project deliverable: d03.1 water resources modelling …project deliverable: d01.1 requirements and...

Project Deliverable: D03.1 Water Resources Modelling Framework

Programme name: Sustainable Management of Scarce Resources in the Coastal Zone

Program Areas: A3, (d)

Project acronym: SMART

Contract number: ICA3-CT-2002-10006

Project Deliverable: D03.1: Water Resources Modelling Framework

Related Work Package: WP 03 Analytical Tools, Model

Type of Deliverable: RE Technical Report

Dissemination level: Public

Document Author: Kurt Feadr, ESS

Edited by:

Reviewed by:

Document Version: R 1.0

Revision history:

First Availability: 2003 06 30

Final Due Date: 2003 06 30

Last Modification: 25.07.2003

Hardcopy delivered to: Mrs. Cornelia Nauen European Commission, Research Directorate General SDME 1/02 B-1049 Brussels, Belgium

D03.1 , ESS GmbH 1 of 52

TABLE OF CONTENTS

1 Executive Summary .................................................................................................. 2 2 An INTRODUCTION TO WATERWARE................................................................... 3

2.1 Monitoring time series..................................................................................................... 3 2.2 Sub-catchment and runoff modelling .............................................................................. 3 2.3 Irrigation water demand .................................................................................................. 4

3. River Basin Objects ..................................................................................................... 7 River Network Representation................................................................................................. 10 RiverNode................................................................................................................................ 14 River Reaches ......................................................................................................................... 14 CrossSections.......................................................................................................................... 15

Sub catchments............................................................................................................. 16 Lakes and reservoirs ..................................................................................................... 22 Irrigation districts ........................................................................................................... 28 Settlements.................................................................................................................... 33 Pumping Stations .......................................................................................................... 38 WRM: Water Resources Management Model ............................................................... 40

2.4 WRM node types .......................................................................................................... 40 2.5 WRM reaches ............................................................................................................... 41 2.6 Model dynamics ............................................................................................................ 41 2.7 Storage Routing in Tributaries ...................................................................................... 47 2.8 WRM Data Requirements ............................................................................................. 47

References .................................................................................................................... 51

D03.1 , Water Resources Modelling Framework

2

1 EXECUTIVE SUMMARY

The overall objective of the SMART project is to develop, implement and test a new, participatory but scientifically sound and rational approach to planning and management of the coastal zone that can help to reconcile conflicting demands on scarce water. In essence, the project is concerned with testing a strategy for solving water demand conflicts.

A central tool for the scenario analysis that is the basis of the analytical approach of SMART is WaterWare, A rive basin scale water resources information system and management model.

WaterWare combines several components and functions

1. An information system that includes:

a. Time series analysis for hydro-meteorological variables which are used in the various simulation models;

b. An embedded GIS (all objects represented in the system are geo-referenced) with an associated web-based MAP SERVER;

c. A heterarchical object data base for river basin OBJECTS;

2. A simulation system that includes:

a. A rainfall-runoff model

b. An irrigation water demand model

c. A statistical drought assessment model

d. A water allocation (demand-supply balance model)

e. A set of water quality models (STREAM, BLTM, XGW) for surface and groundwater, respectively;

In addition, the system provide a set of interfaces for external models; in the case of SMART, this provides a link to the TELEMAC coastal water quality model.

3. A decision-support components based on a discrete multi-criteria assessment methodology (reference point optimisation).

Within the framework of SMART, and to meet the requirements defined in WP 01 and WP02, the set of models is being extended to include

• A dynamic regional development model

• A dynamic land-use change model

• An embedded rule-based expert system for the assessment of socio-economic and environmental impacts based on the simulated demand-supply balance.

Project Deliverable: D01.1 Requirements and Constraints Report

D03.1 ESS GmbH 3 of 52

2 AN INTODUCTION TO WATERWARE WaterWare organises the data describing a river basin in terms of spatial objects: they include elements such as monitoring stations and their associated time series of measurements, sub-catchments and irrigation districts, the river network with it nodes and connecting reaches, as well as the various simulations models and their scenarios (Fedra and Jamieson, 1996a,b, Jamieson and Fedra 1996a,b). With all objects geo-referenced and the models spatially distributed, the embedded GIS is a central component. The embedded GIS The map layers used in WaterWare either provide background for spatial reference and orientation, or direct data input for the simulation models. Examples for the latter are the digital elevation model (DEM), land use maps, and the river network.

The embedded GIS offers tools for layer selection and stacking, zooming, colour editing, a four window mode for map comparison, 3D display of the DEM with any map draped over the elevation data, and read-back functions for locations, distances, or areas.

2.1 Monitoring time series. Historical data of rainfall, river flow, and air temperature, as well as water quality are stored for the various monitoring stations. Continuous ongoing measurements from selected stations can be transferred by GSM phones and incorporated into the data base in real-time to provide an accurate and up to date picture of the situation for real-time operational management applications.

These hydrographical and hydrometeorological observation data are not only analysed in their own right, they also form the input for the various simulation models.

Analysis of droughts A major problem for water resources management are droughts: prolonged periods of below-average rainfall that lead to low soil moistures, lowering of the groundwater table, and, most importantly, low flow in the river. This, in turn, leads to a combination of increased water demand for irrigation and a low availability of irrigation water: below a certain low-flow level, pumping water out of the river in fact becomes impossible, the pumps fall dry. Based on a model by Jamaluddin et al.,(2000), WaterWare links the time series of rainfall observations to a drought analysis module.

2.2 Sub-catchment and runoff modelling The water resources model needs river flow at all of its start nodes, representing inputs. These can be well fields, where groundwater enters the surface water budget, or sub-catchments. For the latter, a rainfall-runoff model provides data for ungaged catchments, but also the possibility for scenario analysis of land-use changes or long-term climate change. Data such as catchment boundaries, elevations and slopes, land use, as well as rainfall inputs are automatically taken from the GIS and time series data base, respectively.



2.3 Irrigation water demand Irrigated agriculture, and rice paddies in particular, are the dominant consumer of water, by far exceeding industrial and domestic demand. The water demand in a given year depends on the naturally available water through rainfall, but also the areas and crop varieties to be irrigated, irrigation technology, the conveyance systems (e.g., lined versus unlined irrigation canals), and operational control. A specific simulation model is used to predict the water demand for any of the irrigation districts in the basin.

Water resources allocation

The central model in the WaterWare system is a dynamic, water resources model that computes a daily water budget for all nodes in the river network. The model computes water budgets in terms of demand and supply, routing the water from the start nodes (sub-catchments) to the demand nodes (irrigation districts and cities) and ultimately the sea. Different allocation strategies and policies can thus be tested for the effectiveness and efficiency. By adding a simple estimation routine for the net economic benefit for different types of water use, an overall economic optimisation of the water allocation is possible.

River water quality The flow in the individual reaches of the river network is a major determinant for water quality: dilution is a major factor in pollution. The dynamic water quality model describes the balance of organic load, measured as BOD (biological oxygen demand) and dissolved oxygen, as well as any arbitrary pollutant, conservative or undergoing first-order decay. Examples would be agrochemicals such as fertilizers and pesticides, or the salts leached out from irrigated agricultural soils. Sources of pollution are major settlements and their waster treatment plants, as well as any major industrial or agricultural water users that return used process or irrigation water to the system. The model treats both points sources of pollution, as well as lateral inflow from diffuse sources.

