STRIVER Deliverable D7.1 Part 1

DELIVERABLE D7.1

Part 1

Scientific report on pollution source assessment, including

source apportionment results and pollution prevention measures

STRIVER Deliverable D7.1 Part 1

Strategy and methodology for improved IWRM - An integrated interdisciplinary assessment in four twinning river basins Title: Scientific report on pollution source assessment, including source apportionment results, and pollution prevention measures Author(s) Fazi S., Lo Porto A. (eds). Contributions by: Line J. Barkved (NIVA), Antonio Lo Porto (IRSA), Stefano Fazi (IRSA), K.V. Raju (ISEC), N. Latha (ISEC), S. Manasi (ISEC), Johannes Deelstra (Bioforsk), Haakon Thaulow (NIVA), Suhas Paranjape (SOPPECOM), K.J. Joy (SOPPECOM) Report No. STRIVER Report No. D 7.1, Part 1 ISBN - Organisation name of lead contractor for this deliverable: Istituto di Ricerca sulle Acque, Consiglio Nazionale delle Ricerche (IRSA) No. of pages: 104 p. Due date of deliverable: July 2008 Actual date of deliverable: June 2009 Dissemination level: PU Key words: nutrient pollution, Glomma, Tungabhadra, modelling

Title of project: Strategy and methodology for improved IWRM - An integrated interdisciplinary assessment in four twinning river basins (STRIVER) Instrument: SUSTDEV-2005-3.II.3.6: Twinning European/third countries river basins. Contract number: 037141

Start date of project: July 2006 Duration: 36 months

Project co-funded by the European Commission within the Sixth Framework Programme (2002-2006)

Disclaimer The information provided and the opinions given in this publication are not necessarily those of the authors or the EC. The authors and publisher assume no liability for any loss resulting from the use of this report. STRIVER Deliverable D7.1 Part 1

1. Summary ...... 5 2. Pressures: qualitative analyses on pollution source and main issues in Tungabhadra ..... 7 2.1 Tungabhadra ...... 7 2.2 Land use ...... 8 2.3 Pollution sources ...... 9 2.3.1 Agriculture ...... 9 2.3.2 Industrial Activities ...... 11 2.3.3 Urban Settlements ...... 15 2.4 Pressures on groundwater ...... 17 2.5 Conclusion ...... 22 2.6 Literature ...... 22 3. Pressures: qualitative analyses on pollution source and main issues in Glomma (Hunnselva and Lena) ...... 23 3.1 Glomma River Basin ...... 23 3.2 The Hunnselva and Lena sub-basins ...... 26 3.3 Physical description of Hunnselva and Lena sub-basins ...... 26 3.3.1 Climate and Climatological data ...... 26 3.3.2 Land use and soil physical characteristics ...... 31 3.4 Pollution sources in Hunnselva and Lena ...... 33 3.4.1 Agriculture ...... 34 3.4.2 Industrial Activities and Urban settlements ...... 36 3.5 Literature ...... 37 4. Impacts: water quality analysis in Tungabadhra ...... 38 4.1 Introduction: Stakeholder perceptions of the problems ...... 38 4.2 Monitoring of water quality and related environmental data ...... 38 4.3 Analyses of the water quality levels, trends, spatial and temporal variability ...... 40 4.3.1 Prescribed Standards ...... 40 4.3.2 Pollution hotspots identified by the CPCB ...... 41 4.3.3 pH Values, Dissolved Oxygen and Biological Oxygen Demand ...... 42 4.4 Faecal and Total Coliform and Nitrogen values ...... 44 4.4.1 Faecal and Total Coliform ...... 44 4.4.2 Nitrogen and nutrient ...... 45 4.5 The IWMI study on environmental flows ...... 47 4.6 Impact on fish ...... 49 4.7 Response from civil society and state ...... 50 4.8 Conclusion ...... 51 4.9 Literature ...... 52 5. Impacts: water quality analysis in Glomma (Hunnselva and Lena) ...... 53 5.1 Water Quality issues in Mjøsa and Hunnselva/Lenaelva...... 53 5.1.1 Lake Mjøsa – excessive eutrophication combatted ...... 53 5.1.2 Hunnselva ...... 54

STRIVER Deliverable D7.1 Part 1

5.2 Monitoring of water flow, water quality and related environmental data ...... 55 5.2.1 Water flow ...... 56 5.2.2 Runoff generation ...... 57 5.2.3 Hydrological characteristics ...... 58 5.3 Analyses of the water quality levels, trends, spatial and temporal variability ...... 60 5.4 Literature ...... 65 Annex to Chapter 2 ...... 66 Annex to Chapter 3 ...... 76 Annex to Chapter 4 ...... 83

STRIVER Deliverable D7.1 Part 1

1. Summary

The main objective in this Work Package 7 (WP7) of STRIVER is to analyse the possibilities for mutual transfer of know-how (e.g. experiences, concepts, results) and technology (e.g., methodologies, models) with regard to IWRM in general, and water pollution in particular, between the twinned basins Tungabhadra in and Glomma in Norway (Figure 1-1). The main aim is to develop strategies towards improved methodology to quantify and analyse water pollution as part of an integrated framework consisting of different water and land use needs and users. Part of the methodology included the application of two simulation models (SWAT and TEOTIL), in the basins, both to quantify present sources of pollution and use them in quantifying scenarios concerning different BMP strategies.

Part 1 of the Deliverable 7.1 includes an assessment of relevant data concerning basin characteristics and pollution including:  analyses of the water quality levels, trends, spatial and temporal variability and river basin characteristics  knowledge base assessment and qualitative uncertainty analyses on pollution source contributions from the competing water uses (e.g., allocation and distribution)  assessment of monitoring programmes and related environmental data  analysis of differences and similarities between the twinning basins

Part 2 of the Deliverable 7.1 deals with the pollution modelling activities within the two basins. Special attention is given to model parameterisation base line simulation and the interaction between modellers and stakeholders in the respective basins, especially concerning scenario development. Part 2 should be seen in connection with Part 1 regarding basin description and data issues.

To reach these objectives, several data were required. These data were identified in WP2 and WP3 of the project and collected during the first phase of the implementation of WP7. For data on Tungabhadra different National and Regional institutions were contacted and visited (E.g. Pollution Control Board, State Remote Sensing Agency, Regional Center for Remote Sensing). Data included: chemical and biological quality of available water resources (actual situation, seasonal changes, trends); water allocation and priorities, water resources needs and quality constrains for optimum performance in the different sectors and expected future needs; data on political priorities and plans. For data of Glomma and particularly the Hunnselva and Lena sub-basins, data were collected from NIVA and Bioforsk work, the State Pollution Control Authority (SFT) , the Norwegian Water Resources and Energy Directorate ( NVE), the county authorities on agriculture and environment and finally from the local municipalities (Gjøvik, Vestre and Østre Toten )

On the basis of 1) the data examined, 2) the discussions held during the STRIVER meetings, 3) the output of the STRIVER multi-stakeholder workshops, and 4) additional documents the major problems, affecting water quality in the two study catchments are highlighted. For the Tungabhadra catchment, a useful source of information was also constituted by a report by the Central Pollution Control Board (Indian Ministry of Environment & Forests) on water quality management and monitoring.

Key water quality problems in the two study catchments Glomma Tungabhadra Eutrphopication in Rivers and lakes Industrial pollution Impact from diffuse pollution Mining activities Impact from urbanization Sediment pollution Agricultural pollution Urban discharge

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Figure 1-1 Location of the Glomma (Norway) and Tungabhadra (India) river basins.

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2. Pressures: qualitative analyses on pollution source and main issues in Tungabhadra

K.V. Raju, N. Latha, S. Manasi (ISEC)

2.1 Tungabhadra The is a tributary to the Krishna, which finally flows into the Bay of Bengal. Tungabhadra is the largest tributary of the river Krishna, contributing an annual discharge of 14 700 million m3 at its confluence point to the main river. The river is formed north of in state of India, by the union of twin rivers, the Tunga and the Bhadra, which rise together in the Western Ghats at an elevation of about 1 200 metres. The emerges from the hills surrounding Varaha Parvata, at a place called Ganga Mula. The river flows through seven districts in Karnataka - Chikmagalur, Shimoga, Davanagere, , , Bellary and . The river has a dam built across it at Gajanur. After traversing a distance of 147 km long merges with the at at about 610 m above MSL, a small town near Shimoga, Karnataka. Tungabhadra Dam was built across the Tungabhadra river after it traverses 265 km from the origin in western ghats. Then the river merges with the Krishna river in Andhra Pradesh state near Kurnool. It has a drainage area of 71 417 km2 out of which 57 671 km2 lies in Karnataka State, after flowing for a distance of 293 km and the remaining part in the state of Andhra Pradesh.

The sub-basin is mostly rainfed, dominated by red soils and the average annual rainfall is 1200 mm. The major crops grown are paddy, jowar, sugarcane, cotton and Ragi (millets). Tungabhadra is the lifeline of Bellary, Koppal and Raichur districts in Karnataka and Kurnool, Ananthapur and Cuddappah in Andhra Pradesh. The Tungabhadra reservoir has been constantly losing its water storage capacity over the decades much to the concern of the governments. About 50 years ago the capacity of the reservoir was 3766.161 M m3 and now after accumulation of mud due to mining, dust, soil erosion, debris, the reservoir has lost capacity of storage as much as as 849.51 M m3 of water which is now filled with silt. The amount of rainfall has also decreased in the past few years and as the reservoir does not get filled up, water is released for only one crop now. Where conflicts have come between Karnataka and AP is that with increasing storage capacity and water use in the upstream part of the basin, in lean years in terms of rainfall and river flow, no or very little water reaches AP. The river catchment includes a number of industrial activities in small and large plants and a wide range of commercial agricultural activities as irrigated agriculture has rapidly taken over areas under rainfed farming.

The Tungabhadra case study is important as a ‗transprovincial case‘ in India where there are a large number of such river basins. It highlights the pure scientific challenge in terms of water use and allocation, water use conflicts, pollution, land-use changes and effects of those changes on the river basin. However, the socio-economic aspects of the case are of very high relevance in a country like India where the differences in standards of living between the various social classes are tremendous and the country is in the middle of an accelerating change. The case study research will identify the procedures for enhanced end-user involvement and public participation in order to develop sustainable collective action in the water sector at all levels of political organisation. Prior to development of large dams and reservoirs, the downstream regions of Tunga and Bhadra sub catchments, comprising mostly of arid and semi-arid regions, water management had reached a high level of sophistication, both for surface as well as groundwater utilization in agriculture. Traditional farming systems, which propagated the use of practices like green manuring and organic recycling, have declined. Even though the shift from traditional sustainable farming system to the intensive "Green Revolution" agriculture brought about a marked increase in gross food production, it also resulted in soil depletion, reduction in land productivity in other parts of command area and the spread of monocultural crops. The hybrids, high-response varieties that react to conditions of plentiful water and chemical nutrition, have failed to make an impact in water-stressed conditions. The collapse of traditional farming resulted in

7 STRIVER Deliverable D7.1 Part 1 the neglect of community-used forests, which were the sources of green manure. Encroachment on public land for cultivation is a common feature and has resulted in more land being brought under cultivation at the expense of tree cover. Excessive irrigation for cash crops, especially plantations, has also led to water stress in the region. The spread of water-intensive cultivation throughout the basin has dramatically altered the water balance, leading to major conflicts between water for cash crop cultivation and staple food production on the one hand, and between irrigation, industrial and drinking water needs on the other. The case of sugarcane and paddy cultivation in the command area of Tungabhadra are two instances of over-exploitation of water resources in the basin for cash crop production and a consequent destabilization of the water cycle, leading to water scarcity in large parts of the sub basin and its downstream. Since the introduction of small-scale, individual and community lift irrigation schemes from the main river and its tributaries, the problem of water scarcity has further magnified. Further downstream of large dams, typical problems associated with mismanaged irrigation projects such as salinity and waterlogging have also generated conflicts in the command areas. The Kudremukh National Park in the western region of Karnataka is one of the largest stretches of evergreen forests of low, mid- and high elevation along with a mosaic of shola-grasslands. The mining of iron ore at Kudremukh and Manganese ore in Sandur in the upper catchments of Tunga and bhadra has seriously affected the stability of the catchment and has led to severe soil erosion and silting of several small reservoirs, traditional tanks and the Tungabhadra reservoir, thus conflicting with irrigation needs. Forest degradation resulting from rampant felling and mining, apart from destroying completely the habitat complex of highly threatened flora & fauna, has also resulted in flash floods, high degree of pollution of the rivers and land surrounding the watercourse. These cascading ecological effects on the adjoining forests are spread over a larger area. Several government agencies have undertaken partially successful, but massive afforestation works to mitigate the damage to the forests and rivers due to mining. According to the government over 7.5 million Acacia, Eucalyptus and other exotic trees have been planted, not realizing that such mono-culture forests are not a replacement to the diverse and unique natural habitats, even as the question remains of verifying independently the claim to such afforestation efforts. A major challenge facing Tungabhadra is the protection and provision of sufficient water of high quality at affordable costs while still maintaining the various functional roles of ecosystems.

2.2 Land use Tungabhadra river Basin is characterised by vast agricultural, industrial and urban settlements. Land- use pattern in the Tungabhadra basin has changed over time (Figure 2-1), which has affected water use significantly. Pressures on land use can be linked to competing water uses across sectors - their allocation and usage, new technologies, institutional roles etc which have influenced land use significantly and in turn have impacts on the environment and people‘s livelihoods. From the experience so far in the Tungabhadra basin, river basin planning as a single unit is not in practice. However, efforts to integrate land and water use are in vogue. Data indicate increasing trend in cropped area from 64 % in 1960 to 74 % in 2005 and decrease in wasteland from 6 % to 3 % and fallow land from 10 % to 9 % respectively. This could be attributed mainly to population pressures and increased usage of ground water for cultivation. However, forest cover shows an increasing trend from 13 to 16 % mainly due to afforestation programmes by the forest department in spite of encroachment and deforestation.

8 STRIVER Deliverable D7.1 Part 1

Land-use in TB Basin from 1960 to 2005

100

80

60

Area (%) Area 40

20

0

1960-61 1965-66 1970-71 1975-76 1980-81 1985-86 1990-91 1995-96 2000-01 2004-05

Years

Forest Not Available for Cultivation Other Uncultvable land excluding fallow land Fallow land Net area sown Area sown more than once Total Cropped area

Figure 2-1: Landuse change in Tungabhadra Basin Source: Compiled from District at a Glance, Published by District Statistical Office, GoK.

Urban demands on land use have also been prominent and there are prominent changes in the basin. In 1960-61 land under non agricultural area (Built Up) was 161553 Ha (5.44 % of the total geographical area) and now it is expanded to 194489 Ha (6.86 % of the total geographical area) in the year 2004-05 (Table 2-1).

Table 2-1: Built up land in Tungabhadra basin Built up land Built up land Year (% of total (Ha) Geographical area) 1960-61 161553 5.44 1985-86 185198 6.40 2004-05 194489 6.86

2.3 Pollution sources The principal sources of pollution in the Tungabhadra river basin are (a) run-off from agricultural fields (b) industrial effluents (c) sewage from urban settlements (d) mining activities and (e) over exploitation of ground water. Domestic and industrial pollution, combined with deforestation, use of pesticides and fertilizers have affected water quality extensively making water unfit for drinking.

2.3.1 Agriculture Runoff from agricultural lands results in water logging, desertification, salinization, and erosion that affect the irrigated areas and water quality. Tillage or ploughing activities results in erosion, which carry phosphorus and pesticides, increasing siltation and loss of habitat. Using extensive fertilizers affects the agricultural fields resulting in runoff of nutrients, especially phosphorus, leading to

9 STRIVER Deliverable D7.1 Part 1 eutrophication causing taste and odour in public water supply, excess algal growth leading to deoxygenation of water and fish kills. Across Tungabhadra river basin, fertilizer consumption has increased to 700 tonnes in 2001-05 from 510 tonnes in 1995-96 (Table 2-2) indicating nutrient loss in the soil.

Table 2-2: Fertilizer Consumption in the River Basin Years Fertilizer consumption Nitrogen Phosphorous Potash Total (Tonnes) (Tonnes) (Tonnes) 1991-92 305.18 192.9 102.14 600.22 1995-96 272.65 145.28 92.08 510.01 2001-02 369.88 200.36 129.77 700.01 2004-05 353.98 199.31 146.73 700.02 Source: Karnataka at a glance, 1992-93, Directorate of Economics and Statistics,

Runoff from the agricultural fields has resulted in increased salinity, alkalinity and water logging problems in the command area. This is mainly seen in downstream of the river basin (Koppal, Raichur and Bellary districts) as shown in Table 2-3. ranks first in salinity problem with the total area being affected as 26000 Ha and the worst affected taluks are Manvi and . Bellary district is affected with an area of 19170 Ha and Siraguppa and Bellary are the worst affected taluks. Similar to salinity, alkalinity and water logging are also high in Raichur and Bellary districts followed by Koppal. The total area affected by Alkalinity is 4546 Ha and 2770 Ha respectively in Raichur and Bellary districts and the area affected by water logging is 23838 and 7997 Ha respectively. The total area affected by (salinity, alkalinity and water logging) in the Tungabhadra command area is 54317.21 Ha, whereas in the Bhadra it is 34688 Ha. The use of fertilizers has also affected ground water quality in the basin. Nitrate is the major contaminant in ground water samples for instance, in the Neeramanvi village of Manvi Taluk (Raichur district), the Nitrate contamination was very high to the extent of 1183 mg/l (DMG, 2005)

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Table 2-3: Taluk-wise areas affected with Salinity, Alkalinity and Water Logging in the TB Basin Area affected (Ha) Dist/Taluk Salinity Alkalinity Water logging Total Tungabhadra Command Area Koppal District Koppal 41.08 50.02 82.57 173.67 Gangavati 6875.43 978.86 3932.02 11786.31 Total 6916.51 1028.88 4014.59 11959.98 Raichur District Sindhanur 9077.41 1271.23 8324.98 18673.62 Manvi 15613.66 2616.24 11888.43 30118.33 Devdurga 48.00 96.00 77.00 221.00 Raichur 1192.50 563.29 3548.47 5304.26 Total 25931.57 4546.76 23838.88 54317.21 Bellary District 2486.99 442.39 365.51 3294.89 Bellary 11536.65 2039.01 3339.05 16914.71 Siruguppa 5146.87 288.8 4292.83 9728.50 Total 19170.51 2770.2 7997.39 29938.10 Grand Total 52018.59 8345.84 35850.86 96215.29 Bhadra Command Area Total 3826.00 1643.00 29219.00 34688.00 Source: Tungabhadra Command Area Development Authority and Bhadra Command Area Development Authority

2.3.2 Industrial Activities Industries are one of the key sources of river pollution. Tungabhadra river is the major source of water for about 77 large-scale industries located on its bank, out of which, 27 are functioning and 50 are under implementation. The major types of industries are iron and steel, paper and pulp, chemical and sugar. Across the river Bhadra, a few large-scale industries are found, the major one being the Kudremukh Iron Ore Company Ltd (presently closed). Across the river Bhadra, the two major industries viz., Paper Mills (MPM) and Vishweshvaraiah Iron and Steel Industries (VSIL) are located at Bhadravathi. Harihara Polyfibres (HPF), Gwalior Rayon Silk Manufacturing Industry (GRASIM), two sugar industries and two distilleries are the major industries located across Tungabhadra river.

