There are 148 rivers in the world flowing through two countries, 30 through three, nine through four and 13 through five or more.1 Some notable examples are:2
In the international law, there are several conflicting views on the property rights to the river waters.5
Kilgour and Dinar were the first to suggest a theoretical model for efficient water sharing.6
Without cooperation, each country maximizes its individual utility. So if a country is an insatiable agent (its benefit function is always increasing), it will consume all the water that enters its region. This may be inefficient. For example, suppose there are two countries with the following benefit functions:
The inflow is Q 1 = 2 , Q 2 = 0 {\displaystyle Q_{1}=2,Q_{2}=0} . Without cooperation, country 1 will consume 2 units and country 2 will have 0 units: q 1 = 2 , q 2 = 0 {\displaystyle q_{1}=2,q_{2}=0} . Then, the benefits will be u 1 = b 1 = 2 , u 2 = b 2 = 0 {\displaystyle u_{1}=b_{1}={\sqrt {2}},u_{2}=b_{2}=0} . This is not Pareto efficient: it is possible to allocate 1 unit of water to each country: q 1 = q 2 = 1 {\displaystyle q_{1}=q_{2}=1} , and transfer e.g. 0.5 {\displaystyle 0.5} units of money from country 2 to country 1. Then, the utilities will be u 1 = 1.5 , u 2 = 0.5 {\displaystyle u_{1}=1.5,u_{2}=0.5} which are better for both countries.7
Because preferences are quasi-linear, an allocation is Pareto-efficient if-and-only-if it maximizes the sum of all agents' benefits and wastes no money. Under the assumption that benefit functions are strictly concave, there is a unique optimal allocation. It structure is simple. Intuitively, the optimal allocation should equalize the marginal benefits of all countries (as in the above example). However, this may be impossible because of the structure of the river: the upstream countries do not have access to downstream waters. For example, in the above two-country example, if the inflow is Q 1 = 0.5 , Q 2 = 1.5 {\displaystyle Q_{1}=0.5,Q_{2}=1.5} , then it is not possible to equalize the marginal benefits, and the optimal allocation is to let each country consume its own water: q 1 = 0.5 , q 2 = 1.5 {\displaystyle q_{1}=0.5,q_{2}=1.5} .
Therefore, in the optimal allocation, the marginal benefits are weakly decreasing. The countries are divided to consecutive groups, from upstream to downstream. In each group, the marginal benefit is the same, and between groups, the marginal benefit is decreasing.8
The possibility of calculating an optimal allocation allows much more flexibility in water-sharing agreements. Instead of agreeing in advance on fixed water quantities, it is possible to adjust the quantities to the actual amount of water that flows through the river each year. The utility of such flexible agreements has been demonstrated by simulations based on historical of the Ganges flow. The social welfare when using the flexible agreement is always higher than when using the optimal fixed agreement, but the increase is especially significant in times of drought, when the flow is below the average.9
Calculating the efficient water allocation is only the first step in solving a river-sharing problem. The second step is calculating monetary transfers that will incentivize countries to cooperate with the efficient allocation. What monetary transfer vector should be chosen? Ambec and Sprumont10 study this question using axioms from cooperative game theory.
According to the ATS doctrine, each country has full rights to the water in its region. Therefore, the monetary payments should guarantee to each country at least the utility-level that it could attain on its own. With non-satiable countries, this level is at least b i ( Q i ) {\displaystyle b_{i}(Q_{i})} . Moreover, we should guarantee to each coalition of countries, at least the utility-level that they could attain by the optimal allocation among the countries in the coalition. This implies a lower bound on the utility of each coalition, called the core lower bound.
According to the UTI doctrine, each country has rights to all water in its region and upstream. These rights are not compatible since their sum is above the total amount of water. However, these rights define an upper bound - the largest utility that a country can hope for. This is the utility it could get alone, if there were no other countries upstream: b i ( ∑ j = 1 i Q i ) {\displaystyle b_{i}(\sum _{j=1}^{i}Q_{i})} . Moreover, the aspiration level of each coalition of countries is the highest utility-level it could attain in the absence of the other countries. This implies an upper bound on the utility of each coalition, called the aspiration upper bound.
There is at most one welfare-distribution that satisfies both the core-lower-bound and the aspiration-upper-bound: it is the downstream incremental distribution. The welfare of each country i {\displaystyle i} should be the stand-alone value of the coalition { 1 , … , i } {\displaystyle \{1,\ldots ,i\}} minus the stand-alone value of the coalition { 1 , … , i − 1 } {\displaystyle \{1,\ldots ,i-1\}} .
