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Article

Climatic Hazards and the Associated Impacts on Households’ Willingness to Adopt Water-Saving Measures: Evidence from Mexico

by
Mina Khodadad
1,
Mohsen Sanei
2,*,
Christian Narvaez-Montoya
1 and
Ismael Aguilar-Barajas
3
1
School of Engineering and Sciences, Tecnológico de Monterrey, Monterrey 64849, Mexico
2
University Center of Arts, Architecture and Design, University of Guadalajara, Guadalajara 44250, Mexico
3
School of Social Sciences and Government, Tecnológico de Monterrey, Monterrey 64849, Mexico
*
Author to whom correspondence should be addressed.
Sustainability 2022, 14(10), 5817; https://doi.org/10.3390/su14105817
Submission received: 25 February 2022 / Revised: 21 April 2022 / Accepted: 5 May 2022 / Published: 11 May 2022
(This article belongs to the Special Issue Climate-Related Hazards and Human Health: Mortality, Psychosocial Aspects, and Mitigation Policies)
Browse Figure
Versions Notes

Abstract

:
Numerous regions across the globe are facing water shortage challenges, and domestic water demands are predicted to grow vastly by 2050. In this regard, household water-saving measures are critical to adapt to future risks. Few studies have evaluated the association between climate change-related threats and their impacts on water-saving activities and intentions. However, a limitation in this line of research is the assumption that only the hazards that directly affect water shortages, such as drought, can influence water conservation behaviors. Our study takes a step forward to examine the possible association between other types of extreme climate events (in addition to drought) and household water-saving behavioral willingness. Mexico is used as a case study. The information from the most recent versions of two Mexican national surveys is employed. The potential roles of three demographic characteristics (age, gender, and education) are also investigated. We found that recent experience of harsh climatic events positively affects willingness to adopt water-saving measures (although this is a small effect). The results validate the significance of experiential knowledge as a driver to increase the willingness to act responsibly regarding water challenges. The lessons we derive are of significance for Mexico and other settings facing water crises and natural hazards.

1. Introduction

Freshwater is a fundamental natural resource with great importance for food and energy security, public health, economic and industrial development, human settlements’ well-being, and ecosystems [1]. However, water-related problems increase over time. It is estimated that current domestic use has quadrupled in the last 60 years due to population growth, wealth, and access to drinking water infrastructure [2]. Furthermore, climate change is likely to generate peaks in water demand and put more pressure on water supply [2,3]. According to the shared socio-economic pathways scenarios produced by the Intergovernmental Panel on Climate Change (SSP-IPCC), which consider socioeconomic and environmental forecasts, an increase of between 50 and 250% in global domestic water extraction has been estimated by 2050, which will lead to acute water shortages [4,5].
To manage these water shortage problems, a sound understanding of the complex dynamics between humans and the natural system is required [6]. Residents, as the basic unit of residential water usage, have emerged as the primary target group for water resource management [7]. Previous research indicates that understanding water users’ attitudes, preferences, and behavior is the primary step toward an operational water efficiency initiative [3,8]. In this regard, Attari’s research [9] reveals that reducing water use through reflexive behaviors is one of the most successful approaches. It is also known that behavioral willingness is a precondition to choosing personal behaviors [10,11]. Thus, the public’s willingness to conserve water has a substantial impact on water conservation behavior [12]. For Shaw (2021) [13] the experimental and behavioral economics of water is a field of increasing importance, especially in places experiencing water scarcity derived from stress on existing supplies, population growth, and climate change.
There are various determinants of individuals’ water conservation behaviors and intentions, including individuals’ environmental beliefs and experiences. A relatively recent analysis of eleven OECD countries revealed a positive and significant association between climate change concerns and water and energy reduction behaviors [14]. Clark and Finley (2007) [15] reported that a person’s intention to save water was significantly influenced by their awareness of climate change and global warming. Their research indicated that the more people knew about climate change and were informed about it, the more inclined they were to take saving measures at home. Similarly, Hannibal et al. (2019) [16] identified that people who resided in drought-affected counties were more likely to adopt behavioral modifications and make small financial contributions to preserve water. These pieces of evidence imply that the community links climate-related issues to their water consumption and saving behaviors [17].
Previous studies have mostly examined droughts and water savings [16,17,18,19]. Nevertheless, it is also evident that other types of climatic hazards can influence pro-environmental actions and intentions. A body of research has explored the link between personal climate change experiences and the following actions and beliefs. Lang and Ryder (2016) [20], for example, analyzed Google trends (2006–2012 period) and discovered that search terms connected to climate change increased in the months after tropical cyclones, implying that individuals recognized severe weather occurrences as global climate change impacts.
In addition, the direct experience of climate-related disasters is positively connected with the climate change risk perception and environmental sensitivity [21]. Experiencing extreme climatic events affects peoples’ views on climate change and their intents to prevent its impacts [22]. People who were affected by floods in the UK expressed higher negative emotional states, greater perceived vulnerability, enhanced awareness of climate change, and higher risk perception, in comparison to a nationally representative sample [23]. More directly connected to pro-environmental engagements, a countrywide survey conducted across the UK found that first-hand experience with floods was positively associated with environmental awareness and a higher willingness to preserve energy to counteract climate change [24]. After Hurricane Irma, individuals showed more solid negative emotions about climate change, were more convinced about the link between the hurricane and climate change, and expressed more willingness to pay higher taxes [25].
Considering the shreds of evidence justifying the possible impacts of all climatic hazards on pro-environmental behaviors, our study expands on the previous research by assessing the possible correlations between the experience of a broad range of climatic hazards and household water conservation intentions. Accordingly, we have formulated two main hypotheses for this research, looking at whether there is an association between the experience of climatic hazards and household water conservation intentions and behavioral willingness. Mexico is a relevant case study to test these hypotheses. Further details are given in the methodological section.
To achieve our results, we analyzed data from the latest versions of two national household surveys conducted in Mexico. We included some demographical characteristics (i.e., gender, age, and level of education) in our analysis to explore any possible impacts on our results, and also contributed to the local body of knowledge regarding these household behavioral determinants. The impacts of these factors on environmental behaviors and willingness have been investigated in previous studies [26,27,28,29,30].
The novelties and contributions of our study are as follows. First, from the experiential knowledge perspective, this research is the first to examine the correlation between the experience of multiple climatic hazards (flood, drought, hurricane, etc.) and households’ willingness to adopt water-saving measures. Second, the analysis was conducted in Mexico, a relevant country to research the effects of climatic events on resource conservation. The country is a relatively data-poor region regarding the focus of our research. Third, the findings of this research can provide insights into other types of saving behaviors and intentions, such as energy saving or waste management.

