MULTIPLE DISTRICT ASSESSMENT OF WATER SAFTEY (MDAWS) IN DARRANG

DISTRICT, ASSAM

Conducted by

DEPARTMENT OF PUBLIC HEALTH ENGINEERING

GOVT. OF ASSAM

The MDAWS – ASSAM Team

MDAWS Advisor:Dr. C. MahantaAssociate ProfessorDepartment of Civil EngineeringIndian Institute of Technology, GuwahatiAssam.

Assisted by Research Scholars from IIT Guwahati:

L.Sailo, PhD ScholarS. Mondal, PhD Scholar

UNICEF Co-ordinator:

Dr. Somnath Basu Project Officer, Water Environment and Sanitation

MDAWS PHED Team:

Team Leader: Kamal Medhi Asst. Executive Engg., PHEDDarrang.

State Level Water Quality Expert cum Master Trainer:

Nripendra Kr Sarma,Asst. Engg., PHEDCommunication and Sanitation Cell, PHED

State Level Data Analyst:

Dr. Annie Duarrah KotokiAsst. Chemist, H.Q. PHED

Survey Leader A: Shorab Ali,Asst. Engg., PHEDDarrang

Survey Leader B:Rajat SarmaJr. Engg., PHEDDarrang

MULTIPLE DISTRICT ASSESSMENT OF WATER SAFTEY (MDAWS) IN DARRANG DISTRICT, ASSAM

1 INTRODUCTION

The Darrang district is located in central Assam, on the northern bank of river Brahmaputra. The district in general is constituted of plain areas dotted by small hillocks. The climate of the district is congenial, variable with distinct seasonal changes. The average temperature during summer and winter ranges from 10ºC to 30ºC respectively. The elevation of Darrang district varies from 50 meters to 250 meters above mean sea level. There is a constant slope from north to south. The central belt of the district is at 50 – 100 meters and covers 40 % of the districts. To the south, this elevation gets further reduced, the Brahmaputra flood plains maintaining a level of 10 - 50 meters. The main tributaries of Brahmaputra in this district are Barnadi, Nowanai and Mangaldai.

Since the north is at high level and hilly, and southern part is low & plain, the district was divided into 3 belts with respect to groundwater potential. The thin north belt has a potential of 5 – 10 liter/sec, while major central belt maintains a range of 10 – 25 liters/sec, the south belt enjoys a generous 25 – 40 liters/sec.

The geology of Darrang can be divided into low-lying plains, covered plains and hills. Gneissic rocks form most part of the hills, which are excellent sources for building stones. The plain is of alluvial origin and consists of sand and clay in varying proportion. The northern border is covered by newer alluvium, accompanied by another thin belt of older alluvium. The landuse pattern of Darrang is shown in Fig 1.

The soil of this district is fertile for cultivation and the main crops are paddy, oilseeds, sugarcane and jute. The district is rich with sizeable production of vegetables. Darrang is well connected with a network of road transport system. The nearest airport is at Guwahati known as Gopinath Bardoloi International Airport which is 70km west of Mangaldai.

1.1 Key Features of Darrang District

The district is situated in the central part of Assam and on the northern side of the river Brahmaputra. Udalguri District is located to the North. The River Brahmaputra flows in the South. The districts Sonitpur and Kamrup are in the East and West respectively. The various features of Darrang districts are mentioned below:

1 (a)

1 (b)

Figure 1. (a) Location map of Darrang district. (b) Land use pattern of Darrang district

Latitude – Longitude 20º 9' N to 26º 95’ N and 91º 45’ E to 92º 22’ E

Distance from state capital 70 km.

Climate Humid and congenial.

Relative humidity 60% to 85%

Annual Rainfall 1500 mm to 2600 mm.

Geographical area 1421 sq.km. Forest Area 804 hectares.

Total Population 7, 53,269 souls. (As per 2001 census)

Male 3, 88,789 souls.

Female 3, 64,480 souls.

SC 36,005 souls.

ST 09, 788 souls.

Urban population 41,703 souls.

Rural population 7, 11,566 souls.

Percentage of Rural population 94.46%

Percentage of SC population 4.77%

Percentage of ST population 1.29%

Literacy 54%

Population density per sq. km. 530 souls.

