storm water management plan for osho ventures slag …projects.gibb.co.za/portals/3/2013-03-16 rv...

Glen Manor Office Park, 1st Floor, Block 4 138 Frikkie de Beer Street, Menlyn Pretoria, South Africa Telephone: +27 (0)12 348 1114 Facsimile: +27 (0)12 348 5030 Web: www.gcs-sa.biz

Storm Water Management Plan for OSHO Ventures Slag Storage and Cement Process

Facility

Report

Version – 1

20 March 2013

OSHO Ventures

GCS Project Number: 13-064

Client Reference: Danielle Welgemoed

OSHO Ventures Stormwater Management Plan OSHO Ventures Cement

13-064 20 March 2013

Report Version – 1

20 March 2013

OSHO Ventures

13-064

DOCUMENT ISSUE STATUS

Report Issue Draft

GCS Reference Number 13-064

Client Reference Danielle Welgemoed

Title SWMP for OSHO Ventures Slag Storage and Cement Process Facility

Name Signature Date

Author Kevin Scott

March 2013

Robert Verger

March 2013

Document Reviewer Leon de Jager

March 2013

Director Alkie Marais

March 2013

LEGAL NOTICE This report or any proportion thereof and any associated documentation remain the property of GCS until the mandator effects payment of all fees and disbursements due to GCS in terms of the GCS Conditions of Contract and Project Acceptance Form. Notwithstanding the aforesaid, any reproduction, duplication, copying, adaptation, editing, change, disclosure, publication, distribution, incorporation, modification, lending, transfer, sending, delivering, serving or broadcasting must be authorised in writing by GCS.


13-064 20 March 2013

EXECUTIVE SUMMARY

GCS was appointed to provide a Storm Water Management Plan for the proposed OSHO

Ventures Slag Storage and Cement Processing Facility in Port Elizabeth in the Eastern Cape

Province of South Africa.

The most relevant legislation pertaining to this study is the regulations contained in the

Government Notice 704 (GN 704) of the National Water Act (DWA 1998). The Best Practice

Guidelines (BPG’s) concerning Storm Water Management was used to assess the criteria of

compliance (BPG1).

The hydrology for the project area and quaternary catchment M30B was analysed for

rainfall patterns, evaporation distribution and runoff distribution.

For the entire Quaternary catchment M30B of 307 km2, Mean Annual Runoff of 4.95 million

cubic meters is expected. For a virgin catchment of 11.4 ha (site boundary) MAR is likely to

be in the order of 1840 m3/year. Runoff from areas which will now be considered dirty

water areas and where this water is now held on site, reducing the effective runoff of the

larger local river system represent a 0.033% reduction of flow in local river systems, which

is considered negligible.

Three water balances were calculated for the proposed infrastructure at the Cement Slag

Storage and Process Facility. These include an annual average water balance, a water

balance for the driest month on average (July) of the year and a water balance of the

wettest month of the year (November).

Two main catchments of concern were identified based on the infrastructural plan of the

project site. One dirty water catchment (catchment 1) and one clean water (catchment 2).

No detailed topographical survey was available. Based on 5m contour data it was visible

that polluted water from the Slag Storage and Cement Processing Plant area could flow into

the natural environment outside the perimeter of the project site and potentially pollute

the natural system.

Flood flows from 1:50 and 1:100 year rainfall storm events were calculated for the two

catchments which are affecting storm water infrastructure. Calculations were based on

current conditions which represent virgin or disturbed conditions in the two catchments.

Generally accepted calculation methods which were used are the rational method, the

alternative rational method and the standard design flood method.

The following is a short summary of the proposed SWM measures:

Create a PCD with sufficient size (~4 500m3)in the southwest corner (GN704);


13-064 20 March 2013

Construct 2 drains/berms at the south western and south eastern portion within

catchment 1 in order to direct all dirty water to the PCD (D1 and D2);

Construct a clean water drain/berm to direct clean water away from the project

site(C1);

Construct two clean water berms. One at the northern and one eastern portion to

keep clean water runoff out of the project area (B1 and B2).

Construct two culverts. One culvert at the end of the clean water berm at the

western portion of the project area.to diverts clean water under the road. The

second under the access road to divert the water from the dirty water drain into

the PCD (E1 and E2). These culverts must be designed by the Client’s Engineer.

Construct one berm parallel to the future railway to keep the dirty water from the

railway area out of the clean water area (F1).

The proposed PCD must meet GN704 criteria. To ensure that the proposed PCD in the

project area will not spill more than once, on average, in 50 years a water balance model

has been developed in the software package Goldsim ®. Model results of the water balance

showed that a PCD size of 4 500m3 seemed sufficient to allow one spill in 85 years. The

RWD was modelled not to spill. The required water amount for the cement mill is

5070m3/year. The calculated long term average water consumption is approximately

4200m3/year. This implies the import of raw water supply can be reduced with

approximately 800m3/year.

Open drainage channels are necessary to convey dirty water to the PCD. This type of

drainage channel should be constructed with a smooth concrete lining to discharge dirty

runoff as fast as possible and to limit the size of the channels. In a similar way the clean

water drains can be designed by diverting storm-water inflow into earth channel drains. All

channels and berms should be designed by a Registered Engineer.


13-064 20 March 2013

GLOSSARY OF TERMINOLOGY

Berm: A wall designed and constructed to change the direction of a natural surface water

flow path.

Catchment: That area from which any surface runoff will naturally drain to a specified

point.

Clean water: Natural runoff water from a catchment area that has not been contaminated

through contact with known pollutants.

Dirty water: Water that has been, or could potentially become, contaminated through

contact with known pollutants.

Dirty water system: Any systems designed to collect, convey, contain, store or dispose of

dirty water.

Drainage channel: An artificial flow path designed to convey water.

Hydrology: The study of natural water cycles that includes rainfall, evaporative and

transpiration losses and resulting surface flows.

Pollution Control Dams (PCD): Specialised storage dams designed to prevent environmental

pollution by containing and storing dirty water runoff for safe disposal through evaporation

or by any other environmentally responsible process.

Raw Water Dam (RWD): Specialised storage dams designed to use water storage for

operational and process purposes.

Runoff: Water that falls as rainfall and is not lost through evaporation, transpiration or

deep percolation into the ground. This water either does not penetrate soils but flows

directly across the soil surface, or re-emerges from local soils to flow on the surface along

natural flow paths or watercourses.

Watercourse: Watercourse refers to a river or spring; a natural channel in which water

flows regularly or intermittently; a wetland, lake or dam into which, or from which water

flows and any collection of water which the Minister may by notice in the Gazette, declare

to be a watercourse, and a reference to a watercourse includes, where relevant, its beds

and banks (National Water Act 1998 (Act 36 of 1998)).


