This section presents the results of our scenario analyses. We first investigate the effects of different scenarios and policy interventions on the distribution of tanker water demand. This provides new insights into the role of the non-observed tanker water market in Amman’s water supply. It also helps us to understand the effects of the different scenarios on consumer surplus, which we examine in the subsequent set of analyses.
6.1. Analyses of Tanker Water Allocation
In order to find out more about water consumption patterns in Amman, we examine the allocation of tanker water supply. This aspect is of special interest, since there are only limited data about the tanker water market. Also, the tanker market might play an important role for short-term adaptation to a changing water supply situation. Thus, understanding the behavior of tanker water demand under different circumstances contributes to the development of a more comprehensive picture of Amman’s water allocation system as a whole.
Table 3 summarizes the distribution of tanker water among the various household agents in the model across different scenarios. In the baseline scenario, we find a total tanker water quantity of 38,451.163 m
3 per day, which would correspond to 14 million m
3 per year. At the assumed price, this translates into an average expenditure of 0.28 JD per household per day, or 25.62 JD in three months. Potter and Darmame [
28] found an average expenditure for tanker water across the three summer months of 19.57 JD for the Amman households in their survey, which is substantially lower. Considering the current scarcity of data about the partially informal tanker market and the resulting uncertainties involved in modeling it, obtaining an upper-bound estimate in the same order of magnitude as a survey outcome seems quite a reasonable result.
As we can see, tanker water supply is most relevant for households in the Qasabet Amman and Wadi Essier districts across scenarios. These two districts are similar with regards to their socio-economic structure, since Wadi Essier has a share of high-income households of 55% and Qasabet Amman has one of 44%. However, looking at the weekly supply durations, the finding seems puzzling, since Wadi Essier receives the lowest (38.712 h), but Qasabet Amman receives the highest mean duration (58.416 h). However, each district contains a number of agents, and the mean value might not tell us enough about the distribution of supply durations within a district. The tanker water quantity in the model is driven by those households whose supply durations are relatively short. Therefore, the median is a better indicator. Indeed, Qasabet Amman and Wadi Essier have the lowest supply durations for their median households with 31 and 34 h, respectively. In comparison, the districts Al-Jameaa, Al-Qwasmeh, and Marka have considerably higher supply durations of 48, 42, and 44 h for their median households.
We have already seen above that, as expected, the total tanker water quantity demanded is monotonically decreasing in the tanker water price. Scenarios 2 and 3 show that this also holds for each individual agent’s tanker quantity demanded. In contrast, the tanker water quantity shows an unexpected reaction to changes in the piped water tariff factor (Scenarios 4–6). It falls with increases in the piped water tariff factor across all agents that use tanker water. At first glance, this seems surprising, as piped water and tanker water are substitutes. To explain this, we have to consider the stepwise nature of the water price structure. In the baseline scenario, the agents using tanker water are the ones that have the weakest position in the competition for piped water, since they have by far the fewest hours of access to the piped water system per week. As the piped water tariff factor increases from 0.1 to 0.5 to 2, the number of higher-duration households not using their full potential to abstract water from the piped water system during the distribution algorithm increases from 38,286 to 79,011 to 84,119. This means that the available piped water becomes more evenly distributed, leaving less demand for tanker water. This effect of the piped water tariff on tanker water demand also indicates that the piped water tariff can even be employed to reduce the overall freshwater use when the piped water constraint is so low that all available piped water will be consumed. When the tariff factor is, for example, doubled (Scenario 6) total piped water consumption remains equal to the total piped water constraint, but due to the tanker water demand reduction, the overall freshwater use falls from 243,127.073 m3 per day to 239,039.540 m3.
Note that an additional factor contributing to tanker water consumption could be the storage constraint, requiring agents with a shorter supply duration to surpass more days with their storage capacity. However, in neither of the tariff scenarios do any agents reach their storage constraint. Therefore, in those scenarios, the mechanism that was described above drives tanker water demand.
Increasing the intermittency of piped water supply to twice its original value without changing the quantity of piped water available (Scenario 7) has the relatively straight-forward effect of increasing the total tanker water demand. However, surprisingly, all high-income agents actually reduce their tanker water consumption. Here, the storage constraint comes into play. In this scenario, about half of the total number of households (215,178) reaches their storage constraint. Consistent with the fact that low-income households have a much smaller storage capacity (3.12 m3) than high-income households (16.24 m3), all of these 215,178 households belong to the low-income class. In contrast, only 59,987 low-income households manage to avoid the storage constraint. Since low-income households reduce their piped water consumption, high-income households can replace expensive tanker water with cheaper piped water.
