The interpolation approach that is best suited for the extent of the data set would be Inverse Distance Weighted. I think that we have enough points and that they are close enough to that this method would work best with the specific data set. The points in the data set looked evenly spaced out and that is the type of data that should be used for that set of sample points. However, the drawback to using IDW would be that it does not look at all of the data trends when interpolating the data.

Based on last year's precipitation events, the Amador-Calaveras area could experience even more drought for the recently burned area. Although the areas that do receive decent rainfall could potentially have a variety of earth flows and slides because the soil is compacted to the ground and is riddled with burned dead material. The soil is no longer being held together by the roots of the vegetation that was once there. The areas that are not as burned and affected by the fire would still have some ability to hold the soil together and therefore would be more stable and be less susceptible to mass movements when precipitation does arrive. Granted in order for mass movements to occur there would have to be an intense amount of precipitation that would saturate the soil enough to cause instability. Although the soil is less stable due to the recent fires in the area.