Post on 23-Nov-2021
Proceedings
Proceedings International Seminar on Water Resilience in a Changing WorldBali, Indonesia, July 29th - 31st, 2016
846 halaman, xiv, 21cm x 30cm2016
Himpunan Ahli Teknik Hidraulik Indonesia (HATHI),Indonesian Association of Hydraulic EngineersSekretariat, Gedung Direktorat Jenderal SDA Lantai 8 Kementerian Pekerjaan Umum dan Perumahan RakyatJl. Pattimura 20, Kebayoran Baru, Jakarta 12110 - IndonesiaTelepon/Fax. +62-21 7279 2263http://www.hathi-pusat.org | email: hathi_pusat@yahoo.com
Scientific Commite:Dr. Christopher B. George Prof. Xie Yuebo Dr. F.X. Suryadi Prof. Tamiji Yamamoto Prof. Kang Doosun Prof. D.S. Arya Prof. Mukand Singh Babel Prof. Liong Shieyui Prof. Indratmo SoekarnoProf. Radianta Triatmadja Prof. Robertus Wahyudi Triweko
Reviewers/Editors:Prof. Dr. Ir. Sri Harto, Br., Dip., H., PU-SDAProf. Dr. Ir. Nadjadji Anwar, M.Sc., PU-SDADr. Ir. Moch. Amron, M.Sc., PU-SDAProf. Dr. Ir. Suripin M.Sc.,Doddi Yudianto, S.T., M.Sc., Ph.D.Ir. I Gusti Bagus Sila Dharma, M.T., Ph.D.
ISBN : 978-602-6289-10-0
iii
FOREWORDS
The International Seminar with special focus on “Water Resilience in a Changing World” has been held successfully from 29th to 31st July 2016 in Bali, attended by experts and professionals from many countries including Indonesian as the host. The discussions of the Seminar covered the entire aspects of the water resilience in a changing world
including its water conservation and risk and impact of extreme events, water security for all, and water governance and partnership.
The overall presentations and discussions during the seminar concluded that the outputs will undoubtedly contribute to remarkable concepts, strategies, lessons learned, and sharing of experiences on the water resilience in a changing world, particularly on the environmentally sound technologies and sustainable practices on the years to come. Based on this fact, I believe that the proceeding of this seminar will be valuable document for the implementation of the adaptation and mitigation to the climate change.
I would like to thank the organizing committee, peers and writers, seniors and all members of HATHI for enormous supports to the seminar. May God bless you all.
Bali, August 2016
Ir. Mudjiadi, M.Sc., Dip-HE.Chairman of HATHI
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TABLE OF CONTENTS
Forewords ........................................................................................................... iii
Table of Content .................................................................................................. v
SUB THEME 1 Water Conservation and Risk and Impact of Extreme EventsBasin conservation, river restoration, reservoir and dam, flood and drought, climate change, urban drainage
1. Water Resilience in A Large Alluvial Fan: Case Study Yahukimo Alluvial Fan ............................................................. 1Happy Mulia, Supriya Triwiyana, Bagus Kurniawan
2. Reliability of Hydrological Model Parameters in Representing The Physical Condition of Jiangwan River Basin ....................................... 11Christian Alfonsus Liguori, Steven Reinaldo Rusli, Doddi Yudianto
3. Soil Loss Prediction At The Catchments of Reservoir in Central Java, Indonesia, Using Rusle-GIS Framework .................................................... 22Muh. Ramdhan Olii, Bambang Agus Kironoto, Sunjoto, Bambang Yulistiyanto,
4. Analysis of Land Cover Change and Its Impact to Surface Runoff within Jakabaring Sub Basin ....................................................................... 33M. Baitullah Al Amin, Sarino, and Reini S. Ilmiaty
5. The Cause of Giant Spring Depletion in The Rejoso Watershed ................ 44Wulan Seizarwati, Agus M. Ramdhan, Lambok M. Hutasoit, Heni Rengganis
6. Developing Bayesian Probabilistic Flash Flood Guidance for Konto River Basin Indonesia ................................................................. 55Astria Nugrahany
7. Local Scour Defense Around The Sluice Gate Based on The Gate Operation and Maintenance ................................................... 66Nina B. Rustiati, Vera W. Andiese
8. Changes to Flow and Turbulence Caused By Hyper-Concentrated Sediment Laden Flow Over Square Ribs Roughness .................................. 75Liany Hendratta, Sukarno, Terunori Ohmoto, Djidon Watania, A.K.T. Dundu
