IEEE Geoscience and Remote Sensing Magazine - September 2014 - 31

30000

40000

In-Situ Discharge (m3.s-1)

In-Situ Discharge (m3.s-1)

50000

30000

20000

10000

25000
20000
15000
10000
5000

Data (Corr = 0.98, p-Val = 0.000)
Forecast Rating Curve
0
2
3
4
5
-1
0
1
-2
J2 242_1 Water Level Anomaly (m) for 6-Days Lead Time

Data (Corr = 0.98, p-Val = 0.000)
Forecast Rating Curve
0
-2
-1
0
1
2
3
4
5
J2 155_1 Water Level Anomaly (m) for 6-Days Lead Time

a. Water Level Anomaly (m) (Corr = 0.98, p-Val = 0.000)

b. Water Level Anomaly (m) (Corr = 0.96, p-Val = 0.000)

Figure 3. Example of 6-day forecasting rating curves (FRC) for JASON-2 at ground track (virtual station) location 242_1 (Brahmaputra river-
Figure 2) for Bahadurabad station (left panel) and 155_1 (Ganges river-Figure 2) for Hardinge Bridge station (right panel). These rating curves
are derived on the basis of historical data during the calibration period (October 2008-June 2009). Taken after Hossain et al., (2013b).

agencies of the South Asian region as well as other floodprone downstream nations in other places outlined in Hossain and Katiyar (2006) (e.g., such as FFWC in Bangladesh;
Center Water Commission- CWC in India; and Water and
Power Development Authority-WAPDA in Pakistan).
If achieving large-scale buy-in for the satellite altimeterbased system is the key goal, we realized that further work
would be needed to: a) train the necessary workforce of the
flood forecasting agency (the Institute of Water ModelingIWM, in this case; http://www.iwmbd.org); b) customize
the JASON-2 system within the software and hardware
constraints of the existing infrastructure in Bangladesh
(such as, internet availability for accessing near-real-time
data, computers and data storage); c) create an environment where the flood forecasting agency could independently generate and own routine flood forecasts during
the Monsoon season without any external incubation or
technical support; and finally, d) make forecasts publicly
available in real-time to maximize decision making for the
public of Bangladesh.
In an attempt to shore up resources for answering the
question posed, Hossain et al. (2014) had already reported
on the necessity of applying a series of seven steps to transition a research finding to the ultimate operational reality
with full ownership for the stakeholder. Herein, we briefly
outline these steps below that we had followed:
◗◗ STEP ONE: Do the Research on Theoretical Feasibility
on a Visible Research Publication Forum.
◗◗ STEP TWO: Disseminate Widely the Theoretical Feasibility to Potential Stakeholder Agencies through a 2-Way
Public Education Process. Generate Interest.
◗◗ STEP THREE: Respond to Skepticism of the Proposed
Scheme in an Engaging Way; Do Not Lose Stakeholder
Interest by Talking More than Listening.
september 2014

ieee Geoscience and remote sensing magazine

◗◗ STEP FOUR: Get Commitment from the Stakeholder

Agency to Prototype and Test the Satellite Forecasting
System; Start with the Simplest of Ideas.
◗◗ STEP FIVE: Begin Hands-on Training of Stakeholder
Agency Staff for Implementing the Prototype System.
Patiently Hand-hold the staff and Teach them Ground
up the Basics of the System in an Active-Learning
Environment.
◗◗ STEP SIX: Allocate Supporting Resources to Address Unexpected Hurdles during Launch of the Prototype System.
◗◗ STEP SEVEN: When Launching the Prototype, Ensure
Complete Ownership and Independent Operation.
Through a 2-way education/hands-on training workshop conducted during early
2013 at the stakeholder premises (of IWM), we adapted
engaging the local
further the design structure
stakeholder agency
of the JASON-2 forecasting
ground up with
system (reported in Hossain
complete ownership
et al., 2013b) that would work
is key to a durable
seamlessly in the operating
satellite based
conditions of the agency. For
Forecasting system.
example, we quickly realized
that we would need to work
with existing hydrologic-hydrodynamic models of IWM and find ways to ingest the
satellite altimetry data accordingly. Suggesting a new model was not an option as that would increase the overhead
costs. We also learned that if a proposed new scheme is
likely to add to further strain on time, effort and computational resources of the agency, that scheme is less likely to
be institutionally embraced without incubation. Thus, all
new modeling schemes and data extraction tools we developed further were based on free software tools that were
31
http://www.iwmbd.org
Table of Contents for the Digital Edition of IEEE Geoscience and Remote Sensing Magazine - September 2014
