Water conservation

Evaluating trends of historical rainfall on a weekly and seasonal basis is needed
for optimizing the design and implementation of lawn water conservation strategies like
outdoor water restrictions. While “day of the week” water restrictions are a typical
strategy to limit the frequency and duration of urban lawn water use, they may not
necessarily result in more conservative behaviors from end-users. Because weekly
rainfall and local climate variables are seldom taken into account in water restriction
strategies, they are not connected to actual lawn water demand. However, since lawn
water demand is directly related to weekly rainfall totals, not to a particular number of
watering days per week, water restriction schedules have the potential to unintentionally
promote overwatering. This study investigated the weekly patterns of average seasonal rainfall and evapotranspiration in South Florida to determine the typical variability of
weekly net irrigation needs and found that typical wet season weekly rainfall often
provides a significant amount of water to meet the demand of residential lawns and
landscapes. This finding underscores opportunity to reduce supplemental overwatering
in residential landscapes if watering guidelines were modified to recognize seasonal
average weekly rainfall in this region
This study also tested a rainfall-based water conservation strategy to determine if
providing residents with information about how local rainfall could promote more
effective lawn watering behavior than just water restrictions alone. Experimental
households reduced lawn water use by up to 61% compared to the control group by the
end of the study. These results demonstrate that the neighborhood “rain-watered lawn”
signs helped experimental study group households become more aware of rainfall as the
primary input of water to their lawns. This study also investigated the role that lawn
irrigation from self-supplied sources plays in the urban lawn water demand and
investigates how the lawn water use and lawn watering behaviors of households that
source from self-supply differ from those who source from the public supply.

Water supply managers often look for easily applied metrics to determine where
water use can be curtailed. Unfortunately, the one-size-fits-all mentality comes with a
price of failing to fully grasp the consequences decision-making based on such metrics.
One issue that water supply regulator like to use is per capita water use. Per capital water use is often used to show where there is “wasted” water use, such as excessive irrigation. However such a metric may not be truly applicable depending on other economic factors. A heavily industrial area may add to apparent per capital use, but actually is an economic development activity. The focus of this project is to look at various water utilities and their per capital usage with the intent of discerning whether or not a better metric could be developed that consider the economic development activities of the region and water use.

Management of water resources has become more complex in recent years as a result of changing attitudes towards sustainability and the attribution of greater attention to environmental issues, especially under a scenario of water scarcity risk introduced by climate changes and anthropogenic pressures. This thesis addresses the conflicts in optimizing multi-purpose hydropower operations under an environment where objectives are often conflicting and uncertain. Mathematical programming formulations can be used to achieve flexible, feasible and optimal operation and planning solutions to satisfy expectations of multiple stake-holders, including regulatory environmental compliance and sustainability. Innovative optimization models using MINLP with binary variables, fuzzy set theory, partial constraint satisfaction and multi-objective formulations incorporating unit commitment problem and adaptive real-time operations are developed and applied to a real life case study. These methodologies provide advances and valuable insights on optimal operations of hydropower systems under uncertain decision making environments.