Hydraulic Engineering

Table of Contents

Introduction.

Literature Review..

Global Climate Model

Climate Change and Factors Responsible.

Climate Change effects on Flood.

Signs of Flood Hazards.

Hydrological Model

Affects of Climatic Factors on Intensity Frequency Distribution Curve.

Literature Summary.

Tasmania IFD..

Conformal Cubic Atmospheric Model (CCAM)

Approach of ARR 2016.

Assumptions.

Limitations.

Flood Estimate.

Advantages and Limitations.

Conclusion.

Reference

Introduction to Hydraulic Engineering

The main purpose of this assessment is to go through a proper literature review that gives a clear idea about various climatic conditions, their change, their impacts on the hydrology or ecosystem and their governing factors also. The study covered the vast area of meteorology that conations, rainfall, runoff, intensity, duration, and frequency of rainfall over a catchment. This study is going through a detail literature review that gives a clear idea about all the factors stated. All the aspects are clearly described from various journals and articles which are reliable enough to consider. They all are selected from scholar. The main aim is to analyze the IFD curve feature of Tasmania, Australia. IFD generally gives the nature of precipitation over several years. This is very useful to conduct any structure or project, especially irrigation or water management projects. Not only the present data but a detail and very close future data are needed. Without future prediction of climatic structure development of the particular region is quite difficult. If a structure is designed without considering the future effects or changes of the climatic conditions, it may lead to a failure in the future. Many natural hazards can be tackled with more efficiency if its occurrence can be predicted before. Hence, every country gives a serious notice over this weathering report. Continuous depletion of the natural elements causes a serious threat to all mankind. If all these can be known before, its effect can be minimized or the cause can be eliminated.

Key Words- Hydrological Model, River Discharge, Flood estimate, Runoff, intensity of rainfall, duration of rainfall, frequency of rainfall, IDF, Downscale Precipitation, Global Climate Model, Regional Climate Model, Crop water availability.

Literature Review of Hydraulic Engineering

As claimed by the Babister et al., (2016) the prediction of weathering condition in the future is quite problematic in the past few years and hence this was a great issue for the meteorologists. Weathering condition change means the change in temperature in air close to the earth surface, a long period of excessive heat or frost, more intensity of precipitation and of a long duration, water runoff change by a high value, other factors that affect the ecosystem or local area excessively. The effect of these factors is greatly explained by the change in water level and their balance system in the nature. If there is a low intensity rainfall over a large duration by days in the winter season, then it could flood the watershed in the spring (Babister et al., 2016). A low intensity but long duration rainfall may cause soil saturation condition which boost up the chance of flood occurring (Ball et al., 2016). A reverse process also can be seen that is a low rainfall rate over a small duration can cause depletion in the ground water level and thus it may cause difficulty in the continuous water supply. This may cause water deficit condition in that particular region and also change the ecosystem. The extreme conditions show a long return period and thus it cause difficulties in the future prediction of weather.

Global Climate Model

As per the study Dang et al.,(2016) the activities oriented to economy are considered a cause of change in the climatic condition. Almost all the government sectors, organizations, industries are trying to deal with the problem of climatic change by modifying respective deliverables that may increase the emission of greenhouse gases. In the structure of the coordinated regional climate downscaling experiment i.e. CORDEX, a gathering of environmental fluctuation projections has made by downscaling the recreations of four Global Climatic Models (GCMs) by considering the Consortium for Small Scale Modeling (COSMO) local atmospheric model. Fluctuations between the anticipated temperature and rainfall reenacted by CCLM and the applied GCMs are studied and talked about. The anticipated increment of occasional temperature is seen as comparable among RCM and GCMs, though huge fluctuations (>1°C) present regionally (Dang et al., 2016). Fluctuations are additionally noticed for extraordinary occasion related amounts, like the extension of the upper edge of the highest temperature likelihood conveyance system and, thusly, the time length of warmth waves.

Greater vulnerabilities are found later on rainfall changes, this is generally an outcome of inter model (GCMs) changeability over few other territories but over different districts the rainfall patterns reenacted by CCLM and the GCMs give inverse indications, with CCLM demonstrating a makeable decrease in rainfall toward the century's end. This unsure and some of the time differentiating conduct is additionally examined by identifying the various models' reaction to the land climate communication and result. Considering the huge vulnerability related with between model changeability across GCMs and the decreasing spread in the outcomes when a solitary RCM is utilized for downscaling, the article firmly underlined the significance of abusing completely the CORDEX Africa multi GCM or multi RCM troupe (Dosio et al., 2016) so as to survey the strength of the environmental change signs and, probably, to distinguish and measure the numerous wellsprings of vulnerability that present yet.