Groundwater flow and quality Similar to the contamination of surface water, groundwater pollution can result from the large-scale application of fertilizers and agrochemicals. Waste management in the form of badly managed land fills is another potential source of groundwater pollution in the humid tropics. The groundwater model describes the first, shallow aquifer that is directly exposed to non-point source pollution. The major driving forces include the spatially distributed recharge from rainfall depending on land use, infiltration or exfiltration from and to the river, and the pumping of groundwater in shallow wells, that constitute the majority of small, domestic wells. Spatially varying characteristics of the aquifer and landuse are directly taken from the GIS. Excessive levels of nitrates that can pose a long-term health hazard are the major problem.

Environmental Impact assessment



A water resources management system is subject to structural changes such as new reservoirs, or policy changes resulting in a modified water allocation pattern. Any such project or policy change will have a range of environmental impacts, positive or negative. For the screening level assessment of such projects, and new reservoirs in particular, WaterWare offers a rule-based expert system for environmental impact assessment (Fedra et al., 1991). A checklist of potential problems is used together with a set of rules for the evaluation, with the data coming from the GIS, the object data base, and model results. The inference engine uses a combination of forward and backward chaining (Fedra and Winkelbauer, 2002), to provide a classification of all potential problems relevant for a given project and environment.



IMPLEMENTATION In SMART, the primary and in any case initial implementation of the WaterWare system will be at a central ASP server, accessible through the web.

This will greatly simplify the hardware requirements for the partners, but also make the continuing updates and user support during the development phase easier than a distributed implementation.



3. RIVER BASIN OBJECTS

WaterWare structures any river basin by sets of interacting objects. These objects are implemented with HOT, the Heterarchical Object Tool which is a central components of the ACAToolKit.

There are three types of objects:

The first type, called RIVER BASIN OBJECTS, represent real world entities: such as reservoirs, catchments, cities, reservoirs, or treatment plants.

The second type, NETWORK OBJECTS, represent a different layer of abstraction, such as models of a river system or network.

The final type are SCENARIOS and they represent model oriented collections of instantiations of NETWORK OBJECTS that are partially derived from RIVER BASIN OBJECTS.

All objects are spatially referenced, that is, they are known by location (map display and selection), as a single point (observation station), as a reference point designating a larger object (lake, city), as a rectangle including one or several points or polygons (irrigation district), or a as polygon (sub catchment).

Objects have two functions:

1. they can obtain or update their current state (load, compute, infer, etc.) in a given context, referring to SOURCES (which may be other objects), through a set of METHODS;

2. can report their current state or parts of the their state to CLIENTS (the screen, to each other, to models, a hardcopy device, etc.).

For example, sub-catchment objects use the rainfall-runoff model RRM to obtain the runoff from the catchment under a set of landuse, internal water use, and meteorological conditions (the latter are obtained as time series from a climate stations object); this runoff, in turn, is used by the water resources model WRM as input for a start node (sub-catchment node). In the same way, demand nodes in WRM are linked to various river basin objects (settlement, industries, irrigation districts), and obtain their detailed behavior over time (e.g., water demand, consumptive use coefficients, losses, etc.) from these objects.

Through the location of objects, the linkage to the GIS layers is established, so that spatial concepts (such as catchment, river reach, or the neighborhood of a point location) can be used for calculations (methods) by the objects.

The objects in WaterWare are grouped by CLASS.

Classes currently supported are:

CS: Climate stations

FM: Flow measurements

WQ: Water quality

SE: Settlements

WW: Water works



TP: Treatment plants

IN: Industries

AF: Animal farms and feedlots

IR: Irrigation districts

SC: Sub-catchments

LR: Dams and Reservoirs

LA: Lakes

SW: Weirs and falls

SG: Gates and sluices

AB: Abstractions

AQ: Aquifers

WE: Wells

BO: Boreholes

XS: Cross sections

SS: Scenic sites

Each of these classes may have any number of elements.

Each class has a set of specific attributes, organized in a set of data structures and associated METHODS that include

1. a HEADER with name and id (mandatory), location, and meta-data information;

2. Tables of Descriptors, using XPS library functions for editing and inference; or references to related objects;

Objects may be linked to other objects, for example, a treatment plant may lead on to a flow and a water quality observation station and its data, and objects have hypertext files that provide further explanation, meta data, and context.

Objects have methods available, which allow them to obtain some of their dynamic or derived properties in a specific context. Many object properties are static and can be stored in their respective data bases and files. Other object properties, such as the outflow from a sub-catchment or the monthly water requirements of an irrigation district, depend on numerous controlling variables or plans, decisions, and assumptions. Models such as the RRM rain-runoff model or the irrigation water demand estimation model IRR can be triggered by the respective objects (i.e., sub-catchments, irrigation districts) to estimate such values as their attributes. They can in turn be fed to a sub-catchment start node or an irrigation demand node in the river network, and provide input the corresponding simulation models.

The context for such an estimation is the default (reference) year and all observations and data pertaining to it. Alternatively, the context can be defined by a model specific scenario (including, for example, the selection of a specific year or period and its hydrometeorological characteristics), and, within this constraint, by a set of user specified assumptions.



2. The Object Data Base In the data base module, a hierarchical class/element selector is displayed with a parallel basin map showing the element's location with unique class symbols.

Selecting a class leads to a selector of the elements of this class, which are also displayed and highlighted on a parallel map window. Selecting any of the elements in the data base invokes a screen display function for the respective data types, for example, time series data, i.e., climate stations, flow measurements, and water quality, all use the same display screen.

This screen display function enables (selective) editing of attributes (currently descriptors only) and provides load and save functions to make changes permanent.



River Network Representation From a hydrological and water resources point of view, a catchment or river basin can be conceptualised as a network or directed graph, of nodes representing objects that affect the flow of water (physical objects like sub-catchment, reservoirs, or irrigation districts), and the reaches connecting them, i.e., the river system proper.

Please note that in estuaries, or with pumped irrigation or storage systems, flows within the channels of the network may be reversed from their original gravitational direction, so that the graph can no longer be treated as strictly directed.

A river network as we know it within the WaterWare system is made up of several classes of objects:

RiverNetwork itself, which described the connectivity or topology of the network.

is component elements, which are:

RiverNodes,

River Reaches, and their

Cross-sections.

A RiverNetwork object may contain a set of RiverNode, Reach, Cross-section objects. The absolute minimal network would consist of two nodes, one reach, and one cross section.

Each of these 4 kinds of objects have data which can be divided into two layers:

Generic

Model specific

The Generic layer of all 4 kinds of objects must contain data which is "generic" in the true sense, reflecting the actual river. There is no model- specific data present at this layer. There may be several model-specific layers (one for each different model), which contains data which is in addition to the data in the generic layer.

The Generic RiverNetwork

The generic representation of the river network stores the connectivity information of the river network, and contains model-independent data for all the 4 different kinds of objects specified above. This may consist of a "superset" representation of the entire catchment which contains ALL the generic information for the river but can be further broken up into different "sub" scenarios or sub-catchments for the various models.

RiverNetwork

The RiverNetwork object contains the RiverNode, Reach, CrossSection objects. It maintains the integrity of the network, and all changes in connectivity are done through it. It also knows how to traverse, and keeps track of changes occurring within the network. In a sense, the RiverNetwork object acts as a controller.

