Rainfall Runoff Modelling Using GR4J Model in Source

52 Pages·2017·2.92 MB·English

b

Rainfall Runoff

Modelling Using GR4J

Model in Source: A Pilot

Study in Bagmati Basin,

Nepal

Submitted to

Commonwealth Scientific and Industrial

Research Organization (CSIRO)

Submitted by

N epal Development Research
Institute (NDRI)

Shree Durbar Tole, Pulchowk, Lalitpur,
K athamandu Nepal
w ww.ndri.org.np

July, 2015
Copyright © 2015
Nepal Development Research Institute (NDRI)

All rights reserved.

Research Team
Team Leader: Laxmi P. Devkota, D.Eng.
Research Associate: Anita Khadka

Published by
Nepal Development Research Institute
P.O. Box: 6975, EPC 2201, Lalitpur, Nepal
Telephone: [phone]
Email:
Table of Contents
1. Introduction ................................................................................................................................................................. 1
2. Study area .................................................................................................................................................................. 2
3. Model description ...................................................................................................................................................... 4
3.1. Description of the model ................................................................................................................................. 4
3.2. Evaluation Criteria ........................................................................................................................................... 7
4. Model Development .................................................................................................................................................. 9
4.1. Data Input .......................................................................................................................................................... 9
4.1.1. Spatial data ............................................................................................................................................. 9
4.1.2. Temporal data ...................................................................................................................................... 10
4.2. Model Calibration and Validation ............................................................................................................ 13
5. Result and discussion .............................................................................................................................................. 15
5.1. Rainfall and Runoff characteristics............................................................................................................. 15
5.2. Calibration and validation results .............................................................................................................. 18
5.3. Conclusion........................................................................................................................................................ 30
6. References ................................................................................................................................................................ 31
7. Annex ........................................................................................................................................................................ 32

List of Tables
Table 1: Basin Features ..................................................................................................................................................... 3
Table 2: Thiessen weighted factor for precipitation data according to sub-catchments .................................. 11
Table 3: Evaporation stations ....................................................................................................................................... 13
Table 4: Gauging stations ............................................................................................................................................. 13
Table 5: Model run in different setting for stations 589 and 581 ........................................................................ 14
Table 6: Rainfall-Runoff statistics ................................................................................................................................. 16
Table 7: Model results for individual runs at station 589 and 581 without calibration weighting ................ 24
Table 8: Regression relationship of parameter x1 to x2 and x3 ......................................................................... 29
Table 9: Model results with different calibration weighting option at station 589 and 581 .......................... 29

List of Figures
Figure 1: Bagmati study basin ......................................................................................................................................... 3
Figure 2: Node link structure of the model in Bagmati basin .................................................................................... 4
Figure 3: Structure of GR4J model ................................................................................................................................ 6
Figure 4: Reclassified landuse map of the study area ........................................................................................... 10
Figure 5: Thiessen polygon area in the basin ........................................................................................................... 12
Figure 6: Isohyteal map based on annual total rainfall ......................................................................................... 12
Page | ii
Figure 7: Trend analysis of discharge at Pandheradivan (Stn589) and Bhorleni (Stn581) station ............... 15
Figure 8: Trend analysis of rainfall at Pandheradivan (Stn589) and Bhorleni (Stn581) station ................... 16
Figure 9: Rainfall-Runoff relationship (200-2008) at Pandheradovan (Stn589) and Bhorleni(Stn581) ....... 17
Figure 10: Hydrographs of maximum, minimum and average flows .................................................................... 17
Figure 11: Rainfall-runoff hydrograph in a catchment area of Pandheradovan (Stn589) and Bhorleni
(Stn581) for the period 0f 2000 to 2008 ................................................................................................................. 17
Figure 12: Probability of exceedance for historical data of flow (a) and rainfall (b) at Pandheradovan
and Bhorleni stations ....................................................................................................................................................... 18
Figure 13: Scatter plots of daily observed versus simulated flow for calibration period of 2000 to 2004,
using four objective function - NSE, NSE-Bias, NSE-FDC, NSE-logFDC represented in a clockwise direction at
Pandheradovan gauging station (without joint calibration) .................................................................................... 19
Figure 14: Daily hydrograph of observed and simulated flow for calibration (2000-2004) and validation
(2005-2008) period at Pandheradovan gauging station (without joint calibration) ........................................ 20
Figure 15: Daily hydrograph of observed and simulated flow for calibration (2000-2004) and validation
(2005-2008) period at Bhorleni gauging station (without joint calibration)....................................................... 21
Figure 16: Daily flow hydrograph comparing base flows at Pandheradovan (Stn589) and Bhorlnei
(Stn581) gauging station with the compound objective weighting at a range of 0.3 to 0.8 (NSE-FDC, NSE-
logFDC) .............................................................................................................................................................................. 26
Figure 17: Comparison of daily hydrograph of observed versus simulated flow for a 38 day period (1July
to 7 Aug of 2002) based on GR4J and GeoSRM model results ........................................................................... 27
Figure 18: Daily hydrograph of observed and simulated flow for calibration (2000-2004) and validation
(2005-2008) period at Pandheradovan gauging station (with joint calibration) ............................................. 28