13-064 20 March 2013 Page vi

CONTENTS PAGE

1 INTRODUCTION .......................................................................................................................... 8

2 SCOPE OF WORK ...................................................................................................................... 10

3 METHODOLOGY ....................................................................................................................... 11

4 SITE CONDITIONS ..................................................................................................................... 12

5 HYDROLOGY ............................................................................................................................. 12

5.1 RAIN ZONES AND REPRESENTATIVE RAINFALL DISTRIBUTION PATTERNS .................................................... 13 5.1.1 Estimating Peak Rainfall Intensities ................................................................................ 15

5.2 EVAPORATION ZONES AND MONTHLY EVAPORATION FIGURES ............................................................... 19 5.3 RUNOFF CALCULATIONS ................................................................................................................ 20

6 WATER BALANCE ...................................................................................................................... 22

7 STORM WATER MANAGEMENT PLAN ...................................................................................... 25

7.1 DELINEATION CLEAN AND DIRTY WATER CATCHMENTS ......................................................................... 25 7.2 DESIGN FLOODS ........................................................................................................................... 26 7.3 PROPOSED SWM MEASURES ON SITE .............................................................................................. 27 7.4 REQUIRED PCD SIZE ..................................................................................................................... 30

7.4.1 Assumptions .................................................................................................................... 30 7.4.2 Results ............................................................................................................................. 31

7.5 CONCEPTUAL DESIGN OF INFRASTRUCTURE AND DRAIN CAPACITIES ........................................................ 32

8 CONCLUSIONS AND RECOMMENDATIONS ............................................................................... 34

9 REFERENCES ............................................................................................................................. 36

LIST OF FIGURES

Figure 1-1 Locality of the OSHO Ventures Slag Storage and Cement Process Facility .......... 9 Figure 5-1 Rainfall Distribution ......................................................................... 15 Figure 5-2 Typical Plot of Ranked Rainfall ............................................................ 17 Figure 5-3 Peak Storm Rainfall .......................................................................... 18 Figure 5-4 Evaporation and Rainfall .................................................................... 19 Figure 5-5 Runoff Distribution ........................................................................... 20 Figure 6-1 Water balance for an average year ....................................................... 22 Figure 6-2 Water balance for a wet month (November) on average year ....................... 23 Figure 6-3 Water balance for a dry month (July) on average year ............................... 23 Figure 6-4 Water process flow diagram of the OSHO Ventures Slag Storage and Cement Processing Facility ......................................................................................... 24 Figure 7-1: Conceptual SWMP ........................................................................... 29 Figure 7-2: Simulation of the volume of the PCD over 85 years .................................. 31 Figure 7-3: Simulation of one spill of the PCD over 85 years ...................................... 32 Figure 7-4: Standard concrete lined drain design for dirty water with possible adjacent berm ......................................................................................................... 33 Figure 7-5 Standard clean water drain with adjacent berm ....................................... 33

LIST OF TABLES

Table 7-1 Overview delineated catchments .......................................................... 25 Table 7-2 Peak floods (1:50 year) calculated for the catchments contributing to storm water infrastructure .............................................................................................. 27


13-064 20 March 2013 Page vii

LIST OF APPENDICES

APPENDIX A ..................................................................................................................................... 37


13-064 20 March 2013

1 INTRODUCTION




The Slag Storage and Cement Processing Facility are situated on the Coega Industrial

Development Zone (Coega IDZ). The project area (~11.4ha) is located in the Nelson Mandela

Bay Metropolitan Municipality, and is part of an important area for industries with a global

perspective.

OSHO Ventures now seeks clarity on the impact of proposed process activities on the water

balance and a Pollution Control Dam (PCD). This study also provides a storm water

management plan for the Cement Slag and Processing Facility operations. The outcome of

this study would be compliance to relevant legislation and best practice guidelines for

storm water management.


13-064 20 March 2013

Figure 1-1 Locality of the OSHO Ventures Slag Storage and Cement Process Facility


13-064 20 March 2013

2 SCOPE OF WORK

The detailed scope of this project will include the following:

1. Project Initiation

• Project Close-out meeting and presentation

• Internal project management

2. Hydrological Analysis

• Meteorological analysis

• Catchment delineation

• Mean Annual Runoff Modelling

• Calculation of peak floods

• Impact of all infrastructure on the Mean Annual Runoff

3. Water balance for OSHO Ventures operations

• Developing a Process Flow Diagram

• Development of an MS Excel Model (accuracy depending on availability of

information) in DWA format for an average year, average wet month and an

average dry month.

• Formatting of water balance into required DWA format.

4. Storm Water Management Plan

• Delineation of contaminated and uncontaminated (clean and dirty)

catchments

• Determine the storm water flows and volumes (1:50 and 1:100 year events)

for both clean and dirty water areas.

• Indicate the placement of berms, channels and pollution control dams on a

map.

• The location for the proposed infrastructure (berms, channels etc.) will be

indicated approved by a registered Civil Engineer / Technologist.

• The dirty water storage (PCD size) required will be calculated / modelled

with GoldSim to prevent spillage of not more than once, on average, in 50

years.

5. Reporting

• Project Close-out report


13-064 20 March 2013

3 METHODOLOGY

Generally accepted calculations and methodologies were used to determine design floods in

the area. Runoff from area was analysed by using accepted techniques to downscale

quaternary catchment data modelled in WR 2005 for the Process Facility Site. Rainfall Data

was obtained from WR 2005 (simulated and patched data) and the South African Weather

Service.

For all runoff calculations, the following assumptions were made:

1 Monthly unit runoff (per square kilometre) for the area corresponds with values

modelled in WR2005 for Quaternary Catchment number M30B.

2 Rainfall of 430 mm per annum will be distributed similarly to records for Rain Zone

M30B of WR2005.

3 Lake Evaporation (evaporation expected off an open body of water) will be a nearly

constant average of 1560 mm per annum (zone 26A), with a fixed average monthly

distribution pattern.

4 Monthly rainfall and monthly runoff across the site is homogeneous. Peak runoff

across the site is homogeneous and was calculated the whole Project area.

Ms. Danielle Welgemoed provided GCS with estimated flow data of the water balance of the

Slag Storage and Cement Processing Facility. She also provided additional information on

expected water consumption data for irrigation of the garden, ablution etcetera. This

information was used to model water balances.

An analysis was made of how the dirty water system could be optimised to manage storm-

water flows and how large the proposed PCD should become.

No detailed designs of storm water management infrastructure were undertaken, but the

concept provided in this report should facilitate later detailed designs by the Client’s

Professional Engineers.

The most relevant legislation pertaining to this study is the regulations contained in the

Government Notice 704 (GN 704) of the National Water Act (DWA 1998). The Best Practice

Guidelines (BPG’s) concerning Storm Water Management was used to assess the criteria of

compliance (BPG1).


13-064 20 March 2013

4 SITE CONDITIONS

The Coega Industrial Development Area lies some 30 km north of the city of Port Elizabeth

in an area which is naturally flat coastal grasslands. The area lies in a marked rainfall

shadow. Areas to the south of a headland that defines the Port Elizabeth bay typically

experience average annual rainfall of between 700 and 720 mm, while to the north of this

headland, annual rainfall is reduced to between 420 and 450mm. The region lies between

summer rainfall areas to the north and winter rainfall regions to the south and rainfall, in

particular flood-producing extreme rainfall events, can occur at any time of the year.