At the generic level, the RiverNetwork object, in itself does not contain any scenario-specific data other than the connectivity.

Convention for IDs



Each object in the river network (including the RiverNodes, Reaches, CrossSections, and the RiverNetwork itself) must have a unique ID. Different kinds of objects cannot share an ID. Thus if there is a River-Node with an ID "NAA10", there cannot be a Reach with the same ID.

All IDs in the river-network (generic and model) must be an alpha-numeric string (no special characters, no underscores/spaces/etc.) having a length not more than 16 characters.

The RiverNodes, by convention, begin with the character "N". The set of alphabets after that identify the branch. This set of alphabets starts from (A, B, ..., Z, AA, AB, ..., AZ, BA, BB, ..) like in a spread-sheet. The set of numbers after that identify the number of the RiverNode in that branch. The numbers are incremented in a step of 10, so that if a node needs to be inserted between two nodes, then the sequence of numbers remains unbroken.

for example: NAA10 means that this is an ID for a RiverNode, branch is "AA" and number is "10". The second node after that will be called NAA20. In future, if a node need to be inserted between NAA10 and NAA20, it can be called NAA15, and the sequence remains unbroken.

The IDs for Reaches, by convention, begin with the character "R". The IDs for Cross-sections must begin with the character "C". The convention for the rest of the name remains the same as that for RiverNodes.

This convention is intended to help in easily identifying branches in the future when the system gets more complex with editing facilities. It also helps in identifying certain nodes or set of nodes when creating the generic superset network. ##################################################################### ### The Generic River Network Template ##################################################################### # start header ------ # Max length of ANY line in header is 96 characters # Max no. of editable ME lines via user interface = 3 NA RNET template header # header information ID LERMA # unique network id ME Meta Information 1 # meta information 1 ME Meta Information 2 # ... ME Meta Information n # meta information n AU patel Thu Feb 23 12:45:55 1995 # automatically inserted # end header ------ ##################################################################### ## Data for River Nodes ##################################################################### # recognized genericNodeType # 10 startNode # 11 startNodeSpring # 12 startNodeSubcatch # 13 startNodeGWater # 14 startNodeTransfer # 30 endNode # 40 confluenceNode # 50 diversionNode # 60 geomNode # 61 geomNodeWeir,



# 62 geomNodeNewreach, # 70 contNode # 71 contNodeFConstraint # 72 contNodeObserv # 73 contNodeCalib # 80 demandNode # 81 demandNodeMuni # 82 demandNodeIndus # 83 demandNodeIrrig # 100 reservoirNode # 101 reservoirNodePower TABLE RNODE # generic river-node E rnode_id # rnode id E rnode_type # genericNodeType (see above) E dpyinfo_x # x-position in schematic diagram E dpyinfo_y # y-position in schematic diagram E georef_x # geo reference (X position/Latitude) E georef_y # geo reference (Y position/Longitude) E georef_z # altitude/elevation E rbhook # link to the RiverBasinObject (id) E description # some description on what-am-i D NA2210 81 43 11 -102.566 20.2667 1577 NULL BRISENAS_DE_MATAMOROS END_TABLE ##################################################################### ## Data for Reaches ##################################################################### TABLE REACH # Reaches E reach_id # reach id E head_rnode_id # id of rnode at head of the reach E tail_rnode_id # id of rnode at tail of the reach E length # length of the reach E slope # slope of the reach E roughness # roughness (Mannings N) E no_csections # No. of cross sections on the reach (n) E csid1_csidn # id's of cross sections on the reach (1..n) # separated with a single underscore "_" D RZZ80 NZZ80 NBB50 0 0 0.013 2 CS10 CS12 D RNZ60 NNZ60 NNZ61 0 0 0.013 0 END_TABLE ##################################################################### ## Data for Cross-sections ##################################################################### TABLE CSECTION # Cross-sections E csection_id # csection id E ref_x # reference point (center of csection): x-position E ref_y # : y-position E ref_z # : altitude D CS31 -100.761 20.57 1706.01



D CS44 99.5217 19.2875 2562.2 D CS41 -100.674 20.0506 1830 D CS51 0 0 0 END_TABLE



RiverNode A RiverNode is a graphical entity in the river-network. It can have either of the following types: # 10 startNode # 11 startNodeSpring # 12 startNodeSubcatch # 13 startNodeGWater # 14 startNodeTransfer # 30 endNode # 40 confluenceNode # 50 diversionNode # 60 geomNode # 61 geomNodeWeir, # 62 geomNodeNewreach, # 70 contNode # 71 contNodeFConstraint # 72 contNodeObserv # 73 contNodeCalib # 80 demandNode # 81 demandNodeMuni # 82 demandNodeIndus # 83 demandNodeIrrig # 100 reservoirNode # 101 reservoirNodePower

Besides that, each River-Node has: - description - (x,y) position in the schematic diagram - geo reference position (x, y, altitude) in the real-world - the ID of the RiverBasinObject to which it is potentially linked to, and from which it should get its additional properties. E rnode_id # rnode id E rnode_type # genericNodeType (see above) E dpyinfo_x # x-position in schematic diagram E dpyinfo_y # y-position in schematic diagram E georef_x # geo reference (X position/Latitude) E georef_y # geo reference (Y position/Longitude) E georef_z # altitude/elevation E rbhook # link to the RiverBasinObject (id) E description # some description on what-am-i (max 96 char)

River Reaches A reach is a geographical entity, representing a "segment" of the real river. It is made up of a list of Cross-sections which make the channel of the river.

A Reach also holds the connectivity information for the network. A reach MUST have a RiverNode at its head, and a RiverNode at its tail. A Reach cannot exist otherwise. Two different reaches may be connected to the same RiverNode.

The following data exists for a Reach: E reach_id # reach id E head_rnode_id # id of rnode at head of the reach E tail_rnode_id # id of rnode at tail of the reach



E length # length of the reach E slope # slope of the reach E roughness # roughness (Mannings N) E no_csections # No. of cross sections on the reach (n) E csid1_csidn # id's of cross sections on the reach (1..n) # (separated with an underscore "_")

CrossSections A Cross-Section represents the cross-section of the river. It is assumed that the cross-section is perpendicular to the flow of the river. A cross-section has a reference point (x, y, altitude), positioned at the bottom center, which specifies the actual geographical location of the cross-section in the real world.

A cross-section consists of a list of points which define the cross-section. However, this is currently not used, hence not editable in the current scenario.

Generic data for a cross-section: E csection_id # csection id E ref_x # reference point (center of csection): x-position E ref_y # : y-position E ref_z # : altitude



SUB CATCHMENTS Catchment objects file are located, by default, in the directory ./data/objects/catchments.

The location of each individual file, however, is determined by the corresponding entry in the object CONFIG file ./data/objects/CONFIG: CLASS Sub-catchments SC E La_Laja_1 SC20 ./data/objects/catchments/SC20.dat ENDCLASS The object data file consists of the standard blocks:

• Header

• Name and hypertext link

• Component widget (input set) declarations

• Individual widget data TABLEs

Header: NA La_Laja_1 ID SC20 LO -100.8304 LA 20.8565 EL 1854.0000 TABLE content E type E value D ID La_Laja_1 D TITLE La_Laja_1 D HYfile catchments/display/La_Laja_1 D HYtitle La_Laja_1 D EXfile catchments/display/La_Laja_1 D EXtitle La_Laja_1 END_TABLE This contains:

NA the display name for the object;

ID unique id string for the object;

LO Longitude, in GIS world coordinates;

LA Latitude, in GIS world coordinates;

EL elevation, in masl (meters above sea level).;

TABLE content

defines TITLE, the hypertext file URL for the embedded hypertext browser, and the help- and explain file accessible through the info icon.