Climate Change and Factors Responsible

As per the author of this study, the intergovernmental panel on climate change (IPCC) illustrates potential effects of environmental change on greenhouse. IPCC was established under the governance of world meteorological organization with also United Nations Environment Programme (Newman et al., 2016). The aim was to analyze the climatic changes and its affect on sea water level change, their cause and to find possible solution. Climatic changes affects are as:

  • Global Warming- IPCC states that, if outflows of green house gases (GHG) keep on rising as of now seeing at that point worldwide means temperatures will increment by 0.2°C to 0.4°C every decade throughout the following century. There gives a very clear sign that a warming of the globe has happened over the previous century, with a maximum range of 0.3°C to 0.6°C. Quite a bit of this warming has been amassed in two periods, between around 1920 and 1940 , the 6 hottest years on record have all been in the 1980s ( et al., 2016).
  • Decrease crop water availability-Presumably the most significant outcomes of anticipated fluctuations in atmosphere for agriculture would rooted from higher genuine evapotranspiration, generally due to increased temperatures of the earth surface and air. In the tropical regions, where temperature increments are supposed to be lesser than somewhere else, the expanded pace of moisture misfortune from plants and soil would be more (Kemp et al., 2016). It might be fairly diminished by more noteworthy humidity and expanded cloudy weather during monsoon, however could be increasingly articulated in dry periods.

There are many other factors present in the ecosystem but these are the most two critical effects. Various factors are also present in the nature those create the change in the climate and they are as follows:

  • Distance of region from sea- Sea influences the atmospheric condition of a region. Coastal regions are wetter and colder than inland regions. When warmer air from the areas far away from sea meets cooler air of sea, cloud formed (Kemp et al., 2016). The core of the regions has a wide scale of temperature. In the late spring, temperatures can become very dry and warm as water from sea dissipates before it arrives at the core of the region.
  • Wind Direction- The Sea wind frequently cause rainfall to the coastal region and dry climate to the regions away from sea. Winds that hit to Britain from warm inland territories, for example, Africa will be dry and warm (Dang et al., 20185). Winds that hit to Britain from inland zones, for example, core Europe will be dry and cold during winter. England's predominant twists originate from a south westerly bearing over the Atlantic. These breezes are cool in the late spring, mellow during winter and will in general bring wet climate.
  • Land shape- Mountains or hills can affect the weathering condition. Comparatively more precipitation occurs in the mountainous regions than flatten areas. This is because, cooler air go above the layers and causes condensation of water. Regions are getting cooler as height increases from the sea level. This situation occurs due to the presence of colder air with the increase in heights and that’s why there is snow on the mountains.
  • Equator distance- Weather or climate of a region is affected by the distance of this place from equator. Energy emitted from sun arrives at the surface of the earth at a flatter angle and then goes through a thick layer of environment than it reaches at equator. This signifies the atmosphere is cooler in the following times from the Equator (Dang et al., 20185). In the poles there is also a huge difference of temperature during summer and that of in winter. During the summer, sun stays at the sky for the whole time and there is a darkness days totally during the full winter.

Climate Change Effects on Flood

The article EL AZIZI et al.,(2016) portrayed the critical issues of environmental change for worldwide flood hazard. Floods occurred diversely in various geographic regions. It may be occur due to excessive rainfall which exceeds the capacity of infiltration of the soil, or due to rainfall over saturated land, for this situation, the quantity of flood from a given quantity of precipitation relies upon the capacity of saturation. Floods also might be created by the melting of snow. The impacts of environmental difference on flood qualities thusly shift across space, contingent upon flood creating component (EL AZIZI et al., 2016). In which place floods are to a great extent created by serious precipitation and predecessor conditions are not important, at that point changes in flood attributes are firmly impacted by changes in the recurrence of extreme rainfall.

Where the degree of immersion is significant, at that point changes in flood attributes are impacted by changes in extreme precipitation, however changes in the event of soaked conditions after some time; this will rely upon both aggregated precipitation and vanishing. In which melting of snow floods are as of now significant, floods in future may increment if amassing of snow increases, and will happen prior if melting of snow happens prior; on the off chance that higher temperatures mean more winter precipitation falls as downpour, at that point snow collection would lessen and snowmelt tops decrease. At the outrageous, the flood system may change from one commanded by spring snowmelt floods to one described by littler, increasingly visit downpour took care of floods in winter. The impacts of environmental change on flood attributes are accordingly subject to setting, and are not really a basic capacity of progress in precipitation (EL AZIZI et al., 2016).

