Water resources development

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.

This research proposes an Infrastructure to model complex systems for hydrological modeling.
Currently, the three main hydrological packages are: i) SEAWAT (modeling groundwater flow); ii) HECRAS
(modeling surface water flow); iii) HEC-HMS (modeling atmospheric water flow). Each of these models is self-contained and has a different timescale and simulation speed. Consequently, any integrated model will only run as fast as the slowest of the models. This makes it difficult to provide reliable and dynamic information on water levels and water availability for a given geographical region in a timely manner. The goal of this research is to facilitate the integration of multiple hydrological models from different hydrological packages by applying Electronic Design Automation (EDA) methodologies, including System Level Design (SLD) methodology, SystemC-AMS language, Python language and libraries (numpy, Statsmodels, and ctypes). The EDA methodology brings in the additional advantage of significantly improved simulation speed. The Infrastructure to Model Complex Systems applications is
demonstrated using the following SEAWAT benchmark problems: i) Case 1; ii) Henry; iii) Elder problem.
Simulation results from the aforementioned benchmarks are analyzed and discussed. Lastly, future research
work is presented.

Water Resources (WR) agencies have recently shifted to holistic management approaches that combine the use of watersheds and ecoregions as complimentary tools. However, the classification of data is based on land used and land cover detection. In contrast, this research is concerned with inferring WR quality from the landscape using satellite imagery and aerial photography combined with collateral data. To conduct the study, three major procedures were devised: (1) construction of a classification system for regional coastal WR, (2) delineation of WR units based on the interpretation of water quality parameters (e.g. land use/cover, soil, vegetation, etc.), and (3) development and implementation of a water quality rating system. The results showed that this technique can be utilized effectively to monitor WR. The distribution of beneficial water quality was correlated with anthopogenic activities and modifications. Temporal events such as sea surface temperature had a short, but detrimental impact on water quality.

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.

Significant changes in climate and their impacts are now visible in various places around the globe and are expected to become more evident in the coming decades. For each increase in temperature, there are environmental and societal consequences. It has important implications for existing water resources systems as well as for future water resources planning and management. Water accounting (identifying, quantifying and reporting information of water flow in a system) is the first step towards formulating productive and sustainable water management strategies in a region. Thus, water balance models could be an empowering tool for water resource managers to prepare for and mitigate the effects of climate change on their local hydrologic resources. This thesis offers an insight into how such a tool can be used to assess and predict future stream flow trends in an effort to mitigate or manage any potential effects.

Water conservation initiatives seldom quantify the volume of water that is at stake in lawn watering. In many communities, including those in South Florida, outdoor water use, which includes lawn irrigation, is not metered separately from indoor water use and is indistinguishable from indoor water usage. A large number of residents use self supply non-potable wells for lawn irrigation that are not regulated by the South Florida Water Management District. The result is that residential lawn water use is difficult to account for and quantify. This thesis project addressed these difficulties by combining semistructured interviews, daily watering observations and irrigation system audits to ascertain how much public supply water and self supply (well) water was being used for residential lawn irrigation. The study also examined lawn watering practices and how factors such as: precipitation, the minimum plant needs of St. Augstinegrass, and how local watering restrictions influenced watering behavior.