Component widget declarations: TABLE input_sets E method E data_table E default_prefix D widget content catchment.widget D disp_hypertext content catchment.htext D disp_gl_properties descriptors catchment.prop D disp_address address catchment.address D disp_map local_map catchment.map D disp_pie pie catchment.pie D disp_bars area/elevation catchment.bar D disp_ts time_series catchment.ts END_TABLE For each component widget, the TABLE specifies the method or function name, the name of the corresponding data TABLE in the object definition, and the standard prefix of the associated defaults (in ./data/defaults.

The component widgets and their functions are:

widget the catchment object display widget itself;

disp_hypertext embedded hypertext display (browser)

display_gl_properties parameter (Descriptor) list

disp_address address and/or symbolic georeference

disp_map local map display

disp_pie pie chart display (for the landuse distribution)

disp_bars display function for the basin orography (hypsographic curve)

disp_ts time series display function

Pie chart The pie chart in the catchment object is used to display the land cover distribution. However, the pie chart widget is fully generic and data driven: TABLE pie E name E descriptor E red E green E blue D forest landcover_forest 0 150 0 D agriculture landcover_agriculture 255 255 0 D meadows landcover_meadows 0 255 0 D residual landcover_residual 150 150 150 END_TABLE



The TABLE items describe:

descriptor Descriptor reference, link to the descriptor list TABLE that instantiates the corresponding values;

red display color (BLUE component of the RGB model) for this element

green display color (GREEN component of the RGB model) for this element

red display color (RED component of the RGB model) for this element

Parameter list This TABLE displays the main set of watershed parameters; they are Descriptors, so that the editing tools of the embedded expert system can be used: this is switched on by the method key word ask_box, which refers to the XPS editing dialog tool. TABLE descriptors E name E value E method D catchment_size 4909.77 ask_box D landcover_forest 74.597046 ask_box D landcover_meadows 3.210581 ask_box D landcover_agriculture 18.048093 ask_box D landcover_residual 4.144280 ask_box D soil_type medium_textured ask_box D basin_length 112.26 ask_box D min_elevation 1854.0 ask_box D max_elevation 2941.0 ask_box D channel_length 77.0 ask_box D channel_width 5.0 ask_box D drainage_length 308.0 ask_box END_TABLE The parameters include:

catchment_size ttoal extend of the catchment (upstream of the outflow point) in km2

landcover_forests landcover (absolute, in km2): forest

landcover_meadows landcover (absolute, in km2): meadows and pastures

landcover_agriculture landcover (absolute, in km2): agricultural fields

landcover_residual landcover (absolute, in km2): uncultivated areas, built-up land

soil_type soil type: one of a set of key words from the USGS soil definitions or FAO soil types

basin_length approximate measure of the basins main extend (along the main channel);

min_elevation minimum elevation describes the elevation (masl) of the outlet; please note that this should be consistent with the hypsographic curve



specified below)

max_elevation maximum elevation describes the maximum elevation of the watershed boundary (catchment boundary); please note that this should be consistent with the hyspographic curve specified below;

channel_length specifies the total length of the main (mainstream and first-order tributaries) channel;

channel_width approximate average (characteristic) width of the channel, e.g., corresponding to a point 2/3 from headwaters to outlet

drainage_length total length of the perennial channels in the natural drainage system

Address and/or symbolic geo-reference This drives the address widget where a set of symbolic geo-references can be specified; please note that the variable State (or district) is used to aggregate the water budget at a sub-area level in the water resources model. TABLE address E type E value D TState State D TMunicipality Municipality D TCatchment Catchment D TRiver_segment River_segment D State Kelantan D Municipality n/a D Catchment La_Laja_I D River_segment Kelantan END_TABLE Area/elevation: hyspographic curve This defines the shape of the catchment, used for altitude temperature (adiabatic lapse rate) and precipitation corrections. The values are absolute (in km2), and describe elevation bands of 100 meters each, counted from their lower (starting) elevation. TABLE area/elevation E elevation E area D 1850. 733.60028 D 1950. 1282.5859 D 2050. 1238.8614 D 2150. 651.00952 D 2250. 364.371 D 2350. 262.34712 D 2450. 174.89808 D 2550. 92.30732 D 2650. 48.5828



D 2750. 14.57484 D 2850. 0.0 END_TABLE Time series All dynamic objects are characterised by different time series; they are displayed in an embedded time series window in the object. The reference is through a name and the full file name (path) of the corresponding time series file. TABLE time_series E name E path_name E red E green E blue E style E min E max D daily_flow ./data/objects/time_series/SC20.flow 0 0 255 bar 0 300 D daily_precipitation ./data/objects/time_series/SC20.prec 0 255 255 bar 0 300 D daily_temperature ./data/objects/time_series/SC20.temp 255 0 0 line 20 28 END_TABLE END_TABLE

name time series name

path_name abosulte file name (path) reference for the time series file;

red red component (RGB model) of the display color, 0-255)

green green component (RGB model) of the display color, 0-255)

blue blue component (RGB model) of the display color, 0-255)

style display style: this can be either vertical bars, or a continuous line

min scaling information: minimum value, corresponding to the lower edge

of the graph's display window;

max scaling information: maximum value, corresponding to the upper edge

of the graph's display window.

Local map display TABLE local_map E type E value



D x 484375 D y 649866 D extent 30000 D index 6 D index 7 D index 1 D index 3 D index 4 D scale on END_TABLE

The TABLE selects the map/overlay indices that should be displayed, and switches on the display of a scale bar with the map. x,y, and extent define a reference point (in the center of the map area) and an extent (radius) around that, in meters.



LAKES AND RESERVOIRS Lake and reservoir objects file are located, by default, in the directory ./data/objects/reservoirs.

The location of each individual file, however, is determined by the corresponding entry in the object CONFIG file ./data/objects/CONFIG:

CLASS Dams_and_Reservoirs LR E Tepuxtepec LR04 ./data/objects/reservoirs/Tepuxtepec ENDCLASS

The object data file consists of the standard blocks:

• Header




Header: NA Tepuxtepec # object anme ID LR04 # unique ID LO 100.2266667 # longitude LA 20.0 # latitude EL 2532.0 # masl, base of the dam TABLE content E type E value D ID Tepuxtepec D TITLE Tepuxtepec D HYfile reservoirs/display/Tepuxtepec D HYtitle Tepuxtepec D EXfile reservoirs/display/Tepuxtepec D EXtitle Tepuxtepec END_TABLE






TABLE defines TITLE, the hypertext file URL for the embedded hypertext browser,



content and the help- and explain file acessible through the info icon.

