Storm Team Digs Up What Went Wrong with Crest - Valley News Live - KVLY/KXJB - Fargo/Grand Forks

Storm Team Digs Up What Went Wrong with Crest

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 There's been a lot of talk about the flood crest ending up much lower than projected in the southern valley. Many more particularly want to know why the numbers were off. The Valley News Live Storm Team dug into the numbers, and this is what they found:

 There are many players in a flood--snowfall, current weather, and timing are few. This year, the focus was on the snowpack and just how much moisture was in it. Somethings called "snow water equivalent" is an estimation of how much liquid was out there just before the more rapid melt. It was estimating widespread areas of 6 to 10 inches. But many of you told us the water just wasn't there. The Storm Team went to see for themselves and found what may be the primary factor in this year's inaccurate flood projections.

 National Weather Service survey flights over the southern valley on April 19th measured an average range of 5 to 7 inches of liquid water. The pilot also reported 70 to 100-percent snow cover in Richland and Wilkin counties. This was about a week before warm weather triggered the melt.

 Four days after the flight survey, our Storm Team went to the same area and found a different picture. They didn't go everywhere the flights did, but the snowpack they saw was anything but uniform. There were many open fields and others underwater. Our meteorologists estimate that the area they surveyed had as little as 30-percent and up to 70-percent snowcover-- a big difference.

 A look at actual data from the survey flights indicates that 90-percent of the ground was covered in snow with an average of at least 6-inches of liquid water. Another key piece of evidence is that the modelers used nearly the same soil moisture value measured in the fall to calculate total water. But our team is certain the muddy fields in the southern valley absorbed more water.

 The flight data, along with measurements on the ground, are the critical information used in the flood model. When the data going into model is bad, it will turn out bad results. We've concluded that the flood model underestimated how much water was lost to the soil and streams during our ideal run of 40-degree temps leading up to the big melt.

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