The document presents a doctoral seminar on hydrological modeling using the Soil and Water Assessment Tool (SWAT), led by Dr. Anil Kumar Mishra. It outlines the necessity of hydrological modeling for assessing water resource impacts, predicting extreme events, and designing for flood and drought conditions, along with a case study in the Upper Blue Nile Basin, Ethiopia. The SWAT model demonstrated reliable performance in simulating hydrological processes, revealing significant insights into the basin's water yield and the importance of various flow components.

1. Hydrological Modelling using SWAT
Doctoral Seminar I (0+1)
Course Leader
Dr. Anil Kumar Mishra
By
Bharath Govindaraju
Roll No. : 12539
Ph.D., Soil and Water Conservation Engineering
Division of Agricultural Engineering
Graduate School
ICAR-IARI, New Delhi-110012
Chairperson
Dr. Murtaza Hasan

2. Contents
Introduction
Soil and Water Assessment Tool
Model Framework
Procedure to run the model
Case study
Conclusions
References

3. What is Hydrological Modelling?
• Hydrological models are simplified,
conceptual representation of hydrological
cycle
• Hydrologic model - effective and viable
means of predicting water availability - its
distribution systems. The watershed as a hydrologic system
(Source: Chow Venn T, 1988)

4. Need for Hydrological Modelling
Assessment of impacts on water resources
Changes in land use/land cover
Changes in Climate variables
Pollution
 Prediction of extreme events
Flood forecasting (Disaster management)
Droughts
Design needs
How much flow will occur in a 100 year storm?
Water availability

5. Soil and Water Assessment Tool (SWAT)
 SWAT model is developed by USDA-ARS, Texas A&M University and Texas A&M AgriLife Research
 SWAT is an open source software, but ArcSWAT is not open source
QSWAT for
ArcSWAT for
Source: https://swat.tamu.edu

6. SWAT tool bar in the ArcGIS software

7. 7
SWAT is a spatially semi-distributed & continuous
time hydrological model
Inputs
Topography
Soil
Land use
GIS Data Weather Data
HRU
Outputs
Runoff, Evapotranspiration, Sediment yield, etc.

8. SWt = SWo + Σ t
i (Rday - Qsurf - ETi - Wseep - Qgw)
8
(Source: Neitsch et al., 2005)
Water balance equation
SCS-CN Method
Runoff from the catchment (Q)
Q = ; Ia= 0.2×S
Surface Retention (S)
S =25.4( 10)
• Penman-Monteith
• Priestley-Taylor
• Hargreaves
Evapotranspiration

9. 9
Soil & Water
Assessment
Tool
(SWAT)
INPUTS
Meteorological
parameters
DEM
Land Use/ Land
Cover map
Soil
Hydrological
parameters
OUTPUTS
Surface Runoff
Evapo-
transpiration
Total water yield
Model Framework

10. 10
Step 1: SWAT Project Setup
Step 2: Watershed Delineation
Step 3: HRU Analysis
a. Land Use
b. Soil
c. Slope
Step 4: Write Input Tables
Step 5: Edit SWAT Input
Step 6: SWAT Simulation
Procedure to run the model
SWAT Output Window: Output Data

11.  Coefficient of determination (R2
):
R2
 Nash-Sutcliffe Efficiency (NSE):
NSE
 Percent Bias (PBIAS)
P
Calibration
Validation
Performance Evaluation Criteria
Range: 1 to ∞
Range: 0 to 1

12. 12
Hydrological Modelling in the Upper Blue Nile basin using Soil and
Water Assessment Tool
Authors: Gebiyaw Sitotaw Takele, Geremew Sahilu Gebre,
Azage Gebreyohannes Gebremariam, Agizew Nigussie Engida
Location: Ethiopia, Africa
Year: 2021
Objectives:
• To simulate and examine the hydrological processes of the basin
• To explore the spatial distribution of the hydrological components of the basin
Case Study

13. 13
Map overview of Upper Blue Nile basin
 Study Area: 1,74,166
km2
 Average annual rainfall
of the basin: 1200-1800
mm/year.