Signs of Flood Hazards

Frequency of Flood

Fluctuations in the frequency of flood are listed by-

(a) Return period change of the present 100 year flood.

(b) Change in the value of the 100 year flood (Ball et al., 2016).

 Hydrological Model

According to the study report Kellomäki et al., (2016) simulation of stream flow is done at spatial goals of 0.5 × 0.5° by the use of Mac-PDM.09, an everyday model of balanced water. Monthly updated information carries this model, disconnected measurably to the everyday scale, for a time of thirty years. The distribution of frequency of flood for a framework cell is analyzed by fitting a generalized extreme value (GEV) appropriation by the technique for L moments to recreate annual highest daily flow. This model works for twenty times in every grid compartment, with various stochastic disconnections of the atmosphere information in a monthly basis, and the general hydrological characteristic determined over the 20 redundancies (Kellomäki et al., 2016). Stream flows are not directed from one compartment to another, so the frequency curve generally gives floods created inside a 0.5 × 0.5° around 2500 km2 catchment (Kellomäki et al., 2016). Curves of flood recurrence will in general become less steep as the catchment zone increments, hence the curves of framework scale here are likely more steep than the genuine curves of frequencies in cells with high upstream commitments. Here the assumption is that there is no adjustment in land use of catchment with time.

Affects of Climatic Factors on Intensity Frequency Distribution Curve

As opined by Rahman et al.,( 2016) continuous increase in the green house gases makes changes in the hydrological cycle and thus changes in the intensity, frequency, and duration of rainfall occurs. Identifying the effects of weather changes can decrease the hazardous effect. For the design of the water structures the rainfall data of several years is very necessary. This data related to the intensity, duration, frequency of precipitation with a future prediction of climate condition data. The objective of this study is to analyze the probable fluctuations in the IFD curves between present weathering condition and that of in future. Here is an IFD curve given of Australia.

Literature Summary of Hydraulic Engineering

From the above elaborated study or literature review it can be noted all the climatic condition change leads to a change of whole ecosystem. After the study of the climatic factors, the prediction of future condition of the same has become quite easy. This can help in the irrigation process, establishment of the water management structures, and other economic works. The weathering report is very necessary for a region or country for its development. Hence a proper system should build to analyze the weathering condition. Exact future data is not possible to calculate or determine but a close value can be evaluated from a huge study report. The analysis of the weathering factors is also necessary to minimize the pollution or adverse reasons to save the region against any natural hazard. A prediction on future also helps to take precautions against any big hazards. All the developmental processes of a country or region are much related to its weathering condition in the present and also in the future. IFD curve helps in the designs of the water management structures, irrigation structures. There are various methods to go through these studies. A long research is needed to conduct them. All these conclusions are done after the literature review.

Tasmania IFD

Water layer depletion, decrease in quality, rise in temperature, change in moisture content in the atmosphere are the reason of changing an IFD curve shape. If a flood occurs in an area it will cause damage to the land, property, life risk and it decreases present water quality. Landslides, soil erosion all can occur as a cause of flood (Ball et al., 2016). A detailed record of rainfall data is analyzed in terms of intensity, frequency, and duration to analyze the past rainfall pattern and predict future rainfall considering a number of climate changing factors (Podger et al., 2018). IFD curve is the representation of the same which gives the past records of rainfall of a particular area in terms of frequency, intensity, and duration and also gives a future indication of rainfall characteristics which helps in building water management structures and also help to fight better with storm or flood situation. With the increase in industrial development worldwide, the increase in carbon dioxide also occurs along with other major greenhouse gases. Which cause a increase in the concentration of GHG and thus a change in the weathering conditions such as change in temperature, change in the rainfall characteristics and other. A change in the downscale precipitation characteristics makes changes in the IFD curves.

