Measuring Components of the Hydrologic Cycle
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Measuring Evaporation:
Not possible to ‘put a lake inside a plastic bag’ therefore various methods to estimate
evaporation have been developed.
some use climatic factors such as temperature, humidity, wind speed, etc but the best
method is to use an evaporation pan.
Evaporation pans
Since a pan is shallow and made of metal it has a higher evaporation rate than an actual
water body. Compensate: concepts of the Kc, Kp, Eo, Eto, Etc
Actual studies:
• Studies of evaporation by USBR, USGS at Lake Hefner, indicate that the water body
evaporates 70% as much as a nearby pan.
• This estimate is usually 15% ccurate.
• Yearly estimates for pan evaporation have been developed for the world and range from
0.75 per year to 0.5m per year. Zim studies????????
Measuring Precipitation.
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Measuring Rain
Predicting weather patterns
Assessing long-term climate
Measurement of Precipitation.
• Precipitation is measured in millimeters of water.
• The simplest gauge is a can, a ruler can be inserted to measure the depth of water.
Clear plastic rain gauges are common and cheap. To prevent evaporation or birds
drinking the water, a gauge with a narrow neck and a narrower calibrated measuring
tube is used. High wind will result in under-estimation.
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Modern gauges:
Since recording rainfall even daily is a pain, recording rain gauges are becoming more
common.
These typically use a bucket inside a gage and a scale or use a tipping bucket. These are
often telemetered or have a ROM chip that can store precipitation minute by minute for
6 months.
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Radar:
Radar can also be used to estimate precipitation and is particularly suitable for spotty,
fast moving storms such as are now common worldwide e.g Met services.
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Remote Sensing.
Data gathered from satellites can help create regional estimates of rainfall as well as
predict major storms, cyclones, droughts, rainfall patterns etc.
Dendrochronology??
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Study of tree rings.
Can aid studies of long term precipitation.
Interpretation and Analysis of Precipitation
Rainfall data is used to make decisions ranging from whether to take an umbrella or not
Decision to evacuate a city or release water from a dam to prevent over-topping, which
work is usually done by a spillway!!!!!!!!! Except only in extreme cases.
Available data:
Actual rainfall for various durations may be available for experimental stations. Also
available form met department at a cost.
From this data intensity on an hourly, daily weekly etc basis is easily calculated.
Maximum Probable Storm Event:
By simple statistical methods the maximum probable storm for any duration of the
storm event and recurrence interval can be estimated.
Typically the maximum hourly and maximum 24 hour storm events for recurrence
intervals of 1, 10 25, 50 and 100 years are determined
Use of maximum probable storm event data:
This information is used in thousands of decisions every year.
This method depends on the rainfall events being random events. They may or may not
be truly random but this is the best available assumption.
Applications:
There are many applications for rainfall and intensity data....
Agriculture.
Civil Engineering.
Water Supply.
Flood Warning.
Reality vs. theory:
Unfortunately, rainfall is usually measured at a single point while the effects of rainfall
such as flooding, stage height at a measuring station, etc are felt elsewhere and reflect
the total contribution of rainfall over a large area.
Extending point data to an area:
In order to convert an estimate of rainfall at a point into an estimate for an area of
interest such as a watershed or a river basin, a method of extrapolation of point data to a
larger spatial area must be employed.
This is called computing an area average. In order to develop an area average estimate
there are three methods:
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Methods of averaging for an area:
The arithmetic average method is simple, works well with even distribution of gages.
The Theissen polygon method is the area weighted average. It can account for uneven
distribution of gages, can take into account data outside basin with appropriate weight
and can be built into a GIS based system (use of a planimeter is out of date).
Examples:
Used by TWDB, with a GIS & the Isohyetal Method:
Uses contour lines of equal rainfall. Area between contours is measured and arithmetic
average of the contour values is multiplied by the area between the contours and divided
by the total basin area. Can be automated with GIS.
Locating Rain Gages:
In order to be used to determine accurate area averages of rainfall, locations of rain
gages must be chosen carefully. In particular, locations in headwater areas, and urban
areas is important. Also in areas of maximum, minimum and average precipitation
within a basin.
Measuring Stream-flow.
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Stage gauges
Stilling well/float method
Pressure transducer based stream level sensors.
Measuring Current Velocity.
If a stage gauge, float or level sensor is used
To estimate stream flow the velocity of the stream must be determined.
This is done with either a propeller current meter or an ultrasonic current meter.
Measuring suspended sediment.