The warm Mozambique Current that flows southwards past the harbour mouth tends to

moderate local climatic conditions. Average mid-winter daily temperatures of

approximately 20ºC are not significantly cooler that mid-summer average daily

temperatures of 26ºC, although temperatures can fall to 0ºC minima in winter, or climb to

36ºC maxima in summer. The area is, however, abnormally windy throughout the year (with

daily wind run in excess of 360 km/day expected in any month of the year).

The site of the proposed cement factory is flat, but at a safe distance from local rivers and

streams. The site is unlikely to be influenced by flooding in river systems. Local soils are

generally sandy and well drained, but the area is prone to flash floods when rainfall

intensities exceed the infiltration capacities of soils. The most significant feature of the

site, in terms of hydrology, is the fact that at least 2.8 hectares (out of 11.4 hectares total

site boundary) will be covered by roofs and roads, where most rain that falls will be

intercepted and will run off directly. This will generate high site-specific runoff peaks.

5 HYDROLOGY

In the South African context, reliable and complete long-term rainfall and runoff records

are rarely available and extensive use must be made of regional or inferred data. This both

makes accurate first order analysis of data extremely difficult and also simplifies and

streamlines the analysis of data. While the above statement seems to contradict itself, in

South Africa, much of the analysis has been done and is recorded or reported in

publications such as the WRC WR20005, Surface Water Resources of Southern Africa series

of reports. If WR2005 is used as the default source of information, local hydrological

studies can be limited to the analysis of factors that will modify rainfall and runoff and also

to processes that downscale information from the model catchments to smaller, local

catchments.


13-064 20 March 2013

It then becomes important to understand exactly what data is used in WR2005 and what

processes can be used to downscale data to a local site. It is important to keep in mind

that WR2005 represents the results of the WRSM (Pittman) hydrological model, which uses a

modified and patched set of input data to estimate runoff for local river systems. The

outputs of this model have been calibrated both for small reference catchments, and at a

regional scale (secondary catchment scale).

5.1 Rain zones and representative rainfall distribution patterns

A basic principle that is widely used to model WR2005 stream-flow data is the extensive use

of dimensionless data that indicate regional patterns of rainfall and runoff distribution. The

model considers characteristic rain zones, where the general pattern of rainfall is unlikely

to vary significantly (although marked variations might occur in the value of, or timing of

individual rainfall events at various individual sites). Rainfall in a specific rain zone is not

expressed in terms of an actual value, but rather as a percentage of annual rainfall for a

site. This dimensionless expression of rainfall allows for a regional assessment of likely

distribution patterns.

Consider a rain zone with 3 records of varying length and Mean Annual Precipitation. An

incomplete record showing an MAP of 720mm could be divided by 7.2 to produce a

dimensionless record. Similarly dimensionless records for other sites could be produced.

Another record might reflect a MAP of 684 mm and a third, one with a MAP of 706mm. If,

for argument sake, it is accepted that these 3 records accurately represent the pattern of

distribution for a local rainfall zone, then it becomes possible to consolidate the 3 partial

records, cross-patching incomplete single records to produce one single dimensionless

rainfall record for the zone. This process constructs a complete record for the zone

(without data gaps), but this new virtual record no longer represents recorded data for any

particular site, but rather the likely distribution of rainfall anywhere within the rain zone.

Having established a virtual record for the rain zone, it is easy to generate a virtual record

for any site within the zone. If we accept that a local site is likely to have a MAP of

440mm, then the virtual record for the site would be derived by:

Site Rainfall = DVR 690/100

Where; DVR = the dimensionless virtual record for the rain zone.


13-064 20 March 2013

A number of issues now emerge. Any statistical analysis that looks at extreme events and

the probability of extreme events occurring is very much more accurate with a long record

of data than with a short record. Ten years of data might include a 1:50 year rainfall

event. Simple ranking of data will flag this event as something that occurred once in ten

years and this single outlier could influence all estimations of extreme event probability.

Similarly, a short record that reflects no extreme events is fairly useless for predicting

extreme events. Ninety years of record would enable investigators to accurately predict a

1:10 year event with a high degree of confidence.

The dimensionless virtual records produced for use in WR2005 are long records which are

made up by consolidating a series of broken or shorter records. Confidence levels in

extreme event predictions tend to suffer. A 10 year record might, therefore, add to

confidence levels when estimating MAR, but is unlikely to add confidence to the rainfall

distribution patterns. More than 60 years of local rainfall records is likely to give a more

accurate picture of rainfall distribution patterns and extreme events than 90 years of

virtual record. Using this record to analyse stream-flow would, however, imply a need to

run WRSM or another hydrological stream-flow generation model, as WR2005 stream-flow

would no longer apply.

The set-up and calibration of a stream-flow model requires a flow record of reasonable

length. Comprehensive flow records for small catchments are extremely rare. Detailed

hydrological modelling is often not feasible for small-scale studies and the cross-calibration

of stream-flow models or model runs using the outputs of another model or model run is

generally frowned upon. The situation could arise that even given 60 years of local rainfall

data, the virtual record produced for WR2005 will be preferred.

For simple hydrological studies in South Africa, GCS, by default accept rainfall distribution

patterns that are based on WR2005 (or later updated reports) virtual records for the stated

rain zone. Rainfall for the Coega site falls within WRC, WR2005 Rain Zone W31. Local

rainfall records reflect a long-term Mean Annual Precipitation for the site of 341mm.

Analysis of rainfall records using the ACCORD model does, however, indicate an underlying

trend of change (climate change) in rainfall patterns, and it is felt that current climatic

conditions are more accurately represented by a Mean Annual Precipitation of 440 mm per

annum.

Rainfall distribution patterns for this simple hydrological study are best represented by a

single graph. If the rainfall record (actual or virtual) is ranked on a monthly time-step, it is

possible to identify and map probability curves as shown below:


13-064 20 March 2013

Figure 5-1 Rainfall Distribution

In the above graph rainfall (for any month) that is likely to be exceeded in 70% of years is

represented by the E70 line. Similarly, rainfall that is likely to be exceeded in 30% of years

is represented by the E30 line. The plot shows that approximately 90% of the time we would

expect more than 15 mm of rainfall in January (average 41 mm). In July (average 23.9

mm), the long term average rainfall clearly represents an abnormally wet condition. It

becomes clear that rainfall cannot be accurately represented in terms of averages or

percentages of averages, but variability in rainfall is rather a function of probability.

