Lab 11 – Remote Sensing in Hydrology, Spring 2009
9 April 2009. Due 16 April 2009
Name:
Hydrologic Streamflow Estimation using MODIS Time Series and NEXRAD
Precipitation
The purpose of this lab exercise is to give you some familiarity with the statistical methods that
were employed in the design of this model as well as to give you experience in data mining and
interpretation of model parameters.
Introduction
You’ve now been introduced to the conceptual basis of a remote sensing model of the
precipitation-streamflow dynamic in several south Texas watersheds. In this laboratory exercise,
you will explore further this statistical model in the Navidad River watershed of the Lavaca
River basin. You will be provided a spreadsheet containing the core time series of the model
parameters and a GIS geodatabase of spatial data for Sandies Creek and Navidad River
watersheds.
Download lab11 data from \\129.115.25.240\XIE_misc\EES5093\
Steps:
1) Generate a precipitation-discharge (X-Y) scatterplot for the 2005 time series for Navidad
River.
a) Explain the increasing scatter of the plot (ie. greater variability of discharge as
precipitation values increase) in the context of the landscape state. In other words, what
primary landscape variable is likely forcing the streamflow or discharge response of the
watershed subsequent to a precipitation event?
b) Bonus (20 pints): Read and examine Ch. 2 of the USDA NRCS TR-55 manual (can be
found online) and explain the above scatterplot in the context of the curve number.
2) Utilize the following streamflow estimation equation from the Sandies Creek watershed
2002-2005 series to generate a modeled flow series for the 2005 Navidad River series.
lnQm = 1.9086 + 0.3429*P - 0.1210*T - 5.7419*VI
Where Qm is log transformed model streamflow, P is precipitation, T is land surface
temperature, and VI is the deseasoned moisture stress index. For comparison to the observed
flow series, Qo, remember to convert Qm back to linear space.
Repeat the above exercise to generate a flow series with both a one time step offset and a two
time step offset of LST. The point of this is to test for antecedent effects. In other words,
does an antecedent LST (ex. LST for the time period Jan 1-8) improve the results for the
model evaluation time period Jan 9-16? (of course, offsetting for the entire time series).
The metric for the statistical comparison of time series should be the Nash-Sutcliffe
Estimation Efficiency. You can find this equation in numerous papers as well as in any of
the three papers I published for my dissertation.
a) Create a plot of modeled (0, 1, and 2 time offsets) and observed discharge. Add the
precipitation record as a second x-axis (top of frame) – the prec. data should be shown as
bars hanging upside down. The discharge data can be shown as continuous line data.
b) Report on the estimation efficiency criteria for each model. Briefly research on the NS
criteria and explain why it is a common metric for evaluation of hydrologic flow series.
What are its drawbacks and are there alternatives? (see Krause et al., 2005. Comparison of
different efficiency criteria for hydrologic model assessment, Advances in Geosciences 5:
89-97.)
3) Generate a new estimation equation and model vs observed discharge plot for the 2005
Navidad River series using the log transformed discharge (ln of Q), the precipitation (P), the
deseasoned MSI, and an LST with an offset of two time periods. You may use SAS, JMP, or
any other stats package you are familiar with. Remember that you are conducting multiple
linear regression, with the dependent variable being lnQ, and the independent variables being
P, LST, and MSI.
In addition to generating a new estimation equation, as part of the statistical evaluation, you
should also report on the coefficient of determination (R2) of the model fit, and the p values
of each of the parameter estimates. You should also include a plot of the model residuals
(All of this is standard output if you use JMP).
4) Compare the re-calibrated Navidad time series with the time series generated from the
Sandies Creek data using the estimation efficiency criteria (Nash-Sutcliffe). (Note: only
compare the time series with two LST offsets). Don’t just say one is better than the other!
The NS metric just tells you the efficiency as a whole – look at the time series in terms of
individual events or time steps. Did the re-calibrated series do better on large events or small
events? Can you see differences in the seasons (spring, summer, etc.)? Report on the
cumulative flow for the year for both series (called relative volume error or flow bias).
5) Additional questions (extra credits of 20 points)
a) Examine the land use land cover (LULC) and the hydrologic soil group data from the GIS
for both Sandies Creek and Navidad River. Summarize these attributes for both watersheds.
Explain why the streamflow estimation equation for Navidad River should work at all given
that these are two different watersheds in two different river basins. How are they similar and
how are they different? What are the annual precipitation totals for the two watersheds for
2005? (Use a NWS weather station or coop station within the bounds of the watershed).
How does the rain gauge station data you found for the Navidad watershed compare to the
NEXRAD data I gave you.