6.6 River, Urban, Farm
103
case presented here, questionnaires were developed and two groups, namely, farmers
and managers were consulted and the results helped to set the numbers assumed for
various variables of the Sefficiency indicators. These crude numbers can serve as
initial data that through years can get closer to reality, particularly if smart data
gathering technologies are used.
Finally, allocating water to multiple users under uncertainty should be the norm.
To develop scenarios, various models, including probabilistic, stochastic and fuzzy
methods have been used. For example, Loucks and Van Beek (2005) utilize the
Monte Carlo simulation in order to distribute the water of a river among three users
according to a number of policies, including a minimum amount of water in the
river. In such cases, Sefficiency can be applied as explained for Kano River in order
to understand the performance of all the allocations together.
6.7 Trade and Water Footprint
The idea of Water Footprint (WF) was first coined by the late Hoekstra (2003) and
then the Water Footprint Network (WFN) developed a methodology in order to
implement it in various circumstances (Hoekstra et al. 2011). WFN defined footprint
as a volumetric metric that was different from its traditional meaning of impact metric
that had been employed by the life-cycle assessment (LCA) community, which later
developed its own water footprint guidelines (ISO 2014) in order to help LCA in its
impact analyses.
Throughout the last decade, many developments made WF globally famous hence
attracting criticisms, which in the most part were not complete nor consistent. Haie
et al. (2018) refuted almost all those criticisms in six categories and employed Sefficiency to highlight a solution for the third phase of the WF methodology - sustainability assessment (Hoekstra et al. 2011). To demonstrate our solution, we utilized
an example put forth by one of the water economists in criticising WF. This is briefly
presented here and we encourage those interested to go to Haie et al. (2018), which
is freely available for download.
According to WFN, WF is the sum of blue, green and/or grey water footprints
(Hoekstra et al. 2011). In Sefficiency terminology, blue and green WF is Consumption
and grey WF may be assumed to be R nq (Sect. 2.5). If this assumption is reasonable
it means that WF = C + (1 − W qR ) R = I − R q . Comparing this expression with
that of TUF q of Eq. 2.5) we notice that in practice WF is greater than TUF q , which
we propose to be the real value of water footprint. The reason for this discrepancy is
that WF, contrary to TUF q , was not developed through a foundational theory and a
consequent solid approach as was done in this book.
For this example, data for grey water is not given making WF equal to Consumption while ignoring pollution. The example compares countries A and B (Fig. 6.5)
that trade cotton and wheat. Country A is relatively water scarce and country B has
a worse climate. The irrigation requirements of the crops and their output prices are
103
case presented here, questionnaires were developed and two groups, namely, farmers
and managers were consulted and the results helped to set the numbers assumed for
various variables of the Sefficiency indicators. These crude numbers can serve as
initial data that through years can get closer to reality, particularly if smart data
gathering technologies are used.
Finally, allocating water to multiple users under uncertainty should be the norm.
To develop scenarios, various models, including probabilistic, stochastic and fuzzy
methods have been used. For example, Loucks and Van Beek (2005) utilize the
Monte Carlo simulation in order to distribute the water of a river among three users
according to a number of policies, including a minimum amount of water in the
river. In such cases, Sefficiency can be applied as explained for Kano River in order
to understand the performance of all the allocations together.
6.7 Trade and Water Footprint
The idea of Water Footprint (WF) was first coined by the late Hoekstra (2003) and
then the Water Footprint Network (WFN) developed a methodology in order to
implement it in various circumstances (Hoekstra et al. 2011). WFN defined footprint
as a volumetric metric that was different from its traditional meaning of impact metric
that had been employed by the life-cycle assessment (LCA) community, which later
developed its own water footprint guidelines (ISO 2014) in order to help LCA in its
impact analyses.
Throughout the last decade, many developments made WF globally famous hence
attracting criticisms, which in the most part were not complete nor consistent. Haie
et al. (2018) refuted almost all those criticisms in six categories and employed Sefficiency to highlight a solution for the third phase of the WF methodology - sustainability assessment (Hoekstra et al. 2011). To demonstrate our solution, we utilized
an example put forth by one of the water economists in criticising WF. This is briefly
presented here and we encourage those interested to go to Haie et al. (2018), which
is freely available for download.
According to WFN, WF is the sum of blue, green and/or grey water footprints
(Hoekstra et al. 2011). In Sefficiency terminology, blue and green WF is Consumption
and grey WF may be assumed to be R nq (Sect. 2.5). If this assumption is reasonable
it means that WF = C + (1 − W qR ) R = I − R q . Comparing this expression with
that of TUF q of Eq. 2.5) we notice that in practice WF is greater than TUF q , which
we propose to be the real value of water footprint. The reason for this discrepancy is
that WF, contrary to TUF q , was not developed through a foundational theory and a
consequent solid approach as was done in this book.
For this example, data for grey water is not given making WF equal to Consumption while ignoring pollution. The example compares countries A and B (Fig. 6.5)
that trade cotton and wheat. Country A is relatively water scarce and country B has
a worse climate. The irrigation requirements of the crops and their output prices are