No. of Parliamentary Constituency 1

No. of Assembly Constituency 4

No. of Development Blocks 7

No. of Anchalik Panchayat 7

No. of Gram Panchayat 79

No. of Revenue Circle 5

No. of Revenue Villages 533

No. of Police station 4

No. of Notified Town 4

The M-DAWS Programme:

To implement the M-DAWS programme in Darrang district, Assam, different steps were adopted, as briefly highlighted in this report under the following heads:

1 INTRODUCTION1.1 Key features of Darrang District.1.2 Project area identification.1.3 Preliminary survey.1.4 Exposure training.1.5 Status survey.1.6 Orientation training.1.7 Formulation of team.2 METHODOLOGY2.1 Water Sampling.2.2 Sample Analysis2.3 Data Entry.3 RESULTS3.1 pH3.2 Temperature3.3 Water Table Depth3.4 Electrical Conductivity3.5 Turbidity3.6 Risk Factors.3.7 Fluoride3.8 Nitrate3.9 Iron3.10 Faecal Coliform and Faecal Streptococci4 MAJOR OBSERVATIONS5 CONCLUSIONS

1.2 Project Area

Darrang was identified as the project district by UNICEF to implement the M-DAWS program considering its geographical location, climatic conditions and other representative factors.

1.3 Preliminary Survey

UNICEF officials with representative from IIT Guwahati visited Darrang district along with PHED officials and conducted preliminary survey to have an overview of the district. This has facilitated in planning and implementation of the M-DAWS program in the Darrang district.

1.4 Exposure Training

The first training for the MDAWS program in the Darrang district was attended by three officials from PHED Darrang and one from Chief Engineer, Sanitation which was held in Bhopal during January 2007.

A four days workshop cum training program was organized in Mangaldai during 1st and 4th February, 2007. Prof Chandan Mahanta (IITG), Er. Kamal Medhi, Er. Nripendra Kr. Sarma and two research scholars from IITG L.Sailo and Sandip Mondal conducted necessary training in the workshop. Participants were given demonstration on field data collection and sample analysis along with dry runs. The workshop was attended by Darrang PHED officials, Chemists and the departmental persons who were selected to take part in the M-DAWS program. During this training, demonstration of the use of various instruments was also shown and hands-on experiments were also conducted in order to have a better exposure to the instruments. On the last day of the training program a field visit was organized, where the participants went to the sites to collect samples and analyze them as per instructions given. The workshop also aimed at generating the organizational structure and coordination of all personnel working in rural water supply wing for successful implementation of the M-DAWS program in the district.

Figure 2 (a). Dr Chandan Mahanta (IITG) and Er Kamal Medhi demonstrating the use of various instruments to the participants.

Figure 2(b). Secretary PHED interacting with the MDAWS personnel in Darrang PHED laboratory.

Figure 2 (c). MDAWS trainees with Dr Ross Nickson (UNICEF), Dr Chandan Mahanta (IITG) and Er. Nripendra Kr Sarma.

1.5 Status Survey

The status survey on rural water supply was carried out in the entire district for the identification of the different types of sources, sampling villages, data potential. The location and the administrative units of the water supply system were also recorded.

Figure 3 (a). Dr Ross Nickson (UNICEF) and Dr Chandan Mahanta (IITG) interact with the participants in the feedback workshop held at Mangaldoi.

Figure 3 (b). Dr Chandan Mahanta (IITG) briefing Dr Ross Nickson on the progress of the MDAWS program.

Darrang district consists of 7 developmental blocks. The district is divided into 79 Gram Panchayats each of which has a public representative body to take up public welfare plan in grass root level.

To implement M-DAWS program, the district have been divided into 4 broad areas. The Geographical location and the socio-economic conditions of the inhabitants of Darrang were taken into consideration while forming these broad areas. The classification is shown below in Table 1. Based on the distribution, a cluster analysis was carried out by Er. Nripendra Kr Sarma and others from PHED to identify the sampling points.

Table 1. Classification of 4 Broad Areas and Gram Panchayats

UNIT BROAD AREA (1)

BROAD AREA (2)

BROAD AREA (3)

BROAD AREA (4)

BLOCK NAME

Pachim Mangaldai & Pub Mangaldai,

Sipajhar Kalaigaon & Khairabari

Bechimari & Dalgaon Sialmari

BLOCK NAME

Flood prone areas. River Brahmaputra flows nearby

Socio-Economic condition of the inhabitant is better. Educationally forward.

Mostly tribal persons reside in this area. Agricultural land predominant.

Literally backward. Mostly immigrant people dominant in the area.