Table 3.
Tanker water allocations (m3/hhld./day).
Table 3.
Tanker water allocations (m3/hhld./day).
Scenario | Al-Jameaa (Low) | Al-Jameaa (High) | Al-Qwasmeh (Low) | Al-Qwasmeh (High) | Marka (Low) | Marka (High) | Qasabet Amman (Low) | Qasabet Amman (High) | Wadi Essier (Low) | Wadi Essier (High) | Total (m3/day) |
---|
1. Baseline | 0.057 | 0.064 | 0.066 | 0.077 | 0.065 | 0.080 | 0.100 | 0.113 | 0.099 | 0.11 | 38,451.163 |
2. = 1.925 | 0.076 | 0.091 | 0.089 | 0.106 | 0.092 | 0.109 | 0.123 | 0.137 | 0.126 | 0.147 | 50,938.482 |
3. = 7.7 | 0.044 | 0.051 | 0.048 | 0.058 | 0.046 | 0.055 | 0.08 | 0.091 | 0.081 | 0.091 | 29,453.320 |
4. = 0.1 | 0.068 | 0.082 | 0.080 | 0.096 | 0.083 | 0.098 | 0.112 | 0.125 | 0.113 | 0.133 | 45,953.797 |
5. = 0.5 | 0.058 | 0.068 | 0.069 | 0.081 | 0.069 | 0.084 | 0.103 | 0.115 | 0.101 | 0.115 | 39,952.404 |
6. = 2 | 0.051 | 0.059 | 0.058 | 0.069 | 0.054 | 0.068 | 0.092 | 0.104 | 0.092 | 0.103 | 34,363.630 |
7. Intermittency × 2 | 0.073 | 0.050 | 0.085 | 0.055 | 0.088 | 0.053 | 0.115 | 0.091 | 0.120 | 0.092 | 39,900.407 |
8. × 0.9 | 0.086 | 0.100 | 0.100 | 0.116 | 0.102 | 0.117 | 0.125 | 0.139 | 0.136 | 0.155 | 54,518.790 |
Table 4.
Consumer surplus difference to baseline (JD/hhld./day).
Table 4.
Consumer surplus difference to baseline (JD/hhld./day).
Scenario | Al-Jameaa (Low) | Al-Jameaa (High) | Al-Qwasmeh (Low) | Al-Qwasmeh (High) | Marka (Low) | Marka (High) | Qasabet Amman (Low) | Qasabet Amman (High) | Wadi Essier (Low) | Wadi Essier (High) | Total (JD/Day) |
---|
1. Baseline | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 | 0 |
2. = 1.925 | 0.122 | 0.146 | 0.145 | 0.173 | 0.148 | 0.178 | 0.212 | 0.237 | 0.210 | 0.243 | 84,179 |
3. = 7.7 | −0.191 | −0.219 | −0.215 | −0.255 | −0.206 | −0.253 | −0.341 | −0.387 | −0.343 | −0.383 | −128,046 |
4. = 0.1 | 0.019 | 0.018 | −0.009 | −0.015 | 0 | 0.003 | 0.017 | 0.018 | −0.028 | −0.033 | 1282 |
5. = 0.5 | 0.033 | 0.032 | 0.023 | 0.021 | 0.023 | 0.023 | 0.026 | 0.026 | 0.015 | 0.012 | 11,694 |
6. = 2 | −0.054 | −0.053 | −0.033 | −0.032 | −0.029 | −0.032 | −0.031 | −0.037 | −0.024 | −0.016 | −16,397 |
7. Intermittency × 2 | −0.072 | 0.084 | −0.084 | 0.103 | −0.080 | 0.111 | −0.061 | 0.086 | −0.091 | 0.107 | −2292 |
8. × 0.9 | −0.116 | −0.123 | −0.140 | −0.152 | −0.128 | −0.130 | −0.100 | −0.107 | −0.147 | −0.154 | −60,474 |
Finally, in Scenario 8, we analyze a situation where the overall piped water availability drops by 10%, representing a significant shortage. In this context, we also analyzed the effects of a simultaneous doubling of the intermittency factor, since such a severe water shortage might be answered by a stricter rationing scheme. This, however, did not change the results in any way. The reasons why intermittency did not have an added effect here are twofold. Firstly, the storage constraints, which could usually become binding under increased intermittency, were not reached, since the greater overall shortage prevented storages from being completely filled. Secondly, the halving of all supply durations preserved the relative power of the different agents in competing for piped water. Therefore, the distribution also did not change. Since the results for both scenarios are the same, this scenario can be read as either a pure piped-water-shortage scenario or as a piped-water-shortage-plus-intermittent-supply scenario. In either case, the scenario increases the pressure on the overall system, causing all agents to consume some quantity of tanker water. The geographical distribution of this tanker water demand is similar for high- and low-income households.