Apart from large-scale industries, there are 2543 small-scale industries as on 2006-07 with the investment of 797.4 Million. The number of small-scale industries is increasing since 2003-04 as shown in Table 2-4. Table 2-5 gives the information on volume of surface water allocated under the Bhadra Reservoir Project and the Tungabhadra Project for industrial activities. The water consumption for industrial activities in TB Basin is 172.733 M m3 (Tungabhadra – 129.125 M m3 and Bhadra – 43.608 M m3).

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Table 2-4: Number of small scale Industries in the Tungabhadra Basin Investment in Years Number Million 2003-04 2425 662.0 2004-05 2374 777.3 2005-06 2494 752.5 2006-07 2543 797.4 Source: Department of Industries and Commerce, H.O Bangalore

Table 2-5: Industrial Water Allocation Utilization Name of the Industry Source (M m3 per year )

Bhadra Reservoir Project

Vishweshvaraiah Iron and Steel Bhadra river (VISL) Bhadravati 7.27 Mysore Paper Mills (MPM), Bhadra river Bhadravathi 20.38 Bhadra Packets Bhadra river 0.16 Harihara Polyfibres Industry Bhadra river 15.03 Tungabhadra Harihara polyfibres Colony river 0.14 Samson‘s Distilleries Tungabhadra 0.16 Samgam Motels Pvt Limited Tungabhadra 0.02 Samnur Sugar Distillaries Tungabhadra 0.14 Davanagere Sugars Sagalehalla 0.11 Total (A) 43.49 Tungabhadra Project Jindal Vijayanagar Steel Ltd., Raya Basava Toranagallu Canal 39.36 Pampasar Distillary Ltd., Hospet Raya Canal 1.69 Kalyani Steel Ltd., Ginigere TB reservoir 8.21 Kirloskar Ferrous Industries ltd., TB reservoir Bevinahalli 3.39 Narihalla NMDC Ltd., Donimalai Project 3.68 Tungabhadra Pulp & Board Mills, Distry 2 of Munirabad TLBC 0.56 Total (B) 56.91 Source: Bhadra Reservoir Project

HPF and GRASIM Industries produce 44 MLD of effluents, which contain organic, inorganic, and toxic chemicals affecting more than one hundred villages closeby. The Table 2-6 gives details on major industrial units, their locations, water consumption and their effluents disposal methods.

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Table 2-6: Industrial pollution across the basin

(KLD)

(KLD)

Location

Water source Water

Major Industries Major

Disposal methods Disposal

Water consumption Water Wastewater generated Wastewater

Mysore Paper Have treatment facilities. There are 2 Bhadravathy 60000 Mills STPS - primary and secondary The industry has treatment facilities. Most Vishweshvaraia Bhadravathy 30000 of it is recycled and used for cooling h Iron and Steel purpose Harihara Harihar 48000 38000 Have treatment plants Polyfibres Sugar Distilleries Koppal Green TB Gangavathi 700 NIL NA Power Ltd river Sri-Indra Power TB Gangavathi 800 NIL NA Energies Ltd river Rajikiran Power TB Gangavathi 1176 Ltd river Kirloskar Koppal 2236 114 Wastewater is reused Ferrous Ltd Kalyani Steels Koppal - 4465 390 Wastewater is reused Ltd Mukand Ltd Koppal 1725 135 Wastewater is reused Treatment plant is available, treated Suverign TB Sindhanur 1900 1135 wastewater is reused for gardening distilleries river purpose Treatment is carried out, treated Raichur-Bellary TB Sindhanur 25 9 wastewater is reused for gardening Milk Union Ltd river purpose From Kowanti kowar Sindhanur Public 1080 power unit supply Source: Complied from respective Regional offices of the Karnataka State Pollution Control Board

The major impacts, locations affected and efforts taken towards minimizing are given in Table 2-7. The most affected are the villages located in the downstream of HPF, MPM and VSIL industries. In addition, the mining industries are affecting the water (Patel, 2005).

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Table 2-7: Major Impacts of industrial pollution Efforts Changes Impacts Locations affected Reasons taken to made rectify Industrial 45 Villages down stream of HPF sewage

inflow from

- HPF At Hirebadare and villages located at a distance of 15 and 20 km from

HPF effluent discharge 13 fishermen were Skin diseases diseases Skin

suffering from skin diseases ‗Superficial - folliculitis‘, Nawalgalu and Airini villages located in the

downstream of HPF industry. Effluents 11 Villages located in the surroundings of from MPM VISL and MPM (Aravinda, 1999)

and VSIL

Respiratory disorder disorder Respiratory

- Residents Installation

filed of drinking Effluents complaint water pacts pacts Holehonnur town from MPM in 2001-02 treatment

and VSIL and there plant by the

were concerned

Stomach ache Stomach Health Im Health protests authorities Fishermen filed a Industrial compliant sewage No changes Fish kills Downstream of HPF in 2003 inflow from with the HPF local ministers Uncontrolled KSPCB discharge of issued a Discharge Downstream of the Birla industries in 1984 industrial notice to was stopped effluents into the the river industry

In March 1994 in the river downstream of the

factories to a stretch of 25-30 kms at HPF effluent

Nandiharalahalli, , Hirebedare and discharge

Guttur villages

Source: Complied from earlier studies

Fish kill is frequent in TB Basin in the downstream of industries affecting the livelihood fishing families. Many fishermen have changed their traditional occupation of fishing to other jobs. There are documentations on the composition of fish species that has been reducing/extinct over the years. In addition, the several local varieties of fish have become extinct. According to fishermen around 50 % of the local breeds have disappeared or decreased in their population. During the field study many fishermen expressed concern over the increasing use of chemical, fertilizers in agriculture. Several stretches of the river are polluted affecting around 75 villages. 47 % of fishermen indicated that water was polluted due to pollution and fish kills had negative impacts in terms of health and reduced income

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- 26 %, while some had a combination of health, reduced income and also witnessed fish kills – 9 %. (STRIVER Task report 9.4).

2.3.3 Urban Settlements Karnataka Urban Water Supply and Drainage Board is responsible for providing water supply and sewerage facilities to all 28 Urban Local Bodies (ULBs) in the basin (Annex to chapter 2). ULBs are a crucial third tier of government, after the Centre and the States. These are included with the enactment of the 74th Constitution Amendment Act, 1992. ULBs are intended to bring about greater decentralisation of functions, proximity of the elected representatives and civic administration to citizens, and enhancement of people's participation in local governance. The Urban Local Body of Karnataka has seven corporations, 43 city municipal councils (CMCs), 79 town municipal councils (TMCs) and 93 town panchayats (TPs). During the study, twelve towns were visited to understand the drinking water supply status and pollution problems. River Tunga, Bhadra and Tungabhadra are the main sources of drinking water supply. In addition, during scarcity, water is supplied through other alternative sources - groundwater and surface water tanks to meet the demand ((Annex 2) for water supply details). The total volume of water supplied is 344.5 MLD (Table 2-8), out of which 122.33 M m3 constitutes surface water and 13.09 MLD is groundwater. Considering 80% as wastewater generated, the domestic sewage generated from ULB is around 267.4 MLD. A majority (around 20) of the ULBs do not have underground drainage system (UGD) and treatment facilities to collect and treat the municipal sewage. In the rest of ULBs though UGD is present, it is partial. The sewage from these ULBs directly enters the river system or agricultural fields without treatment. The details on wastewater disposal by some of the ULBs are given in Table 2-9. In this context, the role of the Karnataka State Pollution Control Board in addressing pollution was addressed. The Karnataka State Pollution Control Board, constituted by the Government of Karnataka in 1974 is the enforcing authority of the various environmental legislations including control of water pollution. The Central Office of the Board is responsible for making general policies relating to enforcement of various environmental legislations. The Regional Pollution Control Boards located at five districts in Tungabhadra river basin carries out frequent river water quality monitoring under Global Environmental Monitoring System Program (GEMS), Monitoring of National Aquatic Resources Programme (MINARS) and Board Programmes by collecting 74 samples (5 under GEMS, 40 under MINARS and 19 under Board Programmes). In addition, the Board has initiated action plans to prevent river pollution in four towns under the National River Action Plan (NRAP), initiated by the National River Conservation Directorate of the Ministry of Environment & Forest, Government of India. NRAP scheme is implemented under two schemes viz., Core and Non-Core Scheme with different activities. Irrespective of these regulatory measures, implementation was not very effective in controlling pollution. The role of the Karnataka State Pollution Control Board is limited to the extent of sending constant reminders and issuing show–cause notices indicating institutional constraints. For instance, KSPCB is not able to ensure construction of Sewage Treatment Plants in towns that are discharging sewage directly into the river. There are only 8 towns amongst the 28 towns that have sewage treatment plants. At times, when initiatives are taken to pressurize certain polluters, pressure from the local ministers and MLAs do not allow the regulatory authorities for the enforcement of legislations. Apart from these, the standards prescribed to discharge into river do not meet the world standards. In case of Harihar polyfibres, the industry is adhering to the standards of the KSPCB, however, the actual impacts on the people still remain high. There is lack of understanding in addressing the problem in a holistic perspective. While the KSPCB is limited to collect the samples and warn the polluters, no serious effort has been taken to understand the future impacts of pollution and ways of preventing it. Accountability is another serious flaw that needs to be addressed. Conflicts have been common where people have protested the impacts of pollution but have remained local. The problem cannot be pointed at regulatory authorities alone as strong political will is also required to bring in the required changes.

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Discussion with the officials of State Pollution Control Board revealed that there is no serious pollution problem in the upper stream of TB Basin in terms of industrial effluents. However, Town Municipal Councils pollute as there are no sewage treatment plants in most of the towns and the sewage from these towns are entering into the river. The officials expressed their difficulty in taking action against ULBs due to political pressures. For instance, once the PCB had filed a case against the ULB for improper management but with political pressures , PCB had to withdraw the case limiting them to only issue show-cause notice to the polluting ULBs.

Table 2-8: Water Supply in ULBs Across the Basin Name of the Surface water Surface water Ground water Ground water town Volume of Volume of GW Per person Number of Source water supplied supplied per capita per wells (M m3) (MLD) day (LPCD) Tarikere Bhadra canal 1.614 10 0.02 100 Tunga river 0.142 - - 70 Koppal Tunga river 0.170 14 0.10 70 Gadag Batageri TB river 0.991 27 0.15 135 Mundaragi TB river 0.963 10 0.50 100 TB river 1.218 12 0.10 100 Haveri TB river 2.633 10 0.50 100 Ranebennur TB river 4.248 14 0.50 100 Shimoga TB river 17.528 32 2.00 135 Thirthahally TB river 0.481 10 0.10 70 Honnali TB river 0.510 12 0.10 70 Davanagere TB river 23.220 22 1.00 135 Harihara TB river 3.540 10 0.20 100 Bellary TB river 20.105 35 2.00 135 Hosapet TB canal 10.449 15 0.20 135 TB power Kamalapura 15 0.10 100 canal 1.019 Kampli TB river 1.671 15 0.15 100 Siruguppa TB river 2.011 10 0.10 100 Tekalkopta TB canal 1.104 10 0.10 100 Huvinahadagali TB river 1.104 15 0.12 100 Sindhanur TB canal 2.888 10 0.10 100 Gangavathi TB river 5.947 15 0.20 135 Koppa TB river 2.662 15 0.20 100 Manvi TB river 1.812 15 2.00 100 Lakeshmeshwar TB river 1.416 15 2.00 100 Harapanahalli TB river 1.926 20 0.20 100 Bhadravathi Bhadra river 10.251 20 0.25 135 Chennagiri Bhadra river 0.850 15 0.10 100 Total 122.471 423 13.09 Source: Karnataka Water Supply and drainage Board, 2005

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Table 2-9: Sewage Disposal by ULBs ULBs Method of sewage disposal Sringeri River Tunga Hospet, Sandur, Siraguppa, Reaches agricultural fields Gangavathi and Sindhanoor Sewage is let into Bathi Tank and Davanagere river Tungabhadra Septic tanks are available, sewage from these let into Haveri Heggere tank and then it reaches Tungabhadra river Koppal, Raichur and Manvi Low-level canal of Tungabhadra Source: Complied from the Discussions with KSPCB Officials

2.4 Pressures on groundwater Ground water is the main source of drinking water for several villages located on the riverbank. Over- exploitation of ground water and seepage of domestic sewage and agricultural runoff are the major causes for groundwater quality contamination. In addition, the ground water dependency for irrigation was also increasing, as the canal water supply was not meeting the demand. There are around 0.6 Million wells in TB basin, and the number of which is increasing over a period of time as shown the Figure 2-2 leading to increased burden on ground water. According to Department of Mines and Geology, the volume of ground water extracted was 2255787 Ha-M in March 2004, which has increased from 60543 Ha-M since 1994.

250000

200000

150000

100000

Number of wells of Number 50000

0 1985-86 1990-91 1995-96 2000-01 2005-06 Years

Figure 2-2: Number of wells in TB Basin over the years. Source: District at a Glance of all 7 districts, 1975 to 2005

The total ground water recharge in the basin is 300,777.62 Ha-M and the net availability is 391,875 Ha-M (Table 2-10). The extraction levels are high in the downstream part of the river (Davanagere, Raichur and Bellary districts) and irrigation is the key sector contributing to extraction.

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Table 2-10: Ground Water Extraction Levels in TB Basin (Ha-M) Extraction (Ha-M) Domestic Total Net District Irrigation and Other uses Total Usage recharge availability industrial Bellary 39364 38307 10420 2706 13126 103923 Chikkamagalur 34464 33046 10781 1728 12510 92530 Davanagere 55371 53797 36896 2939 39835 188838 Haveri 33538 32052 21215 2325 1439168 152830 Koppal 43951 42982 15025 1242 16266 119465 Raichur 58456 57232 6671 2449 9120 133929 Shimoga 35634 34459 7944 1411 9355 88803 Total 300778 291876 108952 14801 1539381 2255787 Source: Report on Dynamic Ground Water Resources of Karnataka as on March, 2004, DMG and CGWB (June 2005)

Over exploitation has resulted in ground water level depletion in the basin. The data from the Department of Mines and Geology revealed that the ground water levels were depleting over a period of three decades as shown in Table 2-10. Table 2-11 In Bellary, the ground water level had decreased from 7.37 meters in 1978 to 10.91 meters in 1997. Similarly in Chickamagalur, it had decreased to 9.95 mts from 8.95 mts, in Raichur from 5.96 mts to 6.58 mts and in Shimoga, from 9.23 mts to 9.76 mts between 1978 to 1997.

Table 2-11: Ground Water Levels in Mtrs Years Districts 1978 1987 1997 Bellary 7.37 7.40 10.91 Chikkamagalur 8.95 9.22 9.95 Raichur 5.96 7.03 6.58 Shimoga 9.23 9.03 9.76

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Table 2-12 provides details on the taluk-wise status of ground water extraction in the TB Basin. Bellary, Davanagere, Koppal, Haveri and Raichur are more prone to ground water extraction.

Table 2-12: Taluk-wise Ground Water Status in TB Basin on March 2004

Ground water Status (%)

District Taluks

critical

tical

-

Cri

Safe area Safe

Semi Over Over exploited

Siruguppa 51 - - 49 Hosapet Safe - - - Bellary Bellary 41 - - 59 Hagaribomman 24 32 - 44 ahalli Chaikamagalur 73 27 - - NR Pura Safe - - - Chikamagalur Sringeri Safe - - - Koppa Safe - - - Tarikere 68 1 31 - Hannalli 4 56 - 40 Harihar - 2 - 98 Davanagere Channagiri 4 - 8 88 Davanagere - - - OE Harapanahalli 4 - - 96 Haveri 27 - - 73 Ranebennur - 5 31 64 Haveri 15 18 62 5 Savanur Safe - - - Safe - - - Kpppal - 28 - 72 Koppala Gangavathi 43 - - 57 Raichur 93 - - 7 Devadurga 97 3 - - Raichur Manvi Safe - - - Safe - - - Shimoga 80 20 - - Shimaoga Theerthahalli Safe - - - Bhadravathi Safe - - - Source: Department of Mines and Geology (2005)

Table 2-13 depicts information on total area with polluted groundwater in Tunga and Bhadra river basin.

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Table 2-14 provides information on district and Taluk- wise ground water affected villages where more than 150 villages are affected with ground water quality contamination. The major pollutants are Nitrate, Flouride, Hardness and Iron. The most affected districts are Raichur and Bellary. In Neeramanvi village of Manvi Taluk of Raichur district, the Nitrate concentration was as high as 1183 mg/l. Fluoride contamination was observed in Jagatkal village, Devdurga taluk of Raichur district to the extent of 10 mg/l.

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Annex to Chapter 2 gives the details on villages affected with ground water quality in all the seven districts.