S.No. BROAD AREA (1) Villages

BROAD AREA (2) Villages

BROAD AREA (3) Villages

BROAD AREA (4) Villages

1 Balabari Danhi Shyamtila Borjhar

2 Bhakatpara Jaljali Rajapukhuri Dalgaon

3 Dhula Sipajhar Tengabari Charabati Khairakata

4 Ondolaghar Sarabari Outala Lalpool

5 Chaulkhowa Deomornoi Bhurargarh Daipam

6 Puthimari Barampur Lakhimpur Baligaon

7 Mowamari Garukhuti Kalitapara Bechimari

8 Bandia Bardaulguri Bhuyakhat No. 5 Baruajhar

9 Abhaipukhuri Byaspara Borkala Kopati

10 Khataniapara Lokrai Jhargaon Golandi

11 Ojagaon Hazarikapara Nam-khola 1 & 2 Baruajhar

12 Chamuapara Dumnichowki Kuhiarkuchi Bihudia

13 Chapai Devananda Kalyan

14 Nagarbahi Ghorabandha Shyampur

15 Ramhari Burhinanagar Khajubil

16 Upahupara Baznapathar Silbari

17 Danhi Kuruah Fakirpara

18 Jaljali Maroi

19 Aulachawka Sanowa

20 Rangamati Ganeshkuwari

21 Janaram chowka Burha

22 Rowmari Patharighat

23 Boumajha

24 Chengaliajhar

25 Tura

26 Dunee

27 Dipila

1.6 Formulation of Teams

Based on the PHE subdivision jurisdiction of Darrang district, three teams of field engineers and helpers and analysts were formed for the four broad areas. The teams’ composition for M-DAWS is shown in Fig 4. To carry out the programme, the team led by Prof. C. Mahanta from IIT-Guwahati provided complete technical support for the entire work while UNICEF, Guwahati co-ordinated the work in every step.

1.7 Duties and Responsibilities

Team Leader: Preparation of project proposal, planning, provide transport, material for survey with sanitary survey forms to conduct M-DAWS smoothly. He was also responsible to arrange the methodology of handing over the samples to the laboratory in stipulated time.

Team Members: The AE and JE’s duty was to collect GPS reading correctly, and fill up the SI Form on every sample collection point. The Program Co-coordinator and Asstt. Program Co-coordinators were responsible for sample collection for chemical and bacteriological parameters, flow rate, field test results of pH, turbidity and H2S vial measuring water table depth with the help of helpers of their team.

The sample size, cluster size with respect to the technology provided and selection of sampling units have been carried out based on the statistical methodology as described in M-DAWS Training program manual and as demonstrated at the Bhopal, workshop.

Figure 4. Formulation of teams in the Broad Areas

TEAM LEADER

TEAM 1(Broad Area I & II)Asst. EngineerPr Co-coordinatorSector Asst.-2 Nos.Helper - 4 No.

TEAM 2(Broad Area II)Asst. EngineerJr. Engineer Pr Co-coordinatorSector Asst.-2 no Helper - 4 no.

TEAM 3(Broad Area III & distant point from D.L.L.)Asst. EngineerSector Asst.-1 noHelper-2 no.

2 METHODOLOGY

Specific methodology as provided in the guidelines, was followed for the sampling of 400 samples, which was calculated by statistical method i.e. cluster analysis. The sampling methods and analysis are briefly discussed below:

2.1 Water Sampling

Water samples were collected after pumping the water for 5 minutes so that stagnant water is removed from the pipe mains and the water collected is the fresh water flowing from the aquifers into the wells. The mouth of the tube-well was sterilized by burning with lighter before the samples were collected. The measurement of EC, pH, Temperature was done using the field kit on the site itself. The depth of water was measure using Dipper. All other relevant information was also collected along with the sanitary inspection survey. The location of the tube-wells and pipe water distribution system was recorded with handheld GPS.

5 (a) 5 (b)

Figure 5(a) Er. Kamal Medhi inspecting the water sample collection procedure in the field. 5 (b) Water samples collected were coded and labeled according to the guidelines provided.

2.2 Sample Analysis

The water samples collected were analyzed for its chemical concentrations and bacteriological counts in the district laboratory of PHED (Darrang). Wagtech portable laboratory and kit were used for the measurement of physical conditions, chemical concentrations and bacteriological counts of water samples. Wagtech portable pH meter, Conductivity meter with a provision for recording temperature, turbidity meter was used for analysis. Digital Photometer of Wagtech with color comparator was used for analysis of various chemical parameters. Potakit was used for the analysis of bacteriological

counts, the petridishes, broth and incubator with a temperature switch between 37˚C and 44˚C allow the incubation of either faecal coliform or faecal streptococci.

Figure 6. Laboratory technician counting a faecal Coliform and faecal Streptococci from the petridish of Potakit instrument.