2. Geographic Setting and the Case of Mexico

Previous research shows that differences in water conservation attitudes and behaviors depend on the water situation (e.g., scarcity) in specific geographical settings [17,31]. Since each location has its own context, each has a complex phenomenon built from social, political, economic, and hydroclimatic interactions that influence behaviors and intentions [32]. Thus, household water decision-making regarding climatic experiences can vary depending on the local context. Sapiains-Arrué and Ugarte-Caviedes (2017) [33] point out that studies on water-saving behavior are more common in developed countries, such as the United States, Spain, Australia, and the United Kingdom. Thus, there is a need for more research on this topic in less-developed countries. Latin America is a case in point.
In terms of cultural and demographic characteristics, Latin America is more homogeneous than Asia, Africa, and Europe. In this region, countries share a similar colonial history that is reflected in their common languages, religion, culture, and legal structures [34]. Latin America is one of the world’s most urbanized regions; rapid urbanization and sprawling cities are affecting the ecosystem structure, the provision of multiple ecosystem functions, and subsequent services and goods, such as water quality and availability [35]. Although Latin America is endowed with abundant freshwater, access to improved water and sanitation services in the region is unequal, service quality is poor, and financing of the sector is inadequate [35]. In fact, in a report on the development of the sustainability of the region, the United Nations Economic Commission for Latin America and the Caribbean (ECLAC) and the United Nations Environment Program (ECLAC-UNEP) considered water management to be one of the five greatest development challenges in the region [36].
In addition to its relative contextual similarity with the rest of Latin America, Mexico has great world importance for research regarding the effects of climatic events on resource conservation. The country is the 14th largest in the world, in terms of surface area [37], and is the second-largest economy in Latin America [38]. Additionally, Mexico has a high level of vulnerability to climate change and natural hazards given its geographical characteristics, such as latitude, relief, and location between two oceans. Hurricanes, droughts, extreme temperatures, and torrential rains have caused serious human losses and high economic and social costs. These events put the life of the population, their well-being, and their heritage at risk [39]. Water impacts are unevenly (spatially and socially) distributed: the northern region experiences prolonged droughts, while the southern region is affected by torrential rains. Drought and heatwaves can reduce the availability and quality of water. Likewise, more frequent and intense extreme meteorological events are projected to increase flood risks and damage the distribution systems of water and drainage, increasing the population’s exposure to water-related challenges [40] (Figure 1).
At the time of conducting this research (2022), around 75% of Mexico’s territory was in a state of drought for the second consecutive year. The adverse impacts of this situation were being felt in a large part of the territory [41]. A one-day water supply cutoff has been started for each sector of the Monterrey metropolitan area, which is the second-largest metropolitan area in Mexico [42]. This situation has directly or indirectly affected the daily lives of 5.4 million people. Within this crisis, which had been largely anticipated [43], the importance of knowing the behavior of the large population in this climatic hazard event has become clear.
This relevance is more noticeable when observing the degree of water pressure in Figure 1, which shows that two thirds of the Mexican territory has similar water conditions to Monterrey. In the same figure, it can be seen that the highest level of water pressure is observed around Mexico City, a metropolis with over 22 million people. Mexico City has a long-standing history of restrictions on water supply, and it is also vulnerable to flood and landslide risks as a result of groundwater overexploitation [44].
Previous research on water conservation behavior in the Mexican context has been limited. Manríquez-Betanzos and Lena (2018) [46] looked at three different emotions (gratitude, remorse, and anger) and their relationship with water consumption actions. Corral-Verdugo et al. (2002) [47] evaluated the impact of people’s perceptions of externalities (PE) on their incentive to save water and, as a result, their household water consumption practices. Manríquez-Betanzos et al. (2016) [48] explored the links between water savings and gratitude, eudaimonia, expenses, and water shortages, using a self-reported structural model. Corral-Verdugo et al. (2006) [49] investigated the connection between people’s time perspective and their willingness to use natural resources responsibly and sustainably, with a focus on water conservation activities.
There is also research on individuals’ perceptions and behaviors regarding the usage of water resources in a multi-national study (which included Mexico). This research focused on water quality, amount, accessibility, and regular use, along with the perception of other people’s behaviors [50]. Corral-Verdugo et al. (2003) [51] investigated, in two Mexican cities, the association between environmental beliefs and water-saving behaviors. Carrus et al. (2013) [52] found intricate interconnections between contextual, perceptual, attitudinal, and behavioral features and in water usage in several countries, including Mexico. Based on their findings, water-saving was hampered by the country’s level of development, a high rate of water accessibility, participants’ socioeconomic standing, and being indifferent to water issues.
At present, the literature on water-saving behavioral willingness regarding the experience of multiple climatic events is limited; this, to the best of our knowledge, is true on the international scale, and certainly in the case of Mexico. Therefore, this study aims to fill this research gap and advance the current understanding of water conservation behaviors in the Mexican context. To achieve this goal, the results of two Mexican national surveys are used to find relationships between water-saving behavior intentions and the experience of climatic events (flood, drought, etc.) in the last year of performing the survey. More methodological bases are provided below.

