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Appendixes
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Appendix A
Site Visits
Members of the committee made site visits to several field offices in which the Advanced
Hydrologic Prediction Service (AHPS) is used in one form or another. These were not all National
Weather Service (NWS) field offices, but rather represent a range of agencies and organizations that
use or generate hydrologic models and forecasts. All were quite familiar with AHPS and each has
used either AHPS data, models, and/or products. Some serve other users who, in turn, use AHPS
data or products, either directly or through the organization visited. Each group of professionals
interviewed voiced strong support for AHPS and encouraged its continued development. Each
pointed to different aspects that they believe are essential elements of AHPS, reflecting their specific
needs and interests, and all had suggestions for improving AHPS. Despite the differences among
the offices in responsibilities and needs, their responses to the interviews can be grouped into three
categories: the science, interaction and connection, and identifying needs. Though each is discussed
separately below, they are not mutually exclusive.
THE SCIENCE
Several people interviewed expressed concerns about the data and models that are the
foundation of AHPS. For instance, many hydrologists who use AHPS products remain
unconvinced about the adequacy of precipitation and temperature data as they affect quantitative
precipitation forecasts (QPFs) and quantitative precipitation estimations (QPEs). Advances are
needed to ascertain the correct usages of QPE, QPF, and probabilistic quantitative precipitation
forecasts (PQPFs). Also needed is a long-term strategy to address systematic deficiencies such as
these.
Other examples were given, but most modeling and scientific concerns centered around the
need for shorter-term forecasts. Shorter-term forecasts require more frequent updating. They are
based on sufficiently sensitive models, and model input needs to be verified and validated for
accuracy. These elements of the shorter-term forecast models were seen as critical to the success of
AHPS. It appears to some in the field that short-term pressures to produce results are a stronger
focus than the development of an end-to-end hydrologic prediction system. Others interviewed
suggested that too much of AHPS seems to offer discrete solutions to localized problems, rather
than an approach that addresses system-wide issues such as data availability and model accuracy.
Therefore, those interviewed were clear that high priority must be given to advancing the science
associated with the forecasting that is at the root of AHPS.
Another theme that surfaced was the need to shorten the time between the inception of
ideas and their implementation. Distributed modeling has been of concern for almost two decades,
yet it has still not been used in operational forecasts. Similarly, QPE from radar have been discussed
as a priority for sometime, but sufficient advances have not been made. These are examples of
elements that are critical to the ultimate success of AHPS. That we have not gotten to where we
need to be is a function of a number of factors, many of which are not easily controlled by the
NWS. Because much of the data collection and some of the modeling are done through field offices
and other agencies, there is a need for close interaction between NWS field offices and cutting-edge
research.
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70 Toward a New Advanced Hydrologic Prediction Service (AHPS)
INTERACTION AND CONNECTION
The need for communication among all players, those in various field offices and related
organizations and those at headquarters, is clearly evident from the data sharing and model building
that take place in various locations. A great deal of modeling that has direct application to AHPS is
done in the field, and much of the necessary data are collected there. Conversely, models that are
developed at headquarters can be most easily tested and implemented by regional and local offices.
Clearly, improved communication can benefit all: ideas can get into operational settings more
quickly and models developed in the field can more easily be incorporated into the AHPS process at
headquarters.
Absence of a clear, integrated chain of command and communication not only leads to
difficulty in developing and implementing an end-to-end system, but it also confuses users who may
need immediate answers and face uncertainty as to where they can go for those answers. For
instance, the River Forecast Centers (RFCs) produce forecasts but do not officially issue them.
Users, then, cannot contact the RFCs directly regarding feedback or problems associated with the
forecasts.
Connections and cooperation are also necessary among the numerous agencies that develop
and use hydrologic data and models. Frustration at the time it has taken to see some ideas become
operational may be lessened by agencies working together rather than by each doing its own
modeling. This is probably a lower priority than the "in-house" cooperation that is discussed above,
but it may be a way to leverage resources to better advantage and to avoid duplication of efforts.
IDENTIFYING NEEDS
One fact that became abundantly clear during the site visits is that hydrologic information is
used by a wide range of users. The needs of these users vary significantly, as do their levels of
sophistication. An important concern of those interviewed relates to the move to probabilistic
forecasts in which a suite of values is provided, each with a given probability of exceedance. While
supportive of this approach, all recognized the implications of this, which will end up shifting
managerial decisions to users. Some will find it very useful, some will not.
A current problem with AHPS that was cited by several of those interviewed is the lack of
consistent data and products available at all locations. It was recognized that such consistency will
take time as necessary data are collected and models developed and calibrated at new locations, but
this is not always as easily recognized by different users and user groups. Some locations have flood
inundation maps available; others don't. Some users look for long term forecasts; others require
short term forecasts with frequent updates. For some users, the 6 hour time step of hydrologic
models works; for others, a 3 hour time step would be more appropriate. Working in close
collaboration and interacting regularly along the chain of command would help identify and
prioritize the varying needs.
Representative terms from entire chapter:
hydrologic prediction