6.2. Analyses of Consumer Surplus Impacts
We evaluate the impacts of the different scenarios by calculating the consumer surplus effects they have on the different household types (see
Table 4 and
Figure 5). As we will see, the main factor driving consumer surplus development in the different scenarios is the fact that the different districts have different distributions of supply durations and different shares of high-income households, which have a higher water demand and a larger storage capacity.
Increasing the tanker water price (from Scenario 2 to 1, and from Scenario 1 to 3) has an unambiguously negative effect on consumer surplus across all agents using tanker water. This result is a natural consequence of the fact that, to these agents, the tanker price is the marginal price, which directly determines their demand quantity. Increasing this price lowers their tanker water consumption without affecting their piped water consumption. The resulting decrease in the consumption quantity and the increase in the overall water expenditure uniformly reduce their consumer surplus. The consumer surplus of those agents not using tanker water is not affected in any way. Al-Jameaa and the low-income households in Al Qwasmeh and Marka are affected the least. Qasabet Amman and Wadi Essier, which are most strongly reliant on tanker water, naturally see the strongest decreases in consumer surplus.
Tariff changes (Scenarios 4–6), on the other hand, can have more interesting effects. Generally in the range from 2 to 0.5, decreases in the tariff factor seem to have unambiguously positive impacts. However, as the tariff factor is further decreased to 0.1, the total consumer surplus decreases again, and Al-Qwasmeh and Wadi Essier experience strong negative effects. This is related to the explanation for the effect of the piped water tariff factor on tanker water consumption. In the baseline scenario, not all of the households with long supply durations use the full leverage they have on the piped water system, since they are already satisfied at a quantity below their potential maximum system abstraction. As the price falls, more and more high-duration households start exploiting their full leverage, creating an increasingly unequal water distribution (see
Section 6.1). Al-Qwasmeh and Wadi Essier have the lowest average supply durations and, thus, low leverage in the distribution, causing them to end up with substantially less piped water than in the baseline scenario. The marginal benefit that this water provides to the high-duration households, however, tends to be lower than average, and the prices they pay belong to increasingly expensive tariff blocks. Therefore, total consumer surplus falls again, and a seemingly unambiguous policy creates a geographical pattern of winners and losers.
Figure 5.
GIS maps showing average consumer surplus deviations from the baseline value due to changes in the piped water tariff and intermittency factors for households in different districts and income groups. Blue = gain; red = loss; darker colors indicate higher deviations from the baseline values, measured on a log-scale.
Figure 5.
GIS maps showing average consumer surplus deviations from the baseline value due to changes in the piped water tariff and intermittency factors for households in different districts and income groups. Blue = gain; red = loss; darker colors indicate higher deviations from the baseline values, measured on a log-scale.
Increasing supply intermittency (Scenario 7) also creates winners and losers, though not differentiated by district, but by income class. The effects of this scenario are almost a zero-sum game and hardly as small as they seem. While the total consumer surplus difference is −2292 JD per day, high-income households gain a total of 18,905.556 JD per day and low-income households lose 21,197.531 JD per day. The reason is again the fact mentioned in
Section 6.1: that most low-income households start to reach their storage constraint, switching to tanker water and thus freeing up piped water for the high-income households. Interestingly, reducing intermittency by half has no effect. The explanation for this is that, in this case as well as in the baseline, no storage constraints are met. This means that all households are able to store enough water to satisfy their demands throughout the supply breaks.
Finally, decreasing the overall availability in the piped water system (Scenario 8) naturally leads to a uniform consumer surplus loss across all agents. The decreased availability of relatively cheap piped water decreases the overall water consumption quantity and increases expenditure. This result, however, does not allow us to draw conclusions with regard to the overall welfare effect of decreasing the total water supply quantity. Since the model does not include the cost of supplying water, its implications are limited to the distribution of benefits from water consumption.