3. Materials & Methods

As expressed in the introduction, we were interested in testing two main hypotheses concerning the association between climatic hazards and behavioral willingness to save water. More specifically, these hypotheses are the following.
Hypothesis 0 (H0).
There is no association between the experience of climatic hazards and household water conservation intentions and behavioral willingness.
Hypothesis 1 (H1).
There is an association between the experience of climatic hazards and household water conservation intentions and behavioral willingness.
The data for this study were gathered from two Mexican national household surveys conducted by the National Institute of Statistics and Geography of Mexico (INEGI) in 2017. These are the latest available data on this subject. The first survey, the National Household Survey (ENH), was carried out with the purpose of determining the characteristics of the dwellings, including sociodemographic data on the members of the household, their occupations, and their education. This survey also contains information about communications technology goods and services in households [53]. The second survey, the Module on Households and Environment (MOHOMA), was conducted as a complementary survey in a questionnaire attached to the ENH survey. In general, the MOHOMA module was designed to generate statistical information on the relationship between population and the environment. More specifically, this module provided data on the actions or practices carried out by households connected with the use of natural resources and their degradation [54].
The MOHOMA module shares both its sample of housing units and its methodological foundations with the original ENH survey [54]. The 2017 surveys were conducted in a two-stage stratified cluster sampling [55]. The selection of the surveyed households was based on the cartographic and demographic information obtained from the 2010 Mexican Population and Housing Census [53]. The complete characteristics of the surveys can be consulted in INEGI’s official publications [53,54].
We determined three demographic characteristics (i.e., age, gender, and education) to analyze their potential influence on our results regarding the main hypothesis. The selection of these factors was based on previous findings in the literature, explaining their possible impacts, and the availability of the data (for example, information about income was not available in the data source). We combined the results of the surveys based on housing and participants’ identifiers (folioviv, foliohog, and id_pobla). The demographic characteristics of households (i.e., gender, age, and level of education—see Table 1) were identified by the results from the ENH survey, while the data regarding the willingness to adopt water-saving measures (8 measures—see Table 2) and the experience of climatic events (7 items, including flood, drought, etc.—see Table 3) were gathered from the MOHOMA module (see Annexes S1 and S2 for the used sections of surveys and the questions, along with the original questionnaires, which are in Spanish). A total of 14,505 households answered the required questions, as a nationally-representative sample.
The data were reconstructed and analyzed using IBM SPSS Statistics for Windows version 26.0 (Armonk, NY, USA). This helped to identify the mean and frequency (percentage), and to conduct across-tabulation analysis and the Chi-square test of independence. The Cramer’s V was used as an effect size measurement for the chi-square test. A p-value below 0.05 was set to illustrate significant associations. The same methodology was used in some related studies (e.g., [17]).
Table
Table 1. The demographic characteristics of the participants based on their experience of climatic hazards in the last 12 months (of completing the survey).
Table 1. The demographic characteristics of the participants based on their experience of climatic hazards in the last 12 months (of completing the survey).
Demographic CharacteristicsVariables Name and AssignmentAffected by Climatic Hazards during the Last YearTotal
YesNo
GenderMale = 1Count89557646659
%47.3%45.7%45.9%
Female = 2Count99668507846
%52.7%54.3%54.1%
TotalCount189112,61414,505
%100.0%100.0%100.0%
Mean (SD)1.53 (0.499)1.54 (0.498)1.54 (0.498)
AgeUnder 30 yo = 1Count50835124020
%26.9%27.8%27.7%
31–45 yo = 2Count67240544726
%35.5%32.1%32.6%
46–60 yo = 3Count44628613307
%23.6%22.7%22.8%
Older than 60 yo = 4Count26521872452
%14.0%17.3%16.9%
TotalCount189112,61414,505
%100.0%100.0%100.0%
Mean (SD) 142.2 (15.82)43.13 (17.03)43.01 (16.88)
Level of EducationNone or preschool = 0Count135745880
%7.1%5.9%6.1%
Primary school = 1Count55531503705
%29.3%25.0%25.5%
Secondary school = 2Count58433603944
%30.9%26.6%27.2%
High school = 3Count30022882588
%15.9%18.1%17.8%
Basic normal to regular undergraduate = 4Count83762845
%4.4%6.0%5.8%
Bachelor or Professional to Doctoral degree = 5Count23423092543
%12.4%18.3%17.5%