Table 2-13: Area with Affected Ground Water in Hectares Area with affected ground water (Ha) Tunga Bhadra Status Pre - Post - Pre - Post - Monsoon Monsoon Monsoon Monsoon Most critical Nil 125.48 Critically 732.59 3875.62 2.00 11715.86 affected Less Critically 3233.95 3550.79 2093.43 17117.13 affected Non-Critically 13087.69 9627.82 54365.54 27502.51 affected Total 17054.23 17054.23 56460.97 56460.97 Source: Department of Mines and Geology (2005)

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Table 2-14: Villages affected by ground water pollution in the TB Basin Number of villages Districts / Taluks affected with GW Major contaminants quality Raichur Devadurga 16 Nitrate and Fluoride Manvi 15 Nitrate, Fluoride and Hardness Raichur 9 Nitrate, Fluoride and Hardness Sindhanur 14 Nitrate and Fluoride Bellary Nitrate, Fluoride, Hardness and Bellary 14 Iron Hagaribommanahalli 6 Nitrate, Fluoride and Hardness Nitrate, Fluoride, Hardness and Hosapet 3 Iron Huvinahadagali 12 Nitrate, Fluoride and Hardness Siruguppa 6 Nitrate, Fluoride and Hardness Chickamagalur Koppa 2 Nitrate NR pura 1 Iron Sringeri 2 Iron Tarikere 6 Nitrate and Hardness Haveri Hanagal 2 Nitrate and Fluoride Haveri 3 Nitrate and Fluoride Hirekerur 4 Nitrate and Hardness Ranebennuru 9 Nitrate, Fluoride and Hardness Savanur 5 Nitrate, Fluoride and Hardness Koppal Gangavathy 7 Nitrate and Fluoride Koppal 7 Nitrate and Fluoride Shimoga Bhadravathi 2 Nitrate, Fluoride and Iron Shimoga 5 Nitrate and Iron Total 150 Source: Department of Mines and Geology (2005)

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2.5 Conclusion Pollution from various sources contaminates the river with no integrated efforts across institutions and sectors towards prevention. Initiatives taken by the Pollution Control Board limits to collecting water samples and sending warning signals to the polluters, particularly industries. However, the influences to make policy changes are insignificant. Although few Industries have effluent treatment plants, pollution still remains due to poor monitoring and accountability. With respect to towns, efforts towards establishing sewage treatment plants are unlikely to be implemented in the short term due to financial constraints, poor governance and lack of political will, although it is part of their plan. Pollution from Agriculture was obvious throughout the basin with impacts on land use changes but no efforts to control. Few studies conducted along the basin indicate the intensity of pollution at specific points and its impacts. However, there are many uncovered issues linking impacts on health, food chain, flora and fauna etc. In this context, it is imperative to work towards curtailing this serious issue through integrated water management to bring in policy changes.

Units MLD = Million litre per day LPCD = Litre per capita per day Ha-M = Hectare meter M m3 = Million cubic metres

2.6 Literature

District at a Glance – Chikamagalur, Shimoga, Davanagere, Harihar, Koppala, Raichur 1975 to 2005, Published by District Statistical Office, Government of Karnataka

Karnataka at a glance, 1992-93, Directorate of Economics and Statistics, Bangalore

Report on Dynamic Ground Water Resources of Karnataka as on March, 2004 (2005), Department of Mines and Geology and Central ground Water Board, South Western Region

Aravinda, H.B. (1999). Study of some physico-chemical properties of TB river in Karnataka.

Joshi, HC, Sukumaran, P.K. (1987). The impact of effluents from Harihar polyfibre and Gwalior rayon factories on the aquatic life in the River Tungabhadra near Harihar in Karnataka: a report, CICFRI, Barrackpore (India).

Patel, A.N. (2005). Studies on the impact of Kudremukh mining activity on the environment of the western-ghats region.

Vanaja, R. (1999). Ecological Studies on River Tungabhadra near Harihar,

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3. Pressures: qualitative analyses on pollution source and main issues in Glomma (Hunnselva and Lena)

Line J. Barkved (NIVA), Johannes Deelstra (Bioforsk) and Haakon Thaulow (NIVA)

Within the Glomma river basin, the focus area for the STRIVER pollution study is the Hunnselva catchment, a sub-basin of the Glomma basin. Also Lena, the neighbouring catchment to Hunnselva is studied in this context. An overview and basic information about Glomma is provided as an introduction to more specific information about Lena and Hunnselva. Information about pollution sources and discharges is given in this chapter, whilst data on in-stream water quality can be found in Chapter 5.

3.1 Glomma River Basin General The Glomma River is Norway‘s largest river. It is located in South Eastern Norway where it covers 41200 km2. This equals 13 % of Norway‘s total area. The catchment is shown in Figure 3-1.

Figure 3-1: Glomma River Basin in SE-Norway (From GLB Annual Report; www.glb.no)

The basin is 600 km long from north to south. The north-western parts consist of high mountain areas (Jotunheimen area with Norway‘s highest peak: Gallhøpiggen (2468 m asl.), Rondane and Dovre).

24 STRIVER Deliverable D7.1 Part 1

30% of the catchment is located at elevation above 1000 m, and 40% between 500 m and 1000 m. The eastern part is covered by forest areas, whereas the central and southern parts comprise large agricultural areas. In total the agricultural areas cover 2400 km2 and constitute 5.8 % of the total catchment. The large side-branch is entering into River Glomma between Lake Mjøsa and Lake Øyeren, see Fig.1. This branch is often referred to as the Låagen Watercourse. It contains Norway‘s largest lake, Lake Mjøsa, which has a surface area of 350 km2, and a maximum depth of 450 m. The total discharge from River Glomma is 22x109 m3/y, and the mean annual flow is 700 m3/s at Solbergfoss (outlet of Lake Øyeren, the lowermost reservoir, see Figure 3-1). The flow normally varies over the year from 150 to 3500 m3/s.

Observed annual precipitation ranges from the driest areas in Norway with 260 mm/y to mountain areas with 1050 mm/y. At the entrance of Lake Øyeren, River Glomma forms Northern Europe‘s largest inland delta, The Northern Øyeren Nature Reserve, which is regarded as an extremely important wetland for migratory water fowl (Ramsar Site).

The Glomma basin comprises approximately 675000 inhabitants. There are 8 cities, in which half of the population lives. The others live along the rivers in rural areas and villages. The mountains and remote forested areas are virtually uninhabited.

Relevant institutions involved in Water Management – the EU Water Framework Directive Politically the Glomma basin consists of a large number of municipalities, and five counties. Only a few fringes (grey fields in Figure 3-1) go into Sweden, but these are very small and contain no waters, so with respect to water management River Glomma is a one nation river. The municipalities are to a large extent self-ruled when it comes to establish water impacting activities, but they have to comply with certain national standards. The municipal administration executes the decisions of the Municipal Council (Kommunestyret).

On the county level, there are two types of water related authorities, one (the Fylkeskommunen – the County Commune) is in a way a co-operative organ for the municipalities constituting the county. Each municipality has representatives in the County Council. The administration of the County Council is called the County Commune and is executing the decisions of the County council. They are taking care of the part of the school system, the road and communication, and parts of the health care systems, e.g. the hospitals. They have also some planning responsibilities when it comes to inter municipal and inter-county plans. The other authority on the county level is called Fylkesmannen – or the County Governor. This is the ―Extended Arm of the State‖ and has a controlling function. They control that the national guidelines are followed by the local and regional authorities. Their responsibility comprises pollution and many other water impacts. Hydropower impacts, is however, not comprised by the control responsibility of the County Governor. These are controlled by a directorate (NVE) under the Ministry of Oil and Energy. The practical management of the many hydropower regulations in the Glomma basin is performed by the association among the hydropower companies the ‗Glommen og Laagens Brugseierforening‘ (GLB) which are responsible for keeping the water flow and water level regulations set by NVE. GLB was established in 1918 and created and owned by the owners of the different hydropower stations. The GLB performs several water management responsibilities in the basin among others to secure that the concession conditions with respect to flow in rivers and water levels in reservoirs are not violated. The GLB is also running the hydrological gauging stations in the catchment (water flows and water levels) and have responsibility for conducting compensation work, like fish stocking programmes, flood protection works, etc.

Norway has decided to implement the EU Water Framework Directive (WFD) as a steering framework for water management. The goal for the water management in this directive is that all the water bodies shall have good ecological status by 2015. According to the WFD, Norway is divided into 9 main water regions (Water Authorities), Glomma being one of them. Norway, as an associate member state, has a 6 years slack on the implementation, but some selected basins follow the general EU time table for implementation. The WDF became effective from as of January 1st 2007.

25 STRIVER Deliverable D7.1 Part 1

To catch up with the rest of Europe a number of water bodies (river basins and marine areas) have been selected to follow standard WDF timetable.

Hydropower production is an important water use in Glomma. The river basin has currently 47 hydro power stations and 26 regulations and water and diversion schemes. The coordination of the manoeuvring of the regulations is taken care by the water management association ‗Glommen og Laagens Brugseierforening‘ (GLB). According to the WFD, water bodies (river stretches and/or reservoirs) that are regulated (physically altered) to provide important society goods, e.g. electricity by hydropower plants can be classified as ―Heavily modified water bodies‖ and thereby get exception from the goal " good ecological status". The less stringent goals to be achieved for such water bodies defined as ―good ecological potential‖. This means that with respect to water environment you should make the best out of it within the constraints created by the regulated flow and water level regime. It also seem like the WFD requires a minimum release downstream dams, even though also this is not clearly defined. Assessing environmental flow is a complicated management task. The methods used up to now take only into account the living conditions for bottom animals and fish. In STRIVER we will try develop a more simplistic way of setting environmental flow based on the pressure impact curve method (STRIVER WP8) which takes into account many user interests and ecological values, it is easy to apply, and it is transparent.

User interests in Glomma In addition to hydropower representing an important water user in Glomma other interest are central to. In the uppermost part of the catchment, an increasingly larger part of the revenues are created by tourism related activities. This comprises both winter sports like alpine and cross country skiing, as summer activities like hiking, hunting and sports fishing. New Hotels, ski resorts, and farm-tourist centres are popping up. This applies both for cities and country side. These activities need clean and undisturbed nature to be attractive, which causes a great challenge for the hydropower sector, for the municipal waste treatment, as well as industrial discharge management. On the country side, agriculture activities are still important. The Norwegian farms are small and the agriculture is heavily subsidised. This makes it possible to maintain a relatively large population in rural areas with service centres (villages) serving the farmland populations. The local population has at all times used the rich fisheries in many of the lakes and rivers for food. The regulation and the pollution discharges have created problems for these activities. Large amounts of money have been invested in abating the eutrophication of the lake Mjøsa and Lake Øyeren. This abatement has been successful, but a new pollution problem have arisen, that from environmental toxins entering the food chain, making it risky to consume fish. For example in Lake Mjøsa, resent studies has revealed that the meat of the popular brown trout exceeds the consume standards for brominated flame retardants, a group of compounds used in textile industry. The former important fisheries have stopped due to this, both commercial fisheries and sport fishing. The many regulations has also affected the fisheries negatively many places. The 150 km long river stretch from Høyegga to Rena, where 80% of the water is diverted to Rendalen, the fish yields are considerably lower than before, se Fig. 4. In some of the high mountain lakes the fish productivity is reduced by high water level fluctuations. In the lower parts of the Rena River, which receives the water from the diversion, the increased and more stable flow has caused a great change in the fish diversity. In several stretches the fish and fisheries are good, due to moderate regulation encroachment and efficient abatement measures. Several places in the catchment, there have been mining industry, which however closed down in the 1980-1990ies. The old mines still cause water pollution problems, locally. The problem of ownership of abandoned mines has been, and still are a challenge when it comes to responsibility for abatement actions.

The Glomma River is used as a recipient for municipal and industrial wastewater. The wastewater is , with very few exceptions, treated in waste water treatment plant.. The pollution situation in the river has improved considerably over the last 25 years. However, there are still many small settlements which do not have efficient effluent treatments. These are polluting the river and creating conflicts with respect to the use of the river as drinking water supply. There are several large water works that supply several hundred thousand people with water from River Glomma. Glomma receives pollution

26 STRIVER Deliverable D7.1 Part 1 from agriculture, both from diffuse runoff and point sources. All along the river, the agriculture takes irrigation water from the river. However, this use is not so large that it affects the water flow notably. Boat traffic is important along most part of river Glomma. This is both for fishing (commercial fisheries and for leisure fishing). In some of the high mountain lakes and in the Lake Mjøsa, and Lake Øyeren, there are commercial boat transports of tourists in the summer season.

During the last 10 to 15 years the controversy between agriculture and water quality has been reduced not only in the Lake Mjøsa, but in most of the Glomma and Laagen basin. In addition to the Lake Mjøsa Campaign, the international agreement on reduction of pollutants to the North Sea (The North Sea Agreement) has been of vital importance for the water quality improvements in the basin.

3.2 The Hunnselva and Lena sub-basins Within the Glomma river basin, the Hunnselva cathcment is one of 8 selected water bodies for the Phase 1 implementation of Water Framework Directive in Norway following the general European WFD timetable; i.e. good ecological status is to be achieved by 2015. For this reason the Hunnselva catchment was selected to be the STRIVER focus area for the water pollution study. STRIVER has established close contact with the Water Authorities in Norway responsible for the implementation of the WFD and the Hunnselva WFD working board. The goal is to make STRIVER results of real value in a practical ongoing IWRM planning.

Hunnselva is a side tributary to Lake Mjøsa in the Glomma basin and the river is polluted by discharges from industry, agriculture and domestic sewage and is regulated for hydropower production. In the upper river, however fish are thriving and recreational use is considerable. Lena is the neighbouring sub-basin of Hunnselva (see Figure 3-1) and also a side tributary to Lake Mjøsa in the Glomma basin. As the Lena catchment is more dominated by agriculture land than Hunnselva, an important source in nutrient pollution, it was also included in the study.

3.3 Physical description of Hunnselva and Lena sub-basins 3.3.1 Climate and Climatological data Different climatologically stations are located in the vicinity of the Hunnselva and Lena catchments (Figure 3-2). The Kise and Apelsvoll are operated by Bioforsk - Plant health and Plant protection. The Einavatn station is operated by the Norwegian Meteorological Agency. The Gjøvik station, operated by the Norwegian Meteorological Agency, is no longer running and is not considered in this report. The stations represent a typical inland climate with cold winters and mild summers.

Kise Data from Kise are available from 1988 and include among others rainfall, air temperature, wind speed, global radiation and relative humidity. The average yearly air temperature varied from 2.9 – 6.4 oC in 1996 and 1997 respectively. The average yearly air temperature is, with the exception of 1996, higher than the long term average yearly temperature (Annex to Chapter 3). The difference between the observed and long term average temperature is most noticeable during the months of November – April (Feil! Fant ikke referansekilden.). The highest and lowest monthly temperatures occur in the months of July and February respectively.

The yearly precipitation varied from 424 – 773 mm in 1991 and 2000 respectively (Annex to Chapter 3). Especially during the years 1991, 1995 and 2005 the annual precipitation is considerably less than the long term yearly precipitation. There is a large variation in monthly precipitation during the observation period. The highest and lowest average monthly precipitation during the observation period occurred during the months of August and March respectively.

Apelsvoll

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Data for Apelsvoll are available since 1989 and include the same parameters as for Kise. The average yearly air temperature varied from 2.7 – 6.0 ºC in 1996 and 2000 respectively (Annex to Chapter 3). The observed average yearly temperature is considerably higher than the long term mean annual temperature. Especially during the months November – April large differences occur between observed and long term average monthly temperature. The highest and lowest observed average monthly temperature occurred in July and January respectively.

The yearly precipitation during the observation period varied from 461 - 1193 mm in 1997 and 1999 respectively. There is a large variation in the monthly precipitation (Annex to Chapter 3). As for the Kise climatological station the highest and lowest average precipitation occurred during the months of August and March respectively.

Figure 3-2: Map of climate stations (circles) and water flow stations (triangle) in the Hunnselva (right) and Lena (left) basins.

Einavatn Meteorological data for Einavatn are available for a longer period but here only data since 1989 are presented. Only precipitation is measured. The yearly precipitation for Einavatn station varied from 486 – 977 mm in 1991 and 2000 respectively (Annex to Chapter 3). The average precipitation since 1989 is 685 mm. The average monthly precipitation varies from 32 – 79 mm in February and July/august respectively. There is a large variation in the monthly precipitation.

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Summarizing it can be concluded that only small differences exist between the observed temperatures recorded at Kise and Apelsvoll respectively (Figure 3-3). It is interesting to notice that a considerable difference exists between the average yearly recorded - and the long term mean temperature. Differences in precipitation between locations exist, with the largest precipitation observed at Einavatn (Figure 3-4). The yearly average recorded precipitation at Kise is considerably lower compared to Apelsvoll and Einavatn. For Kise and Apelsvoll no significant differences in yearly recorded precipitation exist when comparing with the long term average yearly precipitation.

Figure 3-3. Average yearly temperature for Kise and Apelsvoll.

Figure 3-4. Yearly precipitation at Kise, Apelsvoll and Einavatn.

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Winter conditions The greater part of Norway is affected by winter conditions with frozen soils and snow cover. When defining the winter season as the time period between the first and last day with an average daily temperature below zero, on average the winter season for the Hunnselva/Lena watershed starts in late October/beginning of November and lasts until March. At one stage during the winter season, prolonged periods with below - zero temperatures will occur and soil frost can develop. To identify these periods, the principle of a freezing index has been used and which is defined as the number of degree-days between the highest and lowest points on the cumulative degree-days - time curve (Figure 3-5, Glossary of Terms in Soil Science, 2005). The freezing period is the time period indicated by the highest and lowest points on the cumulative degree-days curve. The freezing period and freezing index are indicators of the ―severity‖ of the winter and can be an indicator of frost development in the soil. However it should be realised that such a frost development is influenced by factors like soil moisture condition at the onset of a freezing period, snow cover development, soil type and soil (plant) cover.

Figure 3-5: Freezing index and length of freezing period, Kise meteorological station (example period 1/5/93 – 30.4.94)

During the freezing period, the trend of the sum degree–day curve is downward (Figure 3-5), meaning that during this period the average air temperature is below zero. The degree–day sum gives an indication of the ―severity‖ of the winter season. Based on air temperature data collected at the Kise meteorological station the freezing index has been calculated for the period since 1988 (Figure 3-6). There is a large variation in the freezing index, indicating significant changes in the ―severity‖ of the winter. At the same time a large variation in the number of freeze/thaw cycles during a winter season can be observed (Figure 3-7). Often the winter season is characterised by a series of freeze/thaw cycles, during which runoff can be generated due to snowmelt and/or precipitation. Less severe winters are often characterised by a smaller freezing index and an increased number of freeze/thaw cycles increases (Figure 3-8). Deelstra et al (2008) showed that even during freezing periods a relative large amount of the total yearly nitrogen and phosphorus loss could occur. The relative large amount of nitrogen loss indicated the presence of infiltration even in frozen soils.

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Figure 3-6. Freezing index, Kise meteorological station.

Figure 3-7. Freeze/thaw cycles, Kise meteorological station.

Figure 3-8. Relation between freezing index and number of freeze/thaw cycles, Kise meteorological station.