Annex
Annex 1: Distribution of land based on its utilization in the basin ......................................................................... 32
Annex 2: Sub-catchment wise distribution of land .................................................................................................... 32
Annex 3: List of Hydro-meteorological stations......................................................................................................... 32
Annex 4: Rainfall-runoff relationship during calibration and validation period at Pandheradovan (Stn589)
and Bhorleni (Stn581) gauging station ....................................................................................................................... 33
Annex 5: Scatter plots of daily observed versus simulated flow for calibration period of 2000 to 2004,
using four objective function - NSE, NSE-Bias, NSE-FDC, NSE-logFDC represented in a clockwise direction at
Bhorleni gauging station (without joint calibration) .................................................................................................. 34
Annex 6:Scatter plots of daily observed versus simulated flow for validation period of 2005 to 2008,
using four objective function - NSE, NSE-Bias, NSE-FDC, NSE-logFDC represented in a clockwise direction at
Pandheradovan gauging station (without joint calibration) .................................................................................... 35
Annex 7:Scatter plots of daily observed versus simulated flow for validation period of 2005 to 2008,
using four objective function - NSE, NSE-Bias, NSE-FDC, NSE-logFDC represented in a clockwise direction at
Bhorleni gauging station (without joint calibration) ................................................................................................. 35
Annex 8: Monthly hydrograph of observed and simulated flow for calibration (2000-2004) and validation
(2005-2008) period at Pandheradovan (stn589) and Bhorleni (Stn 581) gauging station (without joint
calibration) ........................................................................................................................................................................ 36
Annex 9: Daily hydrograph of observed and simulated flow for calibration (2000-2004) and validation
(2005-2008) period at Pandheradovan and Bhorleni gauging station with joint calibration ........................ 37
Page | iii
Annex 10: Monthly hydrograph of observed and simulated flow for calibration (2000-2004) and
validation (2005-2008) period at at Pandheradovan (stn589) and Bhorleni (Stn 581) gauging station
(with joint calibration) ..................................................................................................................................................... 37
Annex 11: Flow duration curves for Pandheradovan (Stn589) gauging stations during calibration period
(without joint calibration) ................................................................................................................................................ 38
Annex 12: Flow duration curves for Pandheradovan (Stn589) gauging stations during validation period
(without joint calibration) ................................................................................................................................................ 39
Annex 13: Flow duration curves for Bhorleni (Stn581) gauging station during calibration period (without
joint calibration) ............................................................................................................................................................... 39
Annex 14: Flow duration curves for Bhorleni (Stn581) gauging station during validation period (without
joint calibration) ............................................................................................................................................................... 40
Annex 15: Daily hydrograph of observed flow for calibration (2000-2004) and validation (2005-2008)
period at Bhorleni (Stn581) gauging station (with joint calibration) ..................................................................... 41
Annex 16: Statistical analysis for Pandheradovan station (Stn589) during monsoon season-Jun to Sep (for
calibration and validation period) ............................................................................................................................... 42
Annex 17: Statistical analysis for Bhorleni station (Stn581) during monsoon season-Jun to Sep (for
calibration and validation period) ............................................................................................................................... 43
Annex 18: Statistical analysis for Pandheradovan station (Stn589) during calibration (2000-2004) and
validation (2005-2008) period ................................................................................................................................... 44
Annex 19: Statistical analysis for Bhorleni station (Stn589) during calibration (2000-2004) and validation
(2005-2008) period ....................................................................................................................................................... 45