TotalCount189112,61314,504
%100.0%100.0%100.0%
Mean (SD)2.18 (1.412)2.48 (1.524)2.44 (1.513)
1 Means and Standard Deviations for age are calculated based on numerical values, not the categorical assignments. Source: Authors based upon INEGI [53,54].
Table
Table 2. The analysis of associations between demographic characteristics and the rate of agreement on water-saving solutions.
Table 2. The analysis of associations between demographic characteristics and the rate of agreement on water-saving solutions.
Water-Saving MeasuresDemographic CharacteristicsWillingness to Adopt the Measures
DisagreeIndifferenceAgreeTotal
1. Paying more for water service from the public networkGender **Mean1.551.531.511.54
Test resultsX2 (2, 14,505) = 11.79, p = 0.003, Cramer’s V = 0.029
Age ***Mean (SD)43.39 (16.82)40.46 (17.86)41.82 (16.67)43.01 (16.88)
Test resultsX2 (6, 14,505) = 57.37, p < 0.001, Cramer’s V = 0.044
Level of Education **Mean (SD)4.23 (3.057)4.12 (3.007)4.29 (3.187)4.23 (3.073)
Test resultsX2 (10, 14,505) = 30.17, p = 0.001, Cramer’s V = 0.032
2. Installing fixtures and equipment to save waterGender *Mean1.581.521.541.54
Test resultsX2 (2, 14,505) = 6.86, p = 0.032, Cramer’s V = 0.022
Age ***Mean (SD)48.42 (18.45)49.12 (19.24)42.15 (16.40)43.01 (16.88)
Test resultsX2 (6, 14,505) = 249.60, p < 0.001, Cramer’s V = 0.093
Level of Education ***Mean (SD)3.30 (2.727)3.49 (2.908)4.36 (3.091)4.23 (3.073)
Test resultsX2 (10, 14,505) = 311.92, p < 0.001, Cramer’s V = 0.104
3. Changing the toilet for another with a saving tankGenderMean1.561.541.541.54
Test resultsX2 (2, 14,505) = 2.37, p = 0.306, Cramer’s V = 0.013
Age ***Mean (SD)47.36 (18.83)47.81 (19.06)42.27 (16.40)43.01 (16.88)
Test resultsX2 (6, 14,505) = 192.18, p < 0.001, Cramer’s V = 0.081
Level of Education ***Mean (SD)3.61 (2.916)3.92 (3.160)4.31 (3.072)4.23 (3.073)
Test resultsX2 (10, 14,505) = 172.84, p < 0.001, Cramer’s V = 0.077
4. Treating soapy waterGenderMean1.561.541.541.54
Test resultsX2 (2, 14,505) = 3.10, p = 0.212, Cramer’s V = 0.015
Age ***Mean (SD)45.55 (18.53)45.84 (18.41)42.27 (16.34)43.01 (16.88)
Test resultsX2 (6, 14,505) = 143.98, p < 0.001, Cramer’s V = 0.070
Level of Education ***Mean (SD)3.64 (2.863)3.90 (3.046)4.36 (3.092)4.23 (3.073)
Test resultsX2 (10, 14505) = 183.33, p < 0.001, Cramer’s V = 0.079
5. Turning off the faucet when soaping or brushing the teethGenderMean1.551.531.541.54
Test resultsX2 (2, 14,505) = 0.202, p = 0.904, Cramer’s V = 0.004
Age ***Mean (SD)44.68 (19.55)48.32 (18.95)42.89 (16.78)43.01 (16.88)
Test resultsX2 (6, 14,505) = 41.24, p < 0.001, Cramer’s V = 0.038
Level of Education ***Mean (SD)3.39 (2.807)2.86 (2.518)4.27 (3.078)4.23 (3.073)
Test resultsX2 (10, 14,505) = 125.30, p < 0.001, Cramer’s V = 0.066
6. Repairing water leaksGenderMean1.551.471.541.54
Test resultsX2 (2, 14,505) = 5.89, p = 0.053, Cramer’s V = 0.020
Age ***Mean (SD)42.29 (17.39)48.18 (19.41)42.92 (16.80)43.01 (16.88)
Test resultsX2 (6, 14,505) = 28.81, p < 0.001, Cramer’s V = 0.032
Level of Education ***Mean (SD)3.29 (2.824)3.22 (2.927)4.26 (3.073)4.23 (3.073)
Test resultsX2 (10, 14,505) = 115.28, p < 0.001, Cramer’s V = 0.063
7. Checking the water installations to avoid water leaksGenderMean1.551.491.541.54
Test resultsX2 (2, 14,505) = 2.753, p = 0.252, Cramer’s V = 0.014
Age ***Mean (SD)44.54 (18.90)48.02 (19.50)42.90 (16.79)43.01 (16.88)
Test resultsX2 (6, 14,505) = 32.68, p < 0.001, Cramer’s V = 0.034
Level of Education ***Mean (SD)3.12 (2.699)3.26 (2.954)4.26 (3.074)4.23 (3.073)
Test resultsX2 (10, 14,505) = 115.34, p < 0.001, Cramer’s V = 0.063
8. Checking the water bill to see the consumption amountGender *Mean1.541.501.541.54
Test resultsX2 (2, 14,505) = 6.917, p = 0.031, Cramer’s V = 0.022
Age ***Mean (SD)44.18 (18.57)46.99 (18.42)42.68 (16.68)43.01 (16.88)
Test resultsX2 (6, 14,505) = 60.12, p < 0.001, Cramer’s V = 0.046
Level of Education ***Mean (SD)3.29 (2.822)3.42 (2.795)4.31 (3.086)4.23 (3.073)
Test resultsX2 (10, 14,505) = 181.79, p < 0.001, Cramer’s V = 0.089
* = significant at the 0.05 level, ** = significant at the 0.01 level, *** = significant at the 0.001 level. Source: Authors based upon INEGI [53,54].
Table
Table 3. Comparing the general willingness to adopt water-saving measures among participants affected by climatic hazards and the others.
Table 3. Comparing the general willingness to adopt water-saving measures among participants affected by climatic hazards and the others.
Affected by Climatic Hazards during the Past YearTotal
YesNo
Opinions for adopting water-saving measuresDisagree = 1Count202614,23316,259
%13.4%14.1%14.0%
Indifferent = 2Count70050855785
%4.6%5.0%4.9%
Agree = 3Count12,40281,59493,996
%82.0%80.9%81.0%
TotalCount15,128100,912116,040
%100.0%100.0%100.0%
Mean (SD)2.69 (0.695)2.67 (0.710)2.67 (0.708)
Test ResultsX2 (2, 116,039) = 11.38, p = 0.003, Cramer’s V = 0.01
Note. Percentages and frequencies are based on accumulated total responses (eight times the number of households). Source: Authors based upon INEGI [53,54].

