A resilience methodology was implemented to assess the considered case studies. In Figs. 8 and 9, the tridimensional matrices for Hermosillo and Monterrey are shown, respectively. The functional services for water (m3), energy (MW), and food (Ton) for the case studies are presented in the corresponding matrices. Moreover, five different years were evaluated, which correspond to previous and future years. Because of the frequency of natural disasters in the case studies, the possible failures modes considered are hurricanes, freezing, and drought.
Then, each of the functional services was multiplied for the respective penalization cost (Table 8) for constructing the dimensional matrices (Table 9 and Table 10). For both cases, it can be observed that functional services vary through the years; however, these are the same for each of the possible failure modes. This way, a risk index associated with each of the possible failure modes was used. The indices were calculated based on the methodology established by CENAPRED (Jiménez et al., 2012). According to Tables 9 and 10, an increase in the projection of imposed costs of 41.52% and 43.10% can be observed, for the City of Hermosillo and Monterrey respectively, from 2019 to 2030. Although a decrease in energy costs is expected in the coming years due to the increase in the use of renewable energy (38.28% for both cities), the trend shows an increase in water and food costs, as well as in the number of functional services required due to population growth. The increase in the cost of water for Hermosillo is 22.33% and 20.40% for Monterrey, while the cost of food will increase around 15% for both cities.
Table 8
Penalization costs for Water-Energy-Food Nexus in different years
Year
|
City
|
Cost ($US/unit)
|
Water (m3)
|
Energy (MW)
|
Food (Ton)
|
2013
|
Hermosillo
|
1.378
|
47.0
|
289.0
|
Monterrey
|
0.643
|
47.0
|
278.0
|
2015
|
Hermosillo
|
1.464
|
48.8
|
312.0
|
Monterrey
|
0.724
|
48.8
|
289.5
|
2019
|
Hermosillo
|
1.836
|
47.8
|
340.5
|
Monterrey
|
0.809
|
47.8
|
335.0
|
2025
|
Hermosillo
|
2.017
|
34.1
|
365.3
|
Monterrey
|
0.891
|
34.1
|
357.8
|
2030
|
Hermosillo
|
2.246
|
29.5
|
391.1
|
Monterrey
|
0.974
|
29.5
|
386.3
|
Table 9
Bidimensional matrix for Hermosillo
2013
|
2015
|
2019
|
2025
|
2030
|
|
201,220,890
|
230,369,099
|
280,107,749
|
343,405,393
|
396,424,044
|
Drought
|
201,220,890
|
230,369,099
|
280,107,749
|
343,405,393
|
396,424,044
|
Low temp.
|
201,220,890
|
230,369,099
|
280,107,749
|
343,405,393
|
396,424,044
|
Hurricane
|
Table 10
Bidimensional matrix for Monterrey
2013
|
2015
|
2019
|
2025
|
2030
|
|
340,133,705
|
377,761,763
|
480,403,602
|
572,902,791
|
687,474,157
|
Drought
|
340,133,705
|
377,761,763
|
480,403,602
|
572,902,791
|
687,474,157
|
Low temp.
|
340,133,705
|
377,761,763
|
480,403,602
|
572,902,791
|
687,474,157
|
Hurricane
|
According to the methodology with which the indices were calculated, the risk levels do not vary significantly in the proposed years, even for the projections for future years. Therefore, the risk index for each of the case studies regarding each possible failure is the same throughout all the years. These indices are shown in Figs. 10 and 11, where VL is an exceptionally low risk, L is a low risk, M is a medium risk, H is a high risk, and VH is an extremely high risk.
Subsequently, the resilience indices were calculated for each of the case studies. As the risk indices do not vary through the selected years, only one resilience matrix for each case was calculated. For both cases, only medium to very high-level risks are considered. Table 11 presents the resilience indices obtained from the case study of Hermosillo, it can be observed that some of the resilience indices are equal to 1, which represents a scenario that can be completely replaced if any possible failure appears. However, in the event of a drought, there is a value of 0.85 of resilience index for a medium risk index (with a probability of 15% according to Fig. 10), which indicates that this natural phenomenon could have important consequences for the interrelation of the water-energy-food nexus. This implies an imposed cost of $US 42,016,162 for the year 2019 and a cost of $US 59,463,607 for 2030, to obtain the necessary nexus resources to satisfy the needs of the population. Similarly, lower values can be observed in the failure modes for low and very low-risk indices, but because they are low risks they are not considered.