When the benefit functions of all countries are non-satiable, the downstream-incremental-distribution indeed satisfies both the core-lower-bounds and the aspiration-upper-bounds. Hence, this allocation scheme can be seen as a reasonable compromise between the doctrines of ATS and UTI.11
When the benefit functions are satiable, new coalitional considerations come into play. These are best illustrated by an example.
Suppose there are three countries. Countries 1 and 3 are in a coalition. Country 1 wants to sell water to country 3 in order to increase their group welfare. If country 2 is non-satiable, then 1 cannot leave water to 3, since it will be entirely consumed by 2 along the way. So 1 must consume all its water. In contrast, if country 2 is satiable (and this fact is common knowledge), then it may be worthwhile for 1 to leave some water to 3, even if some of it will be consumed by 2. This increases the welfare of the coalition, but also the welfare of 2. Thus, cooperation is helpful not only for the cooperating countries, but also for the non-cooperating countries!12
With satiable countries, each coalition has two different core-lower-bounds:
As illustrated above, the cooperative core-lower-bound is higher than the non-cooperative core-lower-bound.
The non-cooperative-core is non-empty. Moreover, the downstream-incremental-distribution is the unique solution that satisfies both the non-cooperative-core-lower-bounds and the aspiration-upper-bound.
However, the cooperative-core may be empty: there might be no allocation that satisfies the cooperative-core-lower-bound.13 Intuitively, it is harder to attain stable agreements, since middle countries might "free-ride" agreements by downstream and upstream countries.14
A river carries not only water but also pollutants coming from agricultural, biological and industrial waste. River pollution is a negative externality: when an upstream country pollutes a river, this creates external cleaning costs for downstream countries. This externality may result in over-pollution by the upstream countries.15 Theoretically, by the Coase theorem, we could expect the countries to negotiate and achieve a deal in which polluting countries will agree to reduce the level of pollution for an appropriate monetary compensation. However, in practice this does not always happen.
Evidence from various international rivers shows that, at water quality monitoring stations immediately upstream of international borders, the pollution levels are more than 40% higher than the average levels at control stations.16 This may imply that countries do not cooperate for pollution reduction, and the reason for this may be the unclearness in property rights.17
See 18 and 19 and 20 for other empirical studies.
Dong, Ni, Wang and Meidan Sun21: 3.4 discuss the Baiyang Lake, which was polluted by a tree of 13 counties and townships. To clean the river and its sources, 13 wastewater treatment plants were built in the region. The authors discuss different theoretic models for sharing the costs of these buildings among the townships and counties, but mention that at the end the costs were not shared but rather paid by the Baoding municipal government, since the polluters did not have an incentive to pay.
Hophmayer-Tokich and Kliot22 present two case studies from Israel where municipalities who suffer from water pollution initiated cooperation on wastewater treatment with upstream polluters. The findings suggest that regional cooperation can be an efficient tool in promoting advanced wastewater treatment, and has several advantages: an efficient use of limited resources (financial and land); balancing disparities between municipalities (size, socio-economic features, consciousness and ability of local leaders); and reducing spillover effects. However, some problems were reported in both cases and should be addressed.
Several theoretical models were proposed for the problem.
Emissions trading is a market-based approach to attain an efficient pollution allocation. It is applicable to general pollution settings; river pollution is a special case. As an example, Montgomery23 studies a model with n {\displaystyle n} agents each of which emits e i {\displaystyle e_{i}} pollutants, and m {\displaystyle m} locations each of which suffers pollution q i {\displaystyle q_{i}} which is a linear combination of the emissions. The relation between e {\displaystyle e} and q {\displaystyle q} is given by a diffusion matrix H {\displaystyle H} , such that: q = H ⋅ e {\displaystyle q=H\cdot e} . In the special case of a linear river presented above, we have m = n {\displaystyle m=n} , and H {\displaystyle H} is a matrix with a triangle of ones.
Efficiency is attained by permitting free trade in licenses. Two kinds of licenses are studied:
In both markets, free trade can lead to an efficient outcome. However, the market in pollution-licenses is more widely applicable than the market in emission-licenses.
There are several difficulties with the market approach, such as: how should the initial allocation of licenses be determined? How should the final allocation of licenses be enforced? See Emissions trading for more details.
Laan and Moes (2012)24 describe the polluted-river situation as follows.
Under the above assumptions, there exists a unique optimal emission-vector, in which the social welfare (the sum of benefits minus the sum of costs) is maximized.