4. Results and Discussion

In the first step, we analyzed the demographic characteristics of the respondents, including gender, age, and level of education. Table 1 shows the demographic characteristics of the whole survey population, the participants who were recently affected by climatic hazards (from now on referred to as ACH) and the ones who were not (from now on referred to as NACH).
It can be seen from Table 1 that, although in general there were more women than men (ACH, NACH, and total), the involvement of men in ACH (47.3%, mean = 1.53, SD = 0.499) has increased in comparison to NACH (45.7%, mean = 1.54, SD = 0.498). However, the very close means and SDs make this assumption unclear, as the average values (concerning gender) for all groups show quite similar compositions. Also, in general, the individuals affected by climatic events are slightly younger (about one year) than others (ACH: mean = 42.2, SD = 15.82; NACH: mean = 43.13, SD = 17.03; total: mean = 43.01, SD = 16.88). Considering educational level, ACH includes more individuals with fewer education levels (mean = 2.18, SD = 1.412) than others (NACH: mean = 2.48, SD = 1.524; total: mean = 2.44, SD = 1.513). These outcomes are helpful in explaining the results of the following on the impacts of experiencing climatic events.

4.1. Associations with Demographic Characteristics

The following analysis explores the association between demographic characteristics and the participants’ willingness to adopt the eight surveyed water-saving measures (WSM). Table 2 illustrates which demographic characteristics are correlated with the participants’ willingness to adopt any of the eight water conservation techniques, and how significant these correlations are.
As can be seen above, age and educational level are significantly associated with willingness to adopt all the conservation measures. All significances are at the 0.001 level, except for the correlation between educational levels and the degree of agreement with the first measure, “paying more for water service from the public network”, which is significant at the 0.01 level. The situation is not the same for the gender category. Gender has a significant impact on three measures, namely, “paying more for water service from the public network” (p = 0.003), “installing fixtures and equipment to save water” (p = 0.032), and “checking the water bill to see the consumption amount” (p = 0.031).
It is noticeable that, in seven out of eight measures (WSM1, WSM2, WSM3, WSM4, WSM5, WSM7, WSM8), younger individuals are more likely to agree to uptake the saving measures. This finding is aligned with the results of the study by Russell and Knoeri (2020) [2] on the determinants of household water-saving behaviors and intention. However, according to Fielding et al. (2012) [18], there was a negative association between age and water-saving behavior. Unsurprisingly, for all conservation measures, more educated people agree more with the need to take suitable actions to contribute to water-saving. This finding is in line with the usual findings of previous research, which shows that higher educational levels can positively influence water-saving behaviors and willingness [15,26,30].
Regarding the impacts of gender, in the three WSMs (WSM1, WSM2, WSM8), although there is a common finding in the literature that women are more willing to consume less water and save more [26,28,30,56,57,58], our findings show that, in two measures (WSM1, WSM2), men are more likely to adopt saving actions.
In general, it can be said that the age and educational level, and, in some cases, the gender of participants are significantly associated with willingness to take actions to conserve water. It should be noted that all significant correlations have weak impacts considering their effect sizes (Cramer’s V values from 0.022 to 0.104). However, according to Ellis (2010) [59], small effects can be regarded as meaningful if they have huge repercussions, alter the perception of the likelihood for stronger outcomes, or compound into greater effects. We argue that, as we are dealing with freshwater consumption behaviors on a nationally representative scale for a large country, even weak effects can generate massive and meaningful differences and present practical significance. This approach can be seen in much of the previous research that links water consumption with behaviors (e.g., [28,30,60,61,62,63]).