31 STRIVER Deliverable D7.1 Part 1

Freeze-thaw cycles can have a serious impact on the aggregate stability and shear strength of the soil (Bullock et al. 1988), thereby enhancing the potential for soil loss through erosion processes during periods with runoff. Laboratory studies have shown that with an increasing number of freeze-thaw cycles, increased soil loss was observed (Frame et al., 1992). Similar results were found by Kværnø et al (2006). Also the release of dissolved phosphorus from plant material is enhanced by freezing/thawing (Bechmann et al, 2005). Zuzel at al (1982) concluded on the basis of experiments carried out north-eastern Oregon that as much as 90 % of the yearly erosion was due to snowmelt combined with freeze-thaw cycles. On the basis of their results they proposed the Universal Soil Loss Equation (USLE) to be modified to be able to deal with the typical winter processes. Also van Klaveren et al. (1998) indicate the effect of freezing and thawing on erodibility and the implication for modelling. It is paramount that in modelling of nutrient and soil loss in the Hunnselva/Lena catchments , processes occurring during winter periods have to be taken seriously into consideration.

3.3.2 Land use and soil physical characteristics The main land use type is in the Hunnselva and Lena catchments is forest, covering approximately 66 – and 53% of the total area while agricultural land covers approximately 15 – and 37 % respectively. Detailed information about soil types for forested land is not available. The agricultural soils are dominated by till soils.

Table 3-1: Land use in Hunnselva and Lena catchment Total area(km2) Forest Mountain Lake Agriculture Other (%) Lena 296 53 8 1 37 1 Hunnselva 369 66 10 5 15 1 Source: GIS data from Norwegian Forest and Landscape Institute

All agricultural soil in the Hunnselva and Lena catchments has been characterised by the Norwegian Forest and Landscape Institute. A total of 799 different soil types were identified, 37 of which were mapped as organic soils. Of the mineral soils, 526 and 236 are located in the Hunnselva and Lena catchment respectively. The characterisation among others includes a textural analysis of soil types (Figure 3-9 and Figure 3-10). The dominant soil types in both the Hunnselva and Lena catchment vary from sandy - to silt clay loam soils, however in both catchments loam soils dominate. Apparently there are no major differences between the soils in the Hunnselva and Lena catchment.

No measurements on soil physical characteristics (saturated hydraulic conductivity, soil moisture retention) are carried out as a standard procedure in soil characterisation as practiced by the Norwegian Forest and Landscape Institute. This information is an indispensable input to process based models like SWAT and often this is made available through the use of pedo-transfer function. Pedo- transfer functions were established for dominating soil types in Eastern Norway and provide information about the saturated hydraulic conductivity and soil moisture retention curve as a function of soil texture and organic matter content (Hugh Riley, 1996, see Annex to Chapter 3). Riley divided agricultural soils into soil classes, based on soil texture, for which pedo-transfer functions were developed. The main identified classes were organic soil, clay, loam, silt and sand (Table 3-2).

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Figure 3-9: Textural analysis of the topsoil in Hunnselva

Figure 3-10: Textural analysis soil types in the Lena catchment

Table 3-2. Class definition for agricultural soils in Lena and Hunnselva catchment Soil class Definition Description Sand coarse sandy soils Clay content (particle size < 2 mm) < 15 %; gravel + coarse sand + medium sand > fine sand + silt Silt silty/fine sandy soils Clay content < 15 %; fine sand + silt > gravel + coarse sand + medium sand Loam loamy soils Clay content 15 – 25 % Clay clays/silty clay soils Clay content > 25 % Organic soils organic soils, peat soils Containing humus rich mineral soil (6-20 % soil organic matter (SOM)), humose soil (20 – 40 % SOM), humified peat (40 – 75 % SOM)

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3.4 Pollution sources in Hunnselva and Lena The Hunnselva is discharging into the Mjøsa Lake at Gjøvik. Power development over time has lead to interventions in the river flow. Also with reference to the pollution rather large challenges have been faced over time, both from industrial activities, use of excess fertilizer and untreated sewage runoff from scattered dwellings in the upper part of the catchment.

Hunnselva has considerably contributed in the pollution of the Mjøsa lake in the early 70‘s, mainly through the runoff of organic waste, runoff wood processing industry and paper mills. But also considerable pollution was produced metal and galvo-technical industry. The river was characterized as one of northern Europe‘s most polluted rivers. Already during the 1800 trout was no longer present in the river system, the river was for a long time without life. However a considerable improvement in water quality has been achieved over time partly due to the construction of treatment systems both for industry but also for scattered

Norwegian Institute for Water Research (NIVA) is carrying out water quality monitoring program of Mjøsa Lake and its main contributors ( task from ‗Vassdragsforbundet‘), including among others nutrient concentrations and loads. The results show that the total P load to the Mjøsa has been reduced from ca 120 -170 ton/yr at around 1980 to approximately 65 – 90 tonn/yr during the per3tiod from 2001 – 2007, a reduction of more than 40%. However the concentrations of both N and P show that both the Hunnselva and Lena River have poor water quality. The N-tot concentration in the Hunnselva River varied from 1229 - 1499 μg/l which according the Norwegian State Pollution Board (SFT) can be classified as very poor. The P-tot concentrations varied from 16 - 30 μg/l, which according to SFT can be classified as very poor.

Hunnselva is the highest contributor in P runoff to the Mjøsa Lake, having an area specific contribution of 18 kg P/km2.yr in 2007, with the Lena river being second worse, contributing with ca 11 kg P/km2.yr. The remaining smaller rivers discharging into the Mjøsa contributed significant less. Also concerning N the Hunnselva is, together with the Lena river, the largest contributor to the Mjøsa Lake, having an area specific contribution of 700 kg N/km2.yr

Increased concentrations N can seriously affect species composition and lead to growth of bulbous rush (Juncus bulbous/supinus). On the other hand, increased P concentrations can lead to algae blooms, especially as this element is considered being the limited element for algae growth in freshwater systems. This also means that N level in this respect is less critical. Research however carried out by NIVA has shown that a change in the composition of algae and macro - phytes can be linked to changes in N concentrations.

The Hunnselva is also characterised by the presence of a river mussel (Margaritifera margaritifera). This species live in close existence with salmon and trout and is extinct in from many countries in Europe. Mussels are very sensitive to nitrogen and therefore nitrogen runoff from land-based activities should be controlled and if possible reduced.

A conclusion for the main Hunnselva river can be that since long the water quality in the watershed has been influenced by human activities which can be summarized originating from 1) regulations for hydro-power production, 2) nutrients, organic matter and coli bacteria from scattered housing, 3) nutrient losses, pesticides and sediments from agriculture and 4) toxic effluent from industry and waste deposits, road salt and other runoff from road systems. Most influenced by pollution is the lower section of the Hunnselva River. The smaller - and contributing streams to the main river are to a low degree influenced by the pollution.

34 STRIVER Deliverable D7.1 Part 1

3.4.1 Agriculture The total agricultural area in the Hunnselva catchment is approximately 55 km2 while this in the Lena catchment is 109 km2. The dominating crops grown are grain crops with an average share of 63% and 71% during the last 8 years for the Hunnselva and Lena catchment respectively. The dominating grain crops are barley and oats. The area covered by grass and fodder crops represents a significant part of the agricultural land in both catchments. Also vegetable crops and berries are grown in the catchments representing a larger part in the Lena catchment compared to the Hunnselva (Table 3-3).

Table 3-3. Distribution of agricultural crops and livestock numbers in Hunnselva and Lena catchment (1999 – 2007, source; Norwegian national Statistics/SSB) Agricultural crops, Livestock distribution (%) Hunnselva Lena Hunnselva Lena Grain/oilseeds 63 71 Cattle 7262 12261 Grass/fodder 32 17 Pigs 6095 15898 Vegetables/potato 0 7 Chicken 24084 298938 Strawberry, other 0 1 Sheep 7288 20113 Other 4 4

In the Hunnselva, animal husbandry is mainly practiced on the western side of the Eina lake and in Vesleelva1. Animal manure is spread both before (70 %) and after the growing season (30 %). In the last case ploughing is practices to reduce potential surface runoff losses from animal manure. Often spreading in the autumn is related to a limiting manure storage capacity at the farm level.

A common soil tillage practice in grain production is ploughing, both in autumn or spring, followed by harrowing and sowing. Both grain crops are sown during spring time while at the same time applying fertilizer. In general the harvest takes place in August. Soils which are ploughed in autumn are prone to erosion and the subsequent loss of phosphorus. Phosphorus is one of the main reasons for the deteriorating inland water quality. Often incentives are available to change to more environmental friendly tillage methods one of them being the change in tillage method from autumn ploughing into light autumn harrowing. According to stakeholder information only approximately 40 % of the agricultural land has spring tillage.

Fertilizer application for grain crops varies over the years. An example is shown for the Kolstad catchment, a small agricultural catchment located on the eastern side of Lake Mjøsa (Figure 3-11, Figure 3-12). The catchment is part of JOVA, the agricultural environmental monitoring program in Norway. Data are collected to provide information on the runoff, nutrient and soil loss in addition to information about farming practices. Information about fertiliser application has been collected since 1991. The applied amount of fertilizer in the Kolstad catchment is higher than the recommended fertilizer application (Table 3-4). Information related to fertilizer application provided by stakeholders in Hunnselva/Lena indicates that the applied fertilizer application is higher than recommended and varies from 8 – 14 kg.(0.1 x ha-1) for N and from 1 – 5 kg.(0.1 x ha-1) being more in line with the applications for Kolstad.

1 Based on information during field trip in the Hunnselva basin

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Figure 3-11; Nitrogen application to dominating crops in Kolstad catchment

Figure 3-12: Phosphorus application to dominating crops in Kolstad catchment

Table 3-4. Recommended fertilizer application to various crops (according to Bioforsk/Apelsvol) Expected yield Fertilizer application

kg. (0.1 x ha)-1 (kg. (0.1 x ha)-1) N P K Barley 400 9.5 1.4 7.0 Oats 400 8.5 1.4 7.0 Potato 3000 10.0 4.5 15.5 Grass - one harvest 11.0 1.6 7.0 - two harvests 15.0 1.6 8.5 - three harvests 18.0 1.6 10.0 - four harvests 20.0 1.6 11.5 Strawberry 4-8 1-2 4-6 Cabbage 6000 30.0 4.0 24.0 Cauliflower 1500 24.0 3.0 18.0 Broccoli, 800 18.0 4.0 16.0 Turnip 4000 10.0 4.0 10.0 Carrot 5000 10.0 5.0 14.0 Onion 3500 12.0 6.0 14.0

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3.4.2 Industrial Activities and Urban settlements The main industry in Hunselva is located downstream in the catchment (Figure 3-13). In the Lena cathcment there is no industry. Urban discharges are connected to Waste Water treatment plants in addition there are also some discharges from scattered dwellings. Municipalities and WWTP owners report their data in an electronical system. Values for discharge of nutrients from WWTP are based on measured values in cases where this exists, otherwise it is theoretically estimated. The data are given in Annex to Chapter 3.

Figure 3-13 Industry and waste water treatment plants (WWPT) in the Hunnselva and Lena catchments.

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3.5 Literature

Bullock, M.S., Kemper, W.D, and Nelson, S.D., 1988. Soil cohesion as affected by freezing, water content, time and tillage. Soil Science Society of America Journal 52: 770-776. Frame, P.A., Burney, J.R. and Edwards L., 1992. Laboratory measurements of freeze/thaw, compaction, residue and slope effects on rill erosion. Canadian Agricultural Engineering, 34: 143 – 149 Glossary of Terms in Soil Science, 2005. Research Branch, revised 1976. Canada Department of Agriculture, Ottawa. Publication 1459, 44 pp, (http://sis.agr.gc.ca/cansis/glossary/ freezing_index,_f.html, October 2005). Kværnø, S.H., Øygarden, L. and Deelstra, J., 2005. How is soil aggregate stability and infiltration capacity influenced by unstable winters? Importance for runoff and erosion from agricultural areas. Grønn Forskning 9(2): 140 – 147. ISBN 82-479-0517-5 (In Norwegian). Bechmann, M. E., Kleinman, P. J. A., Sharpley, A. N. and Saporito, L. S., 2005. Freeze–Thaw Effects on Phosphorus Loss in Runoff from Manured and Catch-Cropped Soils. Journal of Environmental Quality. 34: 2301-2309. Deelstra, J., Kværnø, S.H., Granlund, K., Sileika, A.S., Gaigalis, K., Kyllmar, K., Vagstad, N. Runoff and nutrient losses during winter periods in cold climates - requirements to nutrient simulation models. Accepted for publication in Journal of Environmental Monitoring, 2009. Zuzel, J.F., Allmares, R.R. and Greenwalt, R., 1982. Runoff and erosion on frozen soils in northeastern Oregon. Journal of Soil and water Conservation, 37: 351-354. Klaveren, R. W. van, McCool, D. K. 1998. Erodibility and critical shear of a previously frozen soil. Transactions of the ASAE, 41: 1315-1321.

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4. Impacts: water quality analysis in Tungabadhra

Suhas Paranjape and K.J. Joy (SOPPECOM)

4.1 Introduction: Stakeholder perceptions of the problems The presentations by the officers of the Karnataka State Pollution Control Board (KSPCB) during the stakeholder meetings clearly show that there are four main sources of pollution. They are a) industries, b) run off from agricultural fields, c) discharge of sewage from municipalities (towns) and d) mining. There are four major industries in the river basin that are permitted to discharge treated effluents into the river as per the law. Amongst them two are private sector industries and other two are government (public) sector ones. These four industries discharge about 90,000 m3 per day of treated effluents into the river2. According to Shama Pawar of The Kishkindha Trust (TKT), an NGO working in the basin, a distillery unit in the area discharged 6000 tonnes of molasses into the river a few years back resulting in fish death. After public protests, the government instructed the distillery unit to discharge water only after proper effluent treatment. Efforts were also made to pump in oxygen into the affected area Two major iron mining areas, i.e., Kudremukh and Hospet, exist in the river basin. There are no proper mining standards for iron ore extraction, which is open cast mining. Earlier mining was restricted to mine heads, but now it is done at the foothill level also. Apart from the impact on water quality due to the silt from mines, there is also the issue of air pollution (due to the way the ore is transported in open trucks and also the truck movement causes dust nuisance). Agriculture in the region is also getting affected because of mining related dust pollution as the dust gets deposited on crops. There does not seem to be any scientific study conducted to assess crop losses and damage caused by air pollution due to mine dust. In the town municipalities, there are no proper drainage and sewage facilities and sewage is discharged directly into the river. Apparently only in a couple of municipalities there are treatment plants, but not in working condition. Application of chemicals and pesticides in the agriculture area, especially on paddy crop, is another source of water pollution. There are no systematic studies about these non-point pollution sources. There was a recent (in 2006) incident of spraying of pesticides intensively for the paddy crops that affected the water in the river, which also caused lot of foul smell and people were cautioned not to drink the water for some time. Sand mining from the riverbed using mechanized boats though they are not permitted is also causing degradation of the river and is affecting the water quality.

4.2 Monitoring of water quality and related environmental data

The Central Pollution Control Board (CPCB) and the State Pollution Control Boards (SPCBs) for the respective states are the only bodies responsible for the monitoring and control of pollution. They were first set up under the 1974 Water Act. Subsequently their mandate was progressively expanded. At present they are responsible for implementation of a number of pollution related Acts, their various amendments and Rules framed under them. These include a) The Water (Prevention and Control of Pollution) Act, 1974, b) a) The Air (Prevention and Control of Pollution) Act, 1981 and c) The Environment (Protection) Act, 1986. It is especially the Environment Act that has significantly expanded the scope of the activity of the various PCBs. The Rules and Notifications under it have progressively covered a) Hazardous Waste, b) Manufacture, Storage and Import of Hazardous Chemicals, c) Environment Impact Assessment, d) Bio Medical Waste, e) Plastics Manufacture, Sale and Usage, f) Noise Pollution, g) Municipal Solid Waste and h) Batteries.

2 The two important private sector units are of Gwalior Rayon Silk Manufacturing (Weaving) Company Ltd (Grasim) located on its banks at harihar in district of Karnataka. These two industries together generate approximately 33,000 m3 of effluents.

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The individual stretches of the Tunga and the Bhadra river as well as almost all the stretch of the Tungabhadra formed by their confluence lies within Karnataka state, except for a small stretch before it meets the Krishna which falls within Andhra Pradesh. Also it has proved somewhat difficult to get data from the Andhra Pradesh Pollution Control Board (APPCB). Hence most of the description that follows deals mainly with the stretch of the river in Karnataka state, which in any case forms a major portion of it, and relies mainly on the data from the Karnataka State Pollution Control Board (KSPCB) and the Central Pollution Control Board (CPCB). In Karnataka, the Tungabhadra (always understood to include the individual stretches of the Tunga and the Bhadra) is being monitored under three programmes: at one location under the Global Environmental Monitoring System (GEMS), at six locations under the Monitoring of Indian National Aquatic Resources (MINARS) programme, and at eight locations under the Tungabhadra Board‘s programme. A map of all the monitoring locations under all programmes for the Tungabhadra river is given below (Figure 4-1).

Figure 4-1: Tungabhadra Basin KSPCB Water Sampling Stations

However, there is considerable variation in the number of parameters monitored at the different stations over the years. After 2001, the KSPCB decided to restrict the number of parameters monitored and this creates a hiatus in the data. Inspection of the data provided by the KSPCB showed that at most five parameters at ten locations could be traced over a sufficiently long time period (from 1986 to 2005). Those locations are given below (the Harihar point represents a cluster of five locations) (Figure 4-2).

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Figure 4-2: The ten monitoring stations in Tungabhadra: 1) Koodli, 2) Honnali Bridge, 3) Harihar: Intake Point, 4) Harihar: Jackwell Point, 5) Harihar: upstream (U/S) of Poly Fibres (HPF), 6) Harihar: Downstream (D/S) of HPF, 7) Harihar: New Bridge, 8) Haralihalli Bridge, 9) Ullanur, 10) D/S of Gangavati.

4.3 Analyses of the water quality levels, trends, spatial and temporal variability

4.3.1 Prescribed Standards There are various standards set up for allowable concentrations of and parameters related to pollution. The most relevant are the drinking water standards specified by IS 10500:1991 (

41 STRIVER Deliverable D7.1 Part 1

Table 4-1). More detailed standards are also recommended by the CPCB for different classes of surface waters and by the Bureau of Indian Standards (BIS) for Drinking Water (See Annex to Chapter 4).