Component widget declarations: TABLE input_sets E method E data_table E default_prefix D widget content reservoir.widget D disp_hypertext content reservoir.htext D disp_gl_properties descriptors reservoir.prop D disp_address address reservoir.address D disp_map local_map reservoir.map D disp_ts time_series reservoir.ts D disp_plot morphometry reservoir.plot END_TABLE

For each component widget, the TABLE specifies the method or function name, the name of the corresponding data TABLE in the object definition, and the standard prefix of the associated defaults (in ./data/defaults.


widget the reservoir object display widget itself;



disp_address address and/or symbolic georeference

disp_map local map display


disp_plot display function for the reservoir morphometry (volume/depth curve)

Parameter list

This TABLE displays the main set of watershed parameters; they are Descriptors, so that the editing tools of the embedded expert system can be used: this is switched on by the method key word ask_box, which refers to the XPS editing dialog tool. TABLE descriptors E name E value E method D year_of_completion 1935/70 ask_box D geology Tobas_basalto ask_box D mean_annual_inflow 677.0 ask_box D maximum_inflow 182.0 ask_box D dead_storage 0.0 ask_box D useful_storage 575.0 ask_box



D flood_control_storage 0.0 ask_box D total_storage_capacity 585.0 ask_box D current_storage_capacity 00.0 ask_box D dam_type PG/ER ask_box D dam_length 675.0 ask_box D dam_volume 119000.0 ask_box D spillway_type V ask_box D spillway_head 0.00 ask_box D spillway_crest_length 66.0 ask_box D spill_capacity 1660.0 ask_box D outflow_type Condicto ask_box D outflow_head 4.6 ask_box D outflow_capacity 0.0 ask_box D irrigation_command_area 116000.0 ask_box D trophic_state eutrophic ask_box D macrophyte_coverage 80. ask_box END_TABLE The parameters include:

catchment_size total extend of the catchment (upstream of the outflow point) in km2

year_of_completion year of completion of reservoir construction or any major restoration; can be used to estimate operational performance;

geology local dominant geology, can be used to estimate seepage

mean_annual_inflow average ot target value, in Mill m3.

maximum_inflow long-term maximum, daily average peak flow

dead_storage volume of storage below outflow level

useful_storage storage volume between dead and flood storage

flood_control_storage storage volume above useful storage until spill level

total_storage_capacity sum of all storage volume

current_storage_capacity current storage capacity, may be below total due to siltation

dam_type type of dam construction, one out of a set of symbolic labels defined in the expert systems knowledge base

dam_length length of the dam's crest

dam_volume material volume of the dam construction itself

spillway_type type or shape of spillway

spillway_head head or elevation of the spillway (spill level)

spillway_crest_length width, or length of the spillway crest (a fraction of the dam;s entire crest)



spill_capacity maximum flow that can be spilled without damage to the spillways

outflow_type type of outflow, defined as a set of symbolic options in the knowledge base

outflow_head elevation of the outflow (lowest in case of multi-level outlets)

outflow_capacity maximum outflow

irrigation_command_area size of the associated irrigation area, if any

trophic_state trophic state, defined as symbolic label in the expert system's knowledge base

macrophyte_coverage fraction of the area that is typically covered by macrophytes, if any.

Address and/or symbolic gereference

This drives the address widget where a set of symbolic geo-references can be specified; please note that the variable State (or district) is used to aggregate the water budget at a sub-area level in the water resources model. TABLE address E type E value D TState State D TMunicipality Municipality D TCatchment Catchment D TRiver_segment River_segment D State Kelantan D Municipality n/a D Catchment La_Laja_I D River_segment Kelantan END_TABLE Reservoir morphometry This defines the shape of the reservoir, i.e., the relationship between depth or head and associated volumes and surface areas. TABLE morphometry E storage_volume #Mill.m3 E elevation #variables defined (units) as DESCRIPTORS E surface_area #km2 D 000000.00 002327.00 000148.15 D 000005.56 002328.00 000296.30 D 000008.89 002329.00 000444.44 D 000011.11 002330.00 000555.55 D 000016.67 002331.00 000629.63



D 000027.78 002332.00 000851.86 D 000033.33 002333.00 001000.00 D 000050.00 002334.00 001250.00 D 000061.11 002335.00 001428.57 D 000077.78 002336.00 001714.86 D 000094.44 002337.00 002000.00 D 000116.67 002338.00 002148.15 D 000138.89 002339.00 002333.00 D 000160.71 002340.00 002518.52 D 000192.86 002341.00 002740.74 D 000219.64 002342.00 003000.00 D 000246.43 002343.00 003222.22 D 000278.57 002344.00 003518.52 D 000316.67 002345.00 003740.74 D 000355.56 002346.00 003888.88 D 000400.00 002347.00 004142.86 D 000433.33 002348.00 004357.14 D 000483.33 002349.00 004607.14 D 000533.33 002350.00 004821.43 D 000577.78 002351.00 005074.07 D 000621.43 002352.00 005296.30 D 000685.71 002353.00 005592.59 D 000733.93 002354.00 005861.86 END_TABLE Default release policy Currently not displayed in the object. Defines the target flow against different reservoir levels. TABLE default_policy E elevation #masl E out_flow #m3/sec D 2335.0 0.0 D 2345.0 50.0 D 2350.0 50.0 D 2354.0 254.0 END_TABLE Time series All dynamic objects are characterised by different time series; they are displayed in an embedded time series window in the object. The reference is through a name and the full file name (path) of the corresponding time series file. TABLE time_series E name E path_name E red E green E blue E style E min E max



D daily_flow ./data/objects/ 0 0 255 bar 0 300 D daily_precipitation ./data/objects/ 0 255 255 bar 0 300 D daily_temperature ./data/objects/ 255 0 0 line 20 28 END_TABLE END_TABLE







min scaling information: minimum value, corresponding to the lower edge of the graph's display window;

max scaling information: maximum value, corresponding to the upper edge of the graph's display window.

Local map display TABLE local_map E type E value D x 484375 D y 649866 D extent 30000 D index 6 D index 7 D index 1 D index 3 D index 4 D scale on END_TABLE

The TABLE selects the map/overlay indices that should be displayed, and switches on the display of a scale bar with the map.

x,y, and extent define a reference point (in the center of the map area) and an extent (radius) around that, in meters.



IRRIGATION DISTRICTS Irrigation district objects file are located, by default, in the directory ./data/objects/irrigation.

The location of each individual file, however, is determined by the corresponding entry in the object CONFIG file ./data/objects/CONFIG: CLASS Irrigation_districts IR E Santo_Domingo_(D33) IR01 ./data/objects/irrigation/s_domingo33.dat ENDCLASS

The object data file consists of the standard blocks:

• Header




Header: NA Santo_Domingo_(D33) #object name ID IR01 # unique ID LO -99.7578 # longitude (location of abstraction) LA 19.6236 # latitude (location of abstraction) EL 2540.0 # masl, base of the dam TABLE content E type E value D ID Santo_Domingo_(D33) D TITLE Santo_Domingo_(D33) D HYfile irrigation/IR1.pic D HYtitle Santo_Domingo_(D33) D EXfile irrigation/IR1.pic D EXtitle Santo_Domingo_(D33) END_TABLE This contains:






TABLE defines TITLE, the hypertext file URL for the embedded hypertext browser,



content and the help- and explain file acessible through the info icon.