5.1.1 Estimating Peak Rainfall Intensities

The estimation of short duration rainfall and rainfall intensities in Southern Africa poses a

particular problem. Fully automated weather stations that measured the intensity of storm

events were rare prior to the mid 1990’s. While considerably more information is available

to enable accurate estimation of 24 hour peak rainfall events, very little data is available

on short duration events. In 1979 Op den Noordt, analysed patterns of rainfall distribution

in short duration storms and suggested an algorithm to downscale 24 hour peak rainfall

events to represent rainfall of shorter duration. The following formula was derived:

Where;

I = the Intensity of rainfall for a certain event

C = a constant for the site and return period

Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep

E10 95.4 106.4 74.7 67.7 62.7 70.7 83.8 64.1 47.6 51.0 79.9 68.0

E30 50.1 59.4 44.3 46.3 43.4 47.3 49.7 28.8 29.3 25.6 40.9 33.1

E50 32.9 36.3 31.5 33.6 31.1 29.1 33.1 16.9 15.0 13.1 28.1 22.3

E70 23.4 20.8 21.0 24.4 21.1 16.1 21.6 12.1 8.0 7.1 19.2 16.4

E90 8.7 5.9 13.9 15.2 9.9 5.4 12.6 3.7 0.5 0.2 10.0 3.8

0.0

20.0

40.0

60.0

80.0

100.0

120.0M

on

thly

Rai

nfa

ll [m

m]

Rainfall Distribution


13-064 20 March 2013

td = the time of duration of the rainfall event

This formula has been widely accepted in South Africa. If the 1:50 year 24 hour rainfall for

the site has been established to be 147.5 mm, then substituting into the formula;

And; solving for C; C = 104.9

By applying the formula, the 1 hour average intensity = 86.6 mm per hour, while the 6 hour

average rainfall intensity would be 20.6 mm per hour. This implies peak 1 hour rainfall for

the same 1:50 year return period of 86.6 mm, peak 6 hour rainfall of 123.4 mm and peak 24

hour rainfall of (given) 147.5 mm.

Pegram (HRU, University of the Witwatersrand, 1990), Midgely and Pittman (HRU,

University of the Witwatersrand, 1984) and den Noordt (University of Wageningen, 1980) all

went further to try and establish algorithms that would approximate the C factor. While

data sets and methodologies followed did vary, a common approach was followed which

was based on the original Op den Noordt formula. Formulae for estimating C all followed

the same format;

Where;

MAP = Mean Annual Precipitation [mm]

R = the design return period

a,b and x are formula constants.

For inland regions of South Africa, there was little variation in the constants derived; with x

varying between 0.295 and 0.305. Since 1990 there have been significant advances both in

the quantity of data available, and also in the capacity of individuals to analyse data using

more powerful modern computers. Scott (IWFW2, 2008) expanded on the analysis as

follows:


13-064 20 March 2013

Consider the following graphic. If one ranks annual rainfall data from Southern Africa, a

strong trend emerges. Rainfall between values that are exceeded 70% of the time and 30%

of the time (normal wet weather and normal dry weather values) tend to correlate strongly

to a linear relationship. It is only extreme rainfall events that tend to vary significantly

from a normal linear trend. The magnitude of extreme events can be expressed as a power

curve function of the form; P = a Rx, where R represents a return period and x, a constant

for the site. It should be noted that in all previous formulae which estimate C, this

constant is a function of a wet rainfall event that is somewhat higher than MAP (C = (a MAP

+ b) Rx or C= a (MAP + B) Rx). Considering the break-out point where the formula used to

predict rainfall changes, it is logical that (MAP + B) describes precipitation that correlates

to a normally wet year, or annual precipitation that is, on average, exceeded 30% of the

time. The estimation can then be refined to; C = a NWYP Rx.

Figure 5-2 Typical Plot of Ranked Rainfall For the site, normal annual wet weather precipitation is estimated at 494 mm, and curve

fitting analysis of available precipitation intensity data allows us to solve for the constants

a and x, producing a wide-ranging rainfall intensity formula of:

Where:

I = design rainfall intensity [mm/hour]


13-064 20 March 2013

R = the design return period [years]

td = the storm duration [hours]

Peak storm rainfall is calculated by intensity multiplied by duration and can be represented

as follows:

Figure 5-3 Peak Storm Rainfall


13-064 20 March 2013

Figure 5-4 Evaporation and Rainfall

5.2 Evaporation zones and monthly evaporation figures

A process similar to the establishment of rain zones was used to establish WR2005

Evaporation Zones. This data is, however, inherently less accurate. While for rainfall,

WR2005 generated virtual records for 85 years from 1920 to 2005, evaporation zone data is

based on a significantly smaller record (1960 to 1990). While it is accepted that variation

and variability in evaporation data is less than for rainfall data, the small data sample and

model assumptions that monthly evaporation is fixed at the monthly average evaporation is

seen as a weakness in the model. Evaporation zone data provides only average monthly

evaporation data.

Any local record containing more than 10 years of data is likely to provide a more accurate

picture of local evaporation than the model provides. Site evaporation is represented by

WR2005 Evaporation Zone 26A, and is estimated at 1560 mm per annum. Evaporation is

likely to be distributed as follows:


13-064 20 March 2013

Figure 5-5 Runoff Distribution

5.3 Runoff Calculations

Local runoff from open areas and grassed lawns was assumed to be well represented by a

down-scaling of simulated WR2005 runoff data for the Quaternary Catchment M30B. Only

approximately 16 mm of the 440 mm rainfall is expected to run off from these areas.

For the entire Quaternary catchment of 307 km2, Mean Annual Runoff of 4.95 million cubic

meters is expected. For a virgin catchment of 11.4 ha (site boundary) MAR is likely to be in

the order of 1840 m3. Runoff from areas which will now be considered dirty water areas and

where this water is now held on site, reducing the effective runoff of the larger local river

system represent a 0.033% reduction of flow in local river systems, which is considered

negligible.

It is, however, planned that the developed site will contain at least 2.8 ha that is covered

by roofs and roads, where a significantly higher proportion of rain that falls is likely to run

off. It is accepted that some rain that falls on these paved areas is intercepted and

evaporates directly off the surfaces. During extreme storm events, however, the impact of

these interception losses is likely to be small. Runoff from these areas was calculated by

reducing monthly rainfall by a variable Φ index that is a function of average monthly

evaporation and assumes that 75% of all rainfall (on average) runs off these paved areas.

Oct Nov Dec Jan Feb Mar Apr May Jun Jul Aug Sep

E10 2746.7 2855.4 2247.8 2054.1 1841.2 1965.9 2092.6 1747.1 1530.6 1530.6 2095.0 1978.1

E30 1491.2 1454.0 722.3 162.1 1168.2 1214.4 1275.2 882.4 867.0 769.9 1093.0 916.7

E50 921.2 38.0 3.1 0.0 0.0 4.1 827.6 516.8 498.7 432.5 687.0 4.1

E70 0.0 0.0 0.0 0.0 0.0 0.0 8.2 0.0 6.2 0.0 17.4 0.0

E90 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0

0.0

500.0

1000.0

1500.0

2000.0

2500.0

3000.0

Mo

nth

ly r

un

off

[m

^3

]

Runoff Distribution Site


13-064 20 March 2013

Given the high mid-summer evaporation, lower runoff from the site would be expected in

hot summer months as rain is intercepted and tends to be lost to evaporation.

The total expected (long term average) dirty water runoff for the site that must be

accommodated in the planned pollution control dam amounts to 9 917 m3 per annum. This

runoff is likely to be distributed as follows:


13-064 20 March 2013

6 WATER BALANCE

Three water balances were calculated for the proposed infrastructure at the Cement Slag

Storage and Process Facility. These include an annual average water balance, a water

balance for the driest month on average (July) of the year and a water balance of the

wettest month of the year (November).

