Seasonality in Water Tech

Okay so I think the time has finally come for me to address this topic. Properly. Thank you. I mean, this crops up all the time for me. Everywhere I look in my water tech research, it all comes back to seasonality. Seasonality - and weather too.

That is why - although this post focuses on seasonality - weather will be coming too soon. Thank you. It seems to me - and I could be wrong - that there are two main areas of trends in seasonality in water tech: seasonal demand changes and seasonal events.

Let me see if most of my info can be fitted into these two main areas please - thank you. Here we go.

I mean I could probably do a separate blog post on each one.

Seasonal Demand Changes

So what might we class as a seasonal demand change? Well to be honest with you I do actually think that it is the latter, seasonal events, that I am more interested in.

But both are relevant so let me take a look a bit closer - thanks.

Exploring Seasonal Demand Changes

An example of this might be summer - using more water for irrigation or more water for cooling.

Summer Months

More specifically, water is in higher demand in the summer months due to the following:

• Agriculture
• Gardening
• Residential and commercial cooling
• Urban cooling e.g. misters
• Pools and water parks
• Public spaces e.g. like fountains and irrigation in normal parks

Winter Months

In winter months, the demand on water supply seems to drop. There is:

• Reduced irrigation
• Less landscaping demand
• Lower cooling demand
• Decreased outdoor activity.

And there can be some fluctuation across these

Seasonal Variations

All of the above can vary. They are more pronounced in areas with more extreme climates. In regions with snow and ice, these fluctuations and melting circumstances can also affect water supply quite significantly (usually for the better, I believe?). 

Knowing these circumstances can be applied to help water planners make better decisions about infrastructure and planning. 

And AI models being trained in these (by region!!) can help it to make better data-based predictions and decisions overall.

Seasonal Events 

These are all seasonal things that happen that might affect water quality, water supply, and water demand. Some examples are:

• Dry spells
• Rain falls
• Winter freezes
• Ice melting

What about this is relevant to tech?

Apart from to AI, and to making water predictions in general, here are some reasons why the seasonality of water is relevant to tech:

• Fluctuations in water and rivers due to wet/dry seasons can lead to changes in supply and flow
• Increased risk of issues - pipes can be more likely to burst, microbes can be more likely to be present in the water

3 Areas Where Seasonality Can Be Applied To AI In Water Tech

From A Seasonal Perspective

I know I have said this a thousand times before but I need to say this again - thanks.

• Predictive Maintenance
• Seasonal variations such as freezing temperatures can increase stress
• Using AI and its powers of predictive maintenance can help to prevent against this kind of case specifically
• Resource Management
• Dramatic variations in water supply may occur due to seasonal availability
• AI can be used to optimise storage and distribution !!!
• Optimising Operations
• Across the seasons, different amounts of energy may be needed for pumping, distribution or treatment of water
• AI can be used to optimise operational schedules to save on energy and/or on money

A Final Thought on Seasonal Cycles in Water AI

A final thought is that I have just read that apparently the more cycles including in pattern prediction for water AI the better. So daily and weekly and monthly cycles can be useful as well as yearly seasonal cycles and patterns.