Components of the Rio Maipo of Chile, and Their Prospective Evolution under Climate Change. Climate 2018, 6, 57. [Google Scholar] [CrossRef]
  33. Barrett, B.S.; Hameed, S. Seasonal Variability in Precipitation in Central and Southern Chile: Modulation by the South Pacific High. J. Clim. 2017, 30, 55–69. [Google Scholar] [CrossRef]
  34. Salazar, Á.; Thatcher, M.; Goubanova, K.; Bernal, P.; Gutiérrez, J.; Squeo, F. CMIP6 Precipitation and Temperature Projections for Chile. Clim. Dyn. 2024, 62, 2475–2498. [Google Scholar] [CrossRef]
  35. Boisier, J.P.; Rondanelli, R.; Garreaud, R.D.; Muñoz, F. Anthropogenic and Natural Contributions to the Southeast Pacific Precipitation Decline and Recent Megadrought in Central Chile. Geophys. Res. Lett. 2016, 43, 413–421. [Google Scholar] [CrossRef]
  36. Rodríguez, C.; Sánchez, R.; Lozano-Parra, J.; Rebolledo, N.; Schneider, N.; Serrano, J.; Leiva, E. Water Balance Assessment in Schools and Households of Rural Areas of Coquimbo Region, North-Central Chile: Potential for Greywater Reuse. Water 2020, 12, 2915. [Google Scholar] [CrossRef]
  37. Towards Sustainable, F.; Antão-Geraldes, A.M.; Ohara, G.; João Afonso, M.; Albuquerque, A.; Silva, F. Towards Sustainable Water Use in Two University Student Residences: A Case Study. Appl. Sci. 2024, 14, 7559. [Google Scholar] [CrossRef]
  38. Englart, S.; Jedlikowski, A. The Influence of Different Water Efficiency Ratings of Taps and Mixers on Energy and Water Consumption in Buildings. SN Appl. Sci. 2019, 1, 525. [Google Scholar] [CrossRef]
  39. Vazquez-Casaubon, E.C.; Cauberghe, V.; Van de Sompel, D. “I Conserve More Water than Others, Do I?" An Exploratory Study Examining Self-Assessment Misperceptions of Water Conservation. Environ. Dev. Sustain. 2024, 26, 7303–7317. [Google Scholar] [CrossRef]
  40. Ogunbode, T.O.; Oyebamiji, V.O.; Ogundele, J.A.; Faboro, O.O. Household Preference for Wastewater Reuse/Recycling Practice Determinants in a Growing Community in Nigeria. Front. Environ. Sci. 2023, 10, 1051532. [Google Scholar] [CrossRef]
  41. Vuppaladadiyam, A.K.; Merayo, N.; Prinsen, P.; Luque, R.; Blanco, A.; Zhao, M. A Review on Greywater Reuse: Quality, Risks, Barriers and Global Scenarios. Rev. Environ. Sci. Bio/Technol. 2018, 18, 77–99. [Google Scholar] [CrossRef]
Water 16 02811 g001
Figure 1. Study site: Metropolitan Region of Santiago, Chile.
Figure 1. Study site: Metropolitan Region of Santiago, Chile.
Water 16 02811 g001
Water 16 02811 g002
Figure 2. Methodology flowchart.
Figure 2. Methodology flowchart.
Water 16 02811 g002
Water 16 02811 g003
Figure 3. Communes of the Metropolitan Region classified into: (a) type of commune, (b) population, and (c) population density [21].
Figure 3. Communes of the Metropolitan Region classified into: (a) type of commune, (b) population, and (c) population density [21].
Water 16 02811 g003
Water 16 02811 g004
Figure 4. Communes of the Metropolitan Region classified into: (a) households with access to the public water network, (b) poverty rate by income, and (c) liters of water consumed per customer (family) per day [12,21].
Figure 4. Communes of the Metropolitan Region classified into: (a) households with access to the public water network, (b) poverty rate by income, and (c) liters of water consumed per customer (family) per day [12,21].
Water 16 02811 g004
Water 16 02811 g005