As requested, Ms. Danielle Welgemoed provided GCS with expected and available flow data

of the Slag Storage and Cement Processing Facility. She also provided additional

information on expected water consumption data for irrigation of the garden, ablution

etcetera. This information was used to develop a water process flow diagram and model

the water balances.

The water balances are presented in Figure 6-1 to Figure 6-3. The water flow process

diagram is presented in Figure 6-4.

Figure 6-1 Water balance for an average year

Raw Water Supply 1 752 m3/year Losses 1 752 m3/year

RWD 4 971 m3/year Losses 4 971 m3/year

Dirty Water Runoff 9 512 m3/year Evaporation 8 222 m3/year

Rainfall 2 252 m3/year Return Water Dam 10 759 m3/year

Dust Suppression 3 375 m3/year

PCD 9 312 m3/year Evaporation 153 m3/year

Rainfall 42 m3/year Cement Mill 5 040 m3/year

Raw Water Supply 9 034 m3/year Dust Suppression 2602 m3/year

Potable Water Supply 5 037 m3/year Sewage 4 745 m3/year

Losses 292 m3/year

Raw Water Supply 1 424 m3/year Losses 1 424 m3/year

Rainfall 3 503 m3/year Losses 6 878 m3/year

Dust Surpression 3 375 m3/year

TOTAL 50 213 m3/year TOTAL 50 213 m3/year

OSHO CEMENT PROCESS FACILITY WATER BALANCE

WATER BALANCE FOR AN AVERAGE YEAR (m3/year)

IN OUT

Cement Mill

PCD

Return Water Dam

Buildings(Offices, ablutions etc.)

Cooling Tower

Slag Stock Pile

Garden


13-064 20 March 2013

Figure 6-2 Water balance for a wet month (November) on average year

Figure 6-3 Water balance for a dry month (July) on average year

Raw Water Supply 146 m3/month Losses 146 m3/month

RWD 414 m3/month Losses 35 m3/month

Dirty Water Runoff 1 101 m3/month Evaporation 1 051 m3/month

Rainfall 245 m3/month Return Water Dam 1 110 m3/month

Dust Suppression 349 m3/month

PCD 708 m3/month Evaporation 15 m3/month

Rainfall 5 m3/month Cement Mill 420 m3/month

Raw Water Supply 660 m3/month Dust Suppression 154 m3/month

Potable Water Supply 420 m3/month Sewage 395 m3/month

Losses 24 m3/month


Rainfall 1 470 m3/month Losses 1 819 m3/month

Dust Surpression 349 m3/month

TOTAL 5 637 m3/month TOTAL 5 637 m3/month


WATER BALANCE FOR A WET MONTH ON AVERAGE (m3/month)

IN OUT

Cement Mill

PCD

Return Water Dam


Cooling Tower

Slag Stock Pile

Garden


RWD 414 m3/month Losses 35 m3/month

Dirty Water Runoff 339 m3/month Evaporation 473 m3/month

Rainfall 75 m3/month Return Water Dam 865 m3/month

Dust Suppression 314 m3/month

PCD 710 m3/month Evaporation 6 m3/month

Rainfall 3 m3/month Cement Mill 420 m3/month

Raw Water Supply 760 m3/month Dust Suppression 189 m3/month

Potable Water Supply 420 m3/month Sewage 395 m3/month

Losses 24 m3/month


Rainfall 110 m3/month Losses 424 m3/month

Dust Surpression 314 m3/month

TOTAL 3 410 m3/month TOTAL 3 410 m3/month


WATER BALANCE FOR A DRY MONTH ON AVERAGE (m3/month)

IN OUT

Cement Mill

PCD

Return Water Dam


Cooling Tower

Slag Stock Pile

Garden


13-064 20 March 2013

Figure 6-4 Water process flow diagram of the OSHO Ventures Slag Storage and Cement Processing Facility

Slag Stock

Pile

8400m2

Clinker

Stock Pile

Gypsum

Stock Pile

Closed Material Stores

LabWorkshop

Cooling Tower

Guard HouseAdmin Buildings

Cement Mill

Limestone

Stock Pile

Potable Water

4.8kl/day

Garden

4500m2

3.9kl/day

Buildings

Polluton

Control

Dam

Dirty Water Area (Roads,roofs etc)

Raw Water

13.8kl/day~

92persons

90% of time 9.8kl/day ~

10% of time 48kl/day

Rainfall

430mm/annum

Evaporation

1560mm/annum

Dust

Surpression16.8kl/day

16.8kl/day

Sewage13kl/day

Losses

4.8kl/day

Losses

0.8kl/day

Water Flow Chart

Return

Water

Dam

Runoff

Evaporation

1560mm/annumEnclosed Material Stores

Water source

80kl 80kl

Losses90% of time 9.8kl/day ~

10% of time 48kl/day

Backup in case

of

Shortage

Rainfall

430mm/annum


13-064 20 March 2013

7 STORM WATER MANAGEMENT PLAN

In accordance with Government Notice 704 (GN 704), there are main objectives of a SWMP,

namely;

1. To keep clean and dirty water separated;

2. To contain any dirty water within a system and

3. To prevent contamination of clean water

Storm water flow volumes should be used for conceptual design of proposed infrastructure.

All designs should be based on at least a 1:50 year extreme maximum runoff event.

The conceptual SWMP is presented in Figure 7-1

7.1 Delineation clean and dirty water catchments

Two main catchments of concern were identified based on the infrastructural plan of the

project site. One clean water and one dirty water catchment.

No detailed topographical survey was available. Based on 5m contour data it is visible that

this that polluted water from the Slag Storage and Cement Processing Plant area can flow

into the clean natural water outside the perimeter of the project site and could pollute the

natural system (Figure 7-1).

Dirty water catchment 1 was delineated according to natural topography as well as

manmade infrastructure. This catchment will drain all the water in that specific area

towards the specific collection point as proposed to the PCD. The proposed channels and

canals will form the pathways along which this dirty water will be routed towards the

collection point (PCD). All proposed dirty water infrastructure should be lined and designed

against a 1:50 year flood event. These areas are indicated in green on Figure 7-1.

Clean water sub-catchments are thus areas where natural clean rain water will drain freely

into the natural environment. These areas are indicated in blue on Figure 7-1.

Table 7-1 is representative of the clean and dirty water sub-catchment that were identified

and separated on Figure 7-1.

Table 7-1 Overview delineated catchments

Catchment Number Area (ha) Catchment Type Comment

1 8.9 Dirty Dirty Water runoff area from all plant and storage facilities

2 2.5 Clean Undisturbed veld type and virgin catchment


13-064 20 March 2013

7.2 Design floods

Potential flood peak flows for demarcated catchments were determined using the software

Utility Program for Drainage (UPD).

The UPD program was specifically designed and developed for South African conditions and

contains hydrological variables such as roughness coefficients (Manning’s values) and

rainfall records from available measuring stations from South Africa Weather Service

(SAWS).

