[1] Hydrological Modeling:
Hydrologic
models are simplified; conceptual representations of a part of the hydrologic
cycle [1A].They are primarily used for hydrologic prediction and for
understanding hydrologic processes. Two major types of hydrologic models can be
distinguished. (A) Stochastic Models. These models are black box systems, based
on data and using mathematical and statistical concepts to link a certain input
(as example rainfall) to the model output (for instance runoff). Commonly used
techniques are regression, transfer functions, neural networks and system
identification. These models are known as stochastic hydrology models.(B) Process-Based
Models. These models try to represent the physical processes observed in the
real world. Typically, such models contain representations of surface runoff,
subsurface flow, evapotranspiration, and channel flow, but they can be far more
complicated. These models are known as deterministic hydrology models.
Deterministic hydrology models can be subdivided into single-event models and
continuous simulation models. There are various type of hydrological models are
now a days available in public domain [1B][1C]
Citations:
[1B] HEC-RAS website
[1C] SWAT website
[2] SWAT model and its
application:
SWAT model (Arnold et al., 1998)
is a semi-distributed, continuous watershed simulator operating on a daily time
step [2A]. It is developed with the joint effort with USDA and Texas University
for assessing the impact of management and climate on water supplies, sediment,
and agricultural chemical yields in watersheds and larger river basins. The
model is semi-physically based, and allows simulation of a high level of
spatial detail by dividing the watershed into a large number of sub-watersheds.
The major components of SWAT include hydrology, Water supply, Water quality,
weather, erosion, plant growth, nutrients, pesticides, land management, and
stream routing. The robust application of SWAT model has extended all over the
world because of its diversified application [2B]. Government agencies like EPA USDA uses SWAT for tracking environmental problems
like water quantity, water quality, nutrient cycling and in stream process ete[2C,
2D,]. Wider application of SWAT is mostly in the government agency and research
organization of USA and EU. . SWAT model
output often uses indirectly as it has the flexibility of coupling with other models.
A large number of climate and land use studies has been done all over the world
with SWAT model for land use and climate change study [2E, 2F]. Large scale
European Projects also uses SWAT as a central hydrologic model frequently [2G] Here
is an example of SWAT model application in the Himalayan region for impact
assessment of climate change [2H]
Citations
[3] Watershed Delineation
Watershed delineation is required
to provide a boundary of the watershed. SWAT uses ArcHydro algorithm for
watershed delineation [3A]. The watershed delineation carries out advanced GIS
functions to aid the user in segmenting watersheds in to several
‘hydrologically’ connected sub watersheds for use in watershed modeling in
SWAT. [3B] There are two methods for watershed delineation in SWAT model, one
is the DEM-based method, which is based on the DEM of the study area and the other is the pre-defined method in
which users can define the reaches and sub basins manually. Most of the
researchers use the first method at present, which has high precision only in
the area with certain terrain slope [3C]. During watershed delineation flow direction
and flow accumulation process is done.
Citations:
Citations:
[4] HRU analysis
Hydrological response units are areas within a watershed
that respond hydrologically similarly to given input. It is a means to
representing the spatial heterogeneity of a watershed. With the introduction of hydrologic response
unit (HRU), it is possible to expect similar hydrologic behaviour in each unit,
which can be modeled easily. Plenty of hydrological models use HRU as unit
response for a sub basin [4B][4C] .
Citations
[4B] HRU based PRMS model
[5] Weather Inputs and First simulation
The weather data definition
window is divided in six tabs. (1)
Weather Generator (2) Rainfall Data (3) Temperature Data (4) Solar
Radiation Data (5) Wind Speed data and (6) Relative Humidity Data. The first
section for weather data is for the location of stations. The interface will
not allow the user to perform other input data processing until the Weather
Generator Data is defined. The other five sections allow the user to choose
between simulated or measured data for specific type of data. We will use only
precipitation and temperature data for this case study and let the model
generate other data.
[6] Primary results and need of calibration
We obtained a daily discharge
time series from 1996 to 2010 for Mendoza river watershed at downstream
(pointed with the GPS at the sub basin no 7). We will simulate the model 6 years from 1999
to 2004. First 3 years from 1996-1998 we will keep for warming up period it
will stabilize some initial model parameters. And the remaining period 2005 to
2010 we will keep for validation. We will discuss with daily and monthly time
step with some hydrograph analysis. Together with visual observation we will
discuss with statistical performance of hydrological model. For this post we
will not go in detail the calibration process which will be done in another
complete post.
[7] Running SWAT in R environment
The statistical programming tool
‘R’ is also open source [7A] In order to
get a better result from SWAT we need to test the parameter ranges and each
time we have to run (for Manuel calibration). If we use excel we have to plot
each time which is time consuming and tedious. Therefore, we can program the
statistical performance equations like NSE MSE or Percent Bias etc etc. After
that changing the basin parameter we can re run the model without plotting in
excel. Recently there is a R package and a multi objective genetic algorithm tool
in R is available [7B][7C]
Citations:
[7C] Multi objective Automatic Calibration of SWAT Using NSGAII in R
In the next post I will focus three issues. They are [1] SWAT calibration in MATLAB environment. [2] Application of genetic logarithm for SWAT calibration [3] Spatial map preparation from SWAT output. SO PLEASE KEEP TUNED...
Acknowledgements: Contribution of Dr. John Joseph (from
South Texas Uni, USA) greatly acknowledged for sharing his ideas to calibrate
SWAT in R environment and special thanks to Rocio Julia and Gissela for sharing
the observed data file of Mendoza river watershed which is the part of their
M.Sc thesis work.