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Table 4-1: Standards prescribed for Drinking Water in India Highest Max Permissible Limit in Substance/Characteristics Desirable/Essential Desirable Limit Absence of Alternative source (ppm) (ppm) Calcium Desirable 75 200 Magnesium Desirable 30 100 Iron Essential 0.3 1 Chloride Essential 250 1000 Sulphate Desirable 200 400 Nitrate Desirable 45 100 Fluoride Desirable 1 15 Total Dissolved Solids Desirable 500 2000 pH Essential 6.5-8.5 No relaxation Total Hardness Essential 300 600 Source: Bureau of Indian Standards: IS 10500:1991

River waters and water bodies have been classified into 5 classes as follows:  Class A: Drinking water source without conventional treatment but after disinfection  Class B: Outdoor bathing  Class C: Drinking water source with conventional treatment followed by disinfection  Class D: Propagation of wild/aquatic life  Class E: Irrigation, industrial cooling and waste disposal

The KSPCB data for 2005-2006 show that the river can be safely classed as Class C throughout the year, while many locations may also be classed as Class B for some parts of the year and only exceptionally can a monitored river stretch be classed as Class A.

4.3.2 Pollution hotspots identified by the CPCB

Pollution has long been a recognized problem in the Tungabhadra and the CPCB has often taken note of this while reviewing data at the national level. For example, in its Pollution, Assessment, Monitoring & Survey document on the National Water Quality Programme it identifies four stretches in the Tungabhadra basin as follows (Table 4-2).

Table 4-2: Polluted stretches in the Tungabhadra basin according to the CPCB Critical Parameters River Polluted Stretch Source/Town (mg/l) Karnataka Maleshwaram to D/s of Industrial & Domestic waste Bhadra BOD- 7.2 Bhadravathi from Bhadravathi Tunga D/S of Shimoga Shimoga Sewage BOD > 6 Kali Along Dandeli Town West Coast Paper Mill waste BOD > 6 Harihar D/S to Hara eahalli Harihar Sewage & Grasim Tungabhadra BOD- 6-8 Bridge. waste Source: Pollution, Assessment, Monitoring & Survey, CPCB

In its detailed findings, CPCB mentions Tungabhadra sub-basin in the following respects:  The groundwater monitoring locations, where high conductivity exceeding water quality criteria for irrigation (Tungabhadra river in Kurnool and Nandyal in Andhra Pradesh)

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 Potentially polluted locations having higher BOD levels not meeting the water quality criteria (Tunga D/s of Shimoga town; Bhadra at Maleshwaram D/s of KIOCL, Bhadra at D/s of Bhadravati).

The KSPCB has also identified locations in the basin as hotspots with respect to drinking water quality (Table 4-3).

Table 4-3: Deteriorating water quality - Hotspots in Krishna Basin Problem Hotspot location Davangere (Tungabadra river Davangere and Harihar), Shimoga (Bhadra river- Surface Water Bhadrvathi and ), Bellary and Koppal (TB river), Bagalkot (Krishna river) Ground Water Tumkur, Chitradurga, Gadag, Bagalkot, Davanagere, Dharwad, Haveri, Bellary Seepage of Fertilizer Raichur, Koppal, Belgaum, Dharwad, Chikkamangalore, Shimoga, Bellary and Pesticides Adapted from the Basinwise Table on Hotsopts in the Water Resources chapter in the State of the Environment Report 2003, Karnataka.

4.3.3 pH Values, Dissolved Oxygen and Biological Oxygen Demand Only three main parameters are reported as these have been consistently monitored for specific locations over time. These are pH, Dissolved Oxygen (DO) and Biological Oxygen Demand (BOD). The data for the ten locations is provided in Annex to Chapter 4. The summary data is presented below. pH values Figure 4-3 (A) presents the variation of pH values along the river (left to right represents u/s to d/s). The allowable pH values are given as 6.5 to 8.5 and the average pH values manage to stay just within that range. However, it is clear that there is a steady increase in pH as we proceed downstream and the pH value travels from the low extreme to the high extreme. Even more important is the variation of maximum and minimum values. The values here open out like a scissor varying from a minimum of 7 to a maximum of about 8 in the upstream, while it varies from a minimum as low as 5.5 to a maximum of 9.5 at Ullanur. It shows that even though the average value manages to be within the allowable range there are apparently periods when the values are outside allowable limits on both sides. For purposes of comparison we have divided the time span into four different periods: 1985 to 1990, 1991-1995, 1996-2000, and 2001 and later. A comparison of average pH values along the river for these periods (Figure 4-3, B) shows that there has been a steady improvement in the average pH values over time, except for the downstream portion of the river stretch. Except for Ullanur and Gangavathi, the rest of the locations show high pH values that generally come down over time. However, values downstream of Ullanur continue to be high. One possible reason for this is the abandonment of Kudremukh mining in the nineties as well as the improvement in process technology by the Harihar industries under pressure. Meanwhile mining continues unabated in the Bellary district and that may be behind the higher levels at Ullanur and downstream. Seasonal variation is also important. Comparison of seasonal variation along the river (See Figure 4-3, C) corroborates similar trends. Expectedly, the monsoon values lie well within the allowable range. However, here too the downstream values are too close to the allowable limits for comfort. Winter values again are expectedly higher and summer values even more so. All values lie essentially within the allowable ranges, but we must remember that these are average values and the variation already seen for maximum and minimum values means that there will be significant periods when the values lie outside the allowable range.

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10 9 9 9 8.5 8.5 8

8 8

pH pH 7 pH 6 7.5 7.5 5 7 7 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10

A Max Average Min B 85-90 91-95 96-00 01+ C Monsoon Winter Summer

12 8 9 9 6 8 6 4 7

DO mg/lDO 3 DO mg/lDO 2 mg/lDO 6 0 0 5 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 D Max Average Min E 85-90 91-95 96-00 01+ F Monsoon Winter Summer

40 5 5 30 4 4 3 20 3

2

BOD mg/l BOD mg/l BOD 10 1 mg/l BOD 2 0 0 1 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10 1 2 3 4 5 6 7 8 9 10

G Max Average Min H 85-90 91-95 96-00 01+ I Monsoon Winter Summer Figure 4-3: Charts [A-C: pH, D-F: DO, G-I: BOD] show variation in respective parameter min-max values, average values for different periods and average values for different seasons respectively along the river. See Figure 4.2 for sites name and location.

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Dissolved Oxygen (DO) Values Similar comparisons can be found for variation of DO values along the river, along the river in different periods and seasons. The average DO value is around 6, above the recommended value of 4 and this is true all along the river (Figure 4-3, D). However, it is the low value, which is alarmingly low, almost zero all across the stretch of the river. The exception is Kudli, but Kudli has a very short time series. This can be correlated to the DO values across different periods (Figure 4-3, E). They show a striking variation. The 1985-90 values improve in the 1991-95 period but fall drastically in 1996-2000 and again recover though not fully in the coming period. The period 1996-2000 seems to be a particularly bad period and it was also the period when public protest against pollution had peaked. Variation across seasons shows that average values do not change very much with seasons except for a few locations, where monsoon values are significantly higher (Figure 4-3, F). For all locations, however, winter and summer values are very close but above recommended values.

Biological Oxygen Demand (BOD) Values Comparisons for variation of BOD values along the river, along the river in different periods and seasons are given below in Fig.s 9, 10 and 11 respectively. The average BOD value varies between 1 and 4, and does not vary too much along the river course (Figure 4-3, G). However, the maximum values, even after allowing for some anomalous outliers are quite high. The variation across different periods does not show the same pattern as the DO values. While DO values dipped in 1996-2000, here we have a somewhat steady increase in BOD values (Figure 4-3, H). One interesting possibility is that the role of chemical pollution has been replaced by biologically active sewage pollution. However this will need more corroboration. Variation across seasons shows an expected pattern with BOD values generally increasing in the sequence monsoon, winter and summer (Figure 4-3, I).

4.4 Faecal and Total Coliform and Nitrogen values Besides the three main parameters pH, Dissolved Oxygen (DO) and Biological Oxygen Demand (BOD) that have been consistently monitored from 1985, faecal coliform, total coliform and nitrogen values are also available for longer periods and summary trends are presented below (Fig. 4.4). The basis of monitoring underwent a radical change after 2002 and the number of parameters regularly monitored was severely curtailed. Also, after 2002, nitrogen values were no longer tabulated. The tabulated values after 2002 are those of nitrate and nitrite. Care is therefore needed in extrapolating trends across this divide. In the presentation we have preferred to show trends only up to 2002 for nitrogen. In what follows we shall also describe the limitations of the data that are presented.

4.4.1 Faecal and Total Coliform The standards specify maximum permissible limits for total coliform (Annex to Chapter 4) for different classes of waters: these values are 50, 500 and 5000 for Classes A (Drinking water – surface water without conventional treatment but after disinfection), B (Outdoor bathing – organized) and C (Drinking water source with conventional treatment followed by disinfection). Since most of the river water is supposed to be used after conventional treatment and disinfection, for purposes of assessing the situation in Tungabhadra basin, we may take 5000 as the norm for the maximum permissible limit. Faecal coliform should be even lower.

The data for faecal coliform and total coliform also suffer from certain anomalous reporting. In many of the observations the practice is that of recording the value as `above value X' where X is a specific cut off value. Unfortunately, this value is not uniform, different cut off values have been used in different periods and they vary from as low as 1600 to as high as 24000. In what follows we have used reported values where available and used cut-off values where values have been reported as being greater than cut off value. This implies that values above 1600 may reflect broad changes, but will not be accurate. This needs to be kept in mind in interpreting the charts.

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Figure 4-4, A and D present the variation of faecal and total coliform values, respectively along the river in nine locations. In the foregone we have presented maximum, average and minimum values for the parameters. However, the maximum values here lack accuracy because of the cut off value problem described above. Also, the minimum values are invariable very close to zero. For this reason, we have decided to report only the average values.

As we may see, the average values for total coliform lie mostly below 5000. However the values are higher in the last two downstream locations. What should be more worrying is that the values for faecal and total coliform are quite close. It is not clear how far this is due to the cut off value reporting, but it is something that does need to be taken into account. However, if we look at the variation with time (Figure 4-4, B and E, respectively) we may see that the higher averages are for the earlier periods, and that after about 1995, we have average values which are much lower. This is again consistent with the trend of pollution peaking in the nineties and then tapering off. Season wise variation (Figure 4-4, C and F, respectively) shows, expectedly, that monsoon values are much lower.

4.4.2 Nitrogen and nutrient Nutrient load is related to nitrates rather than to total nitrogen. Not all of nitrogen need be in the form of nitrates. However, in the absence of direct values, we may make a provisional assumption, purely for purposes of broad assessment that all nitrogen is in the form of nitrates. This would give us a somewhat higher estimate of nitrates, and this we need to keep in mind. From this point of view, the permissible limit for nitrates for the corresponding class of waters is 50 mg/l and this would translate into about 12 mg/l. With this in view let us turn to the charts.

Minimum values for total nitrogen tend to be near-zero for all locations and we have therefore not reported minimum values in the charts. Figure 4-4, G gives us the variation of maximum and average values along the river. As we may see average values fluctuate around 2 mg/l, well below the proxy limit of 12 mg/l. However, maximum values are close to this value. And there is not much variation along the river. Figure 4-4, H shows the variation in average values for different periods. These values too, for the most part, follow the trend of peaking in the nineties and then receding, but significantly, they do not fall back to older values, but remain substantially higher. This implies that the problem needs special attention. Moreover, for the most downstream points, values are peaking now and since most of the contribution in that zone would come from the irrigated command areas of the Tungabhadra project, it highlights the need for a change in crop practices in these areas.

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4,000 8,000 5,000

6,000 4,000 3,000 4,000 3,000 2,000 2,000 2,000

1,000 0 1,000

2 3 4 5 6 7 8 9 10 2 3 4 5 6 7 8 9 10 2 3 4 5 6 7 8 9 10

Faecal coliform MPN/100 ml MPN/100 coliform Faecal Fecal coliform MPN/100 ml MPN/100 coliform Fecal ml MPN/100 coliform Faecal Average 85-90 91-95 95-00 01+ Monsoon Winter Summer

5,000 8,000 6,000 5,000 6,000 4,000 4,000 4,000 3,000 3,000 2,000 2,000 2,000 1,000 Total coliform MPN/100 ml MPN/100 coliform Total 0

2 3 4 5 6 7 8 9 10 2 3 4 5 6 7 8 9 10 2 3 4 5 6 7 8 9 10 Total coliform MPN/100 ml MPN/100 coliform Total

ml MPN/100 coliform Total Average 85-90 91-95 95-00 01+ Monsoon Winter Summer

14 10 4 12 8 10 3 8 6 2 6 4

4 1 Nitrogen mg/l Nitrogen 2 2 mg/l Nitrogen

Total Nitrogen mg/l 0 0 0 2 3 4 5 6 7 8 9 10 2 3 4 5 6 7 8 9 10 2 3 4 5 6 7 8 9 10

Max Average 85-90 91-95 95-00 01+ Monsoon Winter Summer

Figure 4-4: Charts [A-C: Faecal coliform, D-F: Total coliform, G-I: Nitrogen] show variation in respective parameter min-max values, average values for different periods and average values for different seasons respectively along the river.

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4.5 The IWMI study on environmental flows An important study by the International Water Management Institute (IWMI) on environmental flows deals with the Tungabhadra basin. It proposes a detailed set of indicators regarding the ecological conditions in a basin (Annex to Chapter 4). It divides the Tungabhadra basin into three reaches (higher, middle and lower) and provides the following set of indicators for characterising the ecological conditions in the basin (Table 4-4).

Table 4-4: Indicators for the Tungabhadra sub basin of the Krishna River Basin. Indicator Value Score Justification and Comments Data Sources An arbitrary but quantitative scoring system is used based on the percentage of endangered fish species of the total species in the basin (>20% endangered species—very high, 10–20%—high, 5–10%— moderate, 2–5%—low and <2%—minor or none). Arunachalam (2004)

Rare and Of the total 118 species in the sub-basin, CAMP (1997) endangered High 4 12 are endangered and critically aquatic biota endangered in the headwaters (10.1%). Arunachalam et al. In the middle reaches, 5 endangered Moderate 3 (2002) species are represented (4.2%). In the lower reaches only 3 such species Low 2 are represented (2.5%). A similar scoring system is used as for endangered species—based on a percentage of unique fish of the total fish species in the basin (>20% endangered species—very high, 10–20%–high, 5–10%— moderate, 2–5%—low, <2%—minor or none). Out of 118 fish species, 9 endemics (7.6%) Arunachalam (2004) Moderate 3 are present in the headwaters. Unique CAMP (1997) In the middle and lower reaches, 2 endemic aquatic biota Minor 1 species (1.7%) are present. Arunachalam et al. Headwater reaches support more unique fauna because the streams (2002) in the Western Ghats are mostly bedrock valleys and are strongly confined. Out of 11 endemic species 5 species (Barilius canarensis, Glyptothorax trewavsae, Botia straita, Longischistura bhimachari and Hypselobarbus dobsoni) have narrow distribution. In the upstream reaches of Tunga and Bhadra, falls, cascades, pools, riffles, High 4 glides, runs and ‗pocketwater‘ are all Arunachalam (2004) present. In the middle reaches, reservoir habitat Jayaram (1995) Diversity of types are wetlands and deepwater, while aquatic Moderate 3 downstream of reservoirs and the reaches Scott (1989) habitats in between—runs, deep pools and backwater habitats are present. Arunachalam et al. In the lower reaches, the only habitat types (2005) Minor 2 are runs with fine sand and occasional large pools. The sub basin has 1.62% as protected area with two wildlife sanctuaries (Bard and Presence of Arunachalam (2004) Ghataprabha) and the Kudremukh National protected and 1 – 3 % 2 Manjrekar (2000) Park. More forests can be protected as pristine areas Jayaram (1995) buffer zones of the Kudremukh National Park and sanctuaries. Percentage of In the headwaters almost all the streams Arunachalam (2004) 70 – 100 % 5 watershed are under natural cover type (90%).

49 STRIVER Deliverable D7.1 Part 1 remaining In the reservoirs and the reaches 10–15 km Jayaram (1995) under natural downstream of them, the percentage of vegetation 50 – 70 % 3 natural cover is under 65%, but in most of (for middle and lower the middle reach the percentage is under reaches) 50%. In the lower reach in the Karnataka part up 10 – 30 % 2 to the confluence of Tungabhadra with Krishna river: 28–30%. Percentage of Floodplains are present in the middle and lower reaches only. floodplain Middle reaches before the Tungabhadra 30 – 50 % 3 remaining Reservoir. under natural 2 From the Tungabhadra Reservoir 10 – 30 % 2 vegetation towards the AP boundary. In the headwater reach there are no exotic 0 5 fish species Percentage of In the middle reaches, particularly—in the Arunachalam (2004) aquatic biota reservoir sector—introduced species of that are Cirrhinus mrigala, Labeo rohita are Sugunan (1995 exotics < 5 % 4 present. But the proportion in rivers upstream and downstream of the reservoir is still small in spite of having introduced these species 40 years ago. Upstream reach is represented by 68 50 – 70 % 4 species (57.6%) of the total 118 recorded in the sub basin Middle reach is represented by 78 species 70 – 100 % 5 Arunachalam. (2004) (66.1%). Fish species Lower reaches are represented by 31 Jayaram (1995) 30 – 50 % 3 relative species (26.3%) richness Ponniah and A different scoring system should be designed, which is based on the Gopalakrishnan total number of species present in India, or in the region. But the (2000) estimates of the total number of species nationally vary from 327 (CAMP 1997) to 577 (Arunachalam 2004). If the latter figure is used as a benchmark, the basin is estimated to support 20.4% of this total species. Human population District Planning density in the Score is based on mean values from middle Maps 2001, basin as a and lower reaches, which have an indicator < 10 % 1 percentage of value of 7%. Floodplains have been Karnataka. Census of that in the delineated using GIS. India (2001) main floodplains Headwaters are under relatively natural conditions with high levels of dissolved A 5 oxygen, low levels of TDS, very low Arunachalam (2004) Overall water alkalinity and no enrichment of nitrates and quality in the phosphates Jayaram (1995) basin In the middle and lower reaches, non-point and point sources of pollution and nutrient CPCB (1992) C 3 enrichment from paddy fields contribute to the pollution. CPCB (1992) Adapted Valdimir Smakhtin, Muthukumarasamy Arunachalam, Sandeep Behera, Archana Chatterjee, Srabani Das, Parikshit Gautam, Gaurav D. Joshi, Kumbakonam G. Sivaramakrishnan and K. Sankaran, Developing Procedures for Assessment of Ecological Status of Indian River Basins in the Context of Environmental Water Requirements, IWMI research report 114, IWMI, Colombo.