2.3 Data Entry

During this MDAWS program a total of 400 samples were collected from different sampling points and subsequently analysed. The accurate location of each of the sampling points was recorded with the help of GPS provided. The sampling bottles were coded as per the specified code. The analyses of the samples were carried out in the laboratory of PHED (Darrang). The experimental results were than fed on to the SANMAN software according to the WSS code. The results were exported in an excel sheet, which is used for the generation of data attribute table for the GIS and performing a statistical analysis on various parameter, risk etc.

Figure 7. Dr Chandan Mahanta (IITG) giving instructions to the computer operator on the data entry into the SANMAN software.

3 RESULTS

The water samples from 400 sources were analyzed for physical, chemical and microbiological contamination. The various physical parameters viz. pH, Electrical Conductivity, Turbidity, Color, Appearance and the chemical parameter including total Chlorine, Nitrate, Iron, Fluoride, H2S and the bacteriological test was done on Faecal Coliform and Faecal Streptococci. Additional parameter Hydrogen Sulfide (H2S) and Depth of Water Table was found and their values entered in user fields of the SANMAN software.

The sources of the 400 water samples that have been collected in Darrang varies viz. hand pump sources (both from public and private), Ring well, Piped water supply schemes stand post. The location and the number of the sampling points were estimated using clustered analysis i.e. statistical methodology covering four broad areas.

A digitized map with point locations of all the 400 wells was prepared as a base map for a geo-spatial GIS database. The base map is shown in Fig 8. The entire data base has been converted to the GIS mode.

Figure 8. Darrang District map with sampling points plotted with the help of ARCINFO GIS software

The various physical, chemical and bacteriological analyses done on 400 samples are reported below:

3.1 pH

The values of pH in the area varied from 5.8 to 8.5 i.e. slightly acidic to alkaline with a mean value of 7.1. It shows that pH do not possess a threat i.e. (<8.5) as the pH between 6.5 and 7.5 are considered as good for drinking water quality.

3.2 Temperature

The temperature of the water samples did not show much variation, the values ranging from 21.5˚C to 23 ˚C. 3.3 Water Table Depth

The depth of water table in 400 samples was ascertained to be shallow, as the maximum depth was 25 m below the ground level and a minimum of 0.6 m. The average value was 3.5 m, which is shallow, thus the wells are susceptible to contamination due to surface pollution sources.

3.4 Electrical Conductivity (EC)

The values of EC were highly varying with a maximum of 1124 μmhos/cm and minimum value of 67 μmhos/cm. The average EC was found to be 220 μmhos/cm. Electrical conductivity measure the capacity of substance or solution to conduct electrical current. Higher EC corresponds with higher increase in the total dissolved solids.

3.5 Turbidity

The measured turbidity also highly varied with a minimum of 0.25 NTU to maximum of 200 NTU. Out of total 400 samples analyzed, 137 samples were having turbidity greater than 10 NTU, thus 32 % of the water samples are turbid. As turbidity is caused by suspended and colloidal maters such as clay, silts, finely divided organic and inorganic matters, such factors are suspected to be present.

3.6 Risk Factor

The risk factor was calculated from the questionnaire having ten R’s in which each has a weight of 10, thus making 100% for all positive R. As the sources of the sample varies, the calculated risk was also categorized according to the sources viz. borewell hand-pump(BHHAND), dug well hand pump (DWHAND) and piped-water distribution system (PWDS).

From total 400 samples collected, bore-well hand pumps comprised of 305 samples, dug-well hand-pump 47 in numbers and 48 numbers of piped-water distribution system were covered. It was found that 192 bore-well hand pumps were having a risk greater or equal to 50, this value corresponds to 63 % of the total bore-well tested was having a risk of contamination. And 39 samples of Dug-well hand pumps was also a risk greater than or equal to 50, which makes up to 83 % of the well having risk of contaminations from various sources. All the piped water distribution systems were having a risk lower than 50. The statistics has been shown in bar chart in Fig 9.

0102030405060708090

100

BHHAND DWHAND PWDS

Type of source

% e

xceed

ing

50 r

isk

Figure 9. Percentage exceeding 50 Risk for the three type of sources.

3.7 Fluoride

From the analysis, the concentration of fluoride was found to be generally low, and in most of the sampling points having concentration below target level of 0.8-1.2 mg/l set by the WHO guidelines to the minimization of harmful effects and maximization of benefits.

3.8 Nitrate

Nitrate (NO3) concentration in Darrang district was generally low. The experimental analysis shows that many of the samples were below detection level in the wagtech photometer. The minimum and maximum nitrate concentration was 0 and 9.34 mg/l. The average value being 0.24 mg/l shows that low nitrate in the region. Thus, the influence of agricultural fertilizers, manures, septic systems and other nitrogenous sources was found to be insignificant.