Component widget declarations: TABLE input_sets E method E data_table E default_prefix D widget content irrigation.widget D disp_hypertext content irrigation.htext D disp_gl_properties descriptors irrigation.prop D disp_address address irrigation.address D disp_ftrigger trigger irrigation.trigger D disp_map local_map irrigation.map D disp_ts time_series irrigation.ts D disp_pie pie irrigation.pie END_TABLE



widget the catchment object display widget itself;



disp_address address and/or symbolic geo-reference

disp_ftrigger trigger for the irrigation water demand estimation model


disp_pie pie chart display (for the landuse distribution)

Parameter list

This TABLE displays the main set of irrigation district parameters; they are Descriptors, so that the editing tools of the embedded expert system can be used: this is switched on by the method key word ask_box, which refers to the XPS editing dialog tool. TABLE descriptors E name E value E method D district district_33 ask_box D total_area 2466.0 ask_box D dominant_crop Maize ask_box D soil_type silt ask_box D irrigation_technology flooding ask_box D conveyance_loss 25.0 ask_box



D water_allocation 50.0 ask_box D groundwater 5.0 ask_box D local_storage 200000.0 ask_box D groundwater_table 2.0 ask_box D maize 5 ask_box D alpha_alpha 10 ask_box D corn 50 ask_box D beans 25 ask_box END_TABLE The parameters include:

district name of the irrigation district;

total_area total area under irrigation, in ha

dominant_crop specifies one crop as dominant

soil_type specifies the dominant soil type from a list of supported types, e.g., USGS or FAO classifications

irrigation_technology selects one of a set of irrigation technologies

conveyance_loss specifes conveyance loss as a percentage of primary water input

water_allocation total water allocation (gross), on an annual basis

groundwater totoal groundwater input, if any

local_storage local storage capacity, if any

groundwater_table average distance from the soil surface to the groundwater head

rice_paddy proportion of crop (in % of the irrigated area); this record is repeated for every drop to be considered for this irrigation district

Address and/or symbolic georeference

This drives the address widget where a set of symbolic georeferences can be specified; please note that the variable State (or district) is used to aggregate the water budget at a sub-area level in the water resources model. TABLE address E type E value D TState State D TMunicipality Municipality D TCatchment Catchment D TRiver_segment River_segment D State Kelantan D Municipality n/a D Catchment La_Laja_I D River_segment Kelantan END_TABLE



Pie chart

The pie chart in the catchment object is used to display the crop distribution. However, the pie chart widget is fully generic and data driven: TABLE pie E name E descriptor E red E green E blue D maize maize 0 150 0 D alpha_alpha alpha_alpha 255 255 0 D corn corn 0 255 0 D beans beans 150 150 150 END_TABLE The TABLE items describe:

descriptor Descriptor reference, link to the descriptor list TABLE that instantiates the corresponding values;

red display color (BLUE component of the RGB model) for this element

green display color (GREEN component of the RGB model) for this element

red display color (RED component of the RGB model) for this element

Time series

All dynamic objects are characterised by different time series; they are displayed in an embedded time series window in the object. The reference is through a name and the full file name (path) of the corresponding time series file. TABLE time_series E name E path_name E red E green E blue E style E min E max D daily_flow ./data/objects/time_series/SC20.flow 0 0 255 bar 0 300 D daily_precipitation ./data/objects/time_series/SC20.prec 0 255 255 bar 0 300 D daily_temperature ./data/objects/time_series/SC20.temp 255 0 0 line 20 28 END_TABLE END_TABLE











Local map display TABLE local_map E type E value D x 484375 D y 649866 D extent 100000 D index 6 D index 7 D index 1 D index 3 D index 4 D scale on END_TABLE The TABLE selects the map/overlay indices that should be displayed, and switches on the display of a scale bar with the map.




SETTLEMENTS Irrigation district objects file are located, by default, in the directory ./data/objects/settlements.

The location of each individual file, however, is determined by the corresponding entry in the object CONFIG file ./data/objects/CONFIG: CLASS Settlements SE E Salamanca SE028 ./data/objects/settlements/salamanca.dat ENDCLASS The object data file consists of the standard blocks:

• Header




Settlements (cities, urban areas, municipalities) have the dual role of

• demand nodes (domestic and commercial water demands)

• sources of wastewater.

Header: NA Salamanca # object name ID SE028 # unique ID LO 0000 # longitude LA 0000 # latitude EL 0000 # masl TABLE content E type E value D ID Salamanca D TITLE Salamanca D HYfile settlement/display/Salamanca.exp D HYtitle Salamanca D EXfile settlements/display/generic.exp D EXtitle Salamanca END_TABLE This contains:








TABLE content

defines TITLE, the hypertext file URL for the embedded hypertext browser, and the help- and explain file accessible through the info icon.

Component widget declarations: TABLE input_sets E method E data_table E default_prefix D widget content irrigation.widget D disp_hypertext content irrigation.htext D disp_gl_properties descriptors irrigation.prop D disp_address address irrigation.address D disp_ftrigger trigger irrigation.trigger D disp_map local_map irrigation.map D disp_ts time_series irrigation.ts END_TABLE



widget the settlement object display widget itself;



disp_address address and/or symbolic geo-reference

disp_ftrigger trigger for the irrigation water demand estimation model


Parameter list

This TABLE displays the main set of irrigation district parameters; they are Descriptors, so that the editing tools of the embedded expert system can be used: this is switched on by the method key word ask_box, which refers to the XPS editing dialog tool. TABLE descriptors E name E value E method D current_inhabitants 129301 ask_box D census_year 1992 ask_box D per_capita_consumption 200.0 ask_box



D commercial_use 0000 ask_box D industrial_use 0000 ask_box D consumptive_use_dom 0.30 ask_box D consumptive_use_com 0000 ask_box D consumptive_use_ind 0000 ask_box D sewered 0000 ask_box D sewer_system combined ask_box D untreated_effluents 209.0 ask_box D Solids_conc 0000 ask_box D BOD_conc 234. ask_box D Ammoniacal_N_conc 0000 ask_box D Nitrate_conc 0000 ask_box D Phosphorus_conc 0000 ask_box D Fecal_coliform_count 0000 ask_box D Metals_conc 0000 ask_box END_TABLE The parameters include:

current_inhabitants name of the irrigation district;

census_year reference year for the population figure;

per_capita_consumption average per capita water demand, per day

commercial_use total anual commercial water demand

industrial_use < water industrial annual>

consumptive_use_dom average fraction of consumptive use for domestic water use

consumptive_use_com average fraction of consumptive use for commercial water use

consumptive_use_ind average fraction of consumptive use for industrial use

sewered fraction of population that is connected to sewer systems

sewer_system sewer system (combined or separate storm water system)

untreated_effluents totoal waste water generated, annually

Solids_conc concentration of solids in the waste water

BOD_conc concentration of BOD in the waste water

Ammoniacal_N_conc concentration of Ammoniacal N in the waste water

Nitrate_conc concentration of Nitrates in the waste water

Phosphorus_conc concentration of phsophates in the waste water



Fecal_coliform_count concentration of fecal coliforms in the waste water

Metals_conc concentration of metals in the waste water

Address and/or symbolic georeference

This drives the address widget where a set of symbolic georeferences can be specified; please note that the variable State (or district) is used to aggregate the water budget at a sub-area level in the water resources model. TABLE address E type E value D TState State D TMunicipality Municipality D TCatchment Catchment D TRiver_segment River_segment D State Kelantan D Municipality n/a D Catchment La_Laja_I D River_segment Kelantan END_TABLE Time series

All dynamic objects are characterised by different time series; they are displayed in an embedded time series window in the object. The reference is through a name and the full file name (path) of the corresponding time series file. TABLE time_series E name E path_name E red E green E blue E style E min E max D daily_demand ./data/objects/time_series/salamanca.dem 0 0 255 bar 0 300 D daily_waste_water ./data/objects/time_series/salamanca.waste 0 255 255 bar 0 300 END_TABLE











Local map display TABLE local_map E type E value D x 484375 D y 649866 D extent 100000 D index 6 D index 7 D index 1 D index 3 D index 4 D scale on END_TABLE The TABLE selects the map/overlay indices that should be displayed, and switches on the display of a scale bar with the map.