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4.6 Impact on fish One of the important indicators of water quality is the impact on fish and other aquatic life. However there are contradictory evidences in this regard. Of course the impacts are due to either water quality or pollution and changes in fishing practices often leading to over exploitation. All the three stakeholder meetings clearly brought out the impact of deteriorating water quality on fish. Many stakeholders narrated incidents of fish kills and also how over the years the fish has been on the decline. For example, according to Mr. Gireesha, Assistant Director of Fisheries, Shimoga, ―there were nearly 120 species of fishes in the river, among them 28 species are threatened due to over exploitation and pollution‖. According to him the fish yield decreased by 50% over 10 years - fish catch decreased from about 1200 tonnes to 650 tonnes in a year. However, there are studies that indicate an increase in the fish production. In the case of Tungabhadra reservoir, there has been a reported increase in catch from 15 to 156 t during 1950s and '60s to 2 068 to 4200 t during 1980s. This increase in fish production is accompanied by matching increase of fishing effort, especially in the form of shore seines. According to a latest survey, the fish production during 1993 was estimated at 1500 to 1600 t i.e., 40 to 42 kg/Ha. The higher production notwithstanding, the most disconcerting fact remains that 88 - 92% of the yield emanates from the destructive gear called alivi (a small-meshed giant shore seine which removes small fishes of all categories in large numbers, Singit et al., 1987). Another important impact has been on the fish species especially due to impounding of water in large reservoirs. Tungabhadra reservoir, when it was impounded, had a population of Puntius kolus, which contributed up to a third of its total catch. Other species of Puntius (P. dubius, P. sarana and P. pulchellus), Tor tor, Labeo fimbriatus, L. calbasu, L. porcellus, L. potail and L. pangusia formed the other indigenous forms (Krishnamoorthy, 1979). Most of the native species found the changed environment after impoundment hard to cope with and started declining, the main reasons being destruction of breeding grounds, absence of fluviatile environment, and the changed trophic structure. Their share in the total fish catch has declined drastically from 74.89% in 1958 to 28.91% in 1965 (Table 4-5). Unlike the case of reservoirs in Tamil Nadu, no serious attempts were made in Tungabhadra to introduce Indo-Gangetic major carps to fill the vacant niches created by the receding population of Puntius and Labeo species. As a result, the carp minnows and minor weed fishes took advantage of the new spurt in plankton and benthic communities and these fishes, in turn, provided good forage to predatory catfishes.

Table 4-5: Changes in species composition of fish catches in Tungabhadra reservoir during 1958-1965 Percentage Total fish catch Year Indo-Gangetic carps Catfishes Indigenous carps Miscellaneous (t) 1958 0.18 22.15 74.89 2.78 15 1959 0.21 36.05 59.91 3.71 11 1960 0.23 47.00 48.93 3.88 29 1961 0.53 32.97 63.15 3.12 24 1962 0.38 33.14 64.47 1.95 24 1963 1.07 36.11 57.45 5.39 68 1964 0.18 67.90 31.46 1.57 133 1965 1.50 75.70 28.91 3.80 156 Source: Krishnamoorthy, 1979

The issue of water quality and the availability of fish have added significance as they are directly related to the livelihoods of a large number of families in the basin. The number of families depending on fisheries for their livelihoods in the river basin is about 11,000 (3000 families in the Tunga, 2000 families in the Bhadra and 6000 families in the Tungabhadra).

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4.7 Response from civil society and state The primary agency responsible for monitoring, control and prevention of water pollution at the state level is the respective state pollution control boards. In the case of Tungabhadra river, as mentioned earlier, two state pollution control boards are involved, namely the Karnataka State Pollution Control Board (KSPCB) and the Andhra Pradesh State Pollution Control Board. As part of the STRIVER Project the research team had opportunity to interact with the KSPCB extensively and many of their officers have been participating actively in the stakeholder meetings. The reactions during the stakeholder meetings to the performance of the KSPCB had been mixed. Some of the stakeholders clearly felt that because of the various measures taken by KSPCB in terms of active monitoring of the hotspots the water quality has improved over the years. Of course the KSPCB has been pressured to take proactive steps only because of the pressure from below by the civil society organisations. There is also the other side which feels that enough is not being done by the KSPCB even to the extent of accusing it to be in hand in glove with the polluting industries. During the second stakeholder meeting at Davanagere, Mr. Shanmughappa, District Environmental Officer of Shimoga narrated the efforts of the KSPCB in improving the water quality. For example efforts were made to reduce the effluents discharge from the two industries, namely, Steel Authority of India (SAIL) steel plant and Mysore Paper Mills, both in . SAIL is reusing its effluents for cooling and in scrubbers. Also, Mysore Papar Plant has brought down its effluents to half due to stringent rules, and they have also brought down their water consumption. The paper industry lowers its production in summer in order to reduce water intake and the discharge, since the discharge gives colour to the river water, which is harmful for the aquatic life. Under the National River Conservation Plan (NRCP) efforts are being made to erect sewage treatment plants in towns of Bhadravati and Shimoga, to construct both community and individual toilets for the poor people staying on banks of the river will be constructed and also construct crematoriums.

These efforts, though fragmented, have been necessitated mainly by the consistent agitations and protests by the people in the basin especially spearheaded by the Samaj Parivarthan Samudya (SPS), based at Dharwad. An umbrealla organization called Tungabhadra Parisara Samiti was formed to fight pollution related issues. Most of the agitations have been against Harihara Polyfibres and Grasim industries. According to S. R. Hiremath, of SPS, who led the movement against pollution, apart from resorting to agitations and protests they also took the lead in undertaking scientific studies and submitted the reports to KSPCB. A case was registered in the Karnataka High Court and based on the conditions of fisheries and occupational health, the Court asked the industries to clean up the river. A local watchdog committee was also formed to monitor the pollution control measures of KSPCB. Thus one can say that the basin has a vibrant and informed civil society movement against pollution. However very often these struggles have been protracted and even to get compensation for the losses, especially to the fisher folk, has not been that easy. For example take the case of the 1994 fish kill narrated in the study by the National Environmental Engineering Research Institute (NEERI), Nagpur: ―In response to the 1994 fish kill, the Tungabhadra Parisara Samiti, an organization of affected persons and their sympathizers, held regular protests and processions. Activists also wrote letters to senior politicians as well as the district administration, to little effect. Then, 62 members of the Harihar Taluk Guttooru fishermen's co-operative society filed a case against the industry asking for medical aid and a compensation of 18000 per person for their loss. Thereafter, the industry agreed to give a meagre sum of Rs 2000 as compensation after 8 years in April 2002. In protest, the fisherfolk society filed an application with the additional civil judge, Harihar and the free legal aid cell, for their mediation. However, so far little has come out of the legal battle. Some of the members are now ready to settle the case with whatever compensation the industry is ready to offer.‖ The same study has been also very critical of the efforts made by the government to control pollution in the river. According to the study the government ahs done very little except appointing various committees and have not made much of a difference on the ground. The study showed that the BOD levels in the raw effluents released into the river were very high. The effects of pollution were felt 40 km downstream in the summers.

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The Planning Commission of India initiated study covering the time period of 1992-93 to 1997-98 (the entire Eighth Five Year Plan period) tried to understand the functioning of the SPCBs and their efficacy in controlling water and air pollution, and also the efficacy of functional tools employed by them in carrying out their objectives and identifying the constraints to their effective functioning (Planning Commission of India, 2005). The study report has been rather critical of the functioning of the SPCBs in many respects and also has come up with many significant recommendations to improve their functioning. One of the important recommendations is with regard to the involvement of the local population in the functioning of the SCPBs and transparency in their functioning. It recommends:

―The functioning of SPCBs as of now precludes participation of local populace of the industrial cluster, who may be directly affected by pollution of their environment. There is also no transparency in the pollution control administration and dissemination of information to the public whose interests the SPCBs seek to protect. It is suggested that the pollution control could be better administered and monitored, if local community action groups are created/sensitised to take up vigilant community action against pollution. This could, perhaps take the form of this group monitoring periodically the samples generated by the polluting industries and getting the same tested in private labs. Funding for such activity is to be provided under SPCB separately. This would effectively prevent polluters- authorities nexus. SPCBs could also impart necessary training to such groups.‖ ―Apart from the above, it is desirable that transparency in ‗consent‘ sanction is established. Details of applications, reasons for rejection, date of sanction, etc. could be computerised and periodically published in the SPCB web-site. The pollution control activity seems to have seriously been provided momentum after the Bhopal gas tragedy. There is no comprehensive documentation of the lessons from the tragedy. The MoEF may like to place before the public the action taken by pollution control machinery to identify, relocate and build into the process of consent such dangerous industries from highly populated areas.‖

4.8 Conclusion The Tungabhadra river stretches figure as hotspots in many of the reports of the CPCB. Water quality in the basin is impacted by four major kinds of activity in the basin: a) industry, b) mining, c) urban and rural habitats and their waste disposal systems and d) run off from agricultural fields. Water quality along the river stretch is being monitored at various places under different programmes. However, only a few parameters are consistently being monitored over a long enough period. Trends show that upstream stretches are relatively less polluted than the downstream stretches. The data also show that average water quality had deteriorated dramatically during the late nineties and has subsequently improved. However, the data for the spread – for the maximum and minimum values – also shows, that the spread has also simultaneously increased, implying that there are periods when the pollution levels are quite high. Also downstream pollution levels have not improved as much over their late nineties values. Fish kills and deterioration in fish catch have also been reported, though there are i9ndications that the actual adverse impact may be a compound phenomenon that is impacted not only by water quality per se but also by changes in fishing technology and practices.

Much of the improvement may be related to the rise of a vibrant citizens' initiative against pollution over the nineties. The struggle has mainly been against the chemical companies (rayon and pulp units) and the mining companies. The closing down of the Kudremukh steel plant has led to a substantial decrease in mining the upstream areas of the basin, though legal as well as illegal mining continues in the downstream areas. Under pressure, the chemical industry has also improved its effluent treatment. However, there is a need both for closer monitoring as well as improving stakeholder participation in the process. There is now greater awareness of water quality issues amongst the citizenry in the area, though it is some times narrowly focused only on the two major impacting activities of industry and mining. This awareness needs to be extended to the other two factors and associated changes required in them as well. There is a need for continued monitoring as well as vigilance from the part of the civil society groups and concerned stakeholders as already there are plans for capacity expansion of units like Harihar Polyfibers. Closer participative monitoring feeding into a participative basin management is of great importance in improving and maintaining water quality in the basin.

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4.9 Literature Bureau of Indian Standards. 1991. IS 10500 Government of Karnataka. 2003. State of the Environment Report 2003 available at http://parisaramahiti.kar.nic.in/hp_water.html Krishnamoorthy, K. N., 1979. Fish production trends in certain catfish dominated reservoirs- A case study Tungabhadra reservoir. Lecture delivered in the Summer Institute on culture and capture fisheries of the man-made lakes in India, Central Inland Fisheries Research Institute, Barrackpore, India, pp. 366–373. Planning Commission. 2005. Evaluation Study on the Functioning of State Pollution Control Boards. New Delhi: Government of India available at http://planningcommission.gov.in/reports/peoreport/peo/peostatpoll.htm SOPPECOM and IWLRI. 2007. STRIVER: The Tungabhadra River Basin – Proceedings of the First Stakeholder Meeting (9-10 January 2007, Hospet, Karnataka), Society for Promoting Participative Ecosystem Management (SOPPECOM), Pune and International Water Law Research Institute, Dundee University, Scotland. It is available on STRIVER website. Valdimir Smakhtin, Muthukumarasamy Arunachalam, Sandeep Behera, Archana Chatterjee, Srabani Das, Parikshit Gautam, Gaurav D. Joshi, Kumbakonam G. Sivaramakrishnan and K. Sankaran, Developing Procedures for Assessment of Ecological Status of Indian River Basins in the Context of Environmental Water Requirements, IWMI research report 114, IWMI, Colombo, www.iwmi.cgiar.org/Publications/IWMI_Research_Reports/PDF/PUB114/RR114.pdf

Additional related information can be find at: Pollution, Assessment, Monitoring & Survey, CPCB, available at http://www.cpcb.nic.in/about%20us/Division%20at%20Head%20office/PAMS/PollutedRiverStretche s.html http://www.cpcb.nic.in/about%20us/Division%20at%20Head%20office/PAMS/Findings.html http://www.rainwaterharvesting.org/Crisis/river-krishna.htm

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5. Impacts: water quality analysis in Glomma (Hunnselva and Lena)

Line J. Barkved (NIVA), Johannes Deelstra (Bioforsk) and Haakon Thaulow (NIVA)

Within the Glomma river basin, the focus areas for analysis of pollution and water quality are the Hunnselva catchment and Lena. Information about pollution sources and discharges is given in chapter 3, whilst data on in-stream water quality and water flow are presented in this chapter. As an introduction the water pollution issues of Lake Mjøsa, the largest lake in Norway,, is presented. Hunnselva and Lena discharge into Lake Mjøsa; thus the Mjøsa situation is an important reference and ―driver‖ for pollution abatement measures in the Hunnselva and Lena catchments.

5.1 Water Quality issues in Mjøsa and Hunnselva/Lenaelva.

5.1.1 Lake Mjøsa – excessive eutrophication combatted The most important water quality issue in Glomma has been the excessive eutrophication of Lake Mjøsa. Domestic sewage, industrial waste and runoff from agriculture resulted in large input of nutrients, which led to an excessive growth of algae causing problems for ecosystems and for the use of Mjøsa as source for drinking water supply and recreation. The level of eutrophication was at its peak in the late 1960 ties and 1970ties with a dramatic maximum in 1976-77 with occurrence of a massive bloom of blue –green algae. Gro Harlem Brundtland, then Minister of Environment in Norway at the time, experienced the crisis and initiated a massive action to save the lake. Huge investments were undertaken and the so-called ―Action Lake Mjøsa‖ was launched. It proved to be a success as can be seen in Figure 5-1 below. The scientifically based advice given by NIVA to reduce the input of phosphorous from more than 350 ton/year down to sub critical levels of 175 tons per year proved good results. Figure 5-1 shows the anticipated and measured level of eutrohpication from the year 1900 till today. A sharp decrease in eutrophication level followed the decrease in discharges. A wide variety of actions was behind the success; political, technical, sound and good science and public awareness. New treatment plants for cities were built with chemical treatment removing phosphorous, existing plants upgraded, new sewer network installed and existing network upgraded: Further measures: introduction of treatment plants in densely populated areas, upgrading storm runoff systems, ban phosphates from detergents, improve waste management and industrial treatment plants, reduce inputs from agricultural point sources and improve agricultural land management practices to reduce non-point sources. Relatively good monitoring systems of water quality and quantity were also an important key factor. Public awareness was another key to the success. There were open public hearings by the local authorities and publicity in media. The immediate problems of Lake Mjøsa have been solved, but there are remaining pollution issues in many side tributaries. More measures have to be implemented and in this work participation and compliance with various international agreements and conventions contribute to ensuring improved water quality, in for instance related to the WFD implementation.

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Figure 5-1 Eutrophication of Lake Mjøsa

5.1.2 Hunnselva Hunnselva has considerably contributed in the pollution of the Lake Mjøsa in the early 70‘s, mainly through the runoff of organic waste, runoff wood processing industry and paper mills and pollution caused by metal and galvo-technical industry. The river was characterized as one of northern Europe‘s most polluted rivers. However a considerable improvement in water quality has been achieved over time partly due to the construction of treatment systems both for industry but also for scattered. The population in the Hunnselva catchment is engaged in the water quality issues and wants to actively participate in its improvement. A prove of this is the regular reader contributions in local newspapers.

NIVA is carrying out water quality monitoring program of Mjøsa Lake and its main contributors, including among others nutrient concentrations and loads. The results show that the total P load to the Mjøsa has been reduced from ca 120 -170 ton/yr at around 1980 to approximately 65 – 90 tonn/yr during the per3tiod from 2001 – 2007, a reduction of more than 40%. However the concentrations of both N and P show that both the Hunnselva and Lena River have poor water quality. The N-tot concentration in the Hunnselva River varied from 1229 - 1499 μg/l which according the Norwegian State Pollution Board (SFT) can be classified as very poor. The P-tot concentrations varied from 16 - 30 μg/l, which according to SFT can be classified as very poor.

Hunnselva is the highest contributor in P runoff to the Mjøsa Lake, having an area specific contribution of 18 kg P/km2.yr in 2007, with the Lena river being second worse, contributing with ca 11 kg P/km2.yr. The remaining smaller rivers discharging into the Mjøsa contributed significant less. Also concerning N the Hunnselva is, together with the Lena river, the largest contributor to the Mjøsa Lake, having an area specific contribution of 700 kg N/km2.yr

Increased concentrations N can seriously affect species composition and lead to growth of bulbous rush (Juncus bulbous/supinus). On the other hand, increased P concentrations can lead to algae blooms, especially as this element is considered being the limited element for algae growth in freshwater systems. This also means that N level in this respect is less critical. Research however carried out by NIVA has shown that a change in the composition of algae and macro - phytes can be linked to changes in N concentrations.

The Hunnselva is also characterised by the presence of a river mussel (Margaritifera margaritifera). This species live in close existence with salmon and trout and is extinct in from many countries in Europe. Mussels are very sensitive to nitrogen and therefore nitrogen runoff from land-based activities should be controlled and if possible reduced.

A conclusion for the main Hunnselva river can be that since long the water quality in the watershed has been influenced by human activities which can be summarized originating from 1) regulations for

56 STRIVER Deliverable D7.1 Part 1 hydro-power production, 2) nutrients, organic matter and coli bacteria from scattered housing, 3) nutrient losses, pesticides and sediments from agriculture and 4) toxic effluent from industry and waste deposits, road salt and other runoff from road systems. Most influenced by pollution is the lower section of the Hunnselva River. The smaller - and contributing streams to the main river are to a low degree influenced by the pollution.

5.2 Monitoring of water flow, water quality and related environmental data For Hunnselva (OPPPEH5 and Lena (HEDLEN) located at outlet of the catchments into Mjøsa Lake (Figure 5-2) and Sarpsfoss located approximately at the outflow of the Glomma River into the North Sea, water quality samples are taken approximately every fortnight. The samples are taken as grab samples and analysed for a variety of chemical parameters including nitrogen and phosphorus. However, suspended solids, an important indicator of soil erosion processes in agricultural dominated catchments, is not included in those analyses. In this report, we have only included an analysis on phosphorus and nitrogen as these elements are being drivers in eutrophication processes and deterioration of water quality.