3.9 Iron

The concentration of Iron has a significant impact over the whole area. As the value as high as 43 mg/l was found, the average iron concentration was 6.5 mg/l. But the standard deviation is 7.3 which suggest a great variation in the concentration of iron in Darrang. The hotspots iron concentration may be due to the presence of iron minerals or rusts on

the pipe mains of the tube-wells. The dissolution of these iron bearing minerals at lower redox level due to the alluvial deposit having higher organic contents may become the source of iron in the groundwater.

3.10 Faecal Coliform and Faecal Streptococci

The presence of Faecal Coliform and Faecal Streptococci bacteria in groundwater indicates the contamination of the water with faeces of human and animal waste. The results of the Faecal Coliform in drinking water should be zero. But the results showed high variation of FC count with values ranging from zero to as high as 400 cfu/100 ml. From the experimental analysis it was found that 4.5% of the samples having FC counts in 100 cfu/100 ml (>100 but <1000) and 12 % of samples have FC counts in 10 cfu/100 ml (>10 but <100). The FS counts also shows high values compared to the general guidelines of drinking water. The FS count varies from as low as zero to as high as 1000. Of 400 samples tested 21.75 % of the samples have FS counts in 100 cfu/100 ml (>100 but <1000) and 61.25 % FS counts in 10 cfu/100 ml (>10 but <100), this has been shown in Fig 10.

The risks of being infected with pathogenic bacteria correlates with the amount of the FC counts and FS counts and the amount of water consumed. Higher concentration of Faecal Coliform indicates higher risk of contracting waterborne diseases. The possible reasons for high values may be due to contamination from pipe breaks and bursts, infiltration or seepage from a contaminated source, sewage from groundwater sources, contamination from pit latrines/septic tanks, rubbish and faecal matter around standpipes.

0102030405060708090

100

> 10 > 100

Bacterial Counts

% o

f sam

ple

s

FC Counts

FS Counts

Figure 10. Percentage of sample exceeding 10 and 100 FC counts and FS counts

4 MAJOR OBSERVATIONS

The results of analysis of 400 samples shows that 63 % of bore-well hand pumps and 83 % of dug-well hand pumps having risks score greater than or equal to 50, thus revealing

the risk of contamination very high on these areas. The main factors for the higher risks in the area were attributed to improper drainage system of waste water from drinking water sources, damaged platform thus allowing seepage of waste water into the bore well through breakage point and in water logged area and septic tanks situated in close vicinity, bathing and washing of clothes/domestic vessels near the drinking water sources.

The distribution of the Faecal Coliform (FC), Faecal Streptococci (FS), Arsenic and Iron suggested that the FC and FS counts are distributed in a hotspot places where the various reasons cited above conform. But the distributions of iron in the plain areas away from the foothill region suggest dissolution of iron minerals and ore via oxidation and reduction reaction or other geochemical processes. Similarly, the distribution of Arsenic in the area also required further investigation to ascertain the possible sources.

The plot of percentage confidence with various parameters is shown in Fig 11. It can be inferred from the plot that FC counts vs risk shows 95% and FS counts vs risk 50% which are high. So the main sources of Risk mentioned above are also the possible sources of higher contamination of the samples with Faecal coliform and Feacal Streptococci.

A very high strength of association was noticed from plot of H2S vs Iron which was 98%. The reasons attributed to the results are contamination from septic sources from human and animal wastes, waste water, decomposed organic matter, thus leading to higher reducing conditions. This reduced conditioned may lead to the dissolution of iron from minerals bearing iron, thus becoming a sources of iron in these areas.

0

10

20

30

40

50

60

70

80

90

100

FC

vs

TU

RB

IDIT

Y

FS

vs

TU

RB

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vs

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K

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vs

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NIT

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TE

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IDIT

Y v

sR

ISK

H2S

vs

TU

RB

IDIT

Y

NIT

RA

TE

vs

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Fe

vs H

2S

Figure 11. Percentage Confidence level Vs parameters.

To minimize the risk factor as well as bacteriological contamination, remedial measures such as engineering intervention, IEC and Environmental intervention have been suggested.

4 CONCLUSIONS

The study demonstrates the effective utility of Multi-District Assessment of Water Safety (M-DAWS), and the creation of water quality data base maps showing anticipated levels of physical, chemical and bacteriological contamination of rural water supply, which will be highly useful in the implementation of National Rural Drinking Water Quality Monitoring and Surveillance Programme. The datasets along with the generated maps from M-DAWS will help to plan the different water quality and sanitation policy development in the state at GP, Block or District levels to optimize water quality monitoring and remediation programmes to be undertaken.