Conformal Cubic Atmospheric Model (CCAM)

CCAM represents a rainfall simulation in 2 km resolution and this occurs too step. CCAM simulation at a resolution of 10 km gave no modified result over the same at 2 km (Dosio et al., 2016). CCAM is mainly an enlarged grid model of atmosphere, the natural factorization of the same might control a large scale of spatial, which gives a clear sign for their modification. To select the governing factors for this simulation process, CCAM gave a significant rainfall result at a parameter of about 50 km (Sanglikar et al., 2016). It has proved that in case of sub 10 km range, the settlings of parameters proves as sub optimal in case of resolution in which the structure starts resolving rainfall cases. This shows that a modification needed in factorization to analyze fine elements with more accuracy (Babister et al., 2016). ARR has considered this hydrologic model.

Compared to the analysis based AWAP precipitation result set, the drawbacks of CCAM resolution of 2 km ERA Interim lower simulation describes that in all time periods precipitation remains same almost. Hence, it became a problem to split off the impact of climate factors with the help of GCM from the impact of badly designed CCAM precipitation factorization.

The fluctuated result of precipitation from CCAM over Sydney represents a locally heterogeneous design or pattern having a change in percentage and the magnitude differentiate greatly with the region. The regions at the west Sydney having a high altitude are closely related with the increment of 1 percent AEP and it shown that this orographic condition is not only factor that is responsible for precipitation. Other areas away from the sea coast also experienced a great increment in 1 percent AEP (ARR guideline, 2020). In 2015 CSIR and Bureau of Meteorology released a simulation increment in the value of wettest yearly daily total and 5 percent AEP wettest everyday total in Australia. A prediction of Greater Sydney said that with duration of 24 hour 1 percent AEP a increase in IFD will be up to 20 percent by the year 2050 (Ollett et al., 2016).

Approach of ARR 2016

In the past editions there are many points that give a huge advantage in the engineering field, general field but still needed some modification and this creates the necessity of publishing a new edition (ARR Guidelines 2016). There are many important improvement occurs that helps in gathering modern knowledge considering flood estimate, IFD, storm management and other. This edition gives a description about the use of Monte Carlo methods and stochastic methods. Eliminating all the past edition’s faults and improving the same this edition serves better to the engineering sectors.

Assumptions

Various assumptions are made in this edition of Australia Rainfall & Runoff 2016 edition such as, first assumption made over the practical environmental structure by a systematic hypothesis. Another assumption is made in case of flood estimate considering stagnation in the climate. Practitioners of Australia can use an assumption that consensus of highest GCM cases in case of RCP 4.5 & 8.5 are accurate selection for setting in design.

Limitations

Under limitation there are several topic present in ARR 2016 that are, there are still a question present in the definition of flood design problems, the process of flood estimate is still create problem in various engineering works. Further specifications needed in the design of, culverts, bridges in case of transportation system, management of floodplain and its planning, drainage system design in urban, spillway dam design and in many other area.

Flood Estimate

There are three various approach in the study (Loveridge et al., 2016) such as a) analysis of frequency of flood b) approach of a storm design c) approach of a continuous structure.

Steps

Information Available

Source of uncertainty

Data

Parametric

Regionalization

Structural

Catchment Modeling

1. Estimate

Runoff-

Routing

Model and

Loss Model

Parameters

a. At-site

data

b. Regional

information

only

yes – rainfall

and

stream flow

no

Yes

yes – higher

than case(a)

No

yes

Yes

yes – higher

than case(a)

2. Estimate

Design

Rainfall and

the Temporal/

Spatial

Patterns

Based on

Bureau of

Meteorology

IFD

yes – rainfall

Yes

Yes

Yes

3. Predict

Design

Floods using

Catchment

Modeling

Systems

Based on

steps 1-2

n/a –

identified in

steps 1-2

yes – in

addition to

steps 1-2

n/a – identified in

steps 1-2

yes – in

addition to

steps 1-2

Advantages and Limitations

As per ARR guideline the main advantage of this method is that is gives an accurate direct calculation of flood with the help of gauged data. High flood data gives the collaborative results of an area against storms and this do not affect other parameters like rainfall based processes. Analysis of flood frequency as per the ARR guideline is a quick process than rainfall processes. Flood recurrence analysis gives quite accurate result that rainfall focused processes. Now come to its limitations and they are as, the high flood data that might not reflect the practical condition related to the issue. Limited number of available flood data is the barrier of its efficiency. There are many uncertainties related to the choice of various models of probability and its practical distribution.

Conclusion on Hydraulic Engineering

From the above study, all the detail points can be known related to the flood estimate, IFD and the climatic factors and their effects on environment. The pollution of human activity has a great effect over the climatic factors and this changes the future prediction of the climatic condition. Hence, a large study and guideline requires about the future climate situation to construct new structure or make development in the agricultural field. ARR has published many editions on these guidelines but still there are many questions present and this is for the continuous change in the climatic factors. A revised and updated data is essentially required to conduct further studies.

