N. De la Paz Ruiz (Nestor)

He is currently developing research on Spatio-temporal modelling of domestic wastewater variations for sanitation and health. As a former consultant at UNU-FLORES (Dresden, Germany), Mr. De la Paz developed tasks applying transdisciplinary approaches with a perspective on Geomatics, sustainability, and integrated water management.

During his postgraduate studies at CentroGeo (Mexico City), Mr. De la Paz has participated in applied research to address social needs in the design, development, and implementation of Geomatics solutions supported by Geospatial Information Systems technologies and spatial analysis.

Likewise, his current interest is focused on modelling and monitoring systems on water quality, environment, and health with ABM and ML models.

Expertise

• Earth and Planetary Sciences

  • Implication
  • Variability
  • Efficiency
  • Modeling
  • Waste Water
  • Datum

• Social Sciences

  • Population Census
  • Statistical Dispersion

Organisations

Worldwide, there is a lack of Domestic Wastewater (DWW) Quality and Quantity (QQ) models and data to help decision-makers to improve sanitation and health. Modelling DWWQQ variations with a spatiotemporal approach can yield new knowledge and promotes the study of DWW. However, day-to-day variations of DWW at high spatial resolutions (e.g., neighborhoods) are hard to model. Data on DWWQQ variations (in space and time) is rarely monitored and mapped across neighborhoods. DWWQQ variations are influenced by hours of using toilets, taking showers, using kitchens, cleaning activities, chemical products used by people, people’s diet, etc., and the combination of all these factors are specific to each household.

The topic of the current proposal can be mistakenly assigned to the field of water sciences. The truth is that there is no unique and well-defined scientific field for this transdisciplinary research. This proposal combines an approach of spatiotemporal analytics, wastewater (WW) characterization, artificial intelligence with ML, complex systems with ABM, and the perspective of the empiric knowledge from local stakeholders.

Publications

Research profiles

Master in Geomatics

Address

University of Twente

Langezijds (building no. 19)
Hallenweg 8
7522 NH Enschede
Netherlands

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Organisations