4.2. Associations with the Recent Experience of Climatic Hazards

The first step of this stage of analysis is to see if, in general, there is an association between the experience of climatic hazards and the adoption of water-saving measures. Considering that there are eight WSMs in the questionnaire and there is no single question regarding the overall viewpoint of the participants regarding the adoption of water conservation behaviors, we merged the responses of all eight measures and then analyzed the accumulated frequencies, to represent all participants’ opinions in one variable. Table 3 presents these results and compares the two groups of households (the ones with the experience of a climatic hazard in the last year of answering the survey and the others without such experience). As the measures are combined into one variable, the numbers for this comparison are eight times the number of households for each cell. The percentages are based on these accumulated frequencies.
As seen in the table, the responses are more positive regarding the water-saving measures when there has been a recent climatic hazard experience. It is shown that ACH agrees more (1.1% more than NACH) with adopting the measures. The chi-square test results show that there is a statistically significant correlation (p = 0.003) found in opinions regarding the adoption of water measures between ACH (mean = 2.69, SD = 0.695) and NACH (mean = 2.67, SD = 0.710). However, there is a very weak effect size (Cramer’s V= 0.01).
On the one hand, our previous analysis illustrates that younger and less educated people more frequently reported the experience of natural hazards. Regarding gender, no clear assumption can be made (Table 1). On the other hand, young age, higher education, and male gender have positive correlations with the adoption of water conservation measures (Table 2). Therefore, it can be concluded that, while a lower age might be a positive influence in shaping the correlations between adopting WSMs and the experience of hazards, educational level plays a negative role and gender has no clear role. Therefore, it cannot be assumed that the association is triggered by these demographic characteristics. Thus, we confirm the H1 hypothesis, describing a significant positive correlation (with a small effect) between the direct experience of extreme climatic conditions and the willingness to adopt water-saving behaviors.
To gain more clarity about the confirmation of the H1 hypothesis and the impacts of natural hazards on households’ water-saving intentions, we carried out another two steps of analysis of the data. The first was to explore the difference between the eight WSMs. The second was to find out which climate events (flood, drought, etc.) have the greatest influence on the respondents’ opinions. Table 4 shows a summary of the first step. As can be seen, two out of eight WSMs were significantly correlated with the recent experience of natural hazards.
Although most participants (ACH or NACH) disagree with “paying more for water services”, this WSM is the one with the strongest significant association, with a p value < 0.001. This finding can have great importance, as this measure can be one of the most influential actions in the achievement of water security if water authorities and policymakers use the opportunity correctly. This outcome can be connected to the one found by Bergquist et al. (2019) [25]. In their analysis, they discovered that, after Hurricane Irma, survey respondents showed more negative emotions towards climate change and were more willing to pay higher taxes to prevent future hazards.
The other factor that is significantly associated with the experience of climate events is “installing fixtures and equipment to save water” (p = 0.009). This also can be considered a crucial measure to optimize domestic water use and to achieve household water security. It is said that water-efficient equipment can save 20 percent—at the minimum rate—more water in the residential sector [64]. Therefore, this is another factor that should be seriously considered by policymakers.
Table
Table 4. Associations between types of water-saving measures and groups of households affected/not affected by climate events.
Table 4. Associations between types of water-saving measures and groups of households affected/not affected by climate events.
Types of Water-Saving Measures Affected by Climatic Hazards during the Last Year
YesNoTotal
Paying more for water service from the public network ***DisagreeCount143910,23111,670
%76.1%81.1%80.5%
IndifferentCount127673800
%6.7%5.3%5.5%
AgreeCount32517102035
%17.2%13.6%14.0%
TotalCount189112,61414,505
%100.0%100.0%100.0%
Mean (SD)1.41 (0.766)1.32 (0.700)1.34 (0.710)
Test ResultsX2 (2, 14,505) = 26.26, p < 0.001, Cramer’s V = 0.043
Installing fixtures and equipment to save water **DisagreeCount1469851131
%7.7%7.8%7.8%
IndifferentCount72691763
%3.8%5.5%5.3%
AgreeCount167310,93812,611
%88.5%86.7%86.9%
TotalCount189112,61414,505
%100.0%100.0%100.0%
Mean (SD)2.81 (0.557)2.79 (0.568)2.79 (0.567)
Test ResultsX2 (2, 14,505) = 9.33, p = 0.009, Cramer’s V = 0.025
Changing the toilet for another with a saving tankDisagreeCount1369751111
%7.2%7.7%7.7%
IndifferentCount101805906
%5.3%6.4%6.2%
AgreeCount165410,83412,488
%87.5%85.9%86.1%
TotalCount18911261414505
%100.0%100.0%100.0%
Mean (SD)2.80 (0.550)2.79 (0.570)2.78 (0.568)
Test ResultsX2 (2, 14,505) = 3.95, p = 0.139, Cramer’s V = 0.016
Treating soapy waterDisagreeCount21014101620
%11.1%11.2%11.2%
IndifferentCount16913321501
%8.9%10.6%10.3%
AgreeCount1512987211384
%80.0%78.3%78.5%
TotalCount18911261414505