Use a sediment sampler attached to a wading rod or suspended from a cableway.
Sample is taken to lab then stirred up and a hygrometer is used to determine change in
specific gravity over time. The specific gravity of water with more suspended sediment is
higher.
Flood Prediction:
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Rainfall gauges.
Radar.
Rainfall-run-off models.
Hydraulic Models.
GIS.
You aint seen nuthin yet…
• Are floods worsening?
• Given only 50-100 years of data it is hard to say, but it appears that frequency of peak
flows exceeding a given level is becoming more common? check.
• Especially, the decade of the 1990's has seen many record breaking floods. Eg??
• Possible reasons: Oscillations in climate, change in climate, change in landuse.
CONCLUSION:
• Certainly for any given flood magnitude, the impacts are likely to be worse as more and
more people occupy land particularly in flood plains.
• Therefore, the need to balance development with finding a place for flood waters to go
and controlling land use in flood plains is more important than ever.
GIS & Computer Models in Hydrology.
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What is a GIS.
A group of computer programs to store, analyze and out-put maps and reports about
geographic features linked to descriptive attribute data.
Stored in the form of themes
Supports many types of modeling and spatial analysis.
Basically used as a ‘visualizing’ tool or aid in WR, Hydrology and other related studies
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Water Resources Applications:
Infrastructure management (piping, pressure, service areas, billing, etc).
Environmental impact assessment.
Watershed study & protection
Water quality analysis
Groundwater management & modeling.
Allocation & administration of water rights.
Infrastructure management
Map & manage piping (where are your underground assets?)
Determine pressures and losses within system
Establish service areas
Track billing, etc.
Environmental impact assessment.
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Look at impact of water resources development projects on terestial and aquatic
ecologiy
Study pipeline alignment & routes
determine environmental impacts of groundwater withdrawals
see area to be inundated by reservoirs.
Flood mapping.
Flood prediction and disaster preparedness, eg CPU
Other projects.
Issues: contour interval.
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Use of remotely sensed imagery.
Water quality analysis.
• Take data on soils, landuse locations and types of pollution
• Develop model of water quality impacts from both point & non-point sources.
• Adjust land-use and treatment plant locations and hydrologic parameters to decide
how best to manage receiving body water quality.
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Allocation & administration of water use (rights, permits and concessions)
Input Hydrography, flow information, withdrawal points, existing water rights and
EFR (environmental flow requirements)
Use network models and spatial optimization
Allocate water among competing users. AUMIE
Groundwater management & modeling.
input data about soils geology, recharge, discharge, wells and aquifers, yields in certain
locations in the country
Establish a model of an aquifer (using MODFLOW)
Determine impact of pumping on water levels in aquifer over many years and simulate
various scenarios such as artificial recharge or reduced agricultural pumping..
Examples:
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see studies on Nyamandlovu aquifers
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transcatchmet and transboundary water transfer systems:
Water has been transferred between and within catchments and even across boundaries in
Southern Africa. In order to move water over long distances pipelines, rivers and canals are
employed to bring life-giving and job-creating water to areas where the demand for water is
high. The water supplied by these large transfer schemes comes at a high ecological cost,
opening the debate on sustainability. In many cases there is simply no more water left for
further mobilization in readily accessible river basins. The projects have the characteristic of
complexity, high cost, international in nature and are therefore prone to political factors and
disputes (www.africanfront.com, 2004.
Currently there are 26 major water transfer schemes in Southern Africa (Turton, 1999) as shown
in the following table:
Name of transfer
Scheme
River Basin
Countries
Involved
Other Countries
involved
Source, Turton, 1999.
Okavango Basin
Eastern National Water Carrier (ENWC)
The Eastern National Water Carrier (ENWC) brings water South from Grootfontein. A pipeline is planned from the
Okavango River at Rundu (Ramberg, 1997) to augment the ENWC. A series of pipelines are being planned to take
water from the mouth of the Zaire River, through Angola and ultimately into the Kunene, Okavango and Zambezi
River Basins (Heyns, 2003, in Nakayama, 2003). The pipeline is 250km long, with a 700mm diameter pipeline, to
transfer 0.55m3/s at 400m static head, with four booster pump stations and river outlet works.