References for Hydraulic Engineering

ARR Guidelines- Australia Rainfall and Runoff (2020). Availableat:<http://arr.ga.gov.au/__data/assets/pdf_file/0014/40550/ARR_Project_8__Project_12_Stage_3 _Report.pdf> [Accessed 7 May 2020].

Acecrc.org.au. 2020. ACE CRC | Antarctic Climate & Ecosystems Cooperative Research Centre. [online] Available at: <http://acecrc.org.au/climate-futures-for-tasmania/> [Accessed 7 May 2020].

Arr.ga.gov.au. 2020. ARR Guidelines - Australian Rainfall And Runoff. [online] Available at:<http://arr.ga.gov.au/arr-guideline> [Accessed 7 May 2020]

Babister, M., Trim, A., Testoni, I. and Retallick, M., 2016. The Australian rainfall and runoff datahub. In 37th Hydrology & Water Resources Symposium 2016: Water, Infrastructure and the Environment (p. 17). Engineers Australia.

Ball, J.E., Babister, M.K., Nathan, R., Weinmann, P.E., Weeks, W., Retallick, M. and Testoni, I., 2016. Australian Rainfall and Runoff-A guide to flood estimation.

Beck, H.E., van Dijk, A.I., De Roo, A., Miralles, D.G., McVicar, T.R., Schellekens, J. and Bruijnzeel, L.A., 2016. Global-scale regionalization of hydrologic model parameters. Water Resources Research, 52(5), pp.3599-3622.

Centaur.reading.ac.uk.2020.[online]Availableat:<http://centaur.reading.ac.uk/75357/3/6%20SmartCIties_Clean%20%281%29.pdf> [Accessed 7 May 2020].

Dang, H.L., Li, E., Nuberg, I. and Bruwer, J., 2018. Vulnerability to climate change and the variations in factors affecting farmers’ adaptation: A multi-group structural equation modeling study. Climate and Development, 10(6), pp.509-519.

Dosio, A. and Panitz, H.J., 2016. Climate change projections for CORDEX-Africa withCOSMO-CLM regional climate model and differences with the driving global climate models.Climate Dynamics, 46(5-6), pp.1599-1625.

EL AZIZI, L., 2019. https://ijarcce.com/wp-content/uploads/2019/09/IJARCCE.2019.8901.pdf. IJARCCE, 8(9), pp.16-21.

Kellomäki, S., Strandman, H., Heinonen, T., Asikainen, A., Venäläinen, A. and Peltola, H., 2018.Temporal and spatial change in diameter growth of boreal Scots pine, Norway spruce, and birchunder recent-generation (CMIP5) global climate model projections for the 21st century. Forests,9(3), p.118.

Kemp, D.J. and Hewa, G., 2018. An investigation into the efficacy of Australian rainfall and runoff 2016 procedures in the mount lofty ranges, South Australia. In Hydrology and Water Resources Symposium (HWRS 2018): Water and Communities (p. 407). Engineers Australia

Loveridge, M. and Rahman, A., 2018. Monte Carlo simulation for design flood estimation: a review of Australian practice. Australasian Journal of Water Resources, 22(1), pp.52-70.

Newman, A.J., Mizukami, N., Clark, M.P., Wood, A.W., Nijssen, B. and Nearing, G., 2017.Benchmarking of a physically based hydrologic model. Journal of Hydrometeorology, 18(8),pp.2215-2225.

Ollett, P., Syme, B. and Ryan, P., 2017. Australian Rainfall and Runoff guidance on blockage ofhydraulic structures: numerical implementation and three case studies. Journal of Hydrology (New Zealand), 56(2), p.109.

Rahman, M.M. and Rahman, A., 2017. Changes in Australian Rainfall Runoff and Its Implication for Estimating Design Rainfall. In Proceedings of the 1st International Conference on Engineering Research and Practice, 4-5 February 2017, Dhaka, Bangladesh (pp. 48-53).

Sanglikar, R.V., Upadhye, S.K., Pardhe, D.D., Jadhav, J.D., Amrutsagar, V.M. and Chary, G.R., 2018. Constants in IFD equation for Pandharpur in Scarcity Zone of Western Maharashtra. International Journal of Bio-resource and Stress Management, 9(1), pp.17-22.

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