14. 14
Software used Arc GIS - SWAT Model
Data type Source Resolution
Digital Elevation Model
(DEM)
Alaska Satellite Facility 12.5 km
Land use/Land cover Copernicus Global Land Service 100 m
Soil map World FAO 5 km
Meteorological Data
(18 years)
National Meteorological Service
Agency (NMSA) of Ethiopia
Point
Hydrological data
(14 years)
Ethiopian Ministry of Water,
Irrigation and Energy
Point
An automatic weather station
Data used

15. 15
Spatial locations of the selected meteorological and streamflow gauge stations
Station
name
Average annual
discharge, m3
/s
Kessie 652
Border 1871
Selected streamflow gauge
stations and their spatial location

16. 16
Elevation map of the Upper Blue Nile basin FAO Soil map of the Upper Blue Nile basin
Spatial Data

17. 17
LULC map of the Upper Blue Nile basin

18. 18
DEM
LULC
SOIL
WEATHER
DATA
Watershed
delineation and
HRU definition
SWAT Model
Setup and
Run
Model
output
Calibration
and
Validation
Results of
Water
Balance
Observed
stream flow
data
Methodology
Sensitivity
analysis
using
SWAT-CUP

19. 19
Results
Parameters Description Process Range Fitted
CN2.mgt Initial SCS CN II value Runoff -8 – 10 -2.78
RCHRG_DP.gw Deep aquifer percolation factor Ground water 0-0.3 0.003
REVAPMN.gw Threshold depth of water in the shallow
aquifer for ‘revap’ to occur
Ground water 1-350 227.85
SOL_AWC.sol Available water capacity of the soil layer Soil 0.10.7 0.35
GW_DELAY.gw Groundwater delay (days) Ground water 0-60 2.77
CH_K2.rte Effective hydraulic conductivity Channel 0-200 130
ALPHA_BF.gw Baseflow alpha-factor (day) Ground water 0.1-0.8 0.345
GW_REVAP.gw Groundwater ‘revap’ coefficient Ground water 0.03-0.19 0.14
SOL_K.sol Saturated hydraulic conductivity Soil 0-0.2 0.15
GWQMN.gw Threshold depth of water in the shallow
aquifer required for return flow to occur
Ground water 100-4000 2401
Calibration parameters and their fitted value

20. 20
Observed and simulated flow hydrograph for the calibration and
validation period at Kessie

21. 21
Observed and simulated flow hydrograph for the calibration and
validation period at Border

22. 22
Station
Calibration Validation
R2
NSE PBIAS R2
NSE PBIAS
Kessie 0.81 0.68 -10.8 0.89 0.88 8.3
Border 0.85 0.83 -4.7 0.93 0.89 9.7
R2
, NSE and PBIAS value for calibration and validation
period at Kessie and Border stations
Model Evaluation
Parameters
(mm)
Average of calibration
and validation
Precipitation 1691
Surface runoff 314.65
Lateral flow 85.87
Groundwater flow 280.5
Shallow aquifer storage 328
Evapotranspiration 691.07
Water balance components

23. 23
Spatial Distribution of the components
Simulated Rainfall Simulated Water yield

24. 24
Simulated PET

25. Conclusions
 The SWAT model demonstrated good simulation accuracy in modeling the hydrological processes of
the Upper Blue Nile basin, during both calibration and validation periods. This indicates reliable model
performance in predicting streamflow.
 Groundwater flow parameters were identified as the most sensitive to streamflow variations through
sensitivity analysis, highlighting their critical role in accurately modeling hydrological processes in the
basin.
 The hydrological water balance analysis revealed that 22.43% of basin precipitation contributes to
streamflow as surface flow, while a significant 49.5% is lost to evapotranspiration, making
evapotranspiration a key factor influencing runoff in the basin.

26. Conclusions….
The annual water yield of the basin is primarily composed of surface
runoff (44.95%), followed by baseflow (40.15%), and lateral flow
(12.41%). This distribution underscores the importance of surface and
baseflow in the basin’s water yield.
The research demonstrated the SWAT model’s high potential for basin-
wide water resources planning and management, offering valuable insights
into water resource availability.

27. References
Gebiyaw Sitotaw Takele, Geremew Sahilu Gebre, Azage Gebreyohannes Gebremariam, Agizew Nigussie Engida.
(2021). Hydrological modelling in the Upper Blue Nile basin using SWAT. Modelling Earth Systems and
Environment.
Samuel S. Guug , Shaibu Abdul-Ganiyu, Raymond A. Kasei. 2020 Application of SWAT hydrological model for
assessing water availability at the Sherigu catchment of Ghana and Southern Burkina Faso. HydroResearch.. 124-
133.
Sang, J. , Allen, P. , Dunbar, J. , Arnold, J. and White, J. (2015) Sediment Yield Dynamics during the 1950s Multi-Year
Droughts from Two Ungauged Basins in the Edwards Plateau, Texas. Journal of Water Resource and Protection, 7,
1345-1362.
Jain S.K., Agarwal P.K. and Singh V.P. (2007). Krishna and Godavari Basins. Hydrology and Water Resources of
India, Springer Netherlands, 641-699.
Sharma K.D., Sorooshian S. and Wheater H. (2008). Hydrological Modelling in Arid and Semi-Arid Areas.
International hydrology series. Modelling hydrological process in Arid and semi arid area an introduction to
workshop. 1-18.ISBN 978-0-521-86918-8 handbook.

28. 28
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