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Part 1: Rainfall Runoff Modelling using Rainfall Runoff Library (RRL)

To analyse the performance of Manly Dam to estimate the risk of failure and to design a set of operating rules to decrease the failure risk in times of drought. The tasks are as follows:

Part 1 Rainfall Runoff modelling

  1. Set up and calibrate a rainfall runoff model of the Manly Dam catchment
  1. Using the rainfall runoff model, simulate streamflow for the entire period of record of rainfall and evaporation for the catchment

Part 2 Reservoir analysis and operation

  1. No Demand Restrictions - Using monthly streamflow estimated by the rainfall runoff model, undertake behaviour analysis of a potential new reservoir at the current location of Manly Dam. You must determine the required size for the reservoir to maintain achieve a suitable failure rate. It is up to you to determine an appropriate failure rate.
  1. With Demand Restrictions - Design a set of operating rules to reduce the size of the potential new reservoir whilst maintaining at least the same failure rate. The new size of the reservoir should be less than or equal to 80% of the size recommended without demand restrictions (point 3 above). You should have at least 2 levels of water restrictions in your operating rules. You should not have more than 5 levels of water restrictions.

Use the Rainfall Runoff Library (RRL) to set up your rainfall runoff model. The RRL is available on the computers in the Civil and Environmental Engineering computer labs or can be installed on your own computer using the files provided on Moodle. The RRL documentation is provided on Moodle.

You may choose from any of the rainfall-runoff models available in the RRL to set up your catchment model. Rainfall, evaporation and streamflow data is provided for the catchment on Moodle. Data in all files is provided in mm/day. The catchment area is 5. 33 km.

You will have to select appropriate calibration and verification periods given the data available for the catchment. It is up to you to decide on how best to use the data that is available in setting up the model. You will also have to decide what optimisation method to use for the calibration and what your objective function(s) should be. Note that there is only limited streamflow data available for the catchment so this will dictate what period(s) you can use for the calibration and/or verification.

In your report, you must provide justification for your choice of model, calibration strategy, optimisation and objective function choices. You should also provide in your report a summary of the calibration and verification results including appropriate figures, statistics and a discussion of the parameter sensitivity of the model.

Once you have set up the model, you should run a simulation for the full period of the rainfall and evaporation data. You should save the outputs from your model at a monthly time step.

In excel, Matlab or similar program you must analyse the performance of the reservoir given the monthly streamflow estimates from your rainfall-runoff model from Part 1.

You need to undertake a behaviour analysis to determine a relationship between storage and failure rate. Monthly demand and losses should be assumed to be 80% of the mean monthly streamflow.

Based on the relationship between storage size and failure you should recommend the required size for the reservoir (in ML) to achieve a failure rate that you think is appropriate. You will have to justify the choice of failure rate and show how the recommended storage size is the minimum size that achieves the specified failure rate.

For the Demand Restriction case, you need to repeat the analysis with a set of operating rules that reduce the demand appropriately. This will allow you to achieve a smaller sized reservoir for the same failure rate. You must design the operating rules so that the new reservoir size is less than or equal to 80% of the reservoir size that you recommended in the first stage of Part 2. Remember that the operating rules mean that the downstream users do not get all their water in times of water restrictions so you need to ensure that the rules are optimised to balance the competing demands between users and the reduced cost that would result from a smaller reservoir.

Part 1: Rainfall Runoff Modelling using Rainfall Runoff Library (RRL)

Many researchers have conducted case studies to progress their comprehension and the level of information concerning the hydrological procedures intricate in the rainfall-runoff revolution. The research carried out provides solutions to the water problems and proper environmental conservation. Initially, the hydrology research collected data and performed the analysis on pen and paper. With the advent of technology, it is possible for the researchers to perform very advanced analysis (Dooge, 2008). The analysis provides conducive grounds for advancement of the rainfall-runoff models. The rainfall-runoff model is used with data from a socket rainfall gauge and records on daily potential evapotranspiration (PET) to forecast flood volume and peak rates of the overflow for small drainage areas. The new technology has enabled the analysts to perform simulations on a larger scale. There are three basic components of the hydrologic cycle namely,

  • Infiltration
  • Surface run-off
  • Antecedent moisture

There are a set of hydrological models that have been developed to meet the needs of the environment. Different regions experience rainfall in different measures, as a result there is great need to strategize on the flood protection. Floods refer to the high run-off events. Runoff in streams is the integration of several upstream processes in a watershed or river basin based on the topography. The collection of hillslopes and channels generate runoff from a given pixel and ultimately contribute to streamflow and they can be overland runoff and subsurface runoff.  The reason why a model is developed for the rainfall-runoff practices of hydrology is as an outcome of the confines of hydrological measurement methods. Before the new simulation techniques evolved, researchers had a restricted range of measurement practices and a limited range of measurements in both space and time. Different models seek to provide different means of numerical extrapolation or forecast on the data obtained for proper decision making. Hydrology systems are a bit complex to analyze and as a result, each researcher analyses data using his or her own perceptual model. Owing to the difference, analysts hardly agree on the crucial processes. In addition to that, most of the water tends to flow on the bedrock hence the subsurface flow process brings about a hitch in developing great models for research.