A short description of the different methods to determine flood flows which were used in

this project is given below:

Rational Method

The rational method was developed in the mid-19th century and is one of the most widely

used methods for the calculation of peak flows for small catchments (< 15 km2). The

formula indicates that Q = CIA, where I is the rainfall intensity, A is the upstream runoff

area and C is the runoff coefficient. Q is the peak flow.

Alternative Rational Method

The alternative rational method is based on the rational method with the point

precipitation being adjusted to take into account local South African conditions.

Standard Design Flood Method

The standard design flood (SDF) method was developed specifically to address the

uncertainty in flood prediction under South African conditions (Alexander, 2002). The

runoff coefficient (C) is replaced by a calibrated value based on the subdivision of the

country into 26 regions or Water Management Areas (WMA’s). The design methodology is

slightly different and looks at the probability of a peak flood event occurring at any one of

a series of similarly sized catchments in a wider region, while other methods focus on point

probabilities.

Flood flows from 1:50 and 1:100 year rainfall storm events were calculated for the two

catchments which are affecting storm water infrastructure (paragraph 7.3). Calculations

were based on current conditions which represent virgin or disturbed conditions in the two

catchments.

Table 7-2 below summarises the peak floods calculated. All the runoff calculations are

shown in Appendix A.


13-064 20 March 2013

Table 7-2 Peak floods (1:50 year) calculated for the catchments contributing to storm water infrastructure

1: 50 Peak Flood (m3/s) Rational Method Alternative Rational Method Standard Design Flood Method

Catchment 1 1.24 1.06 1.15

Catchment 2 0.19 0.17 0.18

7.3 Proposed SWM measures on site The construction of a main PCD dam is proposed within the southwest part of the project

site at the lowest point of the project site. The purpose of this PCD will be to manage and

regulate all dirty water on site and to supply water to the RWD for the cement mill. The

final design for both dams should be done by a registered engineer.

The RWD could be constructed next to the PCD so that storm water runoff can be pumped

directly from the PCD to the RWD to supply the cement mill. No volume is calculated or

designed for the RWD, as this design would be dictated by operational philosophies, but a

conservative volume of 200m3 was used for the PCD size calculation in section 7.4.

Drains will link these collection points and regulate flow within the dirty water catchment

towards the proposed PCD. These drains will cause the entire plant site to function as a

closed system with water being pumped and re-used all the time.

GN704 requires that no infrastructure is placed within 100m of a river or within the 100year

flood lines of a watercourse. The project site area is not situated close to a watercourse

within these margins.

The implementation of the above proposed SWM measures and taking into account all

assumptions, together with the existing SWM measures should assure that the activities will

be operated under full compliance of the legal legislation.

The following is a short summary of the proposed SWM measures:

Create a PCD with sufficient size (4 500m3) in the southwest corner (GN704);



Construct a clean water drain/berm to direct clean water out of the project

site(C1);




13-064 20 March 2013




the PCD (E1 and E2).




13-064 20 March 2013

Figure 7-1: Conceptual SWMP


13-064 20 March 2013

7.4 Required PCD size

The proposed PCD must meet GN704 design criteria. To ensure that the proposed PCD in the

project area will not spill more than one time one average in 50 years, a water balance

model has been created in the software package Goldsim ®.

This water balance model is an adaptation of the water balance model from section 5 and is

incorporated into the proposed SWMP. The available data from the proposed Cement Slag

and Process Facility was evaluated and taken into account. Only the facilities and processes

which influence the size of the PCD were incorporated in the Goldsim Model.

7.4.1 Assumptions

The following assumptions were made to develop the water balance model in GoldSim and

to require the optimal PCD size:

Dirty Water Runoff (Road, Roofs etc.)

Monthly runoff data on the surface of this infrastructure were taken from WR2005

database (WRC, 2008) as describes and calculated in section 4;

RWD:

Monthly rain and evaporation data on the surface of this infrastructure were taken

from WR2005 database (WRC, 2008);

Volume of the RWD is assumed at a conservative rate of 200m3;

Average depth of the Return Water Dam is assumed at 1.5m;

Pump to Cement Mill is set at an abstraction rate of 14kl/d. This is based on

provided water requirement rates of 90% of the time 9.8kl/day and 10% of the time

48kl/day;

No overflow of the RWD is simulated.

Dust Suppression

Flow data for dust suppression of the slag storage was assumed at 16.8 kl/day from

the PCD or RWD depending on the water availability in both dams.

Raw Water Supply:

Pump is switched if RWD contains <75% of the volume of the RWD;

Maximum pump rate is assumed at 33kl/day.

Storm water runoff is first priority use


13-064 20 March 2013

PCD:

Monthly rain and evaporation data on the surface of this infrastructure were taken

from WR2005 database (WRC, 2008);

Volume of the PCD is calculated at 4 500m3;

Average depth of the PCD is 1.5m;

Pump to RWD is switched on if the PCD is >5% full and RWD < 85 % full;

Maximum pump rate from PCD to RWD to settling dam 1 is set at 200kl/day;

One spill in 85 years was modelled.

7.4.2 Results

Model results, shown in Figure 7-2 and Figure 7-3, of the water balance showed that a PCD

size of 4 500m3 seemed sufficient to simulate one spill in 85 years. The RWD did not spill

once in 85 years.

The PCD is filled up by dirty water runoff and used for water supply to the cement mill

through the RWD. This system can limit water consumption from raw water supply coming

from the municipality.

The required water amount for the cement mill is 5 070m3/year. The calculated long term

average water consumption is approximately 4 200m3/year. This implies the import of raw

water supply can be reduced with approximately 800m3/year.

Figure 7-2: Simulation of the volume of the PCD over 85 years


13-064 20 March 2013

Figure 7-3: Simulation of one spill of the PCD over 85 years

7.5 Conceptual design of infrastructure and drain capacities

All the locations of proposed additional drains and berms required to complete the (dirty

water) storm water management system are marked on Figure 7-1

Open drainage channels are necessary to divert dirty water to the PCD. This type of

drainage channel should be constructed with a smooth concrete lining to discharge dirty

runoff as fast as possible and to limit the size of the channels.

Design flow rates for 1:50 year storm-water inflow into concrete lined drains were

calculated. Assuming a fixed manning coefficient of 0.016 for a relatively smooth concrete

lining to drains, flow capacities can be designed using a simplified Manning formula of:

. Consider the typical drain cross-section as shown in (side slopes 3:4):

Where:

Q is flow ( m3/s)

d is the design depth (m)

s is the design slope (m/m) .


13-064 20 March 2013

Figure 7-4: Standard concrete lined drain design for dirty water with possible adjacent berm

Figure 7-5 Standard clean water drain with adjacent berm

In a similar way the clean water drains can be designed. Design flow rates for 1:50 year

storm-water inflow into earth channel drains were calculated. Assuming a fixed manning

coefficient of 0.025 for an excavated open drain with a gravel bed, flow capacities can be

designed using the adapted Manning formula of:

. Consider the typical drain

cross-section (side slopes 1:2) as shown in Figure 7-5 including an adjacent berm. Adjacent

berms should be designed with excavated soil from the drainage channel with similar side

slopes (1:2).