Page | iv
Abbreviation

DEM Digital Elevation Model
DHM Department of Hydrology and Meteorology
FDC Flow Duration Curve
GR4J Ge´nie Rural a` 4 parame`tres Journalier
HEC-HMS Hydrologic Engineering Center's Hydrologic Modelling System
ICIMOD International Center for Integrated Mountain Development
IWM Institute of Water Modelling
MODIS Moderate Resolution Spectroradiometer
NSE Nash Sutcliffe Efficiency
RVE Relative Volume Error
SCE Shuffle Complex Evolution
SMA Soil Moisture Accounting
SRTM Shuttle Radar Topographic Mission

Page | v
1. INTRODUCTION
Water resource management activities are crucial from the prospect of development to harness economic
solidity and for sustainability of natural resources and well being. These actions are only achieved through
better understanding of the hydrological system of the area, for which a reliable model and sets of data is
required. Several hydrological models have been developed and used to analyze the functioning and for
the prediction of the response of the hydrological system, that can eventually help policy makers for smart
decisions making on water resources planning and management. These hydrological models have
generally, been classified into three types, namely, a) empirical models, b) conceptual models and c)
physically based models. Physically based model, though considered to be more accurate of all, are very
data intensive and time consuming that require conceptual models are the most widespread used model
that neglects the spatial variability of the state variables and parameters (Zang and Savenije, 2005).
Having their own pros and cons, all these models share a common problem of parameter identification or
accuracy and model equifinality. There are even several uncertainties created in these models associated
with the a) input of data, b) model structure and c) model parameters. Therefore, there is no rainfall-runoff
model that precisely reflects the real situation. Also it is impossible to specify the initial and boundary
conditions required by the model with complete accuracy (Lu et al., 2009). Sometimes too many
parameters in the model (over-parameterization) and systematic errors of input data are also the source
of equifinality (Lu et al., 2009). Moreover, increasing model complexity does not necessarily provide
higher performance for a given catchment. Conceptual hydrological models have been found to perform
better on larger and/or wetter catchments than on smaller and/or drier catchments (van Esse, 2013).
Against this backdrop, this study uses a simplified conceptual rainfall-runoff model of 'Source' which tries to
simulate the flow in a more reliable and accurate way. It is a framework which provides an interface for
input, modelling, and output of flow and water resource related information.
Source has widely been applied from catchment scale, generating evidence based decision making for
water allocation and planning process. With its best practices in catchments like Great Barrier Reef of
Queensland, Lake Tai of China, Drain L catchment of Australia, Murray Darling Basin of Australia etc., for
varied issues of irrigation for crop water use and allocation for decision making, water quality for
environmental flows or wetlands restoration, hydropower etc.1 Source has proven to ease the water based
planning process through its simplified rainfall - runoff models. With this successful approach in these
countries, Source is been applied in Nepal as a pilot study to understand how the model responses in a
catchment with different climatic zone or variations. The output from this research is expected to open up
new ave nues to extensively utilize the model in other catchments of Nepal and assist in solving water
resources problems associated with flooding, drought, agriculture and industrial uses for sustainable
utilization of water resources, which is further likely to strengthen the decision making process. This research
is conducted by Nepal Development Research Institute in collaboration with Commonwealth Scientific
Industrial and Research Organization (CSIRO) of Australia. The major objective of this study is to buil d a
hydrolog ical model in Bagmati basin for better estimation of stream flow in the basin.
Bagmati River is considered as an important river among all rivers of Nepal due to its lowest water
availability per population ( Sharma and Shakya, 2006). Several studies have been conducted in Bagmati
basin by numerous authors with their different purpose. Chen and Shrestha (2006) used TANK model at
Pandheradovan gauging station in Bagmati basin and investigated the uncertainty of the model output
resulting from parameters based on three simulation techniques viz., Markov Chain Monte Carlo, Monte