The RR model uses a library that evaluates the daily time series of rainfall and evapotranspiration data. The data is evaluated to produce everyday catchment runoff. The originator offers several frequently cast-off lumped rainfall-runoff models. There are adjustment optimizers and exhibition tools to enable model calibration. The library contains the following components,

  • Lumped rainfall-runoff models
  • Calibration optimizers
  • Display tools to facilitate model calibration

Part 2: Reservoir Analysis and Operation

Dams are artificial lakes. They are utilized to manage the vacillations in river flow for water supply, flood control or hydro-electric power generation. They become quite important and relevant to civilization in climates that offer the types of extremes in Australia. Building dams affects many ecological problems in many of the industrialized world. There are many reasons why dams are built are for water supply, irrigation, hydro-power, flood control, and water quality. Water supply pools needs to store sufficient water to last the nation through the famine.  Operating plans or release policies for a single reservoir or a system of reservoirs is a set of guidelines for decisive the amounts of water to be stored and released under different conditions. The plans and policies are put in place to provide guidance to reservoir operators and managers. The rules in the policies are built into all the models that simulate the performance of the water resources system. These are expressed as plots of water surface elevation or current storage volume versus time of the year.

  • To analyze the enactment of Manly Dam to evaluate the risk of fiasco and to scheme a set of functioning rules to lessening the failure risk in times of drought.
  • To set up and calibrate a rainfall-runoff model of the Manly Dam catchment.
  • To simulate the streamflow for the complete passé of record of rainfall and evaporation for the catchment area.

There are many environmental and water resource management problems in many nations globally. A lot of hydrological research has been carried out to figure out possible solutions to the problem (Dawdy, Lichty, & Bergmann). In the flat ground areas, rainfall water lacks proper drainage and it is left on the land as stagnant water. The stagnant water make a place less human friendly. There is dire need to come up with solutions on the rainfall water conservation and proper drainage especially on residential and commercial land.

The data posted on the Moodle database is evaluated using the rainfall-runoff library models. There are several inputs required in the case study namely rainfall, evaporation, flow gauging, and catchment area. Information obtained on the rainfall parameter is a incessant time series of rainfall data. This data represents the downpour across a given catchment area in month-day format. The potential evapotranspiration (PET) data represents the evapotranspiration across the catchment as a continuous time series. It also takes the measurements in the month-day format. The flow gauging is done based on the daily runoff input for the gauging station that is to be modelled. The catchment area, thereby, converts the inputs and outputs between the flow and depth of runoff (Podger, 2004). The output is formatted in the daily and monthly flow or depth of runoff. The model designs the output model detailed variables such as fluxes and storage depths. The output is as shown,

Hydrological cycle and Rainfall-Runoff models

The paper chooses one of the following models as the method to use in the rainfall-runoff model,

  • AWBM
  • Sacramento
  • SimHyd
  • SMAR
  • Tank

The rainfall runoff executable and associated DLLs are used in the project. The sample rainfall, evaporation, and flow data is collected from across Australia in a 5.33km2 catchment area.

  • When the data is loaded on the RRL using the Sim-hyd model,

  • Performing further analysis on the set of data, having updated the time and dates of calibration, one is able to determine the lowest runoff, highest runoff, and the calibration warmup.

  • Calibration is performed using the following parameters

Optimization method

Genetic Algorithm

Primary Objective

Nash-Sutcliffe Criterion

Secondary objectives

None

There are about four kinds of rain downpour inputs possible to use in the rainfall-runoff models. These input help in the design establishment in the flood hydrographs. These are:

  • Historical rainfall
  • Design storms
  • Transposed storms
  • Simulated precipitation

The first two types are commonly used in the model implementation as inputs. These two approaches namely, historical rainfall and design storms, are quite unique to each other. They tend to produce different flood frequency estimates. The stochastic and the space-time precipitation are the models implemented to provide the ideal input for the rainfall-runoff model. These two methods have numerous caveats that hold back their applicability. They are quite suitable for a designer modelling floods in small to medium catchment areas.

  • Performing the sensitivity analysis on the data set provided, the sensitivity analysis uses a model parameter, base flow coefficient with the Nash-Sutcliffe Criterion as the objective function. The parameter information is as shown below,

Parameter Information

Min

0

Calibrated value

0.3

Max

1

The Sim-Hyd is a regular abstract rainfall-runoff model that appraises daily streamflow from daily rainfall and areal potential evapotranspiration data. The daily rainfall first fills the interception store and it is, thereafter, emptied daily by evaporation. The excess rainfall is then subjected to an infiltration function that determines the infiltration capacity. The excess rainfall that exceeds the infiltration runoff. The objective functions chosen were vital to ensure that the monthly time steps were well illustrated on the graphs shown in the results. The Nash-Sutcliffe Criterion was opted as the objective function and the model parameters were adjusted to show different simulations. Many researchers have done different models to evaluate different catchment area data for good decision making in their organizations. There are series of models fabricated to analyze the flood peaks using statistical tools and techniques. Every system must encounter errors. The RRL models take into account the errors of the data collected using statistical techniques and practices.