%100.0%100.0%100.0%
Mean (SD)2.69 (0.661)2.67 (0.667)2.67 (0.666)
Test ResultsX2 (2, 14,505) = 4.79, p = 0.091, Cramer’s V = 0.018
Turning off the faucet when soaping or brushing the teethDisagreeCount24150174
%1.3%1.2%1.2%
IndifferentCount44220264
%2.3%1.7%1.8%
AgreeCount182312,24414,067
%96.4%97.1%97.0%
TotalCount189112,61414,505
%100.0%100.0%100.0%
Mean (SD)2.95 (0.268)2.96 (0.252)2.96 (0.254)
Test ResultsX2 (2, 14,505) = 3.23, p = 0.199, Cramer’s V = 0.015
Repairing water leaksDisagreeCount17140157
%0.9%1.1%1.1%
IndifferentCount29240269
%1.5%1.9%1.9%
AgreeCount184512,23414,079
%97.6%97.0%97.1%
TotalCount189112,61414,505
%100.0%100.0%100.0%
Mean (SD)2.97 (0.224)2.96 (0.248)2.96 (0.245)
Test ResultsX2 (2, 14,505) = 1.94, p = 0.379, Cramer’s V = 0.012
Checking the water installations to avoid water leaksDisagreeCount20127147
%1.1%1.0%1.0%
IndifferentCount26231257
%1.4%1.8%1.8%
AgreeCount184512,25614,101
%97.6%97.2%97.2%
TotalCount189112,61414,505
%100.0%100.0%100.0%
Mean (SD)2.97 (0.234)2.96 (0.239)2.96 (0.238)
Test ResultsX2 (2, 14,505) = 2.00, p = 0.367, Cramer’s V = 0.012
Checking the water bill to see the consumption amountDisagreeCount34215249
%1.8%1.7%1.7%
IndifferentCount1328931025
%7.0%7.1%7.1%
AgreeCount172511,50613,231
%91.2%91.2%91.2%
TotalCount189112,61414,505
%100.0%100.0%100.0%
Mean (SD)2.89 (0.361)2.90 (0.358)2.90 (0.358)
Test ResultsX2 (2, 14,505) = 0.11, p = 0.948, Cramer’s V = 0.003
** = significant at the 0.01 level, *** = significant at the 0.001 level. Source: Authors based upon INEGI [53,54].
Considering the significant correlation between WSM1 and WSM2 and the experience of extreme events, in the last stage of our analysis, we decided to explore this in further detail. Table 5 describes this analysis. Due to the few available responses regarding “fire” and “landslide” events and the pre-requirements of the chi-square test for independence, we combined these two hazard sources into the “other” classification of hazards.
According to the results, two statistically significant correlations were observed. The first is between WSM1 and the recent experience of “drought” (p < 0.001), and the second describes the connection between WSM2 and the “flood” experience of the respondents (p < 0.001). The relationship between the occurrence of drought or water scarcity and water conservation behaviors and intentions was discovered by several previous studies throughout the world [16,17,19]. People’s risk-aversion behavior can be effectively shaped by their perception of water scarcity risks [65]. Residents have little motivation to modify their consumption patterns if they do not perceive a threat or risk in their area of residence [66]. Therefore, our outcome confirms previous findings linked to the experience of droughts and water shortages.
It has been previously shown that individuals with experience with floods reported more concern over climate change. These perceptual alterations were translated into a superior willingness to conserve energy to alleviate climate change impacts [24]. From this perspective, flooding can also be associated with other pro-environmental actions oriented to climate change adaptation, one of which is water conservation.
These results (associations between the experience of natural extreme events and willingness to adopt water-saving measures) suggest that highlighting the link between local climate hazards and water security can be a useful strategy for water authorities to promote water-saving behaviors. This is in line with the findings of Gilbertson et al. (2011) [17]. This requires, in turn, professional communication with the public about the climatic hazards and opportunities for water conservation. The role of demographic determinants can also guide local decision-makers to address the target groups more effectively, with a higher potential to increase the adoption of pro-environmental behaviors.
Table
Table 5. Associations between two water-saving measures and different types of climatic hazards.
Table 5. Associations between two water-saving measures and different types of climatic hazards.
Water-Saving MeasuresClimatic HazardAffected by Climatic Hazards during the Last Year
Yes No Total
Paying more for water service from the public networkDrought ***Mean (SD) 1.48 (0.798) 1.32 (0.700) 1.33 (0.705)
Test ResultsX2 (2, 13,169) = 31.50, p < 0.001, Cramer’s V = 0.049
FloodMean (SD) 1.36 (0.735) 1.32 (0.700) 1.33 (0.702)
Test ResultsX2 (2, 13,297) = 1.97, p = 0.374, Cramer’s V = 0.012
FreezeMean (SD) 1.46 (0.811) 1.32 (0.700) 1.33 (0.701)
Test ResultsX2 (2, 12,733) = 4.60, p = 0.100, Cramer’s V = 0.019
Hurricane or CycloneMean (SD) 1.42 (0.781) 1.32 (0.700) 1.33 (0.702)
Test ResultsX2 (2, 12,845) = 4.27, p = 0.118, Cramer’s V = 0.018
Fire, Landslide, OtherMean (SD) 1.37 (0.739) 1.32 (0.700) 1.33 (0.701)
Test ResultsX2 (2, 12,917) = 1.62, p = 0.445, Cramer’s V = 0.011
Installing fixtures and equipment to save waterDroughtMean (SD) 2.79 (0.579) 2.79 (0.568) 2.79 (0.568)
Test ResultsX2 (2, 13,169) = 2.59, p = 0.274, Cramer’s V = 0.014
Flood ***Mean (SD) 2.86 (0.482) 2.79 (0.568) 2.79 (0.564)
Test ResultsX2 (2, 13,297) = 19.01, p < 0.001, Cramer’s V = 0.038
FreezeMean (SD) 2.82 (0.520) 2.79 (0.568) 2.79 (0.568)
Test ResultsX2 (2, 12,733) = 0.90, p = 0.143, Cramer’s V = 0.016
Hurricane or CycloneMean (SD) 2.76 (0.604) 2.79 (0.568) 2.79 (0.569)
Test ResultsX2 (2, 12,845) = 0.54, p = 0.637, Cramer’s V = 0.008
Fire, Landslide, OtherMean (SD) 2.74 (0.635) 2.79 (0.568) 2.79 (570)
Test ResultsX2 (2, 12,917) = 3.37, p = 0.186, Cramer’s V = 0.016
*** = significant at the 0.001 level. Source: Authors based upon INEGI [53,54].

