Towards Informed Water Resources Planning and Management
Xing Lu
Round 1
Reviewer 1 Report
This paper discusses the importance of probabilistic prediction-based decision making. The paper is well written and nicely organized. two minor comments:
Line 245: to weak ïƒ too weak
Line 295- 297: I am not quite sure about this argument. When we talk about mean and standard deviation, lots of time we are assuming standard deviation based on central limit theory (kind of like what the authors are describing using Eq 2-3). So, even though a distribution is not shown explicitly on (b), a normal distribution with certain mean and standard deviation can be visualized.
Author Response
Dear Reviewer, thank you for your effort and the positive comments.
REMARK 1: Line 245: to weak => too weak
REPLY 1: "to weak" has been corrected into "too weak"
REMARK 2: Line 295- 297: I am not quite sure about this argument. When we talk about mean and standard deviation, lots of time we are assuming standard deviation based on central limit theory (kind of like what the authors are describing using Eq 2-3). So, even though a distribution is not shown explicitly on (b), a normal distribution with certain mean and standard deviation can be visualised.
REPLY 2: We have modified the original sentence to clarify the concept:
"If we deal with normally distributed variables the mean and the variance fully qualify the probability distribution, but apart from yearly average values most natural variables, and in particular precipitation and discharge, show clear skewed and more complex distributions when sampled at seasonal, monthly or shorter time intervals. Hence the need of marginalising uncertainty by using the information provided by the predictive density requires the entire probability distribution to lead to more robust decisions and not only the mean and at most two confidence limits."
Reviewer 2 Report
it is a novelty and high scientific paper.
Author Response
Dear Reviewer,
Thank you for you effort and for the positive evaluation.
