Can you build a story to predict the amount of water in each unique waterbody? The challenge is to determine how features influence the water availability of each presented waterbody.
Official Kaggle Competition Website (Please refer to this for a full description of rules): https://www.kaggle.com/c/acea-water-prediction
The Acea Group is one of the leading Italian multiutility operators. Listed on the Italian Stock Exchange since 1999, the company manages and develops water and electricity networks and environmental services. Acea is the foremost Italian operator in the water services sector supplying 9 million inhabitants in Lazio, Tuscany, Umbria, Molise, Campania.
In this competition we will focus only on the water sector to help Acea Group preserve precious waterbodies. As it is easy to imagine, a water supply company struggles with the need to forecast the water level in a waterbody (water spring, lake, river, or aquifer) to handle daily consumption. During fall and winter waterbodies are refilled, but during spring and summer they start to drain. To help preserve the health of these waterbodies it is important to predict the most efficient water availability, in terms of level and water flow for each day of the year.
The reality is that each waterbody has such unique characteristics that their attributes are not linked to each other. This analytics competition uses datasets that are completely independent from each other. However, it is critical to understand total availability in order to preserve water across the country.
Each dataset represents a different kind of waterbody. As each waterbody is different from the other, the related features are also different. So, if for instance we consider a water spring we notice that its features are different from those of a lake. These variances are expected based upon the unique behavior and characteristics of each waterbody. The Acea Group deals with four different type of waterbodies: water springs, lakes, rivers and aquifers.
Can you build a story to predict the amount of water in each unique waterbody? The challenge is to determine how features influence the water availability of each presented waterbody. To be more straightforward, gaining a better understanding of volumes, they will be able to ensure water availability for each time interval of the year.
The time interval is defined as day/month depending on the available measures for each waterbody. Models should capture volumes for each waterbody(for instance, for a model working on a monthly interval a forecast over the month is expected).
The desired outcome is a notebook that can generate four mathematical models, one for each category of waterbody (acquifers, water springs, river, lake) that might be applicable to each single waterbody.