9. The Development of River Performance Assessment Method ................... 84Agus Hari Wahyudi, Suripin, Suharyanto
10. Determination of River Bed Stabilization Structures Placement Based on Satellite Data ............................................................................... 97Santosa Sandy Putra, Bobby Neilzon
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11. Challenges to Achieve Water-Related Disaster Risk Reduction Through Proper Development of The Infrastructures in Bangladesh ........................ 108Kazumitsu Muraoka, Khondaker Khalequzzaman
12. The Relationship Between The Manning Roughness Coefficient and Form the Bed Configuration of Non Cohesive Alluvial Channels ....................... 119Hari Wibowo, Suripin, Kodoatie, Isdiyana
13. The Seismic Analysis of An Earth-Fill Dam on Thick Liquefiable Ground and Countermeasures Against A Large Earthquake .................................... 130Tomoo Kato, Takeshi Honda, and Shigehide Kawato
14. A Genetic Algorithm Model for Optimization of Tank Model Parameters in Keser Sub-Watershed .............................................................................. 141Widandi Soetopo, Lily Montarcih Limantara, and Annisa Akalily
15. Efficient Sediment Flushing for Sustainable Sediment Management in Wlingi and Lodoyo Reservoirs ............................................................... 151Fahmi Hidayat, Harianto, Pitojo Tri Juwono, Agus Suharyanto, Alwafi Pujiraharjo, Arief Satria Marsudi
16. Finite Difference Numerical Scheme for Simulating Dam Break Flow ..... 162Mohammad Farid, Bagus Pramono Yakti, Akbar Rizaldi, and Mohammad Bagus Adityawan
17. Soil Grouting Method Alternative to Preserve Heritage Dams from Collapse: Kedung Uling Dam, Cengklik Dam and Lalung Dam ................ 173Y. Chandra Sari, Sudarsono, Dwiyanto Joko Suprapto
18. Improving Modified ICOLD Method with Loss of Life Index for Dam Safety Risk Assessment in Indonesia ............................................ 184Anto Henrianto, R.W Triweko
19. Fractal Characteristic Analysis of Watershed Based on Geographical Information System ..................................................................................... 194I Gede Tunas, Nadjadji Anwar, Umboro Lasminto
20. Flood Control Management in The Brantas River Basin ............................. 205Hermien Indraswari, Oky Widya Wirabuana, Agung Wicaksono
21. Drainage Impact on Subsidence and Carbon Emissions in Peatland ........... 215L. Budi Triadi
22. Simulation of River Pond Scenario on Reducing The Discharge Peak of Ngotok River ............................................................................................ 225Gilang Idfi, Wasis Wardoyo
23. Flood Forecasting Map of Code River in Yogyakarta .................................. 236Titiek Widyasari and Nizar Achmad
24. Towards Responsive Flood Control Measures in The Philippine Setting .... 246Jessie C. Felizardo
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25. The Effect of Retarding Basin on Flood Management in The Upper Citarum River .............................................................................................. 257Yadi Suryadi, Febya Nurnadiati, and Indratmo Soekarno
26. Evaluation and Mitigation of The Bogel River Flood, Blitar, Province of East Java, Indonesia ..................................................................................... 268Aris Yhadianto, Ulie M.Dewanto
27. Integrated Flood Management Plan of the Huong river basin ..................... 279Le Dien Minh
28. Flood Mitigation Using GIS and Hydraulic Modelling of Urban Agriculture District Pulokerto ...................................................................... 287Febrinasti Alia, Darma Budhy, A. Bastari Yusak, R.A Marlina Sylvia
29. Rainfall-Run Off Simulation and The Associated Extent of Flooding in The South of Bandung, Indonesia ................................................................ 298Tri Annisa Fajri, Poerbandono, Djoko Abi Suroso, Miga Magenika Julian
30. Hydrological Drought Index Using River Discharge Computed from TRMM Rainfall Satellite Data ..................................................................... 305Waluyo Hatmoko, Radhika
31. Flood Early Warning System in Bangladesh As Vital Non-Structural Measures ....................................................................................................... 315Hossain Md. Amirul
32. Determination of Sensitive Area to Peak Flow within a Watershed ............ 325Anthony Raymond Kemur, Robert Verhaeghe, Suharyanto, Suripin
33. Physical Model of Flood Propagation Around Buildings Due to Dambreak .. 336Vitta Pratiwi, Hadi Kardhana, M. Syahril B.K
34. Study on Effectiveness of Diversion Tunnel from Ciliwung River to East Flood Way in Decreasing Flood Water Level............................................... 347Chairunnisa, Agustin Purwanti, Anis Adiana Pratiwi, Gea Alif Hamzah
35. Jakarta Flood Hazard Modeling Framework: The Flood Event of March 2016 .................................................................. 355Maulina Indriyani, Aditya Riski Taufani, Jan Jaap Brinkman, Geert Prinsen, Tarasinta Perwitasari, Muchni
36. Efferctiveness of Hypotetic Rentention Ponds Simulation on The Integrated Flood Management System Case Study: Saddang Watershed, South Celebes, Indonesia ............................................................................. 366Evi Anggraheni, Dwita Sutjiningsih
37. Analysis of Backwater Due to Kalanganyar Shortcut in Pasuruan .............. 377Muhammad Hafiizh Imaaduddiin, Tatas
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38. Catchment Area Management for Sustainable Paselloreng Dam in Connection with The Global Climate Change ............................................. 383Iskandar Rahim, Subandi, Sumardji, Muhammad Akil, Anshar, Mustafa, Tampang, Muhammad Hasbi, M. K. Nizam Lembah, Arnold. M. Ratu, Agus Hasanie
39. Vunerability of Water Resources Due to Climate Change in Batang Regency ........................................................................................................ 394Suseno Darsono, Ronny Sutrisna, Ratih Pujiastuti, Susilowati
40. Rasionalization of Rainfall Station Network in Bengawan Solo River Basin ............................................................................................................. 405Y. Chandra Sari, Fisnu Yudha Pramono, Suripin
41. Projected of Rainfall in Mahakam River Basin Based on Global Circulation Models (GCM) .......................................................................... 416Mislan and Kadek Subagiada
42. Impacts of Climate Change/ Variability on The World’S Lakes: A Case Study of Lake Urmia .................................................................................... 427Alireza Salamat
43. Analysis of Runoff Coefficients Against High of Monthly Rainfall to The Design Criteria of ‘Embung’ in Semiarid Region ........................................ 436Denik Sri Krisnayanti, Wilhelmus Bunganaen
44. Comparison of Ground Stations and GPCC Rainfall Data Set Case Studies: Citarum Basin ................................................................................. 446Levina, Wanny K Adidarma, Hany Agustiani
45. Evaluation of Pumping Operation System Under Daily Basis Rainfall ....... 452Obaja Triputera Wijaya, Utari W., Doddi Y
46. The Use of Rainfall Simulator in The Modelling of Rainfall-Runoff on A Paving Block Surface .................................................................................. 461Laksni Sedyowati, Eko Indah Susanti
47. Analyses on Water Cycle and Land Subsidence for Semarang City and Neighboring Area, Central Java, Indonesia .................................................. 471Ni Made Sumiarsih, Nagata Hitoshi, Ide Yuji, Morishita Kanehiro, Shimizu Hiroshi
48. Potential Mapping of Coastal Inundation in Bali Island .............................. 482Suprapto, C.N.R. Nugroho, Hadisantosa, Sutanto M.H., Leo E. Sembiring
49. The Impact of Bali Mandara Toll Road Construction on The Surrounding Coastal Environment .................................................................................... 493Sulaiman, D.M., M.H. Setiawan, and M. R. Nugraha
50. Analysis of Inundation Mitigation Using SWMM (Storm Water Management Model) ................................................................................... 504Yang Ratri Savitri
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51. Individual Polders as an alternative to flood control in the Center of Padang City Goverment at Air Pacah ........................................................... 515Zahrul Umar, Bambang Istijono, Syafril Daus, Rifda Suryani,
52. Arrangement in Flood Control and Water Quality in Urban Drainage System : Case Study Kali Wonorejo Surabaya ............................................. 526Minarni N. T., Novirina H., Iwan W., and Pancawati D.
53. Building with Nature – Indonesia; Towards A Sustainable Protection of Mangrove Coasts .......................................................................................... 532Winterwerp, J.C., Wilms, T., Van Wesenbeeck, B.K., Cronin, K., Tonneijck, F, Van Eijk, P., Van Thiel de Vries, J.
54. Tsunami Wave Height and Velocity Reduction by Coastal Forest Canopy .... 542Novi Andhi Setyo Purwono, Nizam, Triatmadja, R
55. National Capital Integrated Coastal Development - Stage A: An Adaptive Design, Its Challenges and Opportunities .................................................... 554Dadang Muhamad Yahya, Ferdinanto
56. Tsunami Run-Up on Sloping Beach Based on Dam Break System ............. 565Benazir, Radianta Triatmadja, Adam Pamudji Rahardjo, and Nur Yuwono
57. Wave Predictions and Deformation Along Makassar Coast ........................ 575Frans Rabung*, M. Saleh Pallu, M. Arsyad Thaha, and Achmad B. Muhiddin
58. Scouring Characteristic Around Structure Due to Wave Current ................. 585Oki Setyandito, Juliastuti, P. Simon Sihombing, Irpan Hidayat
SUB THEME 2 Water Security for AllWater conflict, water supply and distribution, water pollution and sanitation, water-food-energy nexus
59. Effect Cropping Schedule for Water Irrigation Efficient ............................. 595Tamrin Rahman
60. Study of Water Resources Availability and Water Supply Needs in Mebidangro North Sumatera Province Indonesia ........................................ 608Makmur Ginting
61. Mahakam River as A Potential Raw Water Source on Regional Basis for Balikpapan, Samarinda and Kutai Kartanegara Area ................................... 619Alimudin, Hasyim Saleh Daulay
62. Klambu Kudu Water Distribution Canal for Semarang City ........................ 630Ni Made Sumiarsih, Djoko Legono, Robert J. Kodoatie
63. An Assessment for Water Supply from Rawa Biru (Blue Lake), Merauke, Papua ............................................................................................ 638Elisabeth Veronika Wambrauw, Happy Mulya
64. The Development of Concrete Filter for Drinking Water Filtration ............ 648Rizaldi Maadji, Radianta Triatmadja, Fatchan Nurrochmad, and Sunjoto
65. Study in Developing of Urban Water Security Dimension in Indonesia ...... 659Jane E. Wuysang, Robertus Wahyudi Triweko, Doddi Yudianto
66. Optimization of Water Use in Delta Brantas Irrigation Area to Improve Water Supply Insidoarjo ............................................................................... 665Mona Shinta Safitri, Nadjadji Anwar
67. Determining The Location of The Floodgates on The Mixing of Brackish Water in Tambak Irrigation .......................................................................... 676Dian Noorvy Khaerudin, Edyson
68. Optimization Model for Cropping Pattern Using Linear Programming: Case Study of Rambut Irrigation in Tegal District, Central Java Province .. 684Dhemi Harlan, Dina Septyana, Winskayati
69. The Development of Numerical Model for Sea Current Energy Site Selection in Indonesia .................................................................................. 695Surya Hermawan
70. Implementation of Decision Support System to Determine Cropping Pattern in Irrigation Operation .................................................................... 706Murtiningrum, Sudjarwadi, Rachmad Jayadi, Putu Sudira
71. An Introduction of Simulation Model for Water, Energy, and Food Nexus ... 717Albert Wicaksono, Gimoon Jeong, Doosun Kang
SUB THEME 3 Water Governance and PartnershipWater council, water governance, community based/drived activity, public private partnership
72. Water Resources Management of Bangladesh Potentials and Problems ..... 727Khalequzzaman, K., Hossain Md. Amirul
73. Water Resources Modelling Framework for Indonesia ................................ 738Irfan Sudono, Maulina Indriyani, Radhika Radhika, Wulan Seizarwati, Neeltje Goorden, and Daniel Tollenaar
74. Post Investment Evaluation of The Cacaban Rehabilitation Project in Central Java Province ............................................................................... 749Putri Arumsari, Juliastuti
75. Creation and Experimentation of Narbo IWRM Indicator ........................... 757Koichiro Omoto, Tadashige Kawasaki, Kenji Komaki, Kentaro Kido
76. Smart Water Management Through Coordinated Operation of Multi-Water Facilities in The Cisangkuy River Basin, Indonesia .................................... 767Ick Hwan Ko, YJ Kim, TW Kim, W Putuhena, I Sudono, SS Lee, SW Kim
77. Historical Efforts on Development of Water Resources for Lower Solo Rivers .................................................................................. 777Y. Chandra Sari, Junichi Fukuwatari
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78. Risk Management of Dam Failure in Brantas and Bengawan Solo River Basins ................................................................ 788Marturiawan Kristyono Putro, Titik Indahyani, Didih Hermawan
79. Challenges in Improving Quality of Life and Restoring Cikapundung River Through Community Empowerment .................................................. 799Yudianto, D., Susanti, I., Roy, A.F., Karyadi, Y., Widjaja, G.P., Nugraheni, S., Suroso, P.C., Putri, F.E.
80. The Motion for Rainwater Management in Household to Improve Water Resilience in A Changing World ........................................................ 810Susilawati and Nisanson
81. Public Participation in Water-Related Flood Mitigation as Inexpensive Early Warning System .................................................................................. 818Reni Mayasari, Mouli De Rizka Dewantoro
82. Restoration of Cikapundung River ............................................................... 826Yudha Mediawan, Dwi Aryani Semadhi Kubontubuh, R. Yayat Yuliana, Devi Kumalasari
83. SI WAMI: A Software System to Determine Water Availability of Main Irrigation Intakes in Indonesia ...................................................................... 837Grashoff, P.S., Sudono, I., Ahyadi, H., Tollenaar, D., Diest, W.J. van, Brinkman, J.J.
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RELIABILITY OF HYDROLOGICAL MODEL PARAMETERS IN REPRESENTING THE PHYSICAL
CONDITION OF JIANGWAN RIVER BASIN
Christian Alfonsus Liguori*, Steven Reinaldo Rusli, and Doddi Yudianto
Civil Engineering Department, Parahyangan Catholic University
* e-mail: alfonchristian@gmail.com
Abstract
Many developed hydrological models are found today due to the necessity of hydrological information. Various studies have been conducted to find the appropriate hydrological model among lot to simulate catchment response. This study, therefore, is aimed to examine the performance of three hydrological models (NAM, HBV96, & Xinanjiang) based on each model quantitative performance and parameter reliability to represent the actual conserved catchment physical condition. By using Jiangwan river basin as the study catchment, it is found that all models deliver satisfying simulation with average NS values for NAM, Xinanjiang and HBV96 respectively are 0.63, 0.47 and 0.59, all categorized as satisfactory simulation. Moreover, the average RVE values are also satisfying at 0.21, 0.06 and 0.21. However, considering the model parameter suitability to the actual condition, NAM and Xinanjiang model are more reliable to deliver better representation of the catchment physical condition than HBV96 model. Their model parameter tends to be consistent, while on the other hand, HBV96 model parameter values are fluctuated. It shows disagreement with the actual catchment conservation, which leads to unreliable model parameters.
Keywords: HBV96 model, Hydrological model parameters, Jiangwan river basin, NAM model, Xinanjiang model
INTRODUCTION
General Background
As a fundamental aspect for human life, integrated water resources management is not only an option, but a must (Zaag, 2005). It was also stated by Uhlenbrook and Sieber (2005), that in achieving optimal management of water resources, the
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ability to reliably model hydrological processes is very essential. Hydrological
models, related to this, are not only capable to analyze land use change pattern,
but also to provide short and long term stream flow forecasting. Moreover, the
proficiency of providing such information becomes also more important than ever,
especially considering its usage in highly wide water-related policies derivation
such as river basin management, river abstraction, effluent dilution, navigation,
ecosystem protection and amenities (World Meteorological Organization, 2009).
Considering the necessity of the hydrological information, various water balance
models have been presented and many researches have been intensively
conducted (Xiong and Guo, 1999), which later results the development of
numerous hydrological models, for example USA (Sacramento model), South
Africa (Pitman model), Ireland (SMAR model), Sweden (HBV96) model,
Denmark (NAM model), China (Xinanjiang model) and so on. With various
hydrological models those have been developed, number of studies have
compared results obtained with models of varying complexities (Das, et. al.,
2008). This study therefore is aimed to examine three hydrological models (NAM,
HBV96, & Xinanjiang) based on each model parameter reliability, which refers to
the model capability in representing the actual catchment physical condition.
Explanation about literature study
NAM (NedbØr-AfstrØmnings Model)
NAM is a rainfall-runoff model developed by Danish Hydraulic Institute (DHI,
1973). Based on its basic concept and spatial variability, NAM is categorized as
deterministic and lumped conceptual model. It generates runoff by continuously
accounting the moisture content in three mutually interrelated storages (snow
storage, surface storage, and lower zone storage). As shown in Figure 1, the inputs
for NAM model are precipitation, potential evapotranspiration, temperature (only
if the snow routine is used), and observed runoff for calibration process. Equipped
with 9 parameters and 4 time constants, NAM model is able to generate reliable
estimated runoff in many different countries with different climates e.g. for
hydrological studies in Greenland, Thailand, and Philippines (de Laat,1999).
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Figure 1. Structure of NAM (de Laat, 1999)
Xinanjiang Model
Xinanjiang model is a world-wide used model and has been proved to perform
consistently better in dry area than most hydrological model developed in any
other part in the world (Gan, 1997). It was initially constructed by Zhao, et al. in
1980 with its main advantages over other model as the capability to consider non-
uniform spatial distribution in its runoff generation. Moreover, Xinanjiang divides
its sub-surface flow in detail into interflow and groundwater flow. Conceptually,
the structure of standard Xinanjiang model consists of four main calculation steps;
they are evapotranspiration calculation (using three layers’ soil moisture concept),
runoff generation (using the repletion of storage concept), runoff separation (using
Horton division of surface runoff, interflow and groundwater flow) and runoff
routing (using Muskingum method) with total of 15 parameters - distributed
within each calculation process (Zhao, et al. 1980). Generally, its model structure
and model parameter can be seen through Figure 2.
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Figure 2. Xinanjiang Model Structure
HBV96 Model (Hydrologiska Byråns Vattenbalansavedlning)
Developed in the close region as NAM in Denmark, HBV96 was developed in
Sweden by the Swedish Meteorological and Hydrological Institute (SMHI),
initially in 1972 before model adaptation and adjustment are numerously made
before its HBV96 model version. Its capability in conducting hydrological
analysis related to water balance has been well known and according to the study
of Bergstrom (1992), HBV model has been used in more than 30 countries.
Without consideration of the snow routine process, HBV model structure consists
of three main box layers; the soil box, upper response box and lower response
box, as shown in Figure 3. The whole water fluxes among boxes are traced and
connected by parameters and formulas to deliver runoff as the model output.
Figure 3. Structure of HBV96 Model
Evapotranspiration calculation Runoff
generation Runoff separation
Runoff routing
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Objective Functions
To assess models’ output quality, Nash-Sutcliffe and Relative Volume Error (NS
& RVE) are employed as it has been used in many researches (Gan, et al., 1997;
Xiong, L. and Guo, S., 1999; Xu, et.al., 2010; Rusli, S.R., 2014, Liguori, C.A.,
2016). Below is the formula to calculate the objective functions values:
(1)
(1)
where
NS : nash – sutcliffe efficiency
Qsim : simulated discharge (m3/s)
Qobs : observed discharge (m3/s)
obsQ : mean observed discharge (m3/s)
(2)
where
RVE : relative volume error
Qsim : simulated discharge (m3/s)
Qobs : observed discharge (m3/s)
Study Area
As it has been mentioned, Jiangwan river basin is selected as the study area in this
research. Located in Zhejiang Province, China at 30º 25' N and 119º 45' E (see
Figure 4) with total area of 20.9 km2, Jiangwan is mostly covered by bamboo
vegetation. Topographically, it slopes at 25º to 45º; therefore, flash floods often
occurred in Jiangwan. However, the river is mostly dry during summer and winter
season. These two contradictory phenomena are happening due to geological
cracks those let the water flow from the surface to the sub-surface layer easily.
∑
∑
=
=
−= n
iobs
n
iobssim
i
ii
Q
QQRVE
1
1
∑
∑
=
=
−
−−= n
iobsobs
n
isimobs
QQNS
i
ii
1
2
1
2
)(
)(1
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Figure 4. Jiangwan River Basin
Methodology of Study
Generally, there are four principal frameworks in this research: (1) data collection,
(2) model construction, (3) model calibration, and (4) results examination. Data
collection compiles the daily precipitation and flow measurement database. In this
study, time-series data from 1971 to 1986 is chosen as the time constrain
considering the data availability. Furthermore, each model is built based on their
own structure and parameters; and typical objective functions are applied as equal
evaluation platform. After determining the objective functions, model calibration
is conducted to achieve the best possible fit between the simulation and observed
data. Annual calibration is the chosen temporal framework in order to evaluate not
only the model capability to simulate runoff, but also the model parameter
stability (Rusli, 2015). The model parameters then are evaluated quantitatively
through the objective function values, with their stability and suitability to the
actual physical condition. In short, there are two main aspects to be observed as
the model evaluation and results examination criteria: (1) the appropriateness
between model parameter value and consistency to the actual catchment physical
condition and (2) the output quality through objective functions values, based on
the categorization made by Movotilov, et al. (1999) which categorize any
simulation to three categories; good (NS > 0.75), satisfactory (0.36 < NS < 0.75)
and unsatisfactory (NS < 0.36).
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RESULTS AND DISCUSSION
Based on the analysis results and the standard made by Motovilov, et al. (1999),
all models are able to deliver good simulation. The average NS for NAM,
Xinanjiang and HBV96 respectively are 0.63, 0.47 and 0.59. Meanwhile, the RVE
value delivers average of 0.21, 0.06 and 0.21 in same fashion, which are also
good. The best simulation of NAM delivers NS and RVE value of 0.82 and 0.04,
Xinanjiang delivers 0.84 and 0.00, and HBV96 delivers 0.75 and 0.00. Figure 5
shows the best fit calibration of the three model, obtained in year 1975. Besides,
the whole calibration results objective functions values are shown in Figure 6,
with green color indicates good simulation and red as poor one.
0.00
10.00
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60.00
70.00
80.00
90.00
100.000
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5
6
7
Rainfa
ll (m
m/day)
Flow
(m3/s
)
Date
Precipitation Qobserved NAM
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Rainfa
ll (m
m/day)
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(m3/s
)
Date
Precipitation Qobserved Xinanjiang
0.00
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Rainfa
ll (m
m/day)
Flow
(m3/s
)
Date
Precipitation Qobserved HBV96
Figure 5. Calibration Result of All Models, 1975
NAM
Xinanjiang
HBV96
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Year 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986NAM 0.73 0.63 0.73 0.75 0.82 0.70 -0.37 0.55 0.75 0.72 0.75 0.74 0.69 0.73 0.39 0.74
Xinanjiang 0.84 0.78 0.57 0.81 0.82 0.36 -1.39 0.72 0.59 0.22 0.54 0.77 0.69 0.62 0.16 0.39HBV96 0.68 0.47 0.62 0.74 0.75 0.38 0.51 0.56 0.66 0.45 0.53 0.63 0.65 0.62 0.66 0.47
Nash-Sutcliffe
Year 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986NAM 0.22 0.24 0.09 0.26 0.13 0.17 0.45 0.39 0.31 0.20 0.23 0.18 0.10 0.13 0.04 0.27
Xinanjiang 0.10 0.01 0.03 0.06 0.00 0.00 0.30 0.06 0.08 0.03 0.06 0.06 0.03 0.06 0.09 0.06HBV96 0.64 0.36 0.03 0.25 0.01 0.10 0.50 0.12 0.08 0.00 0.41 0.44 0.16 0.92 0.32 0.16
Relative Volume
Error
Figure 6. Objective Function Values
Although the NS and RVE values are satisfying, accountable simulation should be
able to represent the actual hydrological cycle within the study area. Thus,
through the examination of annual parameter fluctuation, the suitability of each
model to Jiangwan river basin conserved hydrological characteristics is evaluated.
Suitable model ought to deliver parameters with steady values, as well as the
steadiness characteristics of Jiangwan river basin within the simulated time frame.
Figure 7 to 9 below shows the fluctuation of each model parameter values, with
light color indicates good stability and dark color shows notable alteration.
Figure 7. Xinanjiang Parameter Stability
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Year 1971 1972 1973 1974 1975 1976 1977 1978 1979 1980 1981 1982 1983 1984 1985 1986
Lmax 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
Umax 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
Cmelt 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
CQOF 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
CQIF 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
CBFL 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
CLIF 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
CLOF 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
CLG 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
CK1 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
CK2 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
CKBFU 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
CKBFL 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00 1.00
Figure 8. NAM Parameter Stability
Figure 9. HBV96 Parameter Stability
It can be seen clearly that HBV96 does not give a good performance through its
stochastic parameter changes within each year (represented by dominant dark
colored box in Figure 9); moreover, those results are not in accordance with the
actual physical condition of Jiangwan river basin (Rusli, et al. 2015). The changes
of parameter PERC, kf, k4, α, and β are not suitable, since the actual condition of
Jiangwan is more well-conserved than the values those are given by the
mentioned parameters. Although the objective function values are satisfying
(average NS value of 0.587 and RVE 0.211), the calibrated model and its
parameter are not good enough to be validated or be used for further hydrological
forecast. Meanwhile, the other two models; NAM and Xinanjiang deliver much
better performances than HBV96 through its consistent parameter for the whole
calibration period. Figure 7 and 8 above show the stable parameter of Xinanjiang
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and moreover, NAM. While 4 to 6 parameter of Xinanjiang found to be altered in
several years, the parameters of NAM for the whole 10-year calibration are found
to be constant. The resembling performance of NAM and Xinanjiang and their
performances those overcome one resulted by HBV is then analyzed to be caused
by the similar amount of NAM and Xinanjiang model parameter which, yet again,
is more compared to HBV96; Xinanjiang model has 15 parameters, NAM model
has 12 parameters and HBV96 model has only 9 parameters.
CONCLUSION AND RECOMMENDATION
From the works conducted in this research, several conclusions are derived.
Quantitatively through objective functions values, the hydrological models
calibrations show good performances by NAM, Xinanjiang and HBV96 model.
Average NS value for NAM, Xinanjiang and HBV96 are respectively 0.63, 0.47
and 0.59, all categorized as satisfactory simulation. Meanwhile, the average RVE
value are 0.21, 0.06 and 0.21. The good calibrations are supported not only by the
well-established model structure, but also the data quality which is taken from
Jiangwan research catchment. This emphasizes the importance of qualified
hydrological data, which sometimes are hard to be collected in developing
countries. However, good calibration should not be only judged quantitatively
without considering the actual physical condition of the catchment. This study
proves that good calibration does not ensure model suitability to be implemented
further in a catchment, as HBV96 model parameter is found to alter significantly
in disagree fashion with the conserved Jiangwan river basin. NAM and
Xinanjiang model are chosen as the better model to be applied in Jiangwan
catchment due to the satisfying objective function values and parameter stability.
ACKNOWLEDGEMENTS
This work was supported by the National Natural Science Foundation of China
(grants 41271040), and the Special Fund of State Key Laboratory of Hydrology-
Water Resources & Hydraulic Engineering, Hohai University (No. 20145028012).
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