PUMPING STATIONS Pumping station objects are define in the the directory ./data/objects/pumping.

The location of each individual file, however, is determined by the corresponding entry in the object CONFIG file ./data/objects/CONFIG:

Pumping stations are primarily realted to:

• Irrigation districtcs

• Groundwater abstractions NA Lemal_Pump_House # object name ID SE029 # unique ID LO 0000 # longitude LA 0000 # latitude EL 0000 # masl, base of the dam TABLE content E type E value D ID Lemal D TITLE Lemal_Pump_House D HYfile lemal.html D HYtitle Lemal_Pump_House D EXfile lemal_meta.html D EXtitle Lemal_Pump_House END_TABLE TABLE input_sets E method E data_table E default_prefix D widget content settlement.widget D disp_hypertext content settlement.htext D disp_gl_properties descriptors settlement.prop D disp_address address settlement.address D disp_map local_map settlement.map D disp_ts time_series settlement.ts END_TABLE TABLE address E type E value D TState State D TMunicipality Municipality D TCatchment Catchment D TRiver_segment River_segment D State Kelantan D Municipality Kota_Bahru D Catchment --



D River_segment Kelantan END_TABLE descriptors E name E value E method D institution KADA ask_box D pumping_capacity 6.3 ask_box D peak_capacity 8.5 ask_box D number_of_pumps 3 ask_box D max_power_rating 2000.0 ask_box D pumping_head 12.0 ask_box D primary_use irrigation ask_box D command_area 450.0 ask_box D inflow_level 3.0 ask_box D minimum_flow 10.0 ask_box D year_of_completion 1988 ask_box D operator_name Tajuddin ask_box D contact_phone 1234567890 ask_box END_TABLE TABLE time_series E name E path_name E red E green E blue E style E min E max D daily_flow ./data/objects/time_series/SC20.flow 0 0 255 bar 0 20 D daily_precipitation ./data/objects/time_series/SC20.prec 0 255 255 bar 0 10 D daily_temperature ./data/objects/time_series/SC20.temp 255 0 0 line 20 28 END_TABLE TABLE local_map E type E value D x 461992.9 D y 664600.0 D extent 10000 D index 6 D index 7 D index 1 D index 3 D index 4 D scale on D linewidth 3 D color 16711680 D circle 500 END_TABLE



WRM: WATER RESOURCES MANAGEMENT MODEL The water reouses model WRM is one of the core components of the WaterWare system. It describes the water flow and avilability, demand and supply balance on a daily basis across the basin and its elements, based on conservation and continuity laws.

In order to simulate the behavior of a river basin over time the river basin is described as a system of nodes and arcs. These nodes represent the different components of a river system (i.e., diversions, irrigation areas, reservoirs, etc.), and can indicate points of water inflow to the basin, storage facilities, control structures, demand for specific uses. The nodes are connected by arcs which represent natural or man-made channels which carry flow through the river system.

The WRM incorporates a number of river basin features (objects) which are represented by different node types.

2.4 WRM node types

1. Start node provides the input flow at the beginning of a water course (main river or a tributary) considered explicitly in the model; this could represent:

o a spring,

o an upstream catchment (which in turn can be simulated by the rain-runoff model),

o an inter-basin transfer,

o a major input of groundwater to the surface water system.

2. Confluence nodes provide for the joining of several reaches, that could represent natural tributaries or man-made conveyance channels. It is characterized by more than one inflow.

3. Diversion nodes represent branching of flow to several channels; it is characterized by more than one outflow and rules to distribute the flow. Abstractions to demand nodes may be described by diversions (see below).

4. Demand nodes describe the consumptive use of water. They include:

o Irrigation node represents water demands for irrigation.

o Municipal node represents municipal water demands.

o Industrial node represents water demands for industry.

Each of them can either be situated on the main water course, describing their net consumption, or at an abstraction from the main water course; the latter configuration allows for the explicit treatment of return flows or waste water (see Figure 4).

5. Reservoir nodes represent natural or controlled storage systems with a set of rules that prescribe outflow from the reservoir as a function of time, its inflow and storage.



6. Control nodes, that do not change the flow but imposes an in-stream flow demand (for allocation and performance accounting purposes), for example, for navigation or environmental purposes.

7. Auxiliary or geometry nodes, that again do not affect the flow directly, but are used to start a new reach or serve as a place holder to provide a network structure consistent with other models.

8. Terminal nodes represent outlets from the basin considered in the model, including outflow to the sea or inflow to lakes.

2.5 WRM reaches

Nodes are connected by reaches. Water is routed along these reaches considering their length, slope, and channel characteristics including cross sections and roughness. Along a reach, lateral inflows or outflows (exfiltration) represent very small tributaries not treated explicitly and interaction with the groundwater.

Each reach has its own local catchment area, that provides the potential linkage to spatially distributed water budget models.

2.6 Model dynamics

The model operates on a daily time step to represent the dynamics of water demand and supply, reservoir operations, and the routing through the channel system. This daily time step can be aggregated, for output and reporting purposes, to a weekly, monthly, and annual scale.

Inputs at the individual nodes can again be specified at a daily, weekly, or monthly resolution; different methods than construct a daily input data set from these more aggregate values.

Start Node

This node provides the input flow to the simulation model, which represents the natural flows and the intervening flows (lateral inflow, subsurface base flow). The flow is represented in the following form

where

Qj outflow from start node in day j [m3/day]

Ij inflow at a start node in day j [m3/day]

QIj input flow to a start node in day j [m3/day]

beta = 0 in case where the start node represents a head water source.

Confluence Node

This node provides for the joining of natural tributaries or man-made conveyance channels. The equation governing the flow at a confluence node is



where

Qj outflow from a confluence node in day j [m3/day]

Iji i-th channel inflow to a confluence node in day j [m3/day].

