Mid-July Update

From my literature review I have been able to determine which factors are going to be most important in the groundwater potential of Chaguite. The majority of these determinations are based on a study done in the Theni District of India. The study was deemed highly successful in determining groundwater potential zones within the district and was done using minimal time, labor and money. The researchers found that slope and soil were most important in determining groundwater potential zones with drainage density and lineament density shortly after. Another study done in Iran tested 13 factors twice in 10 years to determine which factors had the greatest impact on the groundwater potential map and how groundwater potential zones change over time. The study found that qanat density (qanats are tunnels built underground to funnel water from the tops of hills to villages at the bottom) had the greatest impact on groundwater potential. Most studies I read did not include mechanism like wells or other water accessibility tools, but this study provides support for including current well depth and recharge data in my final raster.

My next step will be to determine the lithology, soil types and Land use within Chaquite and to find data on SPI and TWI. I will determine land use using supervised classification in ArcGIS and Lithology data for the entire globe is available on ArcGIS online. There are global data sets for soil, but I have found that a lot of countries do soil studies of their own, so I will try to fine soil data collected by the Nicaraguan government. I would also like to incorporate current well data into my analysis and my eventual final raster. One idea I have as to how to do this is simply convert the polygon shapefile into raster, but I believe It would be more useful to collect recharge data for each of the wells to determine how much water is actually available in each.

I was originally concerned that remote sensing would turn out a final raster that was not specific to just the community I have been studying, Chaguite. But, every case study I have read has been done on a study area about the same size, so I will clip the raster I have been using to just the outline of Chaguite in order to get a more focused final raster of just the community’s groundwater potential. I’m encouraged by what I have read about other case studies because this type of groundwater analysis has never been done in Central America, and most research does not discuss the implementation of the research results in projects to build wells, qanats, boreholes, or other water accessibility tools. I hope that my final raster can provide potential groundwater potential zones that can be accessed and tested to determine legitimacy of the model.

Factors Influencing Groundwater Potential
Factor Definition Influence High Potential Low Potential
Drainage The closeness of spacing of stream channels and the measure of the total length of a stream segment Medium Low DD High DD
Land Use Low/Unknown Unknown Unknown
Lithology Low/Unknown Unknown Unknown
Slope The maximum rate of change in value from each cell to its neighbors High Low Slope High Slop
Soil High Unknown Unknown
Lineament Represent zones of faulting and fracturing resulting in increased secondary porosity and permeability and provide pathways for groundwater movement Medium High LD Low LD
Rainfall Low/Unknown High RF Low RF
Qanat Density (Well Depth/Recharge) Qanat = A gently sloping underground channel or tunnel constructed to lead water from the interior of a hill to a village below High
Stream Power Index High/Medium
Topographic Wetness Index Low (but should still consider as a factor)
Fault Distance Inconsequential
Profile Curvature Inconsequential