1 Adams, Geoffrey."eWater Source Case Studies" (presentation lecture, New Horizon India Limited, New Delhi, 4th December,
2014)
Page | 1
Carlo simulation and Latin Hypercube simulation. Their result indicated that the model uncertainty to be
more important than the parameter uncertainty. Shrestha et al. (2008) simulated stream flow for the
period of 2002 to 2004 by comparing with observed rainfall data and with a satellite rainfall estimate
(RFE), using a semi-distributed hydrological model, GeoSFM. The timing and magnitude of flow was found
to be well simulated by the model when observed data were used, while it yielded poor results with the
RFE data. Sharma and Shakya (2006) assessed the changes in hydrology and its probable future
implication in Bagmati basin. The result indicates decrease in flood magnitude but increase in frequency
and duration along with the decrease tendency in hydropower production projected for the period of
2010, 2020 and 2030. Babel et al. (2014) applied five GCM data (CGCM3, CCSR, BRB, ECHAM4,
HadCM3 and CSIRO-MK2) and HEC-HMS model to study the potential hydrological impact in Bagmati
basin in changing climate. The result based on 30 years baseline (1970-1999) compared to three future
period from 2010-2099 (for SRES A2 and B2 scenarios) showed an increase in annual water availability,
with more rise at the end of century varying between 10.82 to 12.84%. Crop models like CROPWAT have
also been applied in the basin to quantify crop yield in different climate change scenarios (Shrestha,
2007). Flood forecasting and flood risk mapping was conducted by IWM institute of Bangladesh (2011)2
using MIKE11 in Bagmati basin. This research recommends that the rating curve at Pandheradovan
gauging station should be updated with the recent data , making them more representatives for high flood
condition.
The runoff simulations reported herein aims at investigating the capability of the Source using GR4J model,
in simulating the stream flow of the Bagmati basin.
2. STUDY AREA
The study is conducted in Bagmati Basin of Nepal as shown in Figure 1. It is a rainfall dominated basin
which ranges at an elevation of 121 to 2913 m. The catchment area of the basin at Pandheradovan is
2827 Km2 and can extend to 3550 Km2 up to the national territory i.e. Nepal-India border. The river
originates in the Mahabharat range of mountains and drains out the hills, then to Terai and finally drains
out of Nepal into India. The basin is covered by eight districts viz. Bhaktapur, Lalitpur, Kathmandu,
Kavrepalanchowk, Makwanpur, Sindhuli, Rautahat and Sarlahi. The basin is divided into three parts viz.
upper, middle and lower. The upper part of the basin where the capital of county is situated is covered by
Kathmandu, Lalitpur and Bhaktapur districts while the middle part of the basin is partially covered by
Makwanpur, Kavrepalanchowk, Sindhuli districts. The lower part lies in Rautahat and Sarlahi districts. The
study area up to Pandheradovan falls in upper and middle part of the basin. Approximately 73% of the
basin lies at an elevation range of <500m to 1500m while 27% of it is situated above 1500 m as given
in Table 1. The length of the main channel is about 195 km within Nepal and 134 km above the
Pandheradovan gauging station. Of the total area approximately 5% of the area is covered by
settlements and that is mainly in the upper part of the basin. Based on landuse map of MODIS satellite
data, majority of the basin i.e. 2/3rd of the study area has forest while 1/4th of the basin is practiced for
agriculture.
There are five gauging stations located at Sundarijal, Gaurighat, Khokana, Bhorleni and Pandheradovan
from the upstream to the downstream of the basin. The basin also harbors the first and second oldest
hydropower station of Nepal with a capacity of 500 KWh and 640 KW in Pharping and Sundarijal
respectively. Along with this, there is a single ever storage type hydropower of Nepal -Kulekhani
hydropower, with a capacity of 92 MW in Makwanpur districts. Besides hydropower, water has