Figure 5. (a) Source of surface and underground water in the Metropolitan Region, (b) distribution of Rural Drinking Water (APR) systems across the region, and (c) monthly average flows of the Maipo and Mapocho Rivers and the Arrayan Estuary over the last 20 years [30,31].
Figure 5. (a) Source of surface and underground water in the Metropolitan Region, (b) distribution of Rural Drinking Water (APR) systems across the region, and (c) monthly average flows of the Maipo and Mapocho Rivers and the Arrayan Estuary over the last 20 years [30,31].
Water 16 02811 g005
Water 16 02811 g006
Figure 6. Precipitations in the Metropolitan Region: (a) isohyet map of the Metropolitan Region, and (b) average precipitation over the last 20 years [30].
Figure 6. Precipitations in the Metropolitan Region: (a) isohyet map of the Metropolitan Region, and (b) average precipitation over the last 20 years [30].
Water 16 02811 g006
Water 16 02811 g007
Figure 7. Survey results on water consumption perception in rural schools: (a) histogram and (b) box plot.
Figure 7. Survey results on water consumption perception in rural schools: (a) histogram and (b) box plot.
Water 16 02811 g007
Water 16 02811 g008
Figure 8. Survey results for rural households: (a) average monthly household water consumption and (b) water-saving and reuse practices.
Figure 8. Survey results for rural households: (a) average monthly household water consumption and (b) water-saving and reuse practices.
Water 16 02811 g008
Table 1. Correlation analysis for communes and socioeconomic factors.
Table 1. Correlation analysis for communes and socioeconomic factors.
PovertyWater
Connection		Water
Consumption		PopulationPopulation DensityArea
Poverty1−0.48 (−0.20; −0.50; 0.62)−0.36 (−0.36; −1.00; −0.95)−0.27 (−0.13; −0.84; 0.28)−0.14 (0.08; −0.55; −0.34)0.12 (0.04; −0.26; 0.20)
Water connection−0.48 (−0.20; −0.50; 0.621−0.44 (0.19; 0.38; −0.50)0.44 (0.22; 0.05; 0.45)0.56 (0.56; 0.30; 0.28)−0.52 (−0.51; −0.20; −0.17)
Water consumption−0.36 (−0.36; −1.00; −0.95)−0.44 (0.19; 0.38; −0.50)1−0.27 (−0.14; 0.83; −0.41)−0.52 (−0.51; 0.58; 0.58)0.37 (0.54; −0.09; −0.49)
Population−0.27 (−0.13; −0.84; 0.28)0.44 (0.22; 0.05; 0.45)−0.27 (−0.14; 0.83; −0.41)10.17 (−0.11; 0.73; −0.47)−0.23 (−0.05; 0.10; 0.60)
Population density−0.14 (0.08; −0.55; −0.340.56 (0.56; 0.30; 0.28)−0.52 (−0.51; 0.58; 0.58)0.17 (−0.11; 0.73; −0.47)1−0.38 (−0.51; −0.56; −0.93)
Area0.12 (0.04; −0.26; 0.20)−0.52 (−0.51; −0.20; −0.17)0.37 (0.54; −0.09; −0.49)−0.23 (−0.05; 0.10; 0.60)−0.38 (−0.51; −0.56; −0.93)1
Note: The values are presented as follows: all communes (Urban, Rural, Mixed).
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Rodríguez, C.; Serrano, J.; Sánchez, R.; Leiva, E. The Hydrosocial Cycle and the Inequalities in Access to Water in Rural Areas of Metropolitan Region of Santiago, Chile. Water 2024, 16, 2811. https://doi.org/10.3390/w16192811

AMA Style

Rodríguez C, Serrano J, Sánchez R, Leiva E. The Hydrosocial Cycle and the Inequalities in Access to Water in Rural Areas of Metropolitan Region of Santiago, Chile. Water. 2024; 16(19):2811. https://doi.org/10.3390/w16192811

Chicago/Turabian Style

Rodríguez, Carolina, Jennyfer Serrano, Rafael Sánchez, and Eduardo Leiva. 2024. "The Hydrosocial Cycle and the Inequalities in Access to Water in Rural Areas of Metropolitan Region of Santiago, Chile" Water 16, no. 19: 2811. https://doi.org/10.3390/w16192811

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop