Hydrologic and Water Resources Modelling for the Ganges Basin

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HYDROLOGIC AND WATER RESOURCES MODELLING FOR THE GANGES BASIN

Public Disclosure Authorized A Compilation and Bibliography

Public Disclosure Authorized

TABLE OF CONTENTS

Introduction ...... 3 Compilation of Recent/ Current Modelling Work ...... 4 Bibliography ...... 58

INTRODUCTION The Ganges River Basin is one of the largest river basins in the world, covering around 1.2 million km2. The basin spans India (84%), Nepal (12%), Bangladesh (3%) and China (1%). It rises in the Himalayas, traverses the fertile plains of India and Bangladesh, and flows into the Bay of Bengal through the world’s largest mangrove ecosystem, the Sundarbans of the Ganges Delta. Its major tributaries are the primarily rain-fed Himalayan rivers of India and Nepal. The delta is characterized by extensive series of distributary channels, including the Damodar-Hooghly River, but the main basin outlet is the main stem of the Ganges – called the Padma in Bangladesh – that merges with the Brahmaputra before flowing into the sea. The hydrology of the basin is dominated by the annual monsoon that delivers about 80% of annual inflows in just three months of the year. On average, around 1200 billion m3 of precipitation fall in the basin each year, of which around 500 billion m3 becomes stream flow. The extensive and high-yielding alluvial aquifers of the basin are critical part of the hydrologic system and the water resource.

The Ganges is the world’s most populous river basin, home to more than 655 million people with high population density and poverty is widespread. It is also one of the world’s most revered rivers with deep spiritual and cultural significance for millions of people both within and beyond the basin. The basin resources are hugely significant economically for the riparian countries. Agriculture dominates water use, with irrigation currently representing about 90% of the basin’s combined surface and ground water uses. However, agricultural productivity in the basin is low compared to global averages. Improving water productivity would significantly contribute to food security, poverty reduction, and economic growth in the basin. Hydropower generation is critical to the economy of Nepal, and developing the untapped hydropower potential in Nepal is an ongoing development challenge with major transboundary dimensions. With increasing in urbanization and industrialization, the magnitude and sector balance of water demand is changing, giving rise to increased competition for water and increased stress on water dependent ecosystems. Flooding is a frequent occurrence in many parts of the basin with serious loss of life and economic damage. There is great potential for economic development and poverty reduction through more balanced and sustainable management of the water resources of the basin, but charting a trajectory towards this future requires a sound analytical basis.

There are many analytical approaches that can help inform policy directions for the Ganges Basin. One important category of analytical tools are models of the hydrological processes and water resources systems. This report provides an introduction to the modelling work of this type undertaken to-date. The report pulls together two resources: (i) a compilation of current and ongoing modelling efforts, and (ii) a bibliography of over one hundred published papers on hydrologic or water resources modelling relevant to the Ganges Basin. The report is intended as a resource document for technical experts interested in water modelling for the Ganges Basin.

The modeling efforts to-date have informed hydrologic characterization, water resource assessments, water resource planning, flood management, water quality assessment, groundwater management, climate change impact assessment, sedimentation and environmental management. Perhaps the biggest challenge faced in hydrologic and water resources modelling for the Ganges Basin pertains to the adequacy and accessibility of data. Much of the data required for setting up and calibrating reliable hydrologic or water resources models is either of poor quality (spatially or temporally sparse, unverified, etc) or not available because of government controls on water data. This has pampers the ability to build robust well calibrated models, which in turn leads to uncertainty and lack of agreement on issues such as flow patterns, surface-groundwater interactions, water availability, consumptive use and sharing. Without improved transparency on water data and knowledge, it will be difficult to move towards more efficient, cooperative and sustainable water management across the Ganges Basin.

COMPILATION OF RECENT/ CURRENT MODELLING WORK

Snowmelt contributions to discharge of the Ganges. Quantify and clarify current Title/Purpose temporal and spatial contributions of snowmelt to runoff in the Ganges basin. C. Siderius1, H. Biemans1, A. Wiltshire2, S. Rao3, W.H.P. Franssen1, P. Kumar4, A.K. Author(s) Gosain3, M.T.H. van Vliet1, D.N. Collins5 1Wageningen University & Research Centre, 2Met Office Hadley Centre, 3IIT Delhi, 4Max Institution(s) Planck Institute for Meteorology, 5University of Salford Model(s) VIC, JULES, LPJmL and SWAT Currency 2013? Unknown duration Scope Surface water quantity simulation (snowmelt contributions) Model/Data Description The article delineated the Ganges basin using gridded cells with a 0.5-degree resolution (for all models except SWAT). It discusses four models: SWAT, Jules, LPJml and VIC. In all, only natural streamflow was modelled. No account was made for water allocation or demand management. Runoff was generated from water percolating through the soil column as a result of rainfall and snowmelt. Since the components were not treated separately when they entered the soil column, the proportion had to be calculated each month for each grid cell. To account for losses in the soil column, the snowmelt runoff did not exceed the total snowmelt from the previous month. Moreover, the proportions of snowmelt runoff did not exceed the snowmelt to rainfall ratio. The WATCH dataset (0.5° X 0.5°) was used to drive the hydrological models. SWAT runoff modelling used the Soil Conservation Service (USDA NRCS) methodology, while the Jules, LPJml, and VIC models were based on the water balance equation. Snowmelt and total runoff were routed using the STN routing scheme. Availability/Accessibility Model Public domain (but requires proprietary ArcGIS) Input data files published: Not Published Data files Output data files: Not published Report(s) Technical report produced: Unknown Report on inter-comparison of the relative performance of the three modelling Other publications approaches {Collins, 2012 #19} Spatial and Temporal Boundaries Spatial Extent Ganges Basin Outlet Point Farakka Barrage Temporal Monthly Resolution Time Period 1971-2000 Data Requirements Component Source Publicly Available DEM GTOPO30 Yes MODIS Yes University of Maryland Global Land Cover Yes Land Use/Cover US Geological Survey Yes IWMI Yes 4

Global Environment Monitoring Yes Soils FAO, International Soil Reference and Information Centre Yes Meteorological Center for Ecology and Hydrology Yes Global Runoff Data Centre Yes Runoff Data Wadia Institute No Key Assumptions and Limitations Reservoirs have no major effect on streamflow. Assumptions Conversion from snowmelt to runoff are the same for glaciers and snowmelt. Air temperature and discharge data are scarce in the Himalayan Region. High altitude climate stations are lacking including Tibetan plateau. No account of water demand and allocation estimates is provided. Data Limitations Coarse grid cells are used for Tehri. Models are affected by heterogeneity of mountainous areas. Global soil thickness database can affect formation of runoff and evaporative losses. SWAT has only a simplified snowmelt model. There is a lack of elevation bands for LPJmL Model Limitations and JULES. In VIC, only natural stream flow is used; groundwater is not accounted. A Hydrodynamic Approach to Address the Yamuna Riverbed Development in Delhi. Title/Purpose Assess channel improvements to the Yamuna River to reduce flooding. Author(s) Ritesh Vijay, Aabha Sargaonkar, and Apurba Gupta Institution(s) National Environmental Engineering Research Institute Model(s) RiverCAD (HEC-RAS) Currency 2008? Unknown duration Scope Hydrodynamic modelling and water simulation Model/Data Description The modelling was performed on the 23 km reach from Wazirabad to Okhla Barrage. Flood frequency flows were determined using the Gumbel Extreme Value for the 10, 25, 50, 100-year storm based on 41 years of record. Surfer was used to generate a DEM using 101 field survey cross-sections with a spacing of 200-300 meters. Seven bridges barrages were included based on hydraulic geometry. Manning’s coefficient values were obtained from the literature value. HEC-RAS were used to determine the water surface profile applying the energy equation an iterative process called the standard step method. Availability/Accessibility Model Public domain but requires proprietary interface Input data files: Not published Data files Output data files: Not published Report(s) Technical report produced: unknown Hydrodynamic Simulation of River Yamuna for Riverbed Assessment: A Case Study of Other publications Delhi Region {Vijay, 2007 #219} Spatial and Temporal Boundaries Spatial Extent Yamuna River (28°28’ 05” – 28°54’ 36” N and 77°09’ – 77°24’ E Outlet Point Wazirabad Barrage (upstream) to Okhla (downstream) (23 km reach)

Temporal Steady State Resolution Time Period NA Data Requirements Component Source Publicly Available DEM Field Survey No Flow Data Flood Frequency Analysis Yes Water Surface Gauge Records Yes Elevation Hydraulic Structure Unknown Unknown Geometry Key Assumptions and Limitations Flood frequency analysis assumes the sample is representative of the population, Assumptions stationarity, and sufficient record length. Stream is a threshold stream (very little sediment). Dredged sediment suitable for the floodplain. Channel bed boundary is fixed. Lack of information on channel morpho-dynamics for Yamuna River. Lack of boring logs Data Limitations and soil profile for stream. Flow frequency source not available. Cross section and hydraulic infrastructure geometry data not provided. HEC-RAS does not account for account for 2D flow. Model assumes channel bed slope too Model Limitations small to avoid vertical pressure head. Tidal River Management (TRM) for Selected Coastal Area of Bangladesh to Mitigate Title/Purpose Drainage Congestion. Assess the Tidal River Management of the Kobodak River to reduce sedimentation and prevent flooding. Author(s) Shampa, Md. and Ibne Mayaz Pramanik Institution(s) Centre for Environmental and Geographic Services Model(s) MIKE11 Currency 2012? Unknown duration Scope Hydrodynamic and water simulation. Model/Data Description Cross section data, water level, and discharge were obtained Institute of Water Modelling and Bangladesh Water Development Board. Downstream water level data were obtained on a 24-hour basis with samples taken every half hour from 2007-2009. TRM model consisted of one upstream boundary and two downstream boundaries. Since modelling was conducted during the dry season, rainfall-runoff was not considered. Dead end rivers had zero flow boundary at the end of the reach and existing water levels in the beel. MIKE11 solves the Saint Venant equation for unsteady flow by using a 6-point Abbott scheme. Availability/Accessibility Model Proprietary Input data files: Not published Data files Output data files: Not published Report(s) Technical report: Not produced 6

Other publications No Spatial and Temporal Boundaries Spatial Extent Kobodak River (Jessore, Satkhira and Khulna districts) Outlet Point Upstream: Mellekbari; Downstream: Gadapur Temporal Unknown Resolution Time Period 2007-2009 (February -May) Data Requirements Component Source Publicly Available Bathymetry Bangladesh Water Development Board (BWDB), No Institute of Water Modelling (IWM) No Discharge Data BWDB, IWM No Water Surface BWDB, IWM No Elevation Key Assumptions and Limitations Assumptions Channel bed boundary is fixed. Data Limitations Flow data is only for 2-years. Model is calibrated but there is no information on validation MIKE11 does not account for account for 2D flow. Model assumes channel bed slope too Model Limitations small to avoid vertical pressure head. DO-BOD modelling of River Yamuna for national capital territory, using STREAM II, a Title/Purpose 2D water quality model. Use a 2D model to assess BOD and DO concentrations on the Yamuna river in Delhi Author(s) Deepshikha Sharma, and Ram Karan Singh Institution(s) TERI University Model(s) STREAM II Currency 2008?, Unknown duration Scope Water quality simulation Model/Data Description The STREAM II model was established as a series of 10 reaches from Wazirabad Barrage to Palla. Each reach assumed uniformed conditions (geometric, hydraulic, and channel-biological coefficients). Outfalls drains were located at the beginning of each reach. Channel geometry was obtained from field survey. Annual flow data were obtained from the CPCB. Water quality data were derived from field data and CPCB. The STREAM-II model solved for water quality using the Crank - Nicholson finite difference. Aeration coefficients were solved using the O’Connor and Dobbins and Churchill Elmore and Buckingham equations. Availability/Accessibility Model Public domain (but not listed EM Centre website) Input data files: Not published Data files Output data files Not published

Report(s) Technical report produced: Unknown Other publications No Spatial and Temporal Boundaries Spatial Extent Delhi Outlet Point Wazirabad Barrage to Palla Temporal Yearly Resolution Time Period 1995-2005 Data Requirements Component Source Publicly Available Channel Geometry Field Survey No Data Flow Data CPCB Yes Water Quality Data CPCB, Field Survey Yes Key Assumptions and Limitations Steady uniform conditions (geometric, hydraulic and chemical-biological parameters) for each reach. Steady state conditions observed within the year. Complete mixing of pollution Assumptions within the reach. No other sources of pollution entering the system. CBOD as the major source of pollution affecting dissolved oxygen; NBOD, COD is assumed to be zero. Sediment oxygen demand is zero. Lack of streamflow data. Hydraulic geometry of channel not available. Water quality and Data Limitations flow data obtained from secondary sources. Temperature data not provided since change in temperature affects the relationship between BOD and DO. Model Limitations Does not account for unsteady flow or varying pollutant loading. Mixed Integer Programming For Pollution Control Of Indian Tropical Rivers: Title/Purpose A Case Study. Develop an optimization model to determine the most feasible treatment option while meeting water quality standards. Author(s) Richa Babbar1, and Himanshu Joshi2 Institution(s) 1Jaypee University of Information Technology and 2IIT Roorkee Model(s) QUAL2E Currency 2010?, unknown duration Scope Decision support system for water quality Model/Data Description The QUAL2E model was configured for the Kali and Hindon River in India. The model divided the reaches into hydraulic homogeneity (constant flow, constant stream characteristics) and further segmented them to ensure that every point outfall was located at the beginning of the reach. Pollution loading concentration and flow data were obtained from field survey. QUAL2E uses the Streeter-Phelps equation to determine dissolved oxygen from BOD. Treatment type and location were determined using mixed linear algorithm using the Lindo software Availability/Accessibility 8

Model Public domain Input data files: Not published Data files Output data files: Not published Report(s) Technical report produced: Unknown A Proposed Decision Support System for River Water Quality Management in Other publications India{Babbar, 2009 #97} Spatial and Temporal Boundaries Spatial Extent Rivers Hindon and Kali Outlet Point Upstream:? Downstream: confluence of River Hindon and Kali Temporal Steady State Resolution Time Period Not provided Data Requirements Component Source Publicly Available Flow Data Field Data No Pollution Load Field Data No Hydraulic Geometry Unknown No Key Assumptions and Limitations Assumptions Uniform steady state conditions (flow, and pollution loading). No additional pollution sources outside the ones listed. CBOD is the primary source pollutant affects the DO; NBOD and COD is assumed to be zero. Constant pollution coefficients. Stream temperature is constant. Low flow conditions representative for other years Data Limitations Flow and pollution observation data are not provided Model Limitations Streamflow and pollution loading are constant Characteristics of the Event Mean Concentration (EMCs) from Rainfall Runoff on Mixed Agricultural Land Use in the Shoreline Zone of the Yamuna River in Delhi, India. Title/Purpose Monitoring, characterize and assess pollution from mixed agriculture lands that drain to Yamuna River. Author(s) Deepshikha Sharma1, Ruchi Gupta2, Ram Karan Singh2, & Arun Kansal3 Institution(s) 1TERI University, 2The Energy and Resources Institute & 3ITM University Model(s) SCS Currency 2006-2007 Scope Surface water quantity Model/Data Description The SWAT model delineated drainage boundaries using SRTM data. The area of interest is 0.2 km from the banks of the Yamuna River. Land cover classification was performed using supervised classification of remote sensing data. Meteorology data were obtained from IMD and included antecedent dry day, event rainfall, runoff duration, and rainfall intensity. Runoff modelling was performed using the Soil Conservation Service (USDA NRCS) methodology. 9

Availability/Accessibility Model Public domain Input data files: Not published Data files Output data files: Not published Report(s) Technical report produced: Unknown Other publications No Spatial and Temporal Boundaries Spatial Extent 0.2 KM adjacent to Yamuna River within Delhi Boundary Outlet Point Limited to the Flow in Delhi Temporal Event Resolution Time Period 2006-2007 Data Requirements Component Source Publicly Available DEM SRTM Yes Land Use/Cover IRS-1C -LISS-II (2006) Yes Soils National Bureau of Soil Survey & Land Use Planning No Meteorological Indian Metrological Dept. Yes Water Quality Field Data, CPCB No/Yes Samples Key Assumptions and Limitations Assumptions Pollution samples are representative of the area. Digital Elevation Model has sufficient resolution to delineate urban drainage area boundaries. There are no other contributing offsite flow or pollution loading, via surface flow, or subsurface flow. Drainage area is sufficiently small so spatial variability of rainfall is not applicable. Agriculture pollution loading is constant. Data Limitations Calibration or validation data of flow data. Inadequate number of pollution loading locations. Pollution grab sample may miss the first flush. No mass balance calculations for pollution loading. Model Limitations Peak discharge is not suitable for pollution loading computations since it does not allow for temporal variability of runoff. Analytical Water Quality Model for Biochemical Oxygen Demand Simulation in River Title/Purpose Gomti of Ganga Basin, India. Derive an analytical equation that relates dissolved oxygen concentration to a sinusoidally varying BOD loading in a river. Author(s) Ramakar Jha1 and Vijay P. Singh2 Institution(s) 1National Institute of Hydrology and 2Texas A&M University Model(s) Mathematical Model Currency 2008?, unknown duration

Scope Water quality modelling Model/Data Description The mathematical model was derived for the Gomti river to account for the effects of diurnal BOD loading. Flow and water quality data were obtained from the Central Water Commission. Coefficients for BOD decay were solved using a 1 or 2 term approximate differential equation. Availability/Accessibility Model Equation: Public domain Input data files: Not published Data files Output data files: Not published Report(s) Technical report produced: Unknown Other publications No Spatial and Temporal Boundaries Spatial Extent Gomti Basin (Neemsar - Maighat) Outlet Point Upstream: Neemsar; Downstream: Maighat Temporal Uniform flow Resolution Time Period 1989-2001 Data Requirements Component Source Publicly Available Flow Central Water Commission Unknown Water Quality Central Water Commission Unknown Key Assumptions and Limitations Assumptions Complete mixing of pollution within the reach. Uniform flow, constant pollution decay coefficients, and diurnal pollution loading. CBOD is the major source of pollution that affects dissolved oxygen; does not include NBOD, or COD. Data Limitations Flow and water quality data were obtained from secondary sources. Secondary sources (CPCB) were not listed in bibliography. Model Limitations Not applicable for complex flow simulations (2D Flow) or unsteady flow. Not applicable for variable pollutant loadings. Water Quality Modelling of the River Yamuna (India) using QUAL2E-UNCAS. Develop Title/Purpose an approach to improve water quality by determining maximum pollutant discharge without violating standards. Author(s) Ritu Paliwal, Prateek Sharma, and Arun Kansal Institution(s) Guru Gobind Singh Indraprastha University Model(s) QUAL2E-UNCAS Currency 2007?, unknown duration Scope Water quality simulation Model/Data Description 11

The Yamuna river was divided into 5 equal reaches and further segmented into 0.25 km lengths. Waste streams from 14 drains and 2 wastewater treatment plants drain from the top of each reach. The power equation was used to calculate coefficients, and exponents of depth and velocity utilising width, velocity and flow rate for different reaches. Incremental flow into the river was assumed to be zero. Stream aeration used the O’Connor and Dobbin equation. QUAL2E used the Streeter-Phelps equation which relate dissolved oxygen concentration and biological oxygen demand over time. Availability/Accessibility Model Public domain Input data files: Not Published Data files Output data files Not Published Report(s) Technical report produced: Unknown Other publications No Spatial and Temporal Boundaries Spatial Extent Yamuna River (25 km reach) Outlet Point Upstream: 2 km upstream of Wazirabad; Downstream: Okhla Barrage Temporal Steady State Resolution Time Period March to May Data Requirements Component Source Publicly Available Flow CPCB Yes NEERI Unknown Pollution Loading CPCB Yes Key Assumptions and Limitations Assumptions Stream is represented with the use of the power equation that relates depth, width, velocity and flow. Discharge and water quality data are representative of other years. CBOD as the major source of pollution affecting dissolved oxygen; NBOD, COD is assumed to be zero. Uniform steady state conditions (flow, and pollution loading). Complete mixing of pollution within the reach. High turbidity prevents phytoplankton oxygenation. From previous studies, settling rate and sediment oxygen demand is zero. Data Limitations Hydraulic geometry of channel is assumed to be rectangular. Temperature data is not provided. Flow and water quality data were obtained from secondary sources. Type of pollutants, and pollutant loading that affect Dissolved Oxygen are not provided (COD). Model Limitations Streamflow, hydraulic geometry and pollution loading are constant. Development of GIS Interface Con2grid for Groundwater Model. Develop a user Title/Purpose interface program, Con2grid that integrates groundwater modelling with ArcInfo GIS.

Author(s) M. S. Mane, D. K. Singh, A. K. Singh and A. K. Bhattacharya Institution(s) Indian Agricultural Research Institute Model(s) MODFLOW (Con2grid - interface for PMWIN)

Currency 2007?, Unknown duration Scope Groundwater flow simulation Model/Data Description Grid cells were set as 1 km x 1 km cells due to the small variability in soil properties and rainfall. Each cell has its own unique soil property, precipitation, and hydraulic conductivity. Aquifer properties were obtained from a Central Groundwater Board. Seepages from stream and canals were based on the MODFLOW stream package. Recharge rate were estimated for monsoon and non-monsoon season. DEM of the surface and bottom elevation, and water table during different seasons were based using an iterative finite difference interpolation technique. The MODFLOW used a finite difference approximation of Darcy’s law equation to model flow from high to low head. Availability/Accessibility MODFLOW: Public domain; Model Con2grid: Proprietary extension; for ArcInfo (Proprietary) Input data files: Not published Data files Output data files: Not published Report(s) Technical report produced: Unknown Other publications No Spatial and Temporal Boundaries Spatial Extent Dadupur distributary, Bulandshahar district Upper Ganges Canal (east), River Karwan (west) and the Southern administrative boundary Outlet Point Khurja block in the south. 28°0′–28°25′N lat, 77°25′–78°0′E long Temporal Daily? Resolution Time Period 1994-2004 Data Requirements Component Source Publicly Available DEM Survey of India Topo Sheet Yes Drainage network Survey of India Topo Sheet Yes Land Use/Cover NBSLP No Soils NBSLP No Pumping/Observatio CGWB Report Yes n Well Aquifer CGWB Report yes Characteristics Key Assumptions and Limitations Assumptions Little variability in input parameters. Pumping rate would increase at the same rate from 1984-1991, and canal water use from 1994-1995 for predictive period. Aquifer properties within a cell are assumed to be uniform.

Data Limitations Data were not provided or listed on location of wells (observation or pumping), and pumping discharge or drawdown. Continuous water-table data are not available. Aquifer data comes from secondary sources. Model Limitations Does not allow for telescopic grid sizing or unstructured grid.

Does not allow for fractures. Unknown if the interface was updated or discontinued. Applicability of MIKE 21 to Assess Temporal and Spatial Variation in Water Quality of Title/Purpose an Estuary under the Impact of Effluent from an Industrial Estate. Assess water quality impacts of industrial pollution from the Hoogly Estuary. Author(s) Ritu Paliwal1 and Rashmi R Patra2 Institution(s) 1TERI University and 2DHI India Model(s) MIKE21 Currency 2010?, unknown duration Scope Hydrodynamic, water quality model and water simulation Model/Data Description The finite element mesh model was developed for the Green Belt Canal where grid sizes varies from 30 meters to 3000 meters at the lower stretch of the estuary. Wind profile was obtained from Haldia where the average wind speed is 3 m/s 80% of the time. Pollution loading data was obtained from CPCB and WBPC. Dissolved Oxygen relationship to BOD was prepared from secondary sources. The MIKE21 methodology was based on the 2D shallow wave equation with depth integrated incompressible Reynolds average Navier Stokes equation. ECO Lab coefficients were calibrated using coefficient from secondary sources. Availability/Accessibility Model Mike 21, ECO Lab: Proprietary Input data files: Not published Data files Output data files: Not published Report(s) Technical report produced: Unknown Other publications No Spatial and Temporal Boundaries Spatial Extent Green Belt Canal and Hoogly Estuary Outlet Point Upstream: Diamond Harbour; Downstream: Sagar Roads Temporal Computation: One second; Reporting: 30 minutes Resolution Time Period November 1 -15, 2005; Validation January 1-15, 2003 Data Requirements Component Source Publicly Available Bathymetry C-Map Yes DHI No Meteorological WBPCB Yes

Water Levels C-Map Yes Pollution Loading CPCB, WBPCB Yes Key Assumptions and Limitations Assumptions Pollution loading is constant. Low flow conditions is constant during non-monsoon season. CBOD as the major source of pollution affecting dissolved oxygen; NBOD, COD is assumed to be zero. Decay, deaeration, sediment oxygen demand, temperature are constants. Data Limitations Lack of data on flow, velocity, pollution loading and water quality. Photosynthesis, deaeration, and sedimentation coefficient were obtained from secondary sources. Limited data availability on dissolved oxygen. No information provided on salinity. Model Limitations Ecolab equation is either customised equation or predefined. mathematical systems when data are unavailable. Inter-comparison Study of Water Level Estimate derived from Hydrodynamic– Title/Purpose hydrologic Model and Satellite Altimetry for a Complex Deltaic Environment. Assess the value of remote sensing data (altimetry) in hydrodynamic modelling. Author(s) A.H.M. Siddique-E-Akbor1, Faisal Hossain1, Hyongki Lee2, C.K. Shum2 Institution(s) 1Tennessee Technological University, 2Ohio State University Model(s) HEC-RAS Ver. 4.0 Currency 2010? Unknown duration Scope Hydrodynamic modelling, and water simulation Model/Data Description The model was discretised with 226 cross sections for the major river basins of Bangladesh, namely, the Ganges, Jamuna, Old Brahmaputra, Surma, Padma and Meghna. Chainage and bathymetry data were obtained from IWM. Cross section data were obtained using differential GPS and Echosounder, and converted into the Bangladesh datum system. Daily flow measurement data from state discharge curves were obtained at the upstream boundary conditions at the India-Bangladesh border. Downstream boundary condition was forced using tidal elevation at Daulatkhan on the Lower Meghna River close to the Bay of Bengal. Satellite radar altimetry data were obtained within 40 km of the gage data. HEC-RAS solve water surface elevation was determined using the energy equation and the standard step method. Availability/Accessibility Model Public domain (but requires proprietary ArcGIS) Input data files: Not published Data files Output data files: Not published Report(s) Technical report produced: unknown Proof of Concept of an Altimeter Based River Forecasting System for Transboundary Flow Other publications Inside Bangladesh {Hossain, 2014 #23} Spatial and Temporal Boundaries Spatial Extent Ganges–Brahmaputra–Meghna Basin Outlet Point Daulatkhan (downstream) Temporal Daily Resolution

Time Period 2003-2005 Data Requirements Component Source Publicly Available Bathymetry Data IWM No Flow, Stage Data Bangladesh Water Development Board Yes Altimetry Data Envisat (ICE-1 ) Yes Key Assumptions and Limitations Assumptions Channel bed boundary is fixed. Manning’s n roughness value does not seasonally change. Temporal mismatch between HEC-RAS and altimetry data is negligible. The Ganges water impoundment has no impact on the randomness of flow. Hydraulic structures does not impact flow depth. Data Limitations Lack of calibration data outside the major points of interest. Envisat may not obtain reliable water surface elevation data during low flow. Envisat cross tracks do not coincide with the location of gage data to ensure validation. Envisat repeat schedule is 35 days so it may miss the peak discharge. Model Limitations HEC-RAS does not account for account for 2D flow. Assumes channel bed slope is small to avoid vertical pressure head (may not be applicable for Ganges). Appropriate Rehabilitation Strategy for a Traditional Irrigation Supply System: A Case Title/Purpose from the Babai Area in Nepal. Assess a potential rehabilitation design using indigenous technologies. Author(s) B. Adhikari, R. Verhoeven and P. Troch Institution(s) Ghent University Model(s) HEC-RAS Version 4.0 Currency 2009?, unknown duration Scope Hydrodynamic modelling, water simulation Model/Data Description The cross section provided by the Babai Irrigation Project was obtained for each canal between the first and last diversion structure. Existing weirs were modelled using solid block with gaps between them to represent leaky conditions. Existing outlets were treated as lateral trapezoidal weirs. Weirs under future conditions were modelled as concrete structures with a weir, sluice, and outlet. Minimum width for each outlet was based on a design flow of 3 l/s per hectare to allow for rotational irrigation. High flow requirements were 25 m3/s, which were based on the requirement for dispersion to all, canals and lows flows. These were modelled as 2, 1, 1.5 m3/s for the Majharakulo, Budhankulo and Rajkulo irrigation areas, respectively. The HEC-RAS water surface elevation was computed using the energy equation and the iterative standard step method. Availability/Accessibility Model Public domain Input data files: Not published Data files Output data files: Not published

Report(s) Technical report produced: unknown Water rights of the head reach farmers in view of a water supply scenario at the extension Other publications area of the Babai Irrigation Project, Nepal [Adhikari, 2009 #217] Spatial and Temporal Boundaries Spatial Extent Babai Irrigation Project (Bardiya district, Nepal) Outlet Point Babai River Temporal Steady Resolution Time Period Not Applicable Data Requirements Component Source Publicly Available Field Cross Section Babai Irrigation Project Unknown Hydraulic Structures Author Design (Existing, Proposed) No/Yes Flow Data Bankfull discharge; canal requirements Yes Boundary Conditions Bed slope Yes Key Assumptions and Limitations Assumptions Assumes all structures will be built to standard and maintained. High flows will not change Water requirements for irrigation will not change. Channel bed boundary is fixed. Modelling of leaky weir is representative of a weir with holes. Changes in Manning’s n value during the crop season has no impact on flow. Data Limitations Insufficient number of cross-section spacing. Flow and variations of flow within the Babai River. Field survey techniques and data not provided.No field verification available on flow data from release flow of leaky weirs Model Limitations HEC-RAS does not account for account for 2D flow. Assumes channel bed slope is small to avoid vertical pressure head. Title/Purpose Investigation into the Effects of Climate Change for the Ajay River Basin using Hydroinformatics Basic Information. Develop a water resource management plan that accounts for climate change. Author(s) Sujana Dhar Institution(s) The Energy & Resources Institute Model(s) HEC HMS Version 2.2.2 Currency 2010?, unknown duration Scope Surface water quantity simulation. Model/Data Description The study area is divided into four sub-basins. HadRm data were re-analysed to 0.44° and used for present and future climate conditions. Runoff volume was computed using the Soil Moisture Accounting methodology. Parameters within the SMA model were determined through calibration. Availability/Accessibility 17

Model Public domain (but requires proprietary ArcGIS) Input data files: Not published Data files Output data files: Not published Report(s) Technical report produced: Unknown Hydrological Modelling of Natunhat Watershed, West Bengal of the Ajay River Catchment Other publications under Changed Climate Scenario[Dhar, 2009 #218] Spatial and Temporal Boundaries Spatial Extent Ajay River Basin Outlet Point Study Point: Katwa Temporal Daily? Resolution Time Period 1997-2001, 2040-2050 Data Requirements Component Source Publicly Available DEM Survey of India Toposheets Yes Drainage network Survey of India Toposheets Yes Land Use/Cover Survey of India, National Thematic Mapping Organization Yes National Bureau of Soil Survey and Land Use Planning No Soils Survey of India, National Thematic Mapping Organization Yes National Bureau of Soil Survey and Land Use Planning No Meteorological Indian Metrological Dept. Yes Indian Institute of Tropical Meteorology Yes Runoff Central Water Commission Yes (limited) Key Assumptions and Limitations Assumptions No change in land use, agriculture or cropping patterns from existing conditions to future conditions. Agriculture ET Coefficients are constant. Groundwater extraction does not play a role on soil moisture or water availability. Wind speed, solar radiance, and cloud cover do not change between existing and future conditions. Land use conditions for each basin are sufficiently homogenous. Data Limitations Lack of information on validation. No listing of hydrography generation and channel flow methodology. Lack of detailed meteorology data which include list of stations. Model Limitations Mathematical Models are uncoupled, which means some components of the model are not solved as a simultaneous equation. All mathematical models use constant parameter values Environmentally Sustainable Management of Water Demand under Changing Climate Title/Purpose Conditions in the Upper Ganges Basin, India. Incorporate environmental flows in basin water allocation under past and future climate scenarios.

Pratibha Sapkota1, Luna Bharati1, Pabitra Gurung1, Nitin Kaushal2, and Vladimir Author(s) Smakhtin1 Institution(s) 1IWMI and 2World Wildlife Fund (India) Model(s) Water Evaluation and Planning (WEAP) Currency 2007-2011?, (Part of Living Ganges Program) Scope Basin water management including environmental flow Model/Data Description The upper Ganges Basin was subdivided into six sub-basins. Major reservoirs, barrages and canals were incorporated into the model. Environmental flows requirements were entered on a monthly basis. Upstream flow data used simulated SWAT model results. Groundwater sources were connected to irrigation site via transmission link. Each sub-basin had three demand sites: domestic, irrigation, and industry. Domestic and industrial demand were obtained from district level data. Irrigation demand was calculated within the model using Penmann- Monteith method. Domestic demand had the highest priority followed by environment, irrigation and then industry. WEAP calculations were based on the water balance accounting. Availability/Accessibility Model Proprietary Input data files published: Unknown (There is CD that is included as part of the WWF report which has technical documents, but it is not available online and may not provide the Data files material) Output data files: not published Report(s) Technical report produced: Unknown (See Data files) Assessment of Environmental Flows for the Upper Ganga Basin [O’ Keeffe, 2012 #27] Including cultural water requirements in environmental flow assessment: an example from the upper Ganga River, India [Lokgariwar, 2013 #87] Other publications The impacts of water infrastructure and climate change on the hydrology of the Upper Ganges River Basin{Bharati, 2011 #99} Use of a distributed catchment model to assess hydrologic modifications in the Upper Ganges Basin [Bharati, 2011 #18] Spatial and Temporal Boundaries Spatial Extent Upper Ganges Basin Outlet Point Kanpur Barrage Temporal Monthly Resolution Time Period January 1990- December 2005 Data Requirements Component Source Publicly Available River Flows SWAT Model No Groundwater and Uttar Pradesh or Uttarakhand Central Groundwater Department Yes Storage Data Reservoirs WIT and Government Publications Yes

Crop, Irrigated Area DACNET Yes Future Climate Data PRECIS-CM Yes Flow Dependent Experts Yes Indicators Key Assumptions and Limitations Assumptions Although there are many dams and barrages in the basin, only six dams are modelled. Reservoir operation rules are adequately defined. Environmental flow requirements were clearly defined and modelled. In the absence of the data on irrigation diversions, irrigation water use was estimated using crop demand modelling. Single demand sites for domestic irrigation are a representative withdrawal from the sub-basin. Groundwater resources do not significantly vary within the sub-basin. Data Limitations Flow observation at three locations within study area. Model Limitations Flows are considered instantaneous, where the flow that is conveyed into the system, is automatically assumed to reach the end of the system at the end of the month. Simplified representation of groundwater. May not account for spatial variability of runoff due to hydroclimatological response. River Flow Forecasting with Artificial Neural Networks using Satellite Observed Precipitation Pre-processed with Flow Length and Travel Time Information: Case Study Title/Purpose of the Ganges River Basin. Assess the use of Artificial Neural Networks in flood forecasting. Author(s) M. K. Akhtar, G. A. Corzo, S. J. van Andel, and A. Jonoski Institution(s) UNESCO-IHE, and University of Western Model(s) Artificial Neural Network (ANN) (Matlab) Currency 2009?, unknown duration Scope Surface water quantity and water simulation. Model/Data Description The GIS analysis of TRMM data determined 25 areal clusters which account for the spatial temporal distribution of rainfall with different time lags. Lag time computations were performed using pre-processed 1 km SRTM data and adjusted to known river lines and basin boundaries. Travel time for a pixel assumed a constant travel velocity for rivers and overland flow. The model setup used the ANN toolbox in Matlab to determine the best model. The ANN model had ten hidden nodes or alternatives. The hidden nodes considered the following factors: (a) discharge from the present day and previous day; (b) lagged 25 average rainfall time series data plus (a); (c) composite rainfall time series data plus (a); and (d) evapotranspiration from the SWAT model plus (c). Availability/Accessibility Model Statistical Analysis (but requires proprietary Matlab) Input data files: Not published Data files Output data files: Not published Report(s) Technical report: unknown Other publications No Spatial and Temporal Boundaries

Spatial Extent Ganges Basin Outlet Point Hardinage Bridge Temporal Event (High flow events) Resolution Time Period 2001-2005 Data Requirements Component Source Publicly Available DEM SRTM Yes Drainage network SRTM Yes Precipitation TRMM Yes Discharge Data Government of Bangladesh Varies Key Assumptions and Limitations Assumptions Assumes no change in usage from reservoirs or diversion upstream and stationarity. Assumes uniform velocity for river and overland flow. Only applicable for high flows, since low flows are dominated by groundwater interaction in the region. Data Limitations Lack of flow observation in India to calibrate model. SWAT evapotranspiration results have not been calibrated. Model Limitations Black box structure Assume direct relationship between precipitation and flow. No account made of future water usage. Does not account for timing errors. Not capable of using all physical knowledge or measurements of the system since the most correlated variables of the system dominate. Use of a Distributed Catchment Model to Assess Hydrologic Modifications in the Upper Ganges Basin. Inform dialogue by understanding the Upper Ganges Basin in present and Title/Purpose more natural flow conditions and calculate environmental flow at three sites along the main channel.

Author(s) L. Bharati1, V. Smakhtin1, P. Jayakody1, N. Kaushal2 & P. Gurung1 Institution(s) 1IWMI, 2WWF Model(s) SWAT Currency 2007-2011?, (Part of Living Ganges Program) Scope Surface water quantity and water simulation. Model/Data Description The model represented 21 sub-basin within the Ganges. Reservoirs, barrages, and irrigation were added to the existing conditions. Each sub-basin was subdivided into Hydrologic Response Units (based on soil type, land cover and land management). Meteorology data (rainfall, temperature, sunshine duration, wind speed and relative humidity) were obtained from 15 climate stations, and spatially interpolated by the model. Groundwater baseflow was determined using SWAT automatic base flow filter. Runoff modelling was performed using Soil Conservation Service (USDA NRCS) methodology. In natural conditions, all hydraulic structures were removed and rained agriculture replaced the irrigated area. Availability/Accessibility

Model Public domain Input data files published: Unknown (There is CD that is included as part of the WWF report which has technical documents, but its not available online and may not provide the Data files material) Output data files not published Technical report produced: The Impacts of Water Infrastructure and Climate Change on Report(s) the Hydrology of the Upper Ganges River Basin Assessment of Environmental Flows for the Upper Ganga Basin {O Keeffe, 2012 #27} Environmentally sustainable management of water demands under changing climate conditions in the Upper Ganges Basin, India{Sapkota, 2013 #35} Other publications Including cultural water requirements in environmental flow assessment: an example from the upper Ganga River, India {Lokgariwar, 2013 #87} The impacts of water infrastructure and climate change on the hydrology of the Upper Ganges River Basin{Bharati, 2011 #99} Spatial and Temporal Boundaries Spatial Extent Upper Ganges Basin Outlet Point Kanpur Barrage Temporal Daily Resolution Time Period 1971- 2005 Data Requirements Component Source Publicly Available DEM SRTM Yes Land Use/Cover LandSat TM Yes Soils FAO Yes Meteorological Unlisted Unknown Runoff Data India Central Water Commission Yes (limited) Barrage, irrigation, Government Authorities Yes reservoirs Key Assumptions and Limitations Assumptions Although there are many dams/reservoirs in the Ganges basin, only six were modelled. Existing delivery information on dams, barrages and irrigation were incorporated in the model using the main features available from relevant authorities. Under natural conditions, all water infrastructure and irrigated crops were removed from the model. Calibration and validation of flows from 2000-2005 can be used to predict flows from 1970- 2000. Data Limitations Quality of observed data cannot be ascertained. Limited flow observations available for three barrages in India. Lack of reliable flow data for calibration and validation between 1970-2000.

Model Limitations Simplified snowmelt model. Glacial Lakes and Glacial Lake Outburst Flood (GLOF) in the Himalayan and GIS Basin Title/Purpose Using Remote Sensing. Assess the impacts of GLOF’s on hydropower. Author(s) Sanjay K. Jain, Anil K. Lohani, R. D. Singh, Anju Chaudhary, L. N. Thakural Institution(s) National Institute of Hydrology Model(s) MIKE11 Currency 2012?, unknown duration Scope hydrodynamic and water simulation Model/Data Description The GLOF lake location were initially determined using a Normalised Water Difference Index and confirmed with Google Earth. Lake volume was estimated using the Huggel equation. Cross Section were discretised downstream from the dam to the outlet where cross section spacing was every 5 KM and critical areas was set to 1 KM. Breach hydrograph assumed a breach width of 40, 60, 80 meters and a depth of 10 meters. A 100-year flood event for the basin was calculated, and distributed flows were entered as lateral inflows. MIKE11 solved the Saint Venant equation for unsteady flow by using a 6-point Abbott scheme. Availability/Accessibility Model Proprietary Input data files: Not published Data files Output data files: Not published Report(s) Technical report: unknown Other publications No Spatial and Temporal Boundaries Spatial Extent Alekandra River

Outlet Point Latitude 30° 15’ 00”N to 31° 07’ 00”N, Longitude 79° 15’ 00”E to 80° 15’ 00”E Temporal Event and 100-year storm Resolution Time Period NA Data Requirements Component Source Publicly Available DEM ASTER GDEM Yes Land Use/Cover Google Earth Yes (Manning’s n) Indian Remote Sensing Satellite Meteorological Not Listed Unknown

Key Assumptions and Limitations Assumptions Assumes newtonian flow. Breach hydrographs are within the margin of error.Huggel relationship is applicable for lakes in the Himalayans. No lakes are covered by snow or

affected by shadow. Dam breach occurs during the 100-year storm event.Slopes do not exceed 10%.Doesn’t assume potential cascade failure of GLOF. Data Limitations Determination of the 100-year storm event is not provided, since there is few very meteorological stations in the Himalayas. Digital Elevation Model is coarse for hydraulic modelling and may not represent channel geometry. Cross section spacing is 1 km to 5 km is coarse and may not account for energy loss.No field verification of GLOF lake. Little information is known about GLOF lake used in study. Glacial Lake mechanism and formation of break are not fully understood. Breach hydrograph equation is not provided. Model Limitations MIKE11 does not account for account for 2D flow. Assumes channel bed slope is small to avoid vertical pressure head. Evaluation of the Short-Term Processes Forcing the Monsoon River Floods in Title/Purpose Bangladesh. Inform dialogue by understanding the dynamic of monsoon river flow components which can be used to improve flood forecasting and dissemination.

Author(s) Flemming Jakobsen1, A.K.M. Zeaul Hoque2, Guna Nidhi Paudyal1 & Md. Salim Bhuiyan3

Institution(s) 1DHI, 2IWM, and 3Flood Forecasting Warning Centre (Bangladesh) Model(s) FF2003 (MIKE11) Currency 1998-2002 Scope Hydrodynamic and water simulation. Model/Data Description The FF2003 model covered most of Bangladesh, including 514 river branches, 156 rainfall-runoff basins, 38 weirs, 15 culverts, 27 update points, 85 boundary points, 40 rainfall and 56 water level stations. Upstream boundary conditions were applied to the Ganges and Jamuna, and downstream, to the Bay of Bengal. The rainfall-runoff model used conservation of water mass water and three linked linear storage: surface, lower zone, and groundwater storage. For runoff conveyed into the stream, the MIKE11 model solved the St. Venant equation for unsteady flow by using the 6-point Abbott scheme. Availability/Accessibility Model Proprietary (Based off of MIKE11) Input data files published: Not published Data files Output data files: Not published Report(s) Technical report produced: unknown Other publications No Spatial and Temporal Boundaries Spatial Extent GBM Basin Outlet Point Bay of Bengal Downstream; Upstream Rivers within Bangladesh Temporal Rainfall-Runoff (1 day); Hydrodynamic (30 mins) Resolution Time Period 1998-2002 Data Requirements Component Source Publicly Available 24

Drainage network BWDB No DEM (Cross- BWDB No Sections) Hydraulic Structure BWDB No Meteorological BWDB Yes Runoff Data BWDB No Key Assumptions and Limitations Assumptions Channel bed boundary is fixed. Upstream flow is not affected by reservoirs or irrigation usage. No errors made in manual reading of rainfall, evaporation, and water levels. Compatible timescale between groundwater, hydrodynamics and rainfall runoff. Data Limitations Model cannot be extended to India and cannot account for reservoirs or future flows into the system. Discharge data quality varies. Irrigation usage is not provided. Model Limitations Model does not account for account for 2D flow. Assumes channel bed slope is small to avoid vertical pressure head. Flood Hazard and Risk Analysis in the Southwest Region of Bangladesh. Inform Title/Purpose dialogue by attempting to prepare a hazard-based zoning map. Author(s) Tawatchai Tingsanchali1 and Mohammed Fazlul Karim2 Institution(s) 1Asian Institute of Technology (Thailand) and 2River Research Institute (Bangladesh) Model(s) MIKE11 Currency 2003?, unknown duration Scope Hydrodynamic and water simulation. Model/Data Description The Thana model is discretised with 10 large rivers, 18 small rivers and floodplain channels, 2215 cross sections, 58 river branches and 36 junctions. Cross sections vary from 2-4 km. Average daily flow enters at three upstream boundary locations. There are five downstream boundaries which use hourly water surface elevation from the Bay of Bengal. Determination of the 100-year flow was based on flood frequency analysis. Discharge hydrograph was constructed from dimensionless hydrograph and the peak discharge from the 100-year storm. Development of downstream water surface elevation hydrographs were based on the same reasoning. Lateral inflow between the bank and the floodplain was computed using a weir equation. The MIKE11 model solved the St. Venant equation for unsteady free surface flow using the 6-point Abbott scheme. Availability/Accessibility Model Proprietary Input data files: not published Data files Output data files: not published Report(s) Technical report produced: unknown Other publications No Spatial and Temporal Boundaries Spatial Extent Thana (Administrative Boundary) Outlet Point Bay of Bengal 25

Temporal 15 minutes Resolution Time Period 1988, 1995 (July - October) Data Requirements Component Source Publicly Available Digital Elevation Unknown Unknown Model Channel Geometry Unknown Unknown Flood Flow Unknown Unknown Tidal Data Unknown Unknown Satellite Inundation Publication Yes Boundary Conditions Unknown Unknown Population Density Unknown Unknown Data Key Assumptions and Limitations Assumptions Channel bed and floodplain boundary is fixed. Hydraulic structures are not sufficient large to provide backwater effects or attenuate flow. Precipitation in Bangladesh has no impact on total flow since majority of rainfall is occurring from Ganges River. Transfer of flow between the channel and floodplain is based on a weir equation. Flood duration is based on remote sensing imagery data. Similarities allow the flood hydrographs from the 1998 to be used as well as water level boundary from the 1987 event. Tidal water level at Malancha is the same at Hiron Point. Structural elevation first floor elevation above ground elevation is based on average conditions. Development of hazard indices, hazard zones, and risk analysis is simplified. Data Limitations Lack of flow data to derive 100-year storm or methodology used. Verification data for the 1995 event not provided. Data sources not listed. Cross section spacing set at 2 -4 km apart affecting the energy balance equation. Model Limitations MIKE11 does not account for account for 2D flow. Assumes channel bed slope is small to avoid vertical pressure head. Proof of Concept of an Altimeter-Based River Forecasting System for the Title/Purpose Transboundary Flow inside Bangladesh. Determine usefulness of using satellite altimetry data to forecast transboundary flow inside Bangladesh. Faisal Hossain1, A. H. Siddique-E-Akbor2, Liton Chandra Mazumder3, Sardar M. Author(s) ShahNewaz3, Sylvain Biancamaria4, Hyongki Lee5, and C. K. Shum6 1University of Washington (USA), 2Tennessee Technological University (USA), 3Institute of Institution(s) Water Modelling (SA), 4Université Toulouse (France), 5University of Houston (USA), 6Ohio State University (USA) Model(s) HEC-RAS Ver. 4.0 Currency 2012?, timing unknown Scope Forecasting hydrodynamic modelling and water simulation 26

Model/Data Description The model was discretized using 226 cross section on the major river basins of Bangladesh which are: the Ganges, Jamuna, Old Brahmaputra, Surma, Padma and Meghna. Spacing ranged from 2.5 km to 10 km. Cross section spacing matched FFWC forecasting stations at 17 locations. Chainage and bathymetry data were obtained from IWM. Daily flow measurement data from stage discharge curves were entered at the upstream boundary conditions at the India-Bangladesh border. Downstream boundary conditions were forced using tidal elevation at Daulatkhan on the Lower Meghna River close to the Bay of Bengal. The HEC-RAS solved water surface elevation by using the energy equation and the iterative standard step method. Availability/Accessibility Model Public domain (but requires proprietary ArcGIS) Input data files: Not published Data files Output data files: Not published Report(s) Technical report produced: Unknown Inter-comparison study of water level estimates derived from hydrodynamic–hydrologic Other publications model and satellite altimetry for a complex deltaic environment Spatial and Temporal Boundaries Spatial Extent Ganges–Brahmaputra–Meghna Basin Outlet Point Ganges U/S: Jangipur Barrage; D/S: Daulatkhan Temporal Daily Resolution Time Period 2008-2010, August 1-20, 2012 Data Requirements Component Source Publicly Available Bathymetry Data Field Survey No Flow, Stage Data Bangladesh Water Development Board Yes Altimetry Data Jason2 Yes Key Assumptions and Limitations Assumptions Channel bed boundary and floodplain is fixed. Manning’s n value does not vary between monsoon or dry season. Temporal mismatch between HEC-RAS and altimetry data is negligible (Average daily flow vs Jason instantaneous recording). Data Limitations Lack of calibration data outside the major points of interest. Jason2 may not provide reliable water surface elevation data. Number of cross sections is limited to ensure energy balance. No information on stream erosion. Model Limitations HEC-RAS does not account for 2D flow. Over prediction from HEC-RAS occurred from tidal or backwater effects. Assumes channel bed slope is small to avoid vertical pressure head. Sensitivity Analysis of Water Quality for the Delhi Stretch of the River Yamuna, India. Title/Purpose Employ sensitivity analysis as a tool for performing uncertainty analysis on water quality parameters and pollution abatement strategies. Author(s) D. L. Parmar1 and Ashok K. Keshari2

Institution(s) 1H.B. Technological Institute and 2IIT Delhi Model(s) QUAL2E Currency 2009?, unknown duration Scope Water quality simulation, sensitivity analysis. Model/Data Description The Yamuna River was divided into 16-sub reach based on 15 drains of partially treated or untreated wastewater being discharged into the river. Drains are located at the top of each reach. Hydraulic geometry, flow, and water quality data were obtained from secondary sources. Flow depth and velocity within the stream were obtained using the power equation relating flow, width, depth and velocity assuming a rectangular channel. QUAL2E used the Streeter-Phelps equation which relate dissolved oxygen concentration and biological oxygen demand over time. Availability/Accessibility Model Public domain Input data files published: Not published Data files Output data files: Not published Report(s) Technical report produced: Unknown Wasteload Allocation Using Wastewater Treatment and Flow Augmentation [Parmar, 2013 Other publications #89] Spatial and Temporal Boundaries Spatial Extent Delhi Upstream: Wazirabad Barrag Outlet Point Downstream: Okhla Barrage (22 KM) Temporal March 15- June 15, 2002 and February 2003 Resolution Time Period Steady state Data Requirements Component Source Publicly Available Geometric Data Delhi Jal Board Yes Runoff Data Delhi Jal Board Yes CPCB Water Quality Delhi Jal Board Yes Key Assumptions and Limitations Assumptions Flow, BOD, and pollution loading assume steady state conditions. CBOD as the major source of pollution affecting dissolved oxygen; NBOD, COD is assumed to be zero. Temperature does not vary. Data Limitations Flow, hydraulic geometry and water quality data was obtained from secondary sources. Temperature data is not provided. Model Limitations Streamflow and pollution load are constant.

Strategic Basin Assessment. Assess impacts of development in Nepal (reservoirs) and climate Title/Purpose change on benefits sharing. Author(s) A. K. Gosain, and. R. Srinivasan, INRM Consultants Institution(s) IIT Delhi and Texas A&M University Model(s) SWAT 2009 Currency 2010/2011 Scope Surface water quantity and water simulation. Model/Data Description The Ganges Basin was represented by 414 sub-basins. These include major reservoirs, diversion structures and major sewage disposal sites. Each sub-basin was subdivided into Hydrologic Response Units (based on soil type, land cover and land management). The daily reanalysis and re-gridded climate data (rainfall, temperature, wind speed and solar radiation) were used. Rainfall data were set at 0.5° X 0.5°. Relative humidity data were generated from long-term statistics and sampled at 1° X 1°. The runoff model used the Soil Conservation Service (USDA NRCS) methodology. Availability/Accessibility Model Public domain (requires proprietary ArcGIS) Data files Public domain Report(s) World Bank DC Implications of climate change for water resources development in the Ganges basin {Jeuland, Other publications 2013 #93} Spatial and Temporal Boundaries Spatial Extent Entire Ganga Basin including Nepal up to Bangladesh border Outlet Point Bay of Bengal Temporal Daily, monthly, annual Resolution Time Period 1975-2005 Data Requirements Component Source Publicly Available DEM GTOPO30 Yes Land use IWMI, NRSC Yes Soil FAO Yes Weather (rainfall and IMD (Available to research institutes), IMD Through Temperature) - request, Public Gridded Aphrodite Discharge GRDC Yes District Statistics Census India, CGWB district reports Yes (Agriculture ground water, population) Fertilizer application FAI, Indiastat Public

Canal Command WRIS-CWC Public for display Area, project purpose location Key Assumptions and Limitations Assumptions Although there are around 206 dams/reservoirs in the basin, only 104 were included given data availability. In the absence of the data on irrigation diversions, irrigation water use is estimated using crop demand modelling. Current crop management practices were inferred from land use map, irrigation source map, command area map and district-wise average irrigation information. Future irrigation demand is estimated using population projections and implied food demand. Point source of domestic pollution has been computed by using average BOD and the average sewer generation per capita. Future BOD load has been calculated based on future water demand using population projection. There are no change in future land use. Irrigation sources, amounts and frequencies are unknown for specific crops throughout the basin. Thus, data available from various sources were compiled and used as average irrigation schedules across the basin Data Limitations Lack of high resolution of soils map and profile. Lack of high resolution Indian land use specially the cropping pattern map. Lack of high altitude climate stations. Lack of climate data for Nepal, Tibet. Point sources location, load, type of pollutants. No flow observations available for India. Flows in the India portion of the basin thus not calibrated/validated. Re-use of water from irrigation was not totally captured upstream/downstream irrigation scheme. Fertilizer and manure application rate were quite different over space due to lack of information. Automatic fertilizer option used for some sub-basins, and crops and other areas where data were available the typical application date and amount were used. Model Limitations Climatic data were assigned to one sub-basin. Simplified snowmelt model. GWAVA (Global Water Availability Assessment). Research project to examine the implications Title/Purpose of climate change and sea level on water resources availability and coastal flooding in Bangladesh. Author(s) Helen Houghton-Carr Institution(s) NERC Centre for Ecology & Hydrology (CEH;) UK Model(s) GWAVA (Global Water Availability Assessment) Currency August 2003- February 2006 Scope Surface water quantity and water simulation Model/Data Description The GWAVA was set up as a gridded hydrological with a 0.5 degree resolution outside of Bangladesh and 0.1 degree resolution within Bangladesh. Fine scale grid resolution was extended outside Bangladesh to capture trans-national river basin. Identified mountain cells were sub-divided into 10 equal elevation zones where distribution of zones is based on the Pareto curve. The glacier was subdivided into 20 elevation. Rainfall within Bangladesh was spatially interpolated from 29 stations. Monthly climate data (precipitation) and temperature were re-gridded to daily data using weather generator. GWAVA used a simple rainfall-runoff model. The probability distributed model (PDM) provided estimates of surface runoff in each cell. Stream routing was performed using the Muskingum method. Availability/Accessibility Model GWAVA

Input Date File: Not available Data files Output Data File: Not available Impact of CLimate And Sea Level Change in part of the Indian Sub-Continent (CLASIC): Final Report(s) Report {Farquharson, February 2007 #38} Exploring the impacts of climate change on water resources—regional impacts at a regional Other publications scale: Bangladesh {Fung, 2006 #91} Spatial and Temporal Boundaries Spatial Extent Ganges-Brahmaputra-Meghna basin Outlet Point Bay of Bengal Temporal Daily Resolution Time Period 1961-1990; 2041-2060; 2070-2100 Data Requirements Component Source Publicly Available Runoff Government Agencies Varies Meteorological UK Met Office, IIT Meteorology Yes, No Drainage network DDM30, Tactital pilotage charts Yes, Unknown DEM Hydro1K Yes Soils FAO Yes Land Cover USGS Global Land Cover Yes Lakes and Wetlands Digital Chart of the World Yes Tactical Pilotage Charts Unknown Tibet Map Institute Yes Glacier Digital Chart of the World, GLCC Yes/Yes Groundwater Groundwater Agencies Varies Population CIESIN, FAO Population Yes/Yes UNDP World Population Prospects Yes Water Usage AQUASTATS Yes Livestock Population FAO Yes Water Transfer Government Agencies Yes Key Assumptions and Limitations Assumptions All variables are uniformly distributed across a cell. Flows in distributaries are based on flow ratios from river cross section, local bed slope and bed resistance. Distributary becomes dry if main river drops a certain magnitude. Land cover is categorized into six classes outside Bangladesh. Population is resampled to required resolution. Spatial population data are adjusted to national statistics. Spatial cell Irrigation area is adjusted to national statistics. Industrial demand set to 25% and 50% of urban demand for low and high scenarios.

Data Limitations No gauging station data in India. Water balance does not account for two water storage (flooding and agriculture). Basin and sub-basin boundary do not fit perfectly with gridded scheme. Nepal runoff records discarded due to short record length. Model Limitations Model resolution is a compromise between availability of data, required detail and acceptable run-time. Groundwater/recharge modelling is currently relatively simplistic. Evaluation of Hydrological Effect of Stakeholder Prioritized Climate Change Adaptation Title/Purpose Options based on Multi-model Regional Climate Projections. Assess impacts of climate change adaptation by incorporating stakeholder knowledge and preference in the model. Author(s) Ajay Gajanan Bhave, Ashok Mishra, & Narendra Singh Raghuwanshi Institution(s) IIT Kharagpur (India) Model(s) WEAP Currency 2013?, unknown duration Scope Surface water quantity, water simulation Model/Data Description The Kangsabati River was divided into two major basins, with each basin further subdivided into 3 sub-basins. Determination of land cover was performed using unsupervised classification. Monthly effective precipitation was based on land use runoff coefficients and basin wide averages. Runoff modelling was performing using the FAO methodology. Check dam location were determined using US SCS curve number methodology and slope. WEAP calculations were based on the water balance accounting across multiple sub-basins. Availability/Accessibility Model Proprietary Input data files: Not published Data files Output data files: Not published Report(s) Technical report produced: Unknown A combined bottom-up and top-down approach for assessment of climate change adaptation Other publications options [Bhave, 2014 #88] Spatial and Temporal Boundaries Spatial Extent Kangsabati river basin Outlet Point Kangsabati reservoir Temporal Monthly Resolution Time Period 1991-2010, 2021-2050 Data Requirements Component Source Publicly Available Land Use/Cover LandSat Yes Soils FAO Yes Meteorological Indian Metrological Dept. Yes Runoff Data Central Water Commission, Irrigation Water Commission, Gov’t of West No Bengal 32

Groundwater Government of West Bengal. Central Groundwater Board Yes

Climate Change High Noon Yes Key Assumptions and Limitations Assumptions Check dams will be continuously maintained; no decrease in check dam storage. Groundwater will be conveyed into the stream instead of being lost to the system. Future water use demand remains constant. Unsupervised classification adequately reflects cover type due to similar spectral response.

Data Limitations Evapotranspiration is not affected by changes in CO2 levels. Runoff flow data are not available. Model Limitations Simplified representation of groundwater. May not account for spatial variability of runoff due to hydroclimatological response. Water Resources Modelling of the Ganges-Brahmaputra-Meghna River Basins Using Title/Purpose Satellite Remote Sensing Data. Determine the potential of developing a river basin model using remote sensing data. Author(s) Bushra Nishat and S.M. Mahbubur Rahman Institution(s) Institute of Water Modelling (Bangladesh) Model(s) MIKE BASIN Currency 2008?, unknown duration Scope Surface water quantity and water simulation. Model/Data Description The Ganges, Brahmaputra, and Meghna (GBM) Basin was represented by 148 sub-basins, with 109 sub-basins located within the Ganges Basin. Schematization of sub-basin was based on probable water use demand and did not require further information Reservoirs or diversion were not included in the model. TRMM data were blended with ground station data when available. Each sub-basin used average value of rainfall, precipitation, and climate data. Runoff modelling used Nedbør-Afstrømnings-Model (NAM hydrological model). Basin routing was performed using the Muskingum and Wave Translation procedure. Availability/Accessibility Model Proprietary Model Input data files: Not published Data files Output data files: Not published Report(s) Technical report produced: Unknown Other publications No Spatial and Temporal Boundaries Spatial Extent Ganges, Brahmaputra, and Meghna (GBM) Basin Outlet Point Bay of Bengal Temporal Daily Resolution Time Period 2005-2007 Data Requirements

Component Source Publicly Available DEM SRTM Yes Drainage network SRTM, Watershed Maps of India Yes Land Use/Cover Not Listed Unknown Soils Not Listed Unknown Meteorological Bangladesh Meteorological Department (BMD) No Bangladesh Water Development Board (BWDB) No Climate Research Unit (CRU) Yes Indian Institute of Tropical Meteorology (IITM) No Tropical Rainfall Measuring Mission (TRMM) Yes Institutional Development of Department of Hydrology and No Meteorology, Nepal Indian Meteorological Department Yes Chinese Rainfall Gauge Stations Yes Runoff Data GRDC Yes Institutional Development of Department of Hydrology and No Meteorology, Nepal BWDB No Key Assumptions and Limitations Assumptions Irrigations and reservoirs have no impact on flows. Land cover does not change. Sub-basin parameters are homogenous. Data Limitations No flow observations are available for India. Flows in the India portion of the basin thus not calibrated/validated. Lack of water diversion information. Lack of information on reservoir storage and operating rules. No information on land use, cropping pattern or soils. Lack of high altitude climate stations. Lack of climate data for Nepal, Tibet. Model Limitations NAM hydrologic model does not allow for spatial variability. Network models are insufficient to answer physically-based questions, such as flood propagation, attenuation and surface groundwater interaction. Simplified snow and glacier assumptions. Opportunities for Harnessing the Increased Contribution of Glacier and Snowmelt Flows in Title/Purpose the Ganges Basin. Assess the impacts of glaciers, snowmelt flows and additional water within the basins in the context of climate change, trans-boundary and benefit sharing.

Author(s) Bharat R. Sharma1 and Devaraj de Condappa2 Institution(s) IWM1 and SEI2 Model(s) WEAP Currency 2013?, unknown duration Scope Surface water quantity and water simulation. Model/Data Description The Ganges Basin was divided by sub-basin and subsequently by elevation band. It was assumed that discretization by elevation accounted for glacier coverage that begins at an elevation of 3000 meters and incremental elevation band of

1000 m upwards. Calculations of ice and snowmelt were based on a degree day approach. WEAP employed a mass balance approach using a link node architecture. Availability/Accessibility Model Proprietary Input data files: not published Data files Output data files: not published Report(s) Technical report produced: unknown Other publications No Spatial and Temporal Boundaries Spatial Extent Ganges Basin Outlet Point Farakka barrage Temporal Monthly Resolution Time Period 1982-2002 Data Requirements Component Source Publicly Available DEM SRTM Yes Glacier Area GLIMS Yes Land Use/Cover Unknown Unknown Soils Unknown Unknown Meteorological Unknown Unknown Runoff Data Global Runoff Data Center (GRDC) Yes Global River Discharge (RivDI)S Yes National Center for Atmospheric Research (NCAR) Yes

Additional Datasets? IWMI Unknown Key Assumptions and Limitations Assumptions Hydraulic infrastructure such as reservoirs or barrages and demand usage is known. Snowmelt coefficient remains constant. Glacier area and volume is accounted for on steep slopes. Data Limitations Limited flow data with variable quality. Meteorology, land use and soil sources not listed. No time series of observed flow for glaciers. Runoff modelling methodology not provided. Calibration of glacier parameters based solely on streamflow and does not account for variations in glacier areas. Additional datasets from previous projects not listed. Model Limitations Glacier module is experimental and simplified. Simplified snowmelt procedure. Groundwater Flow Modelling of Yamuna–Krishni Inter-Stream as Part of the Central Ganga Title/Purpose Plain Uttar Pradesh. Informed dialogue by assessing a groundwater flow system using a steady and transient model to determine potential impacts on the aquifer. Author(s) Izrar Ahmed and Rashid Umar 35

Institution(s) Aligarh Muslim University Model(s) Visual MODFLOW Pro 4.1 Currency 2009?, unknown duration Scope Groundwater quantity and water simulation. Model/Data Description The Yamuna model was discretized using a uniform grid of 1000m x 1000m. A three-layer model was chosen where the top layer and bottom layer have the same hydraulic conductivity. Hydraulic conductivity of the middle was represented using a semi-permeable layer that account for a clay lens. Hydraulic conductivity was determined through seven pumping well tests. The Theissen polygon method was used to determine seven distinct zones. Recharge volumes were based on the methodologies provided in the Groundwater Estimation Committee. The Yamuna and Krishni rivers were modelled using the MODFLOW riverbed boundary package. Groundwater pumping ranged from 500-2500 m3/day with 500 cubic meter flow increment. The MODFLOW used a finite difference approximation of Darcy’s law equation to model flow from high to low head. Availability/Accessibility Model Public domain (but requires proprietary interface Visual MODFLOW) Input data files: Not published Data files Output data files: Not published Report(s) Technical report produced: Unknown Groundwater Flow Modelling of Hindon-Yamuna Interfluve Region, Western Uttar Pradesh [Alam, 2013 #221] Other publications Is shrinking groundwater resources leading to socioeconomic and environmental degradation in Central Ganga Plain, India?[Ahmed, 2014 #220] Spatial and Temporal Boundaries ◦ ′ ◦ ′ ′′ ◦ ′ Muzaffarnagar district (Utter Pradesh) latitudes 29 15 and 29 41 45 N and longitudes 77 05 Spatial Extent ◦ ′ and 77 27 E Yamuna (western) and Krishni (eastern) river boundaries Outlet Point General Head Boundary (northern, southern) Temporal Steady state (November 2006); transient (June 1999-2007) Resolution Time Period 18 intervals from 1999-2007 divided into 152 days (monsoon)/ 213 days (non-monsoon) Data Requirements Component Source Publicly Available DEM SRTM Yes Observation Wells Ministry of Water Resources Unknown Boring Log State Tubewell Department? Unknown Pumping Wells Statistical Department Unknown Location Aquifer Parameters Secondary Sources (Previous Studies), Pumping Tests Yes Key Assumptions and Limitations

Assumptions Assumes constant pumping per day. Hydraulic Conductivity is based on regional values using the Thiessen Polygon from 7 pumping well tests. Recharge values are in accordance with Groundwater Estimation Committee methodology. Hydraulic head does not change between pumping and non-pumping season. Streambed thickness based on regional averages. Lithological data from 27 borehole data provided sufficient representation of vertical and horizontal strata including aquifer and aquitards. Data Limitations Lack of observation wells, pumping wells and number of observations. Aquifer properties occur from secondary sources. Only one aquifer modelled while four distinct aquifers were listed. Model Limitations Average of stressors values (boundary, recharge) can change over time and can affect simulation results. Assessment of Future Climate Change Impacts on Water Resources of the Upper Sind River Title/Purpose Basin (India) using the SWAT Model. Assess the impacts of climate change on future streamflow and potential adaption options. Author(s) Boini Narsimlu, Ashvin K. Gosain & Baghu R. Chahar Institution(s) IIT Delhi Model(s) SWAT 2009 Currency 2013?, unknown duration Scope Surface water quantity and water simulation Model/Data Description The Ganges Basin was represented by 15 sub-basins with a threshold drainage area of 15,000 ha. Each sub-basin is subdivided into Hydrologic Response Units (based on soil type, land cover and land management). Runoff modelled used the Soil Conservation Service (USDA NRCS) methodology. Muskingum method was used for channel routing. Availability/Accessibility Model Public domain (requires proprietary interface) Input data files: Not published Data files Output data files Not published Report(s) Technical report produced: Unknown Other publications No Spatial and Temporal Boundaries Spatial Extent Upper Sind River Basin Outlet Point Pachauli Temporal Monthly Resolution Time Period 1961-2005 Data Requirements Component Source Publicly Available DEM SRTM Yes Land Use/Cover National Remote Sensing Centre Yes

Soils National Bureau of Soil Survey and Land Use Planning No Indian Council of Agricultural Research No Meteorological Indian Meteorological Dept. Yes Hadley Centre for Climate Yes Runoff Data Central Water Commission No Key Assumptions and Limitations Assumptions Future land use is the same as existing usage .Future irrigation demand and hydropower was not considered. Data Limitations Number of climate stations for precipitation is limited. Exact specific irrigation sources, amounts, and frequencies for specific crop is not provided. Model Limitations Simplified snowmelt model (Not applicable). Title/Purpose HEC-RAS Ganges Basin. To map flood inundation extent for different return periods. Author(s) Nishadi Eriyagama Institution(s) International Water Management Institution (IWMI) Model(s) HEC-RAS Currency 2013 Scope Hydrodynamic modelling and water simulation Model/Data Description The HEC-RAS model was developed for the major tributaries of the Ganga Basin. Stream geometry and cross sections were generated using the HEC-GEORAS software. Peak flows from different return periods generated using the HEC- HMS model were entered at the upstream locations. HEC-RAS water surface elevation is computed using the energy equation and the iterative standard step method. Availability/Accessibility Model Public domain (but requires proprietary ArcGIS) Input data files: Currently non available Data files Output data files: Currently non available Report(s) Technical report produced: Unknown Other publications No Spatial and Temporal Boundaries Spatial Extent Gange Basin Outlet Point Farakka Bridge Temporal Daily Resolution Time Period 1987-1999 Data Requirements Component Source Publicly Available River Flows HEC-HMS Not currently

Stage Data Unknown No Hydraulic Structures Unknown Unknown Stream Cross- Unknown Unknown Sections Key Assumptions and Limitations Assumptions Modelling flow as steady flow with peak discharge rates is sufficient to map the maximum flood inundation extent. Data Limitations Observed water level data is not available. Only satellite derived water level data is available. Model Limitations Assumes channel bed slope is small to avoid vertical pressure head. HEC-RAS does not account for account for 2D flow. Water Resources Management in the Ganges Basin: A Comparison of Three Strategies for Conjunctive Use of Groundwater and Surface Water. Inform dialogue by evaluating Title/Purpose conjunctive use strategies that affects irrigation water supply, flood management, reduction of waterlogging, and maintenance of downstream dry season flow. Author(s) Mahfuzur R. Khan1 and Clifford I. Voss2 and Winston Yu3 and Holly A. Michael1 Institution(s) 1University of Delaware, 2United States Geological Survey, 3World Bank Model(s) MODFLOW Currency 2013?, unknown duration Scope Ground water quantity and water simulation. Model/Data Description MODFLOW model was established for three management strategies: Ganges Water Machine (GWM), Pumping along Canals (PAC) and Distributed Pumping and Recharge (DPR). Aquifer cross sections extend from the centre of infiltrating river or canal to half the distance between the two adjacent rivers or canals. Vertical horizontal boundaries and bottom boundaries were considered as no flow. Areal recharge from rainfall and irrigation return flow was determined using the MODFLOW recharge packet; the MODFLOW drain packet was used to limit water surface elevation above the land surface; and MODFLOW rivers package was used to model rivers and canals.. For the GWM, the river was modelled as an ephemeral width of five meters and a constant water depth during the monsoon season. For PAC, the setup is similar to GWM, except for a 100 meter wide, one meter deep infiltration canal. DPR setup included three types of surface canals, where canal type, width and depth were estimated from GIS data. MODFLOW uses a finite difference approximation of Darcy’s law equation to model flow from high head to low head. Availability/Accessibility Model Public domain (but may requires proprietary interface) Input data files: Not published Data files Output data files: Not published Report(s) Technical report produced: No Other publications No Spatial and Temporal Boundaries Spatial Extent Utter Pradesh Outlet Point Half distance between 2 adjacent river canals

Temporal Steady State Resolution Time Period Not applicable Data Requirements Component Source Publicly Available Aquifer Coefficients Published Literature Yes Lithological Logs Unknown Unknown Potential Recharge Government of India Yes Key Assumptions and Limitations Assumptions Although the aquifer characteristics vary from one location to another, a key assumption is that basin wide averages are applicable. Unsaturated conditions between the river bottom and water table are not considered. For DPR, only infiltration was considered and total groundwater monsoon was pumped out during the dry year. To account for basin wide averages, coefficient of vertical anisotropy was based on published lithological data. GWM storage is based on simulation modelling/unit river length, actual river length and factor 2 to account for both sides of the river. DPR storage is based on simulated storage per unit field length by total length of the area. Data Limitations Modelling results does not account for adverse impacts in subsidence, river ecosystems, and social and cultural impacts. To simplify the modelling analysis, complexities in the system are reduced to basic assumptions. Lack of access to groundwater level monitoring data for calibration. Model Limitations Average of stressors values (boundary, recharge) can change over time and can affect simulation results. Hydrogeological framework and water balance studies in parts of Krishni–Yamuna Title/Purpose interstream area, Western Uttar Pradesh, India. Inform dialogue by evaluating the groundwater resources in the basin. Author(s) Izrar Ahmed and Rashid Umar Institution(s) Aligarh Muslim University Model(s) Water Balance Currency 2004?, unknown duration Scope Water balance Model/Data Description The water balance model consisted only of the top aquifer was modeled because it overlay an impermeable layer. Aquifer water levels were obtained in June and November that represent the minimum and maximum head for the specific year. Transmissivity was determined using one long, four short pumping test along with Logan’s equation. Groundwater components were determined using equation and coefficients that are described in public literature. The difference in the water balance is determined by summing the inflows and subtraction the outflows. Availability/Accessibility Model Public Input data files: Not published Data files 40

Output data files: Yes Report(s) Technical report produced: Unknown Groundwater flow modelling of Yamuna-Krishni interstream, a part of central Ganga Plain Uttar Other publications Pradesh {Ahmed, 2009 #9} Spatial and Temporal Boundaries Latitude: 29°11’N and 29°30’N Spatial Extent Longitude: 77°07’E and 78°22’E Outlet Point East: Krishni River; West: Yamuna River Temporal Not Applicable Resolution Time Period Not Applicable Data Requirements Component Source Publicly Available Water Table Field Sampling No Aquifer Pump Test Central Groundwater Board Unknown Aquifer Coefficients Literature Yes Lithologs Boreholes Unknown Unknown Meteorological Indian Metrological Dept. Yes Runoff Data GRDC/ World Bank, Government of Nepal, Government of Bangladesh Yes/no Reservoirs Government reports Yes Key Assumptions and Limitations Assumptions Although there are four aquifers in the system, only the first aquifer is being studied in detail since each aquifer overlays an impermeable boundary layer. In the absence of individual pumping data, average values were used state pump wells, private pump wells, and pumping sets. In the absence of detailed data, average values were obtained from secondary sources. Data Limitations Rainfall data in the area is classified and hence unavailable. A mass balance equation will be determined from secondary sources. Summation of inflows and accounting for the change in storage may double count the amount of water that is being conveyed into the system. Lack of water level data since sampling was obtained in the month of June and November. Lack of long term data for water balance modelling. Water balance coefficient was obtained from secondary sources. Model Limitations Requires detailed information on inflow and outflow components. Regional hydrostratigraphy and groundwater flow modeling in the arsenic-affected areas of the western Bengal basin, West Bengal, India. Inform dialogue by understanding the Title/Purpose interactions of local and regional groundwater flow systems along with control or reach and hydraulic parameters that affect flow. Author(s) Abhijit Mukherjee, Alan E. Fryar & Paul D. Howell Institution(s) University of Kentucky

Model(s) MODFLOW Currency 2004?, unknown duration Scope Groundwater quantity and water simulation. Model/Data Description The West Bengal model was discretised with 1 KM x 1 KM cell with 22 vertical layers. Each layer was 15 meters, except for the surface elevation that had a variable thickness due to topography, and the 4th layer that had a thickness of 5 meters to account for shallow irrigation wells. Aquifer-aquitard wells were modelled using Rockworks. Transmissivity was calculated iteratively using the method of Mace. The topmost layer is classified as unconfined, and second is classified as unconfined (T varying) and the remaining layers is confined. MODFLOW riverbed boundary was used to model Ganges, Jalangi/Ichamati, and Bhagirathi-Hoogly River. The bay of Bengal was modelled as a constant head boundary. Monthly precipitation data were categorised based on seasons and then zonal statistics were created using the Kriging method. MODFLOW uses a finite difference approximation of Darcy’s law equation to model flow from high to low head. Availability/Accessibility Model Public domain (but requires proprietary Groundwater Vistas) Input data files published: Not published Data files Output data files: Not published Report(s) Technical report produced: {Mukherjee, 2006 #217} Elevated arsenic in deeper groundwater of the western Bengal basin, India: Extent and controls Other publications from regional to local scale{Mukherjee, 2011 #115} Spatial and Temporal Boundaries Spatial Extent Eastern Part Murshidabad, Nadia, North 24 Parganas and South 24 Parganas North: Ganges River; East: Jalangi/Ichamati River; Outlet Point South: Bay of Bengal; West: Bhagirathi-Hoogly River Temporal Steady: Pre Monsoon, Monsoon, and Post Monsoon Resolution Time Period Pre1970, 2001, 2011, 2021 Data Requirements Component Source Publicly Available DEM SRTM Yes Aquifer Coefficients Government Reports, Yes Literature Yes Lithology Government Reports, Yes Engineering, Company Report Unknown Unpublished Work No Precipitation NCDC Yes Bathymetry Survey of India Yes Key Assumptions and Limitations Assumptions Wells, domestic wells was not considered outside of Kolkata in this study due to minimum impact on the system. In the absence of detailed meteorological data, ET was calculate using the Pike

equation. In the absence long term drawdown aquifer data, aquifer, meteoric water (rainfall) was estimated using precipitation data. Recharge is measured seasonally due to a wet and dry season. In the absence, of stream conductance, C values were determined using hydraulic conductivity from similar sediment types of adjoining aquifers. Population growth and number of pumps was based on the average growth rate from the district from 1991-2001. Data Limitations No historical data exists on current flooding. Uncertainty in modelling results are related to simplification of seasonality, estimated recharge rate, stream stage estimation, difference between attributed and actual land use (e.g., pumping rate, number of hours of pumping), and local-scale variations in lithology. Lack of meteorological data to calculate evapotranspiration via Penman-Monteith methodology. No detailed recharge data available and was one of the least certain input parameters Model Limitations Flow is assumed constant density. Upstream satellite remote sensing for river discharge forecasting: Application to major rivers Title/Purpose in South Asia Basic Information. Inform dialogue by assessing how accurate is using satellite remote sensings for forecasting streamflow. Feyera A. Hirpa1, Thomas M. Hopson2, Tom De Groeve3, G. Robert Brakenridge4, Mekonnen Author(s) Gebremichael1, and Pedro J. Restrepo5 1University of Connecticut, 2National Center for Atmospheric Research, 3Ispra, 4University of Institution(s) Colorado, and 5NOAA Model(s) Statistical Currency 2011?, unknown duration Scope Statistical and water quantity forecast simulation. Model/Data Description Satellite derived flow for the Ganges River was obtained from 22 gelocated sites. Flow times estimatesfrom river flow signals were plotted agains flow lengths. Wave celerity was estimated using Kleitz–Seddon Law equation. Flow signals from past and current events were used as imputes to the forecasting model and the rating curve of stage-discharge was used as a training set at the outlet. Forcasting variables were determined using cross-validation statistics. Availability/Accessibility Model Public domain (but requires proprietary ArcGIS) Input data files published: Unknown Data files Output data files: Unknown Technical report: Hydrologic Data Assimilation for Operational Streamflow Forecasting{Hirpa, Report(s) 2013 #218} Other publications No Spatial and Temporal Boundaries Spatial Extent Ganges Basin Outlet Point Hardinge Bridge Temporal Daily Resolution

Time Period 2004, 2007 Data Requirements Component Source Publicly Available DEM SRTM Yes Drainage network USGS Yes (Hydroshed) Satellite Derived JRC-ISPRA Yes Flow Runoff Data Bangladesh Water Development Board No Rating Curve Bangladesh Water Development Board No Key Assumptions and Limitations Assumptions River flow is not confined to the main channel. Variable precipitation and distribution has no impact on forecasting results. Kinematic wave theory can be used to approximate flow since it varies slowly in time. In the absence, of wave celerity, correlation of maximum lag time estimates were used as a proxy. Data Limitations Water diversions and low flow affect the area that is being flooded, and affects the satellite reading. Peak flows cannot be captured using satellite flow data. Lack of precipitation data to account for river flow propagation. Model Limitations Not applicable for low flows. Model does not fully account for groundwater flow conditions, unaccounted generated inflow, and intrinsic changes in celerity. Water-use accounts in CPWF basins: Simple water-use accounting of the Ganges Basin. Title/Purpose Inform dialogue by developing a simple water balance model to demonstrate water use within the basin. Author(s) Judy Eastham, Mac Kirby, Mohammed Mainuddin, and Mark Thomas Institution(s) CSIRO Model(s) Excel Currency 20110?, unknown duration Scope Water Balance and water simulation. Model/Data Description Ganges Basin represented by 14 sub-basins. Average precipitation and evapotranspiration for each sub-basin was estimated on a monthly basis. Evapotranspiration was estimated from potential evapotranspiration and partitioned between irrigation and rained based on the ratio of their area. Evapotranspiration from rainfed was divided based on vegetation type and then further subdivided based on ratios of the area, and crop factors to scale evapotranspiration relative to other land uses. Runoff into flows and tributaries are based on water balance accounting. Availability/Accessibility Model Spreadsheet is ubiquitous (Excel is Proprietary) Input data files: Not published Data files Output data files: Not published

Report(s) Technical report produced: No Other publications No Spatial and Temporal Boundaries Spatial Extent Ganges Basin Outlet Point Paksey Temporal Monthly Resolution Time Period 1951-2001 Data Requirements Component Source Publicly Available Land Use/Cover IWMI Global Map Yes Meteorological CRU Yes Runoff Data NCAR Yes Key Assumptions and Limitations Assumptions In the absence of groundwater data, base flow within the catchment is assumed constant throughout the year. Flow to deep aquifer is estimated as a proportion of surface water storage. In the absence of lack of data on channel storage, channel storage and loss is estimated as a function of flow. In the absence of the data on irrigation diversions, irrigation water use estimated using crop demand modelling. Where runoff data is not available, runoff coefficients were obtained from similar nearby catchments with similar climatic and physiographic characteristics when possible. In the northern altitudes of the mountainous areas, discharge exceed precipitation. Discharge was then estimated using relationships between observed discharge and precipitation for each month. Data Limitations Hydrologic process or storage within the sub-basin is not modelled. No flow observations available for 9 of the 14 catchments. Lack of high altitude climate stations. Model Limitations Limited to monthly water account. Ganges River Basin Modelling. Inform dialogue by developing a Ganges basin model and Title/Purpose analyse scenarios and contribute to the knowledge base. Author(s) Institute of Water Modelling Institution(s) Institute of Water Modelling Model(s) MIKE Basin Currency 2009-2010 Scope Surface water quantity and water simulation. Model/Data Description The Ganges Basin represented with 131sub-basin. Includes major reservoirs, and diversion structures. The model accounts for water content in four different storages. NAM parameters were initially derived from catchment characteristics, but the final parameters was calibrated against time series of hydrologic observations. Linear Reservoir and Wave translation routing methods used for hydrological routing in different reaches of the Ganges Basin.

Availability/Accessibility Model Proprietary Input data files: Not published Data files Output data files: Not published Report(s) Technical Report:Ganges River Basin Modelling {Institute of Water Modelling, 2010 #86} Interdependence in water resource development in the Ganges: an economic analysis {Wu, 2013 Other publications #198} Spatial and Temporal Boundaries Spatial Extent Ganges Basin Outlet Point Bay of Bengal Temporal Daily Resolution Time Period 1998-2006 Data Requirements Component Source Publicly Available DEM SRTM Yes Drainage SRTM Yes network/Sub basin Watershed Maps of India Yes boundary Public Literature Yes Land Use/Cover Not Provided Unknown Soils FAO Yes Meteorological TRMM Yes IITM Yes Indian Metrological Dept. Yes IMD Nepal Yes BDWB Yes Runoff Data Government of Nepal No Government of Bangladesh (BDWD) No GRDC Yes Reservoirs/Diversions World Bank Publication Yes Google Earth Yes India CWC Yes Key Assumptions and Limitations Assumptions Water demand for irrigation and urban is based on capacity and water availability. Although there are around 206 dams/reservoirs in the basin, only 36 reservoirs were modelled. The number or diversions that were modelled was 35, but 44 diversions were identified through research. Numerous small reservoir and diversion could not be located. Water demand in canals could not be estimated; diversions was based on flow capacity. Stations that had missing values, nearby stations were use as a ratio during a known time series. Daily flow values were adjusted using a

ratio. Reservoir or diversion that could not be located or obtained were lumped in the respective river basin. Canal operate at full capacity from June-October, and 30% at full capacity from November - May. Data Limitations No flow observations are available for India and are not calibrated/validated. Lack of high altitude climate stations including Nepal. IMD datasets did not properly correlate with TRMM datasets when performed at a monthly scale. Sediment supply is not available.Limited data availability on water storage and water transfer in India. Model Limitations Simplified snowmelt model that does not include glacier formation and melting. Climate change impact assessment of water resources of India. Inform dialogue by Title/Purpose assessing the impacts of climate change to determine hotspots.

Author(s) A. K. Gosain1, Sandhya Rao1 and Anamika Arora2 Institution(s) 1IIT Delhi and 2INRM Consultants Model(s) SWAT Currency 2011?, unknown duration Scope Surface water quantity and water simulation. Model/Data Description The Ganges basin model does not include reservoirs, or diversion structures. Each sub-basin subdivided into Hydrologic Response Units (based on soil type, land cover and land management). The daily reanalysis and re-gridded climate data (rainfall, temperature, wind speed, relative humidity and solar radiation) used. Rainfall data at 0.44° X 0.44°. Runoff model using Soil Conservation Service (USDA NRCS) methodology. Availability/Accessibility Model Public domain (but requires proprietary ArcGIS) Input data files: http://gisserver.civil.iitd.ac.in/natcom Data files Output data files: http://gisserver.civil.iitd.ac.in/natcom Report(s) Technical report produced: Unknown Other publications No Spatial and Temporal Boundaries Spatial Extent Ganges Basin Outlet Point Outlet: India-Bangladesh Border Temporal Daily Resolution Time Period 1961-1990, 2021-2050, 2071-2098 Data Requirements Component Source Publicly Available DEM GTOPO30 Yes Drainage network Hydroshed USGS Yes Land Use/Cover University of Maryland Global Land Cover Yes Soils FAO yes 47

Meteorological IITM Yes Key Assumptions and Limitations Assumptions Existing land use is in virgin conditions. Land use does not change from existing conditions to future conditions. Data Limitations No reservoir or diversion structures represented in the system. Model does not account for irrigation. Lack of high altitude climate stations. Lack of climate data for Nepal, Tibet. Model Limitations Simplified snowmelt model. Ganges Modelling. Informed dialogue by mapping flood inundation extent for different Title/Purpose return periods. Author(s) Nishadi Eriyagama Institution(s) International Water Management Institution (IWMI) Model(s) HEC-HMS Currency 2013 Scope Surface water quantity simulation. Model/Data Description The Ganga Basin was divided into 79 sub basins while the stream network was divided into 53 river reaches in order to set up the model. The hydrologic model consists basically of the Basin model and the Meteorological Model. Daily records from 86 precipitation stations were used and gage weights were derived using Theissen Polygon. Runoff model using Soil Conservation Service (USDA NRCS) methodology. Availability/Accessibility Model Public domain (but requires proprietary ArcGIS) Input data files: Currently non available Data files Output data files: Currently non available Report(s) Technical report produced: Unknown Other publications No Spatial and Temporal Boundaries Spatial Extent Ganga Basin Outlet Point Farakka Bridge Temporal 30 minute intervals Resolution Time Period 1987-1999 Data Requirements Component Source Publicly Available Precipitation data Indian and Nepalese Meteorological Departments No Daily discharge data Bangladesh Ministry of Water Resources No at Farakka Bridge Satellite derived Unknown No discharge data 48

DEM Unknown Unknown Key Assumptions and Limitations Assumptions Evapotranspiration is negligible during times of floods. Flow attenuation due to storage structures may be accounted for with sufficient reductions in Curve Number. Data Limitations Observed data is available at only a few places to calibrate the model. Number of rainfall data stations after 1999 is insufficient to run the model. No reservoir operational data is available. Model Limitations Mathematical Models are uncoupled, which means some components of the model are not solved as a simultaneous equation. All mathematical models use constant parameter values.

A megacity in a changing climate: the case of Kolkata. Surface water quantity, Title/Purpose hydrodynamic, and water simulation. Author(s) Prof A. K. Gosain, Dr Sandhya Rao and others Institution(s) INRM Consultants and IIT Delhi Model(s) SWAT 2005, HEC-RAS, SWMM Currency 2011 Scope Model/Data Description SWAT model was generated for the Hooghly River basin. Water flow from the diversions upstream is included in the model. The basin or sub-basins subdivided into Hydrologic Response Units (based on soil type, land cover and land management). The daily reanalysis and re-gridded climate data (rainfall, temperature) used. Rainfall data at 0.5° X 0.5°. Temperature was sampled at 1° X 1°. Runoff model using Soil Conservation Service (USDA NRCS) methodology. HEC-RAS was model was setup for the Hooghly River. Daily flow data from SWAT was entered at the upstream boundary and downstream boundary was affected by the tidal outlet from different storm return periods. HEC-RAS water surface elevation is computed using the energy equation and the iterative standard step method. Availability/Accessibility Model Public domain (but requires proprietary ArcGIS) Input data files: Not Published Data files Output data files: Not published Report(s) Climate Risks and Adaptation in Asian Coastal Megacities {World Bank, 2010 #219} Other publications Spatial and Temporal Boundaries Spatial Extent Hooghly Basin from Farakka to Ganga Sagar in West Bengal Outlet Point - Temporal Daily? Resolution Time Period 1975-2004 49

Data Requirements Component Source Publicly Available DEM SRTM Yes Landuse Global Land use USGS Yes Soil FAO Yes Weather (rainfall and IMD Available to Temperature) research institutes District Statistics Census India, CGWB district reports Yes (Agriculture ground water, population) Stream Cross- Unknown Unknown Section Tidal Data Literature Yes SWMM Input Unknown Unknown Key Assumptions and Limitations Assumptions Release from Farakka to Hooghly was assumed from the Farakka treaty. No change in future landuse. In the absence of the data on irrigation diversions, irrigation water use estimated using crop demand modelling. Current crop management practices were inferred from land use map, irrigation source map, command area map and district-wise average irrigation information. Hydraulic capacity of sewers in Kolkata have been reduced, so a siltation of 30% was used. Data Limitations Lack of high altitude climate stations. Water diversion: Canal command area, canal network, time series canal diversions and discharges. Lack of information on groundwater depth of shallow and deep aquifer. No calibration or validation data. No detailed information on sewer capacity. Land subsidence affects conveyance capacity is not evaluated. Major pumping stations operate much less than their related capacity. Urban ground elevation z data is not provided and maybe be suitable determine extent of flooding. Model Limitations Simplified snowmelt model. Temporal mismatch between coupling of models. HEC-RAS does not account for account for 2D flow. Model assumes channel bed slope too small to avoid vertical pressure head. Dynamic modelling of the Ganga river system: impacts of future climate and socio- Title/Purpose economic change on flows and nitrogen fluxes in India and Bangladesh. Assess impacts of climate change and socio economic changes on flow and water quality. P. G. Whitehead1, S. Sarkar2, L. Jin3, M. N. Futter4, J. Caesar5, E. Barbour1, D. Butterfield1, Author(s) R. Sinha2, R. Nicholls6, C. Hutton6 and H. D. Leckie1 1University of Oxford, 2IIT Kanpur, 3SUNY at Cortland, 4Swedish University of Agricultural Institution(s) Science, 5Met Office Hadley Centre, 6University of Southampton Model(s) Integrated Catchment Model (INCA) Currency Completed July 2014

Scope Model flow and water quality on the Ganga Model/Data Description INCA model was setup with 70 reaches that covers all tributaries. Reach boundaries were selected based on confluence point, sampling or monitoring point, of effluent input/abstraction associated with major irrigation scheme or large river. Land use data was aggregated from 26 classes to 6 classes. INCA performs a mass balance accounting for all inputs and output into the basin. Availability/Accessibility Model Subject to use agreement Input date files: Unknown Data files Output data files: Unknown Report(s) Reports and papers in preparation Other publications Spatial and Temporal Boundaries Spatial Extent Ganges Basin Outlet Point Outlet: Bay of Bengal Temporal Daily Resolution Time Period 1981-2000, 2015-2099 Data Requirements Component Source Publicly Available Climate data UK Met office No NASA satellite data Yes Land use data India National remote sensing centre Yes River reach and DTM NASA shuttle data Yes Sewage treatment India CWPU Yes data Flow data India states No Water quality data CWPU Yes Key Assumptions and Limitations Assumptions Dams were not considered as part of the model. Assumes groundwater abstractions will increase by 22.7%. Water transfer is based on 20% of the upstream reaches. Data Limitations Observed flow data is sparse on the Ganga River System.Water quality points are limited to monthly observations along the river and observations from Hardinge Bridge. Population, land use, and atmospheric nitrogen can vary widely. Model Limitations Can model up to 6 land use. Cannot model variations in nitrogen based on land use and age. Applicable if there is a forest with different ages, where an average value is used.

Highnoon. Informed dialogue by assessing the impact of Himalayan glaciers retreat and possible changes of the Indian summer monsoon on the spatial and temporal distribution Title/Purpose of water resources in Northern India and provide recommendations and strategies that strengthen the cause for adaptation to hydrological extreme events. Author(s) Prof A K Gosain1 Dr Sandhya Rao2 and others Institution(s) 1IIT Delhi and 2INRM Consultants Model(s) SWAT 2009 Currency 2010/2011 Scope Surface water quantity and water simulation. Model/Data Description Ganges Basin represented by 414 sub-basins. Includes major reservoirs, diversion structures and major sewage disposal sites. Each sub-basin subdivided into Hydrologic Response Units (based on soil type, land cover and land management). The daily reanalysis and re-gridded climate data (rainfall, temperature, wind speed and solar radiation) used. Rainfall data at 0.5° X 0.5°. Relative humidity generated from long-term statistics and sampled at 1° X 1°. Runoff model using Soil Conservation Service (USDA NRCS) methodology. Availability/Accessibility Model Public domain (but requires proprietary ArcGIS) Input data files: Not published Data files Output data files: Not published Report(s) Technical Report: Snow and Glacier originated run-off generation{Gosain, 2012 #85} Other publications Snowmelt contributions to discharge of the Ganges{Siderius, 2013 #28} Spatial and Temporal Boundaries Spatial Extent Ganga Basin up to Bangladesh border Outlet Point Temporal Daily, monthly, annual Resolution Time Period 1965-2001 Data Requirements Component Source Publicly Available DEM SRTM Yes Landuse IWMI, NRSC IWMI Public, Soil FAO Yes Meteorlogical WATCH Research Institutes Discharge GRDC Yes

Nepal (ICIMOD) No

District Statistics Census India, CGWB district reports Yes (Agriculture ground water, population) Key Assumptions and Limitations Assumptions Although there are around 206 dams/reservoirs in the basin, only 104 were included given data availability. In the absence of the data on irrigation diversions, irrigation water use estimated using crop demand modelling. Current crop management practices were inferred from land use map, irrigation source map, command area map and district-wise average irrigation information. Future irrigation demand estimated based on population projections and implied food demand. No change in future land use. Data Limitations No flow observations available for India. Flows in the India portion of the basin thus not calibrated/validated. Lack of high altitude climate stations. Lack of climate data for Nepal, Tibet. Point sources location, load, type of pollutants. Weather generator creates weather parameters of wind speed, relative humidity etc. Lack of time series data on water diversion. Point sources location, load, type of pollutants. Lack of data on snow and glaciers. Irrigation assumptions on the source and amount of irrigation, cropping pattern. Model Limitations Simplified snowmelt module. Assumes uniform climatic data per sub-basin. Modelling hydrology, groundwater recharge and non-point nitrate loadings in the Himalayan Upper Yamuna basin. Inform dialogue by validating an integrated Title/Purpose hydrological, groundwater-and water quality framework for the prediction of water quality and quantity and climate change on water resource management in the upper Himalayans. Author(s) Kapil K. Narula1 and A.K. Gosain2 Institution(s) 1Columbia University, and 2IIT Delhi Model(s) ArcSWAT 2000, MODFLOW MT3DMS, Aquaveo GMS Ver. 5.1 Currency ? Scope Surface water quantity and quality, groundwater, and water simulation. Model/Data Description Upper Yamuna basin is divided into multiple sub basins. Each sub-basin subdivided into Hydrologic Response Units (based on soil type, land cover and land management) The daily reanalysis and re-gridded climate data (rainfall, temperature, wind speed and solar radiation) used. Runoff modelled using Soil Conservation Service (USDA NRCS) methodology and Green-Ampt infiltration method. SWAT’s hydrologic components were combined to specify fluxes for MODFLOW for each sub-basin and then distributed to each grid cell. Each grid cell assumes uniform aquifer properties. Sub-basin boundaries are considered no flow boundaries. Aquifer spatial parameters are derived from geostatistical and stochastic techniques. Aquifer thickness was obtained from borehole logs. Well package of MODFLOW simulates pumping and injection well. MODFLOW simulates aquifer systems using Darcy’s Law where water is conveyed from high head to low head. MT3DMS grid model was setup based on the results of MODFLOW. Nitrate reduction was modelled using a first order irreversible reaction. Availability/Accessibility Public domain ((but SWAT requires proprietary ArcGIS); Model Public domain MODFLOW and MT3DMS requires proprietary Aquaveo GMS)

Input data files published: not available Data files Output data files not published Report(s) Technical Report Produced: Unknown Other publications No Spatial and Temporal Boundaries Spatial Extent Upper Yamuna Watershed Outlet Point Tajewala Temporal Monthly Resolution Time Period 1961-1990, 2071-2100 Data Requirements Component Source Publicly Available DEM Survey of India Yes Land Use/Cover Survey of India, Landsat Yes State Agriculture Board Unknown Soils National Bureau of Soil Survey and Land use Planning No National Thematic Map Organisation Yes Meteorological Indian Metrological Dept. Yes Runoff Data Central Water Commission No Water Quality Data CPCB, SPCB Yes Crop and Fertilizer Fertilizer Association of India Yes Hydrogeological Geological Survey of India Yes National Thematic Map Organization State Groundwater Boards Yes Varies Key Assumptions and Limitations Assumptions Future pollution loading, land use, water usage demands, fertilizer and pumping remains constant. Compatible time steps between models. Data Limitations Limited flow and groundwater observations in India. Lack of high altitude climate stations. Lack of information on pollution source loading location, and type. Lack of water quality observation data. Regional groundwater model where sub basin do not follow the sub - basins. Does not include any other form of Nitrogen(NO2 ) Model Limitations SWAT uses simplified snowmelt model. Principal directions of horizontal hydraulic conductivity and transmissivity do not vary within the system in MODFLOW. Transport time step is more stringent than the flow time step in MT3DMS, so the transport step assumes constant hydraulic head and fluxes. Ganges River Basin Modelling. Inform dialogue by developing a hydrodynamic model to Title/Purpose analyse scenarios in changes in flow regime and contribute to the knowledge base.

Author(s) Institute of Water Modelling Institution(s) Institute of Water Modelling Model(s) MIKE11 Currency 2009-2010 Scope Surface water quantity and water simulation. Model/Data Description The MIKE11 rainfall-runoff model consists of 156 catchments out of which 17 border catchments. Weirs and culverts were incorporated into the model. The model consists of regional rivers, floodplain channels, and linked channels to transfer the floodplain flow. Groundwater abstraction is used in irrigation. The HD model has 13 observed water level boundaries, 25 rated discharge boundaries, and 51 constant discharge boundaries. Downstream boundaries are water surface elevation and upstream boundaries are constant discharge. MIKE11 hydrodynamic model solves the Saint Venant equation for unsteady surface flow using a six point Abbott scheme. MIKE11 salinity model is based on Advection Dispersion module. Availability/Accessibility Model Proprietary Input data files: Not published Data files Output data files: Not published Report(s) Technical Report: Ganges River Basin Modelling {Institute of Water Modelling, 2010 #86} Other publications Spatial and Temporal Boundaries Spatial Extent Ganges Basin Outlet Point Bay of Bengal Temporal Daily Resolution Time Period 1998-2006 Data Requirements Component Source Publicly Available Bathymetry Data IWM No Stage Data Bangladesh Water Development Board No Meteorological BDWB No Runoff Data Government of Bangladesh (BDWD) No Key Assumptions and Limitations Assumptions In the absence rated discharge, the upstream-observed water levels were used at upstream boundaries. Channel bed boundary is fixed. Manning’s n value doesn’t seasonally change. Data Limitations Lack of information on water usage. Lack of information on sediment transport rates. Limited data availability on water storage and water transfer in India. Lack of detailed river models for India and Nepal. Lack of detailed salinity model for India.

Model Limitations MIKE11 does not account for account for 2D flow. Model assumes channel bed slope too small to avoid vertical pressure head. Estimating Nutrient Outflow from Agricultural Watersheds to the River Kali in India. itle/Purpose Inform dialogue by developing water quality equation that can be used to estimate pollution loading. 1 2 Author(s) Ramakar Jha ; C. S. P. Ojha, M.ASCE ; and K. K. S. Bhatia1 Institution(s) 1NIH, and 2IIT Roorkee Model(s) Mass Balance Currency 1999-2000 Scope Water quality modelling Model/Data Description The water quality was performed on a 10.35 km stretch of the River Kali at 4 locations. Drainage patterns, contour maps, spot heights, and built area maps were digitized into GIS. DEM was generated from the GIS data to determine flow direction and watershed area. Land cover determination was performed using a supervised classification using remote sensing data. Vegetative growth utilizing fertilizers, manure was determined using the Normalized Difference Vegetation Index (NDVI). Sampling was obtained three times daily on the 10th and 11th of every month during non-monsoon season while water quality sampling was done on storm basis. Four different grab samples were obtained at three different points across the river. The data were used to develop a distributed modelling equation that models nutrient decay in the stream. Availability/Accessibility Model Public Domain Input data files: Not published Data files Output data files Not published Report(s) Technical report produced: Unknown Other publications Development of Refined BOD and DO Models for Highly Polluted Kali River in India Spatial and Temporal Boundaries Spatial Extent River Kali Outlet Point Rastam - Miragpur Temporal Events? Resolution Time Period March 1999-February 2000 Data Requirements Component Source Publicly Available DEM Survey of India Yes Drainage network Survey of India Yes Land Use/Cover IRS Remote Sensing Yes Water Quality Grab Sample No Runoff Data Field Survey No 56

Key Assumptions and Limitations Assumptions There is a uniform distribution of pollution loading entering the reach are uniformly distributed. Stream has uniform hydraulic, geographic and climatic conditions. Nitrogen and phosphorus attenuation parameter do not vary. No point source pollution is discharged into the river. Regional groundwater flow (outside drainage boundary) is not being conveyed into the stream. When the overland slope was negligible, the flow direction was based on the previous section. NDVI computations were performed using reflection data. Data Limitations Lack of calibration or validation data outside the year of event. No long term pollution monitoring to ensure validation. Model Limitations Uniform distribution pollution loading entering the stream. Not applicable is there are point sources. Impact Assessment of Climate Change and Sea Level Rise on Monsoon Flooding. Title/Purpose Inform dialogue by assessing the impact on flooding during monsoon due to climate change. Md. Zahir-ul Haque Khan1, Mobassarul Hasan1, Md. Sohel Masud1, Tarun Kanti Author(s) Magumdar1, and Manirul Haque2 Institution(s) 1Climate Change Cell, 2Institute of Water Modelling Model(s) MIKE BASIN Currency 2009?, unknown duration Scope Surface water quantity and water simulation. Model/Data Description Ganges-Brahmaputra-Meghna Basin represented by 95 sub-basins where 55 basins were in the Ganges. Ganges tributaries were traced using the MIKE BASIN model. Irrigation demand was not included in the model Mean monthly pan evapotranspiration was computed using Christiansen method. Runoff modeling uses Nedbør- Afstrømnings- Model (NAM hydrological model). Basin routing is performed using the Muskingum and Wave Translation procedure. Availability/Accessibility Model Proprietary Input data files: Not published published Data files Output data files: Not published Report(s) Technical report produced: Unknown Other publications No Spatial and Temporal Boundaries Spatial Extent Ganges-Brahmaputra-Meghna Basin Outlet Point Bay of Bengal Temporal Daily Resolution Time Period 2005-2007,

Data Requirements Component Source Publicly Available DEM GTOPO30 Yes SRTM Yes Land Use/Cover Unknown Unknown Soils Unknown Unknown Meteorological IMD Yes TRMM Yes Gatech Unknown Runoff Data BDWB No Literature Yes Key Assumptions and Limitations Assumptions Irrigation water usage was not considered in the system. Data Limitations Data was obtained from secondary sources.

Ground measured evaporation data was only available for few sites in Bangladesh. Instantaneous discharge in India Nepal and Tibet was not available. Lack of high altitude climate stations. Lack of climate data for Nepal, Tibet..Rain-fed catchments subject to irrigation were ignored in the study. Model Limitations Simplified snowmelt model that does not include glacier formation and melting. NAM hydrologic model does not allow for spatial variability. Network models are insufficient to answer physically based questions such as flood propagation, attenuation and surface groundwater interaction. Simplified snow and glacier assumptions.

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