2 http://hydrology.gov.np/new/hydrology/_files/efa57c381519c85c482428163535f05a.pdf
Page | 2
extensively been extracted from Bagmati River and its tributaries for dirinking purpose in Kathmandu
2
valley. About 159 km of the area in the upper part of the basin has also been gazetted as Shivapuri
Nagarjun National Park. Two 24m and 64m dam are also to be constructed in the Dhap and Nagmati
River, a major tributary of the Bagmati River, respectively to augment the dry season flow in the Bagmati
River. A Bagmati irrigation canal has also been constructed at the downstream of the Pandheradovan
gauging station in the basin.

Figure 1: Bagmati study basin
Table 1: Basin Features
District Coverage within the basin Area elevation of the basin
2 2
District Area (Km ) Percentage Elevation Zone Area (Km ) Percentage
<500 m 768.6 27.19
Bhaktapur 121.58 4.34
500-1000 m 556.9 19.71
Kathmandu 370.56 13.23
1000-1500 m 740.3 26.19
Kavrepalanchowk 342.51 12.23
1500-2500 m 747.8 26.46
Lalitpur 393.57 14.05 >2500 m 12.6 0.45
Makwanpur 626.26 22.36 Total Area 2827.2
Sindhuli 946.62 33.79

Page | 3
3. MODEL DESCRIPTION
3.1. Description of the model
GR4J is simple parsimonious conceptual, lumped, water balance model based on node-link network
(Figure 2), which translates inputs of daily rainfall
and potential evapo-transpiration data into runoff.
This is a four parameter model which has evolved
from previous three parameter model after myriad
testing and refinement in varied catchments. With
its numerous experiments conducted in France and
other countries, the model has proven to provide
better results than other rainfall runoff models like
Tank model, IHACRES, HBV, SMAR, TOPMODEL,
Xinanjiang etc (cited in Harlan et al., 2010). GR4J
model has thus been successfully applied in several
countries and used by different authors in various
hydrological studies (Servat and Dezetter 1993;
Yang and Parent, 1996; Kuczera and Parent,
1998; Yang and Michel, 2000; cited in
Andreassian et al)
Figure 2: Node link structure of the model in
In this model, the catchment is divided into number of
Bagmati basin
sub-catchments, where the flow from each sub-
catchment is computed through lumped simulation and then routed to the outlet of the catchment. As
illustrated in Figure 3, potential evapo-transpiration (E) is subtracted from rainfall (P) to determine the net
precipitation (Pn) or net evaporation (En). When rainfall is greater than potential evapo-transpiration, net
rainfall is P-E and net evapo-transpiration is considered to be zero. If rainfall is less than potenial evapo-
transipiration, net evpo-transpiration is the difference between E and P, where net rainfall is considered to
be zero. If Pn is not zero, it is partitioned between two components: production storage (S) and the channel
routing. The flow component (Pr) contributed from the combined effect of percolated flow (Pperc) from the
production storage and the rainfall component (Pn-Ps) is divided into two parts: 10% of this rainfall is
routed via a single unit hydrograph, while 90% is routed via a unit hydrograph and a non linear routing
store (R). And finally water gain or loss function (F) is applied to both flow components, representing
ground water exchange (eWater Ltd, 2013a; Harlan et al., 2010, van Esse, et al., 2013).
The key feature of the model is that it simply consists of two stores and few parameters as explained
below:

a. Production store (mm) :
Also known as Soil moisture accounting (SMA) store that determines the maximum capacity of this
store. It is storage in the surface of soil which can store rainfall, where its storage capacity highly
depends on the soil porosity. As illustrated in the model diagram (Figure 3), the process of evapo-
transpiration and percolation is prevalent in this storage (Harlan et al., 2010; Luis et al.).
Numerous modeling results indicate the parameter to provide best result at a range of 100 -1200
mm with 80% confidence interval (eWater Ltd, 2013a).
b. Water exchange coefficient:
Page | 4