There also exists a unique Nash equilibrium emission-vector, in which each country produces the emission best for it given the emissions of the others. The total amount of emission ∑ i e i {\displaystyle \sum _{i}e_{i}} in equilibrium is strictly higher than in the optimal situation, in accordance with the empirical findings of Sigman.25
For example, suppose there are two countries with the following benefit functions:
The socially-optimal levels are e 1 = 0.1621 , e 2 = 0.2968 {\displaystyle e_{1}=0.1621,e_{2}=0.2968} , and the utilities are u 1 = 0.376 , u 2 = 0.334 {\displaystyle u_{1}=0.376,u_{2}=0.334} . The Nash equilibrium levels are e 1 = 0.3969 , e 2 = 0.1847 {\displaystyle e_{1}=0.3969,e_{2}=0.1847} , and the utilities (benefit minus cost) are u 1 = 0.473 , u 2 = 0.092 {\displaystyle u_{1}=0.473,u_{2}=0.092} . In equilibrium, the upstream country 1 over-pollutes; this improves its own utility but harms the utility of the downstream country 2.26
The main question of interest is: how to make countries reduce pollution to its optimal level? Several solutions have been proposed.
The cooperative approach deals directly with pollution levels (rather than licenses). The goal is to find monetary transfers that will make it profitable to agents to cooperate and implement the efficient pollution level.
Gengenbach and Weikard and Ansink27 focus on the stability of voluntary coalitions of countries, that cooperate for pollution-reduction.
van-der-Laan and Moes28 focus on property rights and the distribution of the gain in social welfare that arises when countries along an international river switch from no cooperation on pollution levels to full cooperation: It is possible to attain the efficient pollution levels by monetary payments. The monetary payments depend on property rights:
This model can be generalized to rivers that are not linear but have a tree-like topology.
1. Dong, Ni and Wang30 (extending a previous work by Ni and Wang31) assume each agent i {\displaystyle i} has an exogenously given cost c i {\displaystyle c_{i}} , caused by the need to clean the river to match environmental standards. This cost is caused by the pollution of the agent itself and all agents upstream to it. The goal is to charge each agent i a vector of payments x i j {\displaystyle x_{ij}} such that c j = ∑ i x i j {\displaystyle c_{j}=\sum _{i}x_{ij}} , i.e., the payments of all agents for region j cover the cost of cleaning it.
They suggest three rules for dividing the total costs of pollution among the agents:
Each of these methods can be characterized by some axioms: additivity, efficiency (the payments exactly cover the costs), no blind costs (an agent with zero costs should pay zero - since he does not pollute), independence of upstream/downstream costs, upstream/downstream symmetry, and independence of irrelevant costs. The latter axiom is relevant for non-linear river trees, in which waters from various sources flow into a common lake. It means that the payments by agents in two different branches of the tree should be independent of each other's costs.
In the above models, pollution levels are not specified. Hence, their methods do not reflect the different responsibility of each region in producing the pollution.
2. Alcalde-Unzu, Gomez-Rua and Molis33 suggest a different rule for cost-sharing, that does take into account the different pollution-production. The underlying idea is that each agent should pay for the pollution it emits. However, the emission levels are not known - only the cleaning-costs c i {\displaystyle c_{i}} are known. The emission levels could be calculated from the cleaning costs using the transfer rate t (a number in [0,1]), as follows:
V i ( t , c 1 , … , c n ) = { c i 1 − t if i = 1 c i 1 − t − c i − 1 1 − t t if i = 2 , … , n − 1 c i − c i − 1 1 − t t if i = n {\displaystyle V_{i}(t,c_{1},\ldots ,c_{n})={\begin{cases}{c_{i} \over 1-t}&{\text{if }}i=1\\{c_{i} \over 1-t}-{c_{i-1} \over 1-t}t&{\text{if }}i=2,\ldots ,n-1\\c_{i}-{c_{i-1} \over 1-t}t&{\text{if }}i=n\end{cases}}}
However, usually t is not known accurately. Upper and lower bounds on t can be estimated from the vector of cleaning-costs. Based on these bounds, it is possible to calculate bounds on the responsibility of upstream agents. Their principles for cost-sharing are:
The rule characterized by these principles is called the Upstream Responsibility (UR) rule: it estimates the responsibility of each agent using expected value of the transfer-rate, and charges each agent according to its estimated responsibility.
In a further study34 they present a different rule called the Expected Upstream Responsibility (EUR) rule: it estimate the expected responsibility of each agent taking the transfer-rate as a random variable, and charges each agent according to its estimated expected responsibility. The two rules are different because the responsibility is a non-linear function of t. In particular, the UR rule is better for upstream countries (it charges them less), and the EUR rule is better for downstream countries.
The UR rule is incentive compatible: it incentivizes countries to reduce their pollution since this always leads to reduced payment. In contrast, the EUR rule might cause a perverse incentive: a country might pay less by polluting more, due to the effect on the estimated transfer rate.
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See Jordan River#Importance as a water source /wiki/Jordan_River#Importance_as_a_water_source ↩
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