Zambezi basin
Matabeleland Zambezi water Project
The Matabeleland Zambezi Water Project (MZWP) involves the construction of the Gwayi-Shangani dam and a
450-kilometre pipeline from the Zambezi River to bring water to Bulawayo and surrounding areas. The project is
funded by Export–Import Bank of Malaysia to the tune of US$50 million. The major stakeholders in the project are
the Matabeleland Zambezi Water Trust (MZWT) and Zimbabwe-Malaysia Holdings ZimMal. These own 80 and
20% of Mount-Hope Services (PVT) Limited respectively which is a joint venture company formed and registered
by MZWT and ZimMal to implement the project. The first phase of the ambitious project, involving the construction
of the Gwayi-Shangani Dam has already commenced. A Chinese firm, Chinese Electrical Machinery and
Equipment, has since been contracted to construct the dam.
Other water transfers in this basin include the proposed Kazungula, and Katima-Mulilo projects in the Caprivi Strip,
Zambezi-Botswana project and the Zambezi-Gauteng project. All these projects represent a major shift from the
non-consumptive (Recreation, hydropower, fisheries) uses the Zambezi River had been put to (Hynes, 2003 in
Nakayama, 2003 Ed).
Save Basin
Chiredzi Right Bank Canal (Mwedzi canal)
The canal system transfers water from Runde Catchment dams i.e. Lake Mtirikwi, Muzhwi, Bangala dams through
the Tokwe and Mutirikwi river systems to be picked up at the Tokwe weir into the canal to the lowveld sugar
estates.
Pungwe-Mutare water project
Skanska International was contracted to build a 4 km tunnel and 70 km of gravity pipeline from the Pungwe River
via the Nyakupinga Valley to a water purification system at Odzani and then on to the city. Work began in 1997 and
the pipeline went into service in the summer of 1999 (Skanska.com, 1999).
Limpopo basin
Proposed Zhove Dam Canal project
Zhove dam is located about 30km from Beitbridge. A project to construct a canal to Beitbridge for water supply and
irrigation is still in its infancy. Initial work has already commenced with the designs of the off take and canal already
in place ready for construction.
Lesotho Highlands Water Project (LHWP)
The Lesotho Highlands Water Project (LHWP) is a multi billion project being implemented between Lesotho and
South Africa. It is one of the most comprehensive engineering projects of its kind in the world. It aims at harnessing
the water resources of the highlands of Lesotho to the mutual advantage of both South Africa and Lesotho. The
project will be implemented in 4 phases and is aimed at delivering 70m³/s of water from the highlands of Lesotho to
the Vaal River system by the year 2020,), and 110 MW of electricity. The scope of works involves the construction
6 dams (5 large and 1 small), 2 hydropower plants, 3 pumping stations and of 225km of tunnel (Lesotho Highlands
Water Project Authority, 2005).
North-South Water Carrier Project
The NSC was commissioned in 2002 following an agreed policy by the Botswana government and was designed to
provide water for Gaborone, and major villages en-route to the year 2025. Its major objective was to provide safe
water supplies to south eastern districts of Botswana where demand for water was becoming increasingly strained by
developing water resources in the northeast of the country. It involves the construction of the Letsibogo dam on the
Moutloutse tributary and links it with major groundwater wellfields to Gaborone via a large diameter pipeline
400km in length (Kalahari Conservation Society in Botswana North- South Water Project, 2003).
References
Botswana North-South Carrier Water Project Field Survey, July 2003
Nakayama N (2003) Ed.United Nations University Press series, Water Resources Management and Policy:
International waters in Southern Africa. www.internationalwaters/pdf
Overview of the Lesotho Highlands Water Project (LHWP) New civil engineer 14th Sept. 1995, pp. 20 – 29.
Ramberg, L. 1997. A Pipeline from the Okavango River? In Ambio, Vol. 26, No. 2; 129.
Skanska.com (1999). The Pungwe Water Project. http://www.skanska.com/skanska/templates/page____403.aspx
Turton R. A, 1999 Water and Social stability: The Southern African dilemma. SOAS Water Issues Group
Occasional Paper Number 21Paper presented at the 49th Pugwash Conference on Confronting the Challenges of the
21st Century 7-13 September, 1999 Rustenburg, South Africa. http://www.jbic.go.jp/english/oec/post/2004/pdf/250_full.pdf
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Computer Models
Surface water models: HEC, CAS2D, WMS, TOPMODEL,
Groundwater flow models: MODFLOW and others.
Contaminant Transport models: MOC, MT3D EXAMS & others.
MATHEMATICAL MODELLING
Modeling is the ability to recognise pattern and general structures of a system. A mathematical
model, is an abstract model that uses mathematical language to describe the behaviour of a
system.