Berms are proposed to divert clean water away from dirty water areas or the other way

around (as indicated in Figure 7-1). The berms B1 and B2 should divert clean water to the

southwest and the southeast of the project site. The two berms D1 and D2 next to the dirty

water drains need to keep dirty water runoff within the project area. Berms F1 is situated

parallel to the railway line and is necessary to prevent spilling of dirty water into the clean

water catchment. All berms should be constructed with side slopes of 1:2.

All channels and berms should be designed by a Registered Engineer.


13-064 20 March 2013

8 CONCLUSIONS AND RECOMMENDATIONS




Hydrology was calculated for the project area based on quaternary catchment M30B. For

the entire Quaternary catchment M30B of 307 km2, Mean Annual Runoff of 4.95 million

cubic meters is expected. For a virgin catchment of 11.4 ha (site boundary) MAR is likely to

be in the order of 1840 m3. Runoff from areas which will now be considered dirty water

areas and where this water is now held on site, reducing the effective runoff of the larger

local river system represent a 0.033% reduction of flow in local river systems, which is

considered negligible.

The project area was divided into 2 catchments, which represent a clean and dirty water

area. Storm water management measures for each catchment were proposed on a

conceptual level.

Clean and dirty water measures need to improve my means of the following measures:

Create a PCD with sufficient size (4 500m3) in the southwest corner (GN704);



Construct a clean water drain/berm to direct clean water out of the project

site(C1);






the PCD (E1 and E2).



A water balance model was calculated to determine the size of the proposed PCD. Model

results of the water balance showed that a PCD size of 4 500m3 seemed sufficient to

simulate one spill in 85 years. The RWD did not spill once in 85 years. By pumping water

from the PCD to the RWD, import of raw water supply can be reduced with approximately

800m3/year.


13-064 20 March 2013

Should all the measures be followed, implemented, and maintained, the OSHO Ventures

Slag Storage and Cement Processing Facility will operate on a full legal compliance level.


13-064 20 March 2013

9 REFERENCES

Best Practical Guidelines G1, 2006.

GCS, 2013. Guidelines for small scale hydrological studies.

The South African National Roads Agency. (2007). Drainage Manual,5th edition. Pretoria.

Water Research Commission. (2008). Atlas of Climatology and Agrohydrology, 2008,Report

No. K5/1489.

Water Research Commission. (2008). Surface Water Resources of South Africa. WR2005

Report No. TT 382/08.


13-064 20 March 2013

APPENDIX A

Date

Size of catchment (A) 0.1

Longest watercourse (L) 0.3

Average slope (Sav) 0.0100 Rural (α) Urban (β) Lakes (γ)

Dolomite area (D%) 0 0 1 0

Mean annual rainfall(MAR) 440

% Factor Cs Description % Factor C2

0.00 0.03 0.00 Lawns

0.00 0.03 0.00

Sandy,flat<2

%67 0.075 5.025

0.00 0.08 0.00

Sandy,steep

>7%0 0.175 0

0.00 0.16 0.00

Heavy

s,flat<2%0 0.15 0

0.000.26 0.00

Heavy

s,steep>7%0 0.3 0

% Factor Cp

Residential

Areas

0 0.04 0.00 Houses 0 0.4 0

0 0.08 0.00 Flats 0 0.6 0

0 0.16 0.00 Industry

0 0.160.00

Light

industry0 0.65 0

0 0.440.00

Heavy

industry0 0.75 0

% Factor Cv Business

0 0.04 0.00 City centre 0 0.87 0

0 0.11 0.00 Suburban 0 0.6 0

0 0.21 0.00 Streets 33 0.87 28.71

0 0.28 0.00 Max flood 1

0 0.64 0.00 Total (C2) 100 33.735

0.429 hours hours

Return Period (years) 2 5 10 20 50 100 PMF

0.337 0.337

0.337 0.337

0.9 1

0.304 0.337

0.304 0.337


64.36 80.34

150.12 187.39

0.980 0.990

147.118 185.520


1.241 1.74

Point rainfall (mm), PT

Point Intensity (mm/h), P it

Area reduction factor (%),ARFT

Average intensity (mm/hour),IT

Peak flow (m3/s)

Rainfall

Use overland flow - r = 0.02 for paved areas and 0.2

for lawns

r=.16

Run-off coefficient

Run-off coefficient, C1

Adjusted for dolomitic areas, C1D

Adj factor for initial saturation, Ft

Adjusted run - off coefficient, C1T

Combined run - off coefficient, CT

Impermeable

Permeability

Very permeable

Overland flow Defined watercourse

Total

Vegetation

Thick bush & plantation

Light bush & farm-lands

Grasslands

No vegatation

Total

Time of concentration (TC)

Vleis and pans (<3%)

Flat areas (3 - 10%)

Hilly (10 - 30%)

Steep Areas (>30%)

Permeable

Total

Semi-permeable

Surface slope

Physical characteristics

km2 Rainfall region 2

km Area distribution factors

m/m

%

mm

Rural

Calculated by Kevin Scott 2013/03/18

RATIONAL METHODDescription of catchment Catchment nr 1.

River detail -

URBAN

385.02

1000

87.0

AV

cS

LT

467.0

604.0

av

CS

rLT


13-064 20 March 2013

Date

Size of catchment (A) 0.012


Average slope (Sav) 0.0100 Rural (α) Urban (β) Lakes (γ)

Dolomite area (D%) 0 0 1 0

Mean annual rainfall(MAR) 440

% Factor CsDescription % Factor C2

0.00 0.03 0.00 Lawns

0.00 0.03 0.00

Sandy,flat<2

%67 0.075 5.025

0.00 0.08 0.00

Sandy,steep

>7%0 0.175 0

0.00 0.16 0.00

Heavy

s,flat<2%0 0.15 0

0.000.26 0.00

Heavy

s,steep>7%0 0.3 0

% Factor Cp

Residential

Areas

0 0.04 0.00 Houses 0 0.4 0

0 0.08 0.00 Flats 0 0.6 0

0 0.16 0.00 Industry

0 0.160.00

Light

industry0 0.65 0

0 0.440.00

Heavy

industry0 0.75 0


0 0.04 0.00 City centre 0 0.87 0

0 0.11 0.00 Suburban 0 0.6 0

0 0.21 0.00 Streets 33 0.87 28.71

0 0.28 0.00 Max flood 1

0 0.64 0.00 Total (C2) 100 33.735

0.279 hours hours


0.337 0.337

0.337 0.337

0.9 1

0.304 0.337

0.304 0.337


52.50 65.50

187.85 234.37

0.980 0.990

184.097 232.027


0.186 0.261



km2 Rainfall region 2

RATIONAL METHODDescription of catchment Catchment nr 2.