Diversion Node

This node represents diversions of flow to other nodes in the system or to other tributaries. The diversion rule is such that a minimum downstream release is given priority. The operation rule is described as follows

where

Qj actual downstream flow from a bifurcation node in day j [m3/day]

Ij inflow to a bifurcation node in day j [m3/day]

ADj actual diversion flow in day j [m3/day]

DWT downstream target flow in day j [m3/day]

TDj diversion target flow in day j [m3/day]



TDj diversion target flow in day j [m3/day]

To determine the target diversion TDj the following formula is used

where

where

CUj total area crop water requirements per day j [m3/day]

ETcropj crop water requirements per day j [mm/day]

ET0j reference crop evapotranspiration per day j [mm/day], based on climatic data

Kc crop coefficient

Pj total area effective precipitation per day j [m3/day]

Peffj effective precipitation per day j [mm/day]

Ptotj total precipitation per day j [mm/day]

pl fixed percentage to account for losses from runoff and deep percolation. Normally pl = 0.7 - 0.9

epsilon conveyance loss coefficient

cu consumptive use coefficient

A irrigation area [ha]

alpha unit conversion coefficient

The flow that actually reaches the irrigation area is

The flow that is percolated to groundwater



Figures/mit.eps Irrigation Return Flow Schemes

The outflow from the irrigation node is

where

Rj amount of flow available after consumptive use by the crop

GWj flow percolated to groundwater

k river return flow coefficient

beta flag for different cases of irrigation, beta = 1 in implicit, beta = 0 in explicit (Figure irrig.eps

Municipal and Industrial Water Supply Node

The Municipal and Industrial Water Supply Nodes represent water demands for industry and other purposes. The allocation rule for diverting water to the MI node is described by the following equations:

where

Ij inflow to a MI node in day j [m3/day],

ADj actual diversion flow in day j [m3/day],

DWTj minimum downstream flow target in day j [m3/day],

TDj diversion target flow in day j [m3/day].

The downstream flow Qj from the MI node is described by the equation



where

Rj return flow to the river available,

cu consumptive use coefficient.

Reservoir Node

Reservoir node can represent three possible configurations:

• storage reservoir

• storage reservoir and power plant

• run of the river power plant

Storage Reservoir

Figures/res.eps Reservoir "Standard Operating Policy"

The operating policy of a reservoir used in WRM is the "Standard Operating Policy" [Fiering, 1967]. It is illustrated in Figure res.eps and is described by the following equations:

The release policy is divided into three separate cases:

Similarly, the storage available in the reservoir at the beginning of day (j+1) corresponds to the three cases as follows:

where



The following notations are used:

Ij inflow to reservoir in day j [m3/day],

Qj reservoir reservoir in day j [m3/day],

Wj available water in day j [m3],

Sj reservoir storage at the beginning of day j [m3],

SMINj reservoir minimum storage [m3],

SMAXj reservoir maximum storage [m3],

Vj reservoir storage capacity [m3],

TRj target reservoir release in day j [m3]day],

Pj total reservoir area precipitation in day j [m3/day],

EVj reservoir evaporation in day j [m3/day],

prj daily precipitation coefficient [mm/day],

evj daily evaporation coefficient [mm/day],

RAj reservoir surface area at the beginning of day j [ha], is a function of the storage RAj = psi[Sj],

alpha unit conversion coefficient.

Hydroelectric Power Generation

The production of energy is calculated as a function of the output variables from the reservoir node Qj and Sj:

where

PGj energy generated at plant in day j [KWH/day],

ef efficiency of power plant,

nhj number of hours in day j,



Hj average turbine head in day j,

Hj* average turbine head between the base of the dam and the

elevation of the water surface of the reservoir in day j,

HCj depth between turbine and the base of the dam,

beta = 0in case of a run-of-the-river plant.

2.7 Storage Routing in Tributaries

The Muskingum flood routing method [Engineer School, Ft.Belvoir, Va.,1940] is applied in WRM. In this method the conditions relating inflows into and outflows from a river reach to the water stored within the reach are described by the continuity equation and an empirical linear storage equation:

where

I rate of inflow [m3/day],

Q rate of outflow [m3/day],

K storage coefficient [day], approximates the time of travel of the wave through the reach,

sigma weighting factor, in natural channels usually varies between 0.1 and 0.3, specifying the relative importance of the inflow and outflow in determining storage.

where

2.8 WRM Data Requirements

1. Start Node

Ij inflow to a start node in day j [m3/day],

QIj input flow to a start node in day j [m3/day].

2. Confluence Node

3. Diversion Node



DWTj target flow in day j [m3/day],

TDSUB>j diversion target flow in day j [m3/day].

4. Irrigation Node

DWTj downstream flow target in day j [m3/day],

ET0j reference crop evapotranspiration per day j [mm/day],

Kc crop coefficient,

Ptotj total precipitation per day j [mm/day],

pl fixed percentage to account for losses from runoff and deep percolation,

varepsilon conveyance loss coefficient,

k river return flow coefficient,

A irrigation area [HA],

5. Notice that to calculate ET0j different methods, depending on available data might be used. For areas where available climatic data cover air temperature data only the relationship recommended by the Blaney-Criddle method, representing mean value over the given month, is expressed as

6. 7. where

T mean daily temperature over the month considered [centigrade],

p mean daily percentage of total annual daytime hours,

c adjustment factor which depends on minimum relative humidity, sunshine hours and day time wind estimates.

8. For areas where measured data on temperature, humidity, wind and sunshine duration or radiation are available an adaptation of the Penman method is suggested. The equation used in this method is:



9. 10. where

W temperature related weighting factor,

Rn net radiation in equivalent evaporation [mm/day],

phi(u) wind-related function,

ea saturation vapor pressure at mean temperature [mbar],

ed mean actual vapor pressure of the air [mbar],

c adjustment factor.

11. Municipal Node


TDj diversion target flow in day j [m3/day],


12.

13. Industrial Node


TDj diversion target flow in day j [m3/day],


14. Reservoir Node

Sj reservoir storage at the beginning of day j [m3],

SMINj reservoir minimum storage [m3],

SMAXj reservoir maximum storage [m3],

TRj target reservoir release in day j [m3]day],

prj daily precipitation coefficient [mm/day],

evj daily evaporation coefficient [mm/day],

RAj reservoir surface area at the beginning of day j [HA],

15. Additional data for power plants:

ef efficiency of power plant,

nhj number of hours in day j,



HCj is the depth between turbine and the base of the dam.

16. Terminal Node Storage Routing in Tributaries

L reach length,

AD reach altitude difference.



REFERENCES Fedra, K. (2002) GIS and simulation models for Water Resources Management: A case study of the Kelantan River, Malaysia. 39-43 pp., GIS Development, 6/8.

Fedra, K. (2000) Environmental Information and Decision Support Systems. Informatik/Informatique 4/2000, pp. 14-20.

Fedra, K. and Feoli, E. (1998) GIS Technology and Spatial Analysis in Coastal Zone Management. EEZ Technology, Ed. 3, 171-179.

Fedra, K. (1996a) Multi-Media Environmental Information Systems: Wide-Area Networks, GIS, and Expert Systems. GIS: Geo-Informations-Systeme 9/3, pp. 3-10.

Fedra, K. (1996b) Distributed Models and Embedded GIS: Strategies and Case Studies of Integration. In: Goodchild, M.F., Steyart, L.Y., Parks, B.O., Johnston, C., Maidment, D., Crane, M. and Glendinning, S. [Eds.], GIS and Environmental Modeling: Progress and Research Issues. pp. 413-417. GIS World Books, Fort Collins, CO.

Fedra, K., and Jamieson, D.G. (1996) An object-oriented approach to model integration: a river basin information system example. In: Kovar, K. and Nachtnebel, H.P. [eds.]: IAHS Publ. no 235, pp. 669-676.

Jamieson, D.G. and Fedra, K. (1996) The WaterWare decision-support system for river basin planning: I. Conceptual Design. Journal of Hydrology, 177/3-4, pp. 163-175.

project deliverable: d03.1 water resources modelling …project deliverable: d01.1 requirements and...

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