The enactment of a reservoir given the monthly streamflow estimates from the rainfall-runoff model was analyzed. The analysis was done on the no demand restrictions and with demand restrictions basis. The whole idea behind the reservoir analysis is to ensure that the water is well conserved. Many models have been used to evaluate the potential criteria system wide for the flood management effects from changing reservoir operational criteria for the 2012 CVFPP. There has been an increase in the density and development of the global scales. The storm water runoff from increased impermeable surfaces presents challenges on local and global scales. The flow patterns are easier to see and can be used to select best management practices for storm water management. Such management practices include re-routing of the flow out of drainage infrastructure (Knapp, Durgunoglu, & Ortel).

Dams and its relevance to civilization

Conclusion

In a nutshell, the paper is able to analyze the rainfall and reservoir sections using the SimHyd and Sacramento models. The rules in the policies are built into all the models that simulate the performance of the water resources system. These are expressed as plots of water surface elevation or current storage volume versus time of the year. The RRL models are able to effectively analyze data on the rainfall parameters in a catchment area and provide information for decision making.

References

D, J. L., & Burges, J. S. (n.d.). Precipitation-Runoff Modelling: Future Directions. Applied Modeling in Catchment Hydrology, 291-312.

Dawdy, D. R., Lichty, R. W., & Bergmann, J. M. (n.d.). Synthesis in Hydrology. A Rainfall-Runoff Simulation Model for Estimation of Flood Peaks for Small Drainage Basins, pp. 1-28.

Dooge, J. C. (2008). A General Theory of the unit hydrograph. Journal of Geophys. Research, 241-256.

Knapp, V. K., Durgunoglu, A., & Ortel, T. W. (n.d.). A Review of Rainfall-Runoff Modelling for Stormwater Management. In U. G. Survey, Illinois State Water Survey: Hydrology division (pp. 4-96). Illinois District: Champaign, Illinois Department of Energy and Natural Resources.

Podger, G. (2004, June 18). CRC for Catchment Hydrology. Retrieved from Rainfall Runoff Library: https://www.toolkit.net.au/rrl

Lichty, R.W., and F. Liscum. 1978. A Rainfall-Runoff Modeling Procedure for Improving Estimates of T-Year (Annual) Floods for Small Drainage Basins. U.S. Geological Survey Water-Resources Investigations 78-7, Lakewood, CO.

Marsalek, J. 1978. Research on the Design Storm Concept. Addendum to Urban Runoff Control Planning, by M.B. McPherson, U.S. Environmental Protection Agency Report EPA-600/9-78-035:158-187.

McPherson, M.B. Urban Runoff Control Planning, U.S. Environmental Protection Agency Report EPA-600/9-78-035.

McPherson, M.B., and F.C. Zuidema. 1977. Urban Hydrological Modeling and Catchment Research: International Summary, ASCE Urban Water Resources Research Program, Technical Memorandum No. IHP-13, New York, NY.

National Research Council (NRC). 1988. Estimating Probabilities of Extreme Floods: Methods and Recommended Research. National Academy Press, Washington, DC. Pilgrim, D.H. Bridging the Gap Between Flood Research and Design Practice. Water Resources Research 22 (9): 165-176.

Sherwood, J.M. Estimation of Volume-Duration-Frequency Relations of Ungaged Small Urban Streams in Ohio. In Proceedings of the AWRA Conference on Urban Hydrology, Denver, CO, in preparation.

Singh, K.P. Runoff Conditions for Converting Storm Rainfall to Runoff With SCS Curve Numbers. Illinois State Water Survey Contract Report 288, Champaign, IL.

Thomas, W.O. 1982. An Evaluation of Flood Frequency Estimates Based on Rainfall/Runoff Modeling. Water Resources Bulletin 18 (2): 221-230.

Thomas, W.O. 1987. Comparison of Flood-Frequency Estimates Based on Observed and Model-Generated Peak Flows. In Hydrologic Frequency Modeling. V.P. Singh (ed.), Proceedings of the International Symposium on Flood Frequency and Risk Analysis, Baton Rouge, LA, pp. 149-161.

Troutman, B.M. Errors and Parameter Estimation in Precipitation-Runoff Models. Water Resources Research 21 (8): 1195-1222.

Weiss, L.S., and A.L. Ishii. Investigation of Techniques to Estimate Rainfall-Loss Parameters for Illinois. U.S. Geological Survey Water-Resources Investigations Report 87-4151.

Wenzel, H.G. Rainfall for Urban Stormwater Design. In Urban Stormwater Hydrology, D.F. Kibler (ed.), American Geophysical Union, Water Resources Monograph 7, pp. 35-67

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[Accessed 09 December 2024].

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