Table 11
Resilience indices for Hermosillo
|
VL
|
L
|
M
|
H
|
VH
|
Hurricane
|
0.88
|
0.24
|
0.92
|
0.96
|
1.00
|
Low temp.
|
0.49
|
0.70
|
0.90
|
0.91
|
1.00
|
Drought
|
0.62
|
0.53
|
0.85
|
1.00
|
1.00
|
Table 12 presents the results of the case study of Monterrey, in this case, high resilience values for the case of hurricanes are presented, which indicates that this city will not present a major problem if any occurs (probability of 92% for very low risk). However, the occurrence of low temperatures or drought presents resilience values below 0.50, which indicates that these phenomena can drastically alter food and/or energy production, as well as the availability of water in this area. Besides, Monterrey presents a probability of 55% in medium-risk in case of scenarios with low temperature, and a probability of 56% in high risk in case of drought (Fig. 11). The imposed costs for Monterrey in 2019 in case of low temperature and drought are $US 264,221,981 and $US 269,026,017, respectively. While for the projection for the year 2030 are $US 378,110,787 in case of a low temperature, and $US 384,985,528 for a drought.
Table 12
Resilience indices for Monterrey
|
VL
|
L
|
M
|
H
|
VH
|
Hurricane
|
0.08
|
0.92
|
1.00
|
1.00
|
1.00
|
Low temp.
|
0.94
|
0.85
|
0.45
|
0.76
|
1.00
|
Drought
|
0.93
|
0.96
|
0.67
|
0.44
|
1.00
|
Both case studies present similar conditions concerning climate and resource scarcity, for both cities the main issue is related to the availability of water. Therefore, the more threatening factor for the security of the water-energy-food nexus is the intensification of droughts, a result of climatic changes due to global warming. The analyzed cities are of national importance; however, their current distribution and management systems of basic resources are not resilient to climate change disturbances, nor to the growth demanded by society, limiting sustainable development. The resilience index indicates that in future years the nexus will be vulnerable to extreme events if conditions do not change; then, actions to improve the integration of resources are essential. To overcome the low availability of water, water reuse is an effective way to reduce freshwater consumption and increase its accessibility, consequently, this information can be used to enhance the security of the nexus and its resilience. Furthermore, the optimization of water management in the agricultural sector is key to decrease water consumption. In this sense, different types of irrigation could help significantly, in addition, new forms of cultivation can contribute to the change in land use and the production of food that under normal conditions would not be achieved. Likewise, a balance in food production and consumption must be found to reduce food waste. On the other hand, renewable energy must be included in the energy sector, the incorporation of flexible energy systems to enhance the security and the resilience of the nexus is urgent. Therefore, the resources and climatic conditions of these cities must take advantage of to create an environment of a circular economy.
Addressing resilience is a key factor for a sustainable system, it has many contributions in the ecological, economic and social sectors, and it has been used in many practical and social applications. Practical applications of the assessment of resilience in the water-energy-food nexus are to design systems that could recover quickly from disturbances by performing corrective actions. In addition, through the study of the systems and the probability of disruptive events that may occur, preventing actions can be implemented to build resilience optimally and effectively as well as maximizing the security of resources at those conditions. The water-energy-food nexus has important societal applications, but even more, if the nexus thinking involves a resilience approach. For instance, the study of these concepts together is essential for the development of long-term policies that help to regulate the unsustainable consumption of resources and this way reduce the impacts of climate change. Furthermore, planning resilient systems could ensure access to sufficient resources, reduce the poverty percentage, improve living conditions and create job opportunities. All this implicates to improve human well-being.
The main limitation of the proposed approach is that it requires accurate data for the studied resources in the considered region; therefore, the seasonal analysis would enhance the accuracy but in cases where predictions of future years are made, there is linked a range of uncertainty in the results. In addition, the proposed model is designed for its application at a regional level, and its application to large scales could bring more uncertainty in the results. On the other hand, it is important to mention that the main uncertainties related to the model are in the hydrometeorological variables for the calculation of the risk indexes. Data available related to natural disasters usually corresponds to monthly average parameters, but this type of data is constantly changing; therefore, this implies that the uncertainty is linked to the model.