River detail -

Rural URBAN

Surface slope


km Area distribution factors

m/m

%

mm

Very permeable

Permeable

Semi-permeable


Hilly (10 - 30%)

Steep Areas (>30%)

Total

Permeability


Grasslands

No vegatation

Total


Impermeable

Total

Vegetation


r=.16

Run-off coefficient




Use overland flow - r = 0.02 for paved areas and 0.2




Peak flow (m3/s)




Rainfall


385.02

1000

87.0

AV

cS

LT

467.0

604.0

av

CS

rLT


13-064 20 March 2013

Date

Size of catchment (A) 0.1 18 days


Average slope (Sav) 0.0100

Dolomite area (D%) 0

Mean annual rainfall(MAR) 440 Rural (α) Urban (β) Lakes (γ)

2-year return period rainfall (M) 53 0 1 0

% Factor Cs Description % Factor C2

0.00 0.03 0.00 Lawns

0.00 0.03 0.00

Sandy,flat<2

% 67.00 0.08 5.03

0.00 0.08 0.00

Sandy,steep>

7% 0.00 0.18 0.00

0.00 0.16 0.00

Heavy

s,flat<2% 0.00 0.15 0.00

0.000.00

Heavy

s,steep>7% 0.00 0.30 0.00

% Factor Cp

Residential

Areas

0.00 0.04 0.00 Houses 0.00 0.40 0.00

0.00 0.08 0.00 Flats 0.00 0.60 0.00

0.00 0.16 0.00 Industry

0.00 0.16 0.00Light industry

0.00 0.65 0.00

00.00

Heavy

industry 0.00 0.75 0.00


0 0.04 0.00 City centre 0.00 0.87 0.00

0 0.11 0.00 Suburban 0.00 0.60 0.00

0 0.21 0.00 Streets 33.00 0.87 28.71

0 0.28 0.00 Max flood 0.00 1.00 0.00

0 0.00 Total (C2) 100.00 33.74

hours


0.337 0.337

0.337 0.337

0.9 1

0.304 0.337

0.304 0.337


55.03 63.41

128.37 147.91

0.980 0.990

125.80 146.43


1.06 R 1.37Peak flow (m3/s)

Surface slope






Rainfall

Run-off coefficient






0.429

Impermeable

Total

Vegetation



Grasslands

No vegatation

Total


Very permeable

Permeable

Semi-permeable

Permeability


Hilly (10 - 30%)

Steep Areas (>30%)

Total


%

mm

Rural URBAN

Area distribution factors

mm


km2

Weather service number

km Weather service station Port Elizabeth

Days of thunder per year (R)

m/m


ALTERNATIVE RATIONAL METHODDescription of catchment Catchment nr 1.

River detail -

385.02

1000

87.0

AV

cS

LT

467.0

604.0

av

CS

rLT


13-064 20 March 2013

Date




Dolomite area (D%) 0

Mean annual rainfall(MAR) 440 Rural (α) Urban (β) Lakes (γ)

2-year return period rainfall (M) 53 0 1 0

% Factor CsDescription % Factor C2

0.00 0.03 0.00 Lawns

0.00 0.03 0.00

Sandy,flat<2

% 67.00 0.08 5.03

0.00 0.08 0.00

Sandy,steep>

7% 0.00 0.18 0.00

0.00 0.16 0.00

Heavy

s,flat<2% 0.00 0.15 0.00

0.000.00

Heavy

s,steep>7% 0.00 0.30 0.00

% Factor Cp

Residential

Areas

0.00 0.04 0.00 Houses 0.00 0.40 0.00

0.00 0.08 0.00 Flats 0.00 0.60 0.00

0.00 0.16 0.00 Industry

0.00 0.16 0.00Light industry

0.00 0.65 0.00

00.00

Heavy

industry 0.00 0.75 0.00


0 0.04 0.00 City centre 0.00 0.87 0.00

0 0.11 0.00 Suburban 0.00 0.60 0.00

0 0.21 0.00 Streets 33.00 0.87 28.71

0 0.28 0.00 Max flood 0.00 1.00 0.00

0 0.00 Total (C2) 100.00 33.74

hours


0.337 0.337

0.337 0.337

0.9 1

0.304 0.337

0.304 0.337


46.74 53.86

167.25 192.72

0.980 0.990

163.91 190.79


0.17 0.214543


Peak flow (m3/s)


Rainfall




Run-off coefficient





0.279





Grasslands

No vegatation

Total

Semi-permeable

Impermeable

Total

Vegetation

Total

Permeability

Very permeable

Permeable



Hilly (10 - 30%)

Steep Areas (>30%)

mm

mm

Rural URBAN

Surface slope

m/m Weather service number

% Area distribution factors


km2 Days of thunder per year (R)

km Weather service station Port Elizabeth

River detail -


ALTERNATIVE RATIONAL METHODDescription of catchment Catchment nr 2.


13-064 20 March 2013

Date


Longest watercourse (L) 0.3 25.723 minutes


SDF Basin

2-year return period rainfall (M) 53

Weather Service Station MAP 440 mm

Weather Service Station no. Coordinates

2 5 10 20 50 100 200

1 day 147.5 184.1

2 days

3 days

7 days

Return Period (years), T 2 5 10 20 50 100 200

55.0345 63.4136

1.0000 1.0000

128.3686 147.9129

Calibration factors C2 (%)


0 0.84 1.28 1.64 2.05 2.33 2.58

0.323318734 0.333333

1.15 1.37Peak flow (m3/s)

TR102 n-day rainfall data

Duration

Return Period (years)

Port Elizabeth

0 29o43' (Lat) & 31o04' (Long)

Rainfall


Point precipitation depth (mm) Pt,T


Run-off coefficient

25 C100 (%) 33.3333

Run-off coefficient, CT

Return period factors (YT)


km2 Days of thunder per year (R)

km Time of concentration, t

mm

Time of

concentration

, Tc 0.4287

m/m

20


STANDARD DESIGN FLOOD METHODDescription of catchment Catchment nr 1.

River detail -

467.0

604.0

av

CS

rLT

Date


Longest watercourse (L) 0.12 16.768 minutes


SDF Basin

2-year return period rainfall (M) 53

Weather Service Station MAP 440 mm

Weather Service Station no. Coordinates

2 5 10 20 50 100 200

1 day 147.5 184.1

2 days

3 days

7 days


46.7424 53.8590

1.0000 1.0000

167.2523 192.7167

Calibration factors C2 (%)


0 0.84 1.28 1.64 2.05 2.33 2.58

0.323318734 0.333333

0.18 0.21Peak flow (m3/s)

Run-off coefficient

25 C100 (%) 33.3333

Run-off coefficient, CT

Description of catchment Catchment nr 2.

-

Kevin Scott 2013/03/18


Days of thunder per year (R)

km Time of concentration, t

Time of

concentration

, Tc 0.2795mm

TR102 n-day rainfall data

Port Elizabeth

0

Rainfall

Return period factors (YT)

Point precipitation depth (mm) Pt,T



29o43' (Lat) & 31o04' (Long)

Duration

Return Period (years)

km2

m/m

20

STANDARD DESIGN FLOOD METHOD

River detail

Calculated by

467.0

604.0

av

CS

rLT

storm water management plan for osho ventures slag …projects.gibb.co.za/portals/3/2013-03-16 rv...

Documents