5. Concluding Remarks

Recognizing the impacts of climate hazards on water savings is a key means of understanding, required to uptake effective communication, as well as mitigation and adaptation initiatives. Our work contributes to this understanding by providing new pieces of knowledge, in a relatively data-poor country, on the association between the households’ willingness to adopt water conservation acts and the experience of multiple climatic hazards.
The results show that the experience of disasters positively influences households’ intentions to uptake water-saving behaviors, although, this effect is small. Although the demographic conditions (age, education, and, to a lower degree, gender) of households were found to be influential on their willingness degree (without considering the climate events), these factors do not affect the impact of climatic hazards on the households’ intentions. More precisely, we found that “paying more for water service from the public network” and “installing fixtures and equipment to save water” have significant associations with climatic events in general, and with the experience of “drought” and “flood” specifically.
These results are of key relevance for strategies oriented to reducing water demand, as is widely recognized in the water economics literature [13,67,68]. The literature makes it clear that, in practice, saving water could also be seen as a supply strategy. There is an additional highly relevant political implication. The revealed willingness to pay more for water reduces the political conflicts that usually come with raising rates [13]. This unpopular measure is common not only in Mexico but in several less industrialized countries.
Our findings emphasize the fact that not only the experiences of drought and water shortages may affect water-saving behaviors. Other extreme events (e.g., floods) also have the potential to do so. By using references to climatic disasters and extreme events, authorities may be able to more constructively communicate the risks of water-related challenges and climate change threats. These findings contain useful policy insights, specifically in water crises-prone regions, in Mexico and elsewhere.
We suggest that future studies expand the scope of this research and explore the possible causal associations between multiple natural climatic events and other environmental conservation behaviors and intentions, such as waste reduction or energy efficiency.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/su14105817/s1, Annex S1. The used (translated) questions and the possible choices extracted from the National Household Survey (ENH) and the Module on Households and Environment (MOHOMA). Annex S2. Original questionnaires used for the analysis (ENH 2017 and MOHOMA 2017).

Author Contributions

Conceptualization: M.K.; methodology: M.K. and M.S.; formal analysis and investigation: M.K., M.S. and C.N.-M.; writing—original draft preparation: M.K., M.S. and C.N.-M.; writing—review and editing: M.K., M.S., C.N.-M. and I.A.-B.; supervision: I.A.-B. All authors have read and agreed to the published version of the manuscript.

Funding

This research was carried out as a requirement for the doctoral studies of the first author, granted by the National Council of Science and Technology of Mexico (CONACYT–CVU: 1019583).

Institutional Review Board Statement

Ethical review and approval were waived for this study, as the used datasets and information are freely available in the public domain.

Informed Consent Statement

Not applicable.

Data Availability Statement

The responses to the ENH and MOHOMA questionnaires are publicly available on the official website of INEGI, Mexico [53,54].

Conflicts of Interest

The authors declare no conflict of interest.

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Sustainability 14 05817 g001 550
Figure 1. Degree of pressure on water resources of Mexico in the hydrological division. Degree of pressure refers to the percentage relationship between the volume of water granted and the volume of renewable water in 2020. Data from: [45].
Figure 1. Degree of pressure on water resources of Mexico in the hydrological division. Degree of pressure refers to the percentage relationship between the volume of water granted and the volume of renewable water in 2020. Data from: [45].
Sustainability 14 05817 g001
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Khodadad, M.; Sanei, M.; Narvaez-Montoya, C.; Aguilar-Barajas, I. Climatic Hazards and the Associated Impacts on Households’ Willingness to Adopt Water-Saving Measures: Evidence from Mexico. Sustainability 2022, 14, 5817. https://doi.org/10.3390/su14105817

AMA Style

Khodadad M, Sanei M, Narvaez-Montoya C, Aguilar-Barajas I. Climatic Hazards and the Associated Impacts on Households’ Willingness to Adopt Water-Saving Measures: Evidence from Mexico. Sustainability. 2022; 14(10):5817. https://doi.org/10.3390/su14105817

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Khodadad, Mina, Mohsen Sanei, Christian Narvaez-Montoya, and Ismael Aguilar-Barajas. 2022. "Climatic Hazards and the Associated Impacts on Households’ Willingness to Adopt Water-Saving Measures: Evidence from Mexico" Sustainability 14, no. 10: 5817. https://doi.org/10.3390/su14105817

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