Figure 5-2. Location of water flow (triangles) measurement and water quality (circles) sampling

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5.2.1 Water flow There are four water flow stations located in the Hunnselva and Lena catchment being Lena, Skreia, Einavatn and Hunnselva (Table 5-1 and Figure 5-2). Of those, only the inland station Lena seems still to be in operation. The mean runoff for the Lena, Hunnselva and Skreia catchments are in the same order of magnitude while the runoff for Einavatn is significantly higher (Table 5-2 and Figure 5-3). At the same time large variations in runoff exist, the main reason for this being the variation in precipitation.

Table 5-1. Water flow series in the Hunnselva and Lena catchments NO_OF_SERIES NAME START END 2.209.0.1000.2 Einavatn ndf. 14.05.1951 2.618.0.1000.1 Skreia 02.07.1987 12.01.1996 2.619.0.1000.1 Hunselv 01.01.1987 27.04.1993 2.634.0.1000.1 Lena 11.03.1991

The precipitation measured at Einavatn and Apelsvoll is representative for the precipitation of the Einavatn catchment. When calculating the water balance for the catchment (precipitation – runoff), there appears to be no water available for evaporation. Einavatn is a nested catchment within the Hunnselva catchment, and though it is regulated for hydropower there is no divergence of water so on an annual basis one should therefore expect approximately the same runoff compared to Hunnselva. A possible reason for the difference between the two stations can be due to errors in the water flow measurement. However, measured water flow is only available for the outlet of Hunnselva for a few years in the past so direct comparison is not possible. Nevertheless, use of the Einavatn station in the calibration of watershed models could therefore not be recommended at this stage.

Table 5-2. Summary of unit area runoff (mm) for Lena, Hunnselva, Skreia and Einavatn catchments Runoff mean maximum minimum st.dev Period Lena, 465 740 331 176 1992 - 2007 Hunnselva 433 871 169 218 1987 - 1994 Skreia 467 808 253 131 1987 - 1995 Einavatn 689 1497 325 319 1997 - 2006 Precipitation Einavatn 685 977 486 97 1989 - 2007 Apelsvoll 659 1143 461 152 1989 - 2007 Kise 565 773 424 81 1988 - 2007

Figure 5-3. Yearly runoff at Lena, Hunnselva, Skreia and Einavatn

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5.2.2 Runoff generation For the period from 1998 – 1994, both discharge measurements and water quality data are available for the Lena station, in which case the nutrient loads can be calculated. As the water samples are collected as grab samples, the concentration between samplings had to be estimated. In this case linear interpolation has been used. The results are presented in Table 5-3.

Table 5-3. Runoff and nutrient loads at Skreia for period 1998 - 1994 1988 1989 1990 1991 1992 1993 1994 Runoff (mm) 681 169 357 267 291 410 459 P-load (kg/ha) 0.1 0.3 0.2 0.1 0.2 0.2 0.2 N-load (kg/ha) 4.3 10.7 10.6 14.1 15.4 15.3 9.1

Runoff is generated mainly during the off – season from November – April. For the Skreia catchment, the runoff among the different seasons has been calculated. In this case, the winter includes the months December – March, April and May represent the spring period, the summer is from June – August while the autumn is covered by months September – November (Table 5-4). As can be seen the major part of the yearly runoff occurs during the spring months. The main reason for this is snow melt generated runoff. Also during the autumn period a considerable part of the runoff occurs. For comparison also the results for the Kolstad catchment are presented showing no major differences between the two catchments. The Kolstad station is part of the national agricultural monitoring programme (JOVA).

Table 5-4. Seasonality in runoff, Skreia station and Kolstad catchment winter spring summer Autumn Skreia 16 43 16 25 Kolstad 10 41 23 25

A more detailed analysis showed that the major part of the yearly runoff is generated during only a limited number of days (Table 5-5 and Figure 5-4). On average over the measurement period it appears that it takes only 38 days to discharge 50 % of the yearly runoff, while 90 % is drained in 174 days. As can be seen the nitrogen loss generation is quite in agreement with the runoff. However the phosphorus loss generation occurs faster. This is in agreement with other findings and is due to the fact that P-loss often is associated with erosion this often occurring during high flow events. This information is important in designing water sampling routines as nutrient losses is directly linked to the runoff. It raises serious questions concerning the validity of grab sampling routines based on fortnight sampling.

Table 5-5. Cumulative runoff and nutrient loads for Skreia catchment Fraction of yearly total runoff nitrogen phosphorus (%) number of days 50 38 38 24 90 174 166 132 100 365 365 365

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Figure 5-4. Runoff generation as a function of time

5.2.3 Hydrological characteristics Flashiness, or rate of change, refers to how quickly flow changes from one condition to another and has been widely used to describe urban hydrology. Baker et al (2004) has developed a flashiness index (FI), which describes those changes by calculating the total path length of flow and dividing this by the sum of the average daily discharges. The total path length is equal to the sum, usually over one year, of the absolute values of the day to day changes/differences in the average daily discharge values. The index is derived by dividing this path length by the sum of the daily discharge volumes for the year as

n  qi  qi1 i1 FI  n qi i1

The index is dimensionless and its value is independent of the units chosen to represent flow. When based on the average daily discharge, the FI does not take into account the in-day variation in discharge. Baker et al. (2004) tested the effect of using hourly instead of daily average discharge values and found, due to an increase in the total path lenght, a considerable increase in the FI by a factor 1–3. In this case also a FI has been calculated on hourly discharge values for Lena (Bru). The FI for Lena, Skreia and Hunnselva is presented in Figure 5-5 and Table 5-6. The mean FIday – values for Lena and Skreia catchment are 0.2 and 0.3 respectively while the Hunnelva has a mean value, FIday = 0.1. For the Lena and Skreia catchment the FIday varies from 0.1 – 0.3 and 0.2 – 0.5 respectively while for Hunnselva the variation is from 0.1 – 0.2. Less variation can be seen for the Hunnselva catchment, this due to regulatory operations on the runoff. When the flashiness index is based on hourly discharge values the index for the Lena catchment increases by a factor 2.

For comparison also the FI – values as obtained for the Kolstad catchment are presented. The Kolstad catchment is small compared to the Lena, Skreia and Hunnselva catchments, having a total area of 308 ha. The FI for the Kolstad is considerably larger catchment compared to Lena, Skreia and Hunnselva catchments, both based on hourly as well as average daily discharges, increasing by a factor 3. Both, the larger values and the significant increase in FI for the Kolstad catchment indicate large in-day variations in discharge, which can significantly influence the erosion and sediment transport processes.

Reasons for the large difference can be the size of the catchment, with Kolstad being small compared to Lena, Skreia and Hunnselva but also the subsurface drainage system might have a considerable

60 STRIVER Deliverable D7.1 Part 1 influence. Agriculture represents almost 70 % of the total area. All the agricultural land is provided with artificial subsurface drainage systems, with a drain spacing, L = 10 m and a drain depth, d = 0.80 m below soil surface. The objectives of the subsurface drainage system are three-fold, being; 1) to provide optimal moisture conditions for crop growth, 2) to drain excess water during spring to enable farmers to start land preparation in spring as soon as possible as any delay in sowing time would had a serious yield reduction effect and 3) to enable land tillage during autumn.

Table 5-6. Summary of flashiness index for Lena, Hunnselva and Skreia mean maximum minimum st.dev Lena, Fihr 0.47 0.61 0.38 0.08 Lena, FIday 0.24 0.34 0.12 0.06 Hunnselva, FIday 0.14 0.20 0.10 0.04 Skreia, FIday 0.27 0.45 0.17 0.08 Kolstad, FIhr 0.94 1.83 0.66 0.27 Kolstad, FIday 0.29 0.40 0.24 0.05

Figure 5-5. Flashiness at Lena, Skreia and Hunnselva based on daily and hourly discharge values

Also the baseflow index (BFI) has been calculated. The BFI is a measure of the proportion of groundwater flow in the total runoff measured at the catchment outlet. In our case we used the method developed by Gustard et al. (1992), which is based on a smoothed minima technique. The BFI was calculated on the basis of average daily discharge values and for periods of one year. The average BFI value for the Lena, Skreia and Kolstad catchment are 0.42, 0.41 and 0.32 respectively. This indicates a larger baseflow at the larger catchment. However one might wonder whether BFI-values based on average daily discharges represent the true baseflow contribution in the total runoff when at the same time it was shown that large in-day variations in discharge can occur. This was shown by the differences between FIday and FIhr for both the Lena and Kolstad catchment.

Table 5-7. Base flow index and flashiness index for the Lena, Skreia and Kolstad catchment Catchment BFI FIday FIhr Lena 0.42 0.24 0.47 Skreia 0.41 0.27 Kolstad 0.32 0.29 0.94

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5.3 Analyses of the water quality levels, trends, spatial and temporal variability

Lena, Hunnselva and Sarpsfoss

Based on existing water quality monitoring programmes an analysis has been carried out on the observed values for nitrogen and phosphorus concentrations. In this case also the Sarpsfoss station has been included, located at the outlet of the Glomma into the North Sea. There is a marked difference in nitrogen concentrations between Hunnselva and Lena on the one hand and Sarpsfoss (Figure 5-6 and Table 5-8). Sarpsfoss represents the total Glomma catchment and a reason for the low concentrations can be the relative small share of agricultural land in the Glomma catchment. There is also a rather large difference in nitrogen concentration between the Lena and Hunnselva catchment. This can most likely be attributed to the higher share of agricultural land in the Lena catchment compared to Hunnselva (37 and 15 % respectively). Sarpsfoss also shows the lowest phosphorus concentrations most likely due to the same reason as for nitrogen (Figure 5-7 and Table 5-8). There is very little difference in phosphorus concentration between the Hunnselva and Lena.

Figure 5-6. Cumulative distribution of nitrogen concentrations for Lena, Hunnselva and Sarpsfoss sampling locations

Table 5-8. Concentrations summary Lena, Hunnselva and Sarpsfoss Lena Hunnselva Sarpsfoss Lena Hunnselva Sarpsfoss Phosphorus (µg l-1) Nitrogen (µg l-1) Minimum 2 2 2 744 216 283 Maximum 867 417 171 10840 4820 2060 Mean 39 43 23 3202 1708 574 Median 22 32 16 3000 1590 529 St. Dev. 64 40 22 1385 547 202

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Figure 5-7. Cumulative distribution of phosphorus concentrations for Lena, Hunnselva and Sarpsfoss sampling locations

The Lena catchment For the Lena catchment, also the concentrations have also been calculated for the different seasons. The spring season includes the months of March – May, the summer season includes the months June – August, the autumn period includes the months September – November while includes the months December – February. Characteristic for the Lena catchment is the high average P concentration during the spring season (Figure 5-8 and Table 5-9). This can most likely be attributed to the snowmelt and accompanying runoff and erosion processes. The highest average nitrogen concentrations occur during the winter season (Figure 5-9 and Table 5-10). As for phosphorus, the highest maximum concentration occurred during the spring period. There is a considerable variation in the P concentrations, which is considerably larger than the variation in N – concentrations. A possible reason for this can be that P concentrations are very much influenced by runoff processes, more specifically by periods with high runoff.

Table 5-9: Characteristics phosphorus concentration (µg L-1) Lena watershed outlet Spring Summer Autumn Winter Maximum 867 551 353 175 Mean 50 35 35 32 Median 29 20 21 20 St. dev 83 65 48 31 CV(1) 166 186 137 97 1 – coefficient of variation (%)

Table 5-10: Characteristics nitrogen concentration (µg L-1) Lena watershed outlet Spring Summer Autumn Winter Maximum 10840 6032 7370 6680 Mean 3433 2679 3199 3668 Median 3040 2620 2980 3526 St. dev 1876 954 1081 1074 CV 55 36 34 29

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Figure 5-8. Distribution of phosphorus concentration for the Lena catchment

Figure 5-9. Distribution of nitrogen concentration for the Lena catchment

The Hunnselva catchment As for the Lena catchment, also for the Hunnselva catchment the N and P concentrations were calculated for the different seasons. Characteristic for the Hunnselva catchment is the almost similarity in the average P concentrations during the different seasons (Figure 5-10 and

64 STRIVER Deliverable D7.1 Part 1

Table 5-11). The highest average nitrogen concentrations occur during the winter season (Figure 5-9 and Table 5-10). However, as for phosphorus, the highest maximum concentrations occur during the spring period. The reason for the high maximum values in N - concentrations during spring time are difficult to apprehend but could be attributed to a combination of surface runoff and animal manure in addition to point source contributions. There is a considerable variation in the P concentrations, which is considerably larger than the variation in N – concentrations. Most likely this can be attributed to runoff processes.

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Table 5-11: Characteristics phosphorus concentration (µg L-1) Hunnselva watershed Spring Summer Autumn Winter Maximum 417 355 224 280 Mean 42 44 44 41 Median 32 33 32 30 St. dev 45 40 35 38 CV 107 91 80 93

Table 5-12: Characteristics nitrogen concentration (µg L-1) Hunnselva watershed Spring Summer Autumn Winter Maximum 4820 3470 2980 3470 Mean 1814 1569 1717 1743 Median 1650 1470 1642 1676 St. dev 699 475 417 479 CV 39 30 24 27

Figure 5-10. Distribution of phosphorus concentration for the Hunnselva catchment

Figure 5-11. Distribution of nitrogen concentration for the Hunnselva catchment

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The average yearly N and P concentrations have been calculated for the Lena, Hunnselva and Sarpsfoss monitoring stations and compared with the water quality criteria developed by the Norwegian State Pollution agency (Feil! Fant ikke referansekilden.).

Table 5-13. Water quality status classes according Norwegian State Pollution Agency (SFT 1997). Water quality status 1 2 3 4 5 Very good Good Moderate Poor Very poor P-tot, μg/l 0-7 7-11 11-20 20-50 >50 N-tot, μg/l 0-300 300-400 400-600 600-1200 >1200

Concerning phosphorus, the water quality for both Hunnselva and Lena can be classified as poor to very poor while this for Sarpsfoss can be classified as moderate (Figure 5-12). Concerning nitrogen, the water quality at both Hunnselva and Lena can be classified as very poor, while for Sarpsfoss this is varying from moderate to poor (Figure 5-13). For both Lena and Hunnselva, the results show that an improvement in the average yearly P concentration might have occurred during recent years. This improvement can also be noticed in the N concentration for the Hunnselva but is absent for Lena. For Sarpsfoss no real changes can be noticed.

Figure 5-12. Phosphorus concentrations at Hunnselva, Lena and Sarpsfoss

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Figure 5-13. Nitrogen concentrations at Hunnselva, Lena and Sarpsfoss

5.4 Literature Baker D. B., Richards R. P., Timothy T. Loftus T. T. & Kramer J. W. (2004) A new flashiness index: characteristics and applications to midwestern rivers and streams. Journal of the American Water Resources Association, 40: 503-522

Gustard A., Bullock A. & Dixon, J.M. (1992) Low flow estimation in the United Kingdom. Institute of Hydrology, Wallingford, UK. IH Report no. 108, Institute of Hydrology, Wallingford, Oxfordshire, United Kingdom.

68 STRIVER Deliverable D7.1 Part 1

Annex to Chapter 2

List of Urban Local Bodies (ULB) across the TB Basin Name of the Town Name of the Town 1 Tarikere 15 Hosapet 2 Sringeri 16 Kamalapura 3 Koppal 17 Kampli 4 Gadag Batageri 18 Siruguppa 5 Mundaragi 19 Tekalkopta 6 Byadagi 20 Huvinahadagali 7 Haveri 21 Sindhanur 8 Ranebennur 22 Gangavathi 9 Shimoga 23 Koppa 10 Thirthahally 24 Manvi 11 Honnali 25 Lakeshmeshwar 12 Davanagere 26 Harapanahalli 13 Harihara 27 Bhadravathi 14 Bellary 28 Chennagiri

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Water Supply to ULBs Located Across the TB Basin Population Quantity Name of Water supply (2001 drawn LPCD Issues, if any the Town source census) (MLD) T.B.H.L. & After treatment of the effluent will Bellary 317,000 40 100 TBLL reach the Hagari river Tungabhadra Hadagali 23,404 2.5 75 No treatment plants, no UGD system River T.B.Power No treatment plants, UGD system canal and Hospet 163,284 17 75 only partly, after it reaches natural Rayanbasava valley canal No UGD system, no treatment Narihalla Sandur 27,601 3.7 75 plants, effluent flows into reservoir agricultural fields No UGD system, no treatment Tungabhadra Siraguppa 42,862 3.13 75 plants. The effluent will flows river agricultural field 90% UGD System is there, no treatment plants, effluent flows into Tungabhadra Davanagere 363,780 40 135 both Bathi Tank and river river Tungabhadra, Proposed treatment plants are there No UGD systems, no treatments,septic tanks are there, and Haveri 55,900 Tungabhadra 7.2 after use it goes into the Heggere tank then it reaches TB river in the rainy season Partly UGD systems are there. No Koppal 56,145 T.B.reservoir 9.09 100 treatment plants, after use it flows to low level canal No UGD system, no treatment Tungabhadra Gangavathi 93,249 8.5 100 plants, effluent will flows river agricultural field No, UGD system, no treatment Manvi 37,555 T.B.river 4.54 90 plants, effluent will flows low lying areas Partly UGD systems are there, no Raichur 205,634 Krishna river 30 135 treatment plants, after use it flows to low level canal No UGD system, no treatment T.B.left bank Sindhanoor 61,292 6.81 90 plants. The effluent flows into canal agricultural field Total 1,447,706 - 172.47 - -

70 STRIVER Deliverable D7.1 Part 1

Availability of underground drainage (UGD) facilities in Towns as on 2005 Availability of UGD Availability of UGD Name of town Name of Town facility (%) facility (%) 1 Tarikere Nil 15 Hospet 80 2 Sringeri Nil 16 Kamalapura Nil 3 Koppal Nil 17 Kampli Nil 4 Gadagbatageri Nil 18 Siruguppa Nil 5 Mundaragi 80 19 Tekalkopta Nil 6 Byadagi Nil 20 Huvinahadagali Nil 7 Haveri Nil 21 Sindhanur Nil 8 Ranebennur Nil 22 Gangavathi 60 9 Shimoga 80 23 Koppa Nil 10 Thirthahally Nil 24 Manvi Nil 11 Honnali Nil 25 Lakeshmeshwar Nil 12 Davanagere 60 26 Harapanahalli Nil 13 Harihara 60 27 Bhadravathi 60 14 Bellary 80 28 Chennagiri Nil Source: KUWSDB, 2005

