Applied Economics Ph.D. Candidate
Water and sanitation
I have wide experience working in water and sanitation topics from a poverty perspective. Also using GIS techniques.
The MNWOO package is an advanced quantitative data tool. This quantitative tool has two major functions. The first one is to describe the data that is collected by MNWOO. The second one is to provide socio-economic and nitrate information for future places where data collection are planned to be held. This tool takes information from three main sources: i) socio-economic information from the most updated American Community Survey; ii) nitrate information data which was obtained from the Minnesota Department of Natural Resources (2023); and iii) private well owners’ information collected by MNWOO.
Software: R, ArcGIS, QGis, Git.
Basin upstream and downstream links in Colombia
Water quality of a given municipality depends on water quality of municipalities located upstream within the same river network. To account for this relationship in my studies, I developed an expected water quality level index that integrates the water quality of the municipalities upstream from a target municipality using GIS techniques.
To develop this index, I first identify the adjacent downstream micro-watersheds belonging to every micro-watershed using the watershed information provided by the WorldWide Organization. Once the downstream connections across all micro-watersheds are known, it is possible to identify which micro-watersheds are upstream of a target micro-watershed. Then, I made a spatial join to know which municipalities belong to each micro-watershed. With all this information what I have at the end is, for each municipality, the whole range of upstream municipalities and their corresponding water quality.
Software: R, ArcGIS, QGis, Git.
Water efficient investment simulations
In this project I work together with Dr. Ahmed Rashid El-khattabi to find optimal levels of investment in water treatment plants. For this, we use microsimulations of different levels of optimal investment using as reference water quality in Colombia.
Software: Stata, R, ArcGIS, QGis.
