Meet Our Community Collaborators: Monica C.


Community Programs Specialist, Chino Basin Water Conservation District

Monica works for our Operation Smart Water project which aims to find ways to efficiently use water for plant life during time of water droughts, while also studying how watering plants can work with and against environmental factors to provide air cooling effects.

Monica photographed leading a community event with gardeners

What is your role in Operation Smart Water (OSW)? /

I am supporting the team with community engagement on the Huerta del Valle Community Gardens Project. My role allows me to assist with the design and implementation of garden meetings, research, and the water conservation practices.

Why did you want to participate in OSW? 

It is important to our team that we are supporting the project’s reach to the community. Assuring that the project is practical, applicable and replicable for both participating gardeners, and fellow garden members who will learn from them. I am involved to make sure the research serves their needs and that the whole community can benefit from the resources we are able to provide while at the same time coming to sound conclusions.

What has been your favorite experience with the project so far? 

My favorite part of the project is the opportunity to bring new ways to assess water usage in community gardens and provide resources to help gardeners become more water wise. Often, as they mentioned, gardeners are told about the strategies for water conservation but then don’t have access to the materials to implement those strategies.

What do you see as the most valuable aspect of the work you’re doing with OSW? 

I believe community gardens are such an integral part of urban resiliency. They provide autonomy in food production, cooling places, green space, access to the outdoors and habitat. I am excited to be part of a project that takes one aspect—water—and works with the community members to learn more and create change.

Any anecdotes from time spent on the project? 

Huerta del Valle is such a bustling place. It is a joy to visit. There are always families there, the co-op is selling produce and every time we hold a meeting there, someone makes lemongrass and honey tea that is delicious and restorative. It was quite impressive to hear the participating gardeners narrow down all the aspects of gardening they wanted to research. While they finally settled on creating a research project around water usage methods, they also discussed the importance of knowing your soil and how water can help control pests and plagues. There is so much the gardeners could research and I am glad they are as interested as we are in the results.


Claremont: An Operation Healthy Air Data Story

The data collection period was July – August 2017.

Goal: Does air temperature differ when comparing a backyard, front yard, and neighboring park? To examine this, we looked at three air temperature sensors (called iButtons) in Montclair. Each sensor had been located about 2 meters (~ 7 feet) high in a tree. Here are the sensor numbers and information about the trees each sensor was located in:

  • Sensor # 35: in a backyard. Tree species: Tangelo, 8 feet average tree canopy radius and about 15 feet high.
  • Sensor # 45: in a park (cemetery). Tree species: Plum/cheery tree, 8.6 feet average tree canopy radius and about 16 feet high.
  • Sensor # 47: in the frontyard/street. Tree species: Coast live oak, 24 feet average tree canopy radius and about 35 feet high.

Figure 1.
Upper Left (A): Satellite image of neighborhood in Montclair with locations of sensors.
Upper Right (B): Locations of sensors in Montclair.
Bottom (C): Map from ESMC web site of same neighborhood in Montclair with locations of sensors. HabitatNetwork maps ( of the same neighborhood with the sensor locations.

How does the air temperature vary across the different sensors? Do you have any predictions? For example, do you think backyards or front yards would be cooler during the day? What about night time? What about differences between trees along a road with asphalt which heats up during the sunny day compared to no asphalt?

(Tip while using the ESMC Data Explorer: On the left side you can choose which of the three campaigns you wish to learn about. Get more tips in our “How to Use ESMC iButton Data Explorer” blog.)

Figure 2.

Using the ESMC data tool (top figure), we were able to select a narrow range of dates (to more clearly see the patterns) and look at how air temperature (on the y axis) changed across several days (time is on the x axis).

What patterns do you see? The first most obvious pattern, to me, is how air temperature changes over a 24-hour period, with a high temperature peak between 1 and 4 pm. Air temperature tends to drop thereafter with it being most cool around 5 am.

The sensor that tends to be the hottest during the day is # 37 (located in the medium size tangelo tree in the backyard)—which is 4-8 degrees F hotter than either of the other two trees. The other two trees have similar daytime air temperatures.

However, the coolest location at nighttime is the cemetery park (by 2-6 degrees F). One possible reason may be that the park is surrounded by trees and not asphalt or buildings which themselves tend to radiate out heat at night.

This is just one snapshot comparison across some sensors which has revealed interesting patterns. We are interested in hearing from you about what you find and what questions you might have. Let us know, and we can post your questions/findings! Send your findings and questions to