A mathematical model is "a representation of the essential aspects of an existing system (or a
system to be constructed) which, represents knowledge of that system in a usable format
Rutherford (1994). Math models and computer simulations are useful experimental tools for
building and testing theories, assessing quantitative assumptions, answering specific questions,
determining sensitivities to changes in parameter values, estimating key parameter values and are
are an essential tools in decision making processes and guiding intervention strategy.
TYPES OF MODELLING
There are five major types of modeling namely;
Empirical modeling,
Theoretical modeling,
Discrete time modeling,
Continuous time modelling and
Simulation modeling
Defined as the process of designing a model of a real system and conducting experiments with
this model, with the purpose of either understanding the behaviour of the system or evaluating
various strategies (within the limits imposed by a criterion) for the operation of the system
(Shannon, 1975). It takes the form of a set of assumptions about the operation of the system,
expressed as mathematical or logical relations between the objects of interest in the system
(Winston, 1987). In contrast to the exact mathematical solutions available with most analytical
models, the simulation process involves executing or running the model through time, to
generate representative samples of measures of performance. Harrel and Tummy (1997) added
that Simulation is an activity whereby one can draw conclusions about the behaviour of a given
system by studying the behaviour of a system whose cause and effect relationships are the same
as (or similar to) those of the original. (Modeling!!!!!!!!!!)
CLASSIFICATION OF SIMULATION MODELS
a. Linear or non-linear
Models are usually composed by variables which are abstractions of quantities of interest in the
described systems and operators that act on these variables which can be algebraic operations,
functions, difference operators and so on. If all operators in the model present linearity, the
resulting model is defined as linear eg. Equation of a line y= mx+c. A model is considered nonlinear otherwise.
b. Static or Dynamic
Models are classified as either static or dynamic depending on whether or not the model
variables change over time. A static model does not account for the element of time, while a
dynamic model does. Dynamic models typical are represented with difference equations or
differential equations.
b. Open loop or closed loop
The notion of an open loop or closed loop model is defined by the structure of the model rather
than by the variables. Open loop models have no provision for the output of the model to feed
back as inputs to modify subsequent outputs. A closed loop model is one in which the output
feeds back and compared with some desired level or goal to alter the system such that it remains
the desired value.
c. Deterministic or stochastic (probabilistic)
The difference between stochastic and deterministic models is on the model variables. A
deterministic model is one in which every set of variable state is uniquely determined by
parameters in the model and by sets of previous states of these variables. Therefore, deterministic
models perform the same way for a given set of initial conditions. Conversely, in a stochastic
model, randomness is present and variable states are not described by unique values but rather by
probability distributions. These models produce output that is itself random in nature.
Most deterministic models use sets of differential equations to describe the dynamics of a
system.
There are four basic types of modeling studies viz
Descriptive studies demonstrate pattern and distribution.
Analytic studies are planned investigations designed to test specific hypothesis. They aim to
define the causes or determinants and or magnitude of a problem more precisely than is possible
using descriptive studies alone.
Intervention studies are essentially experiments described to measure the efficiency and safety of
particular types of corrective measures (e.g. ???????????????????????).
Evaluation studies attempt to measure the effectiveness of different interventions or measures.
SENSITIVITY ANALYSIS
Sensitivity Analysis is the study of how the variation in the output of a model (numerical or
otherwise) can be apportioned, qualitatively or quantitatively to different sources of variation. It
is a form of Simulation that enables decision makers to experiment with decision alternatives
using the what-if approach. Sensitivity analysis is a process used to determine the reaction of the
outcomes of an alternative to changes in parameters (Saltelli, 2005). If a small change in a
parameter results in relatively large alteration in the outcomes, then: sensitive to that parameter.
This may mean that the parameter has to be determined very accurately or that the alternative has
to be redesigned for how sensitive.
Good modeling practices require the modeler to provide an evaluation of the confidence in the
model possibly by assessing the reservations associated with using the model. Uncertainty and
sensitivity analysis offer valid tools for characterizing the uncertainty associated with the model.
Sensitivity analysis can be used to determine;
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Model likeness with the process (es) under study
The quality of model definition
Factors contributing to output variability
The region in space of input factors for which the model variation is maximum
Optimal or instability regions within the space of factors for use in a subsequent
calibration study
Interactions between factors.
Usually tested using statistical concepts, e.g. R2 value????
Saltelli A, Tarantola S, Campdongo F,Ratto M(2004) Sensitivity analysis in practice: Aguide to
Assessing scientific models. John Wiley and sons publishers
Shannon, 1975).
Winston, 1987).
Harrel and Tummy (1997)