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Number of villages across the TB Basin Number Number Districts Taluk of Total Districts Taluk of Total villages villages Siruguppa 84 317 Haveri 87 538 Hospet 74 Ranebennur 107 Bellary Bellary 103 Haveri Hirekerur 128 Hagaribommanahalli 56 Savanur 65 Chikamagalur 229 665 Hangal 151 N R Pura 58 Koppala 151 308 Koppala Chickmagalur Sringeri 49 Gangavathi 157 Koppa 80 Raichur 160 692 Tarikere 249 Devadurga 188 Raichur Honnali 173 752 Manvi 171 Harihar 84 Sindhnur 173 Davanagere Channagiri 249 Shimoga 214 606 Davanagere 166 Shimoga Theerthahalli 247 Harapanahalli 80 Bhadravathi 145 Source: Village Directory, 2001

Number of wells in TB Basin over the years Years Districts Total 2000-01 2005-06 Bellary 36107 44883 158397 Chikkamagalur 28502 32630 89416 Davanagere 43500 58403 101903 Haveri 33774 40208 73982 Raichur 21542 27062 118552 Shimoga 24351 25110 53682 Total 187776 228296 595932

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Number of villages affected with ground water pollution in Nitrate Fluoride TH Taluks Village (mg/l) (mg/l) (mg/l) Guddada Mattihalli 55 2.8 Hanagal Hangal 56 Haleritti I 66 Haveri Negalur 2.25 Lhimmenahalli 47 Gangapura 62 Masur 64 Hirekerur 608 Rradakanahalli 67 Honnati 67 53 3.8 Kajari 1.6 Karur 55 1.8 Ranebennuru Kotihal 89 Navalgol 1536 Ranebennur 56 748 Ranebennur 66 Vaderayanahalli 53 Savanur 56 Halsur 52 Ichangi 2.0 Savanur 101 Savanur 624

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Villages affected with ground water pollution in Bellary District Nitrate Fluoride TH Total Iron Taluks Villages (mg/l) (mg/l) (mg/l) (mg/l) Aladahalli 68 Bellary 1008 Burranayakana halli 112 Chandrashekarapura 165 1.6 Emmiganur 347 2 Godehal 652 Joladarasi 111 4.4 708 Bellary Kammarachedu 3.4 676 Karichedu 81 1064 Kudathini 104 Kudathini 102 Obalapura 86 1.22 Somasamudram 370 1240 Koralagundi 86 1.6 Chilagodu 49 1.5 1.2 Pinjariheggadahatti 77 2 Hagaribommanahalli 79 Hagaribommanahalli Malavi 68 Nellukudiri 5.5 Nellukudri 56 5.6 B Gollarahatti 4.1 1.1 Hospet Dharmasagar 142 2.2 Konarahatti 49 2.4 1.08 Adavimallanakere 56 Adavimallanakere 67 Hadagali 4.75 Hagaranur 204 616 Hirehadagali 137 616 Hirehadagali 244 1312 Huviniahadagali Huviniahadagali 4.4 Nagatibasapura 61 Nagatibasapura 65 Kombihalli 161 2.1 Koyilaragatti 125 Nandihalli 2.1 Karur 133 1.8 Siddaramapura 158 Siruguppa 378 1.6 1264 Siruguppa Siruguppa 74 4.1 Tekkalakote 150 2.75 676 Tekkalakote 205 1.6 664

74 STRIVER Deliverable D7.1 Part 1

Villages affected with ground water pollution in Chikamagalur District Nitrate Fluoride TH Total Iron Taluk Village (mg/l) (mg/l) (mg/l) in mg/l Avathi 108 Avathi 96 Kalasapura 108 Chikkamagalur Kalasapura 87 Uddeboranahalli 65 Uddeboranahalli 78 Uddeboranahalli 79 Koppa 57 Koppa Kudregundi Narasimharaiapura Kadlemakki 1.36 Sringeri Kigga 3.22 Kuntur 3.09 Bettadahalli 49 Bettadahalli 118 Duglapura 54 Duglapura 93 856 Tarikere Duglapura 108 880 Lingadahalli 85 900 Lingadahalli 51 Lingadahalli 93 1244

Villages affected with ground water pollution in Koppal District Nitrate Fluoride TH Taluks Villages (mg/l) (mg/l) (mg/l) Chickbenakal 114 Gangavati 300 1.7 Hulihyder 90 2.3 Gangavathi Kanakgiri 175 Kanakgiri 2.25 Siddapur 234 Somasagar 1.9 Hiresindogi 263 2.6 Hoshalli 105 2.6 Irkalgada 70 Koppal Jabbalgudda 53 2.2 Katarki 139 Kinhal 283 Koppal 747 1528

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Villages affected with ground water pollution in Davanagere District Nitrate Fluoride TH Total Iron Taluks Villages (mg/l) (mg/l) (mg/l) (mg/l) Honnali Benakanahalli 221 784 Benakanahalli 117 Devanayakanahalli 1.8 Hebbalgere 57 752 Kundur 652 Harihar Kumbluru 174 Malebennur 103 Channagiri Benakana halli 221 784 Channagiri 188 1280 Chinnikatte 620 3 Devarahalli 2 Devarahalli 227 2080 Dodghatta 233 1320 Hebbalagere 362 1760 Hebbalagere 234 1260 Hebbalagere 362 1760 74 1.86 Jeenahalli 64 Kariganur 115 960 Kogalur 135 800 Nyamathi 102 Santhebennur 89 Tavarekere 300 612 Davanagere Anagodu 57 704 Kandagallu 84 Harapanahalli Arasikere 135 Arasikere 135 888 Chirastahalli 111 4 Harapanahalli 392 900 Kanchikeri 720 Teligi 96 Uchangidurgam 79

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Villages affected with ground water pollution in Raichur district Nitrate Fluoride TH Taluks Villages (mg/l) (mg/l) (mg/l) Devadurga Arkere 96 2.2 Bommanahalli 57 2.25 Bommanahalli 3 Devadurga 4.5 80 111 Jagatkal 10 204 2.5 Jalhalli 93 Jambaldinni 92 1.8 Jambaldinni 75 2.6 Kotigud 61 Rekalmardi 4.5 Rekalmardi 3 Rekalmardi 256 2 Rekalmardi 4 Hallihosur 2.6 Hirehanagi 237 6.5 1580 Hirehanagi 369 4.6 1760 Kallur 192 612 Kallur 168 3 620 Kowtal 1.75 Kowtal 1120 2080 Manvi Kurkunda 2.4 Kurkunda 5 Malat 85 2 Malat 141 720 1183 1320 Potanhal 52 Potanhal 57 Sirawar 288 Deosugur 98 1040 Deosugur 87 864 Hanchinal 225 2.2 Hanchinal 3.8 Raichur Jambaldinni 127 6 Jambaldinni 471 1344 165 628 Raichur 129 Yapaldinni 69 212 3 1439 Sindhanur Gorebal - 2.5 - 2.2

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Gudadur 96 4 126 4 Gudadur - 5 Kalmangi 124 2.5 134 Mullur - 2 Sindhanur 59 4.5 Sindhanur - 6 Sindhanur 92 4 843 1.6 1236 Umloti 177 Source: DMG

Villages affected with ground water pollution in Shimoga District Nitrate TH Iron Taluks Villages (mg/l) (mg/l) (mg/l) Bhadravathi Arabilachi 97 800 Bhadravathi 20 Shimoga Harnahalli 64 Kunchenahalli 73 M Hanasavadi 61 2.8 Shimoga 68

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Annex to Chapter 3

Air temperature for Kise climatological station Month 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 mean normal1 January -1.1 -0.2 -2.3 -5.4 -2.0 -1.7 -8.0 -5.8 -9.7 -6.2 -3.0 -4.3 -1.7 -4.1 -7.5 -8.0 -6.8 0.3 -3.6 -3.0 -4.2 -7.4 February -3.0 1.1 2.9 -7.8 -2.1 -1.9 14.6 -2.5 12.0 -2.1 -1.4 -6.9 -2.9 -8.5 -2.7 -8.4 -5.5 -1.9 -5.4 -5.8 -4.6 -8.1 March -3.0 2.2 3.8 -0.1 1.6 -0.5 -2.7 0.3 -5.6 1.9 -1.7 -1.3 0.7 -4.7 -0.2 -0.7 -0.8 -3.3 -7.3 2.3 -1.0 -3.1 April 1.6 3.6 3.4 3.8 2.3 4.1 4.0 3.2 1.8 4.1 2.1 4.3 4.0 3.2 5.1 3.5 5.3 5.2 2.8 5.5 3.6 2.2 May 9.3 9.1 9.8 8.9 11.5 10.1 8.6 8.1 6.8 8.0 9.2 7.8 10.4 9.6 10.5 8.6 10.3 8.0 9.0 9.8 9.2 8.5 June 16.4 13.7 13.7 10.5 16.0 11.7 12.4 13.7 13.3 16.4 11.6 12.9 12.4 13.2 15.2 14.9 12.9 12.8 14.6 15.1 13.7 13.6 July 15.8 15.6 14.8 16.3 14.7 13.8 19.1 15.9 15.0 20.3 14.1 16.0 14.6 16.5 16.1 17.7 14.9 17.1 18.4 15.5 16.1 15.2 August 14.0 13.2 14.7 15.2 12.9 12.0 14.8 15.9 16.6 21.2 13.1 14.2 13.9 14.4 18.3 15.4 16.1 14.9 16.9 15.2 15.1 14.0 September 11.4 10.6 9.5 10.0 9.8 7.0 9.3 10.7 9.1 12.8 10.7 13.6 10.2 10.5 12.4 11.3 11.5 11.9 13.6 9.7 10.8 9.6 October 3.5 5.3 5.4 4.9 1.4 3.0 4.3 8.4 7.4 3.5 4.0 5.6 8.5 7.5 2.5 2.9 5.5 5.9 7.3 5.7 5.1 5.1 November -2.6 1.6 -1.4 0.4 -1.5 -2.3 0.7 -2.3 -1.9 0.3 -2.2 3.9 4.9 1.4 -3.6 1.4 -0.5 3.6 2.4 0.0 0.1 -0.8 December -5.6 -5.0 -2.0 -1.9 -2.7 -6.5 -1.6 -9.2 -6.1 -3.2 -2.9 -5.1 -0.4 -5.2 -8.3 -2.0 -1.9 -3.2 1.4 -3.9 -3.8 -5.3 Year 4.7 5.9 6.0 4.6 5.2 4.1 3.9 4.7 2.9 6.4 4.5 5.1 6.2 4.5 4.8 4.7 5.1 5.9 5.8 5.5 5.0 3.6 1 – long term average temperature

Precipitation for Kise climatological station Month 1988 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 mean normal1 January 57 13 36 24 12 20 73 52 26 12 38 50 15 43 53 30 50 32 20 38 35 36 February 53 65 41 9 15 14 13 24 32 28 18 28 15 23 35 19 28 7 39 31 27 29 March 43 26 13 45 43 2 30 17 4 6 46 83 9 38 30 10 19 19 37 9 26 27 April 17 99 63 9 49 15 33 26 18 1 73 44 70 42 35 39 28 16 38 15 36 34 May 30 92 16 9 29 71 24 58 82 105 6 22 42 39 79 69 28 44 75 49 48 44 June 15 45 58 127 15 27 44 78 72 59 118 124 73 47 43 65 118 51 25 74 64 59 July 123 94 87 35 96 134 4 78 52 50 54 48 91 37 120 63 67 59 24 110 71 66 August 97 81 69 25 94 99 116 15 74 41 47 20 68 92 33 80 143 79 83 105 73 76 September 115 15 17 53 26 32 83 43 49 48 71 104 26 59 22 96 61 18 42 56 52 64 October 42 27 60 32 47 81 42 19 75 38 79 72 145 75 36 13 49 62 121 6 56 63 November 16 27 31 42 97 44 20 15 35 50 24 14 167 17 48 58 36 44 61 52 45 50 December 38 21 15 14 21 62 49 5 29 67 22 39 53 26 22 26 6 40 31 47 32 37 Year 645 604 507 424 544 601 529 428 548 504 596 649 773 537 556 567 631 470 596 591 565 585 1 – long term average precipitation

79 STRIVER Deliverable D7.1 Part 1

Air temperature for Apelsvoll climatological station Month 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 mean normal1 January -0.1 -2.2 -5.0 -1.6 -2.0 -8.0 -5.0 -9.2 -10.8 -3.7 -4.4 -1.5 -4.9 -6.6 -6.0 -7.0 0.1 -3.8 -2.9 -4.5 -7.4 February 0.8 2.3 -7.3 -1.9 -2.1 -12.8 -3.1 -10.3 -1.1 -5.7 -3.2 -7.9 -1.6 -6.8 -3.8 -2.5 -5.1 -6.0 -4.3 -7 March 1.5 3.1 0.0 1.2 -0.7 -2.6 -1.2 -3.9 0.9 -1.7 -1.4 0.2 -4.6 -0.1 0.6 -0.1 -2.6 -6.0 2.3 -0.8 -2.5 April 3.5 4.4 4.0 2.1 4.4 3.8 1.7 2.4 3.6 2.4 4.7 4.1 2.5 5.4 3.9 5.8 5.5 2.8 5.9 3.8 2.3 May 9.7 11.3 8.9 12.4 11.1 8.6 7.4 6.3 7.6 10.7 8.3 11.5 10.1 11.3 8.8 10.9 8.2 9.4 9.7 9.6 9 June 13.7 13.6 10.4 16.2 11.7 12.2 12.9 12.9 14.4 11.9 13.2 12.5 13.3 15.0 14.6 12.9 12.9 15.4 15.2 13.4 13.7 July 15.9 14.6 16.8 14.6 13.5 19.1 14.9 14.0 18.1 14.1 16.2 14.5 16.3 15.8 17.3 14.5 17.0 18.3 14.8 15.8 14.8 August 12.8 14.5 14.9 12.3 11.2 13.9 14.6 15.8 18.4 12.8 13.9 13.6 13.9 18.2 15.0 15.8 14.1 16.2 14.7 14.6 13.5 September 10.2 8.8 9.9 9.3 6.7 8.5 9.3 8.2 10.8 10.8 13.1 9.6 9.9 11.5 11.0 11.0 11.4 13.1 9.3 10.1 9.1 October 4.7 4.7 4.4 0.9 2.7 3.5 7.2 6.1 3.1 3.4 5.0 7.7 6.9 1.6 2.7 4.9 5.5 6.5 5.1 4.6 4.6 November 1.2 -1.7 -0.4 -1.8 -3.1 -0.1 -3.2 -2.9 -0.5 -2.8 3.3 3.8 1.0 -3.5 0.6 -0.8 2.9 2.1 -0.3 -0.3 -1.3 December -5.1 -9.6 -1.6 -2.7 -6.8 -2.4 -9.5 -6.6 -3.6 -2.9 -5.6 -1.0 -5.3 -8.6 -1.6 -2.1 -3.2 1.7 -4.0 -4.2 -5.3 Year 5.7 5.3 4.6 5.1 3.9 3.6 3.8 2.7 5.6 4.5 5.0 6.0 4.3 4.9 5.0 5.2 5.8 5.9 5.3 4.9 3.6 1 – long term average temperature

Precipitation for Apelsvoll climatological station Month 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 mean normal1 January 15 123 39 23 18 73 54 31 1 22 164 16 69 62 55 50 26 25 51 48 37 February 73 49 34 21 15 99 23 38 0 26 55 17 29 79 19 39 10 65 47 39 26 March 33 20 45 36 2 33 30 13 11 45 164 20 47 26 9 23 27 53 10 34 29 April 57 77 16 70 16 33 26 17 7 86 64 80 50 41 40 30 13 47 14 41 32 May 56 23 13 25 68 18 48 84 129 15 47 42 40 80 70 25 44 67 49 50 44 June 38 85 103 17 41 25 94 71 52 121 131 67 44 54 77 95 48 31 89 68 60 July 78 71 46 101 131 6 99 59 17 62 72 90 44 104 70 85 86 30 118 72 77 August 102 35 43 186 145 132 25 70 46 51 26 50 104 47 53 137 59 131 77 80 72 September 23 18 55 62 33 85 51 44 49 80 111 24 77 29 85 54 20 51 73 54 66 October 36 93 35 49 118 47 21 90 40 95 80 168 64 65 21 54 81 129 6 68 64 November 28 53 52 92 49 49 22 50 59 32 26 195 12 48 60 32 35 61 45 53 53 December 33 1 16 23 56 50 12 26 51 44 203 51 24 42 20 49 65 31 210 53 40 Year 572 650 496 704 691 651 504 595 461 679 1143 818 602 675 576 671 514 721 789 659 600 1 – long term average precipitation

80 STRIVER Deliverable D7.1 Part 1

Precipitation for Einavatn climatological station Month 1989 1990 1991 1992 1993 1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 mean January 8 68 38 17 25 78 63 36 9 43 51 19 66 55 35 64 33 22 41 41 February 60 64 19 18 27 23 28 31 35 18 24 17 26 45 19 33 9 59 52 32 March 33 16 43 51 3 32 31 5 6 56 111 21 49 44 15 23 37 57 15 34 April 80 81 15 67 18 41 27 17 1 84 63 87 59 40 48 30 25 53 21 45 May 35 18 6 31 81 16 51 100 115 8 41 52 46 77 80 36 62 75 56 52 June 73 85 112 12 27 40 110 77 91 137 131 75 48 70 78 111 46 43 102 77 July 41 85 34 111 169 5 92 89 72 63 41 112 41 135 109 41 101 21 132 79 August 128 47 27 91 95 175 21 49 43 67 12 97 122 30 84 123 96 108 90 79 September 17 50 53 60 33 111 101 66 74 94 100 33 124 35 106 108 26 43 71 69 October 35 86 65 70 125 41 27 87 50 88 75 182 81 70 30 67 83 127 19 74 November 35 51 63 98 80 49 21 67 42 30 23 207 20 68 62 60 56 85 55 62 December 33 19 10 31 89 61 8 37 99 28 56 75 40 35 35 17 56 35 46 43 Year 578 668 486 657 771 673 580 661 637 715 727 977 722 703 701 712 629 727 700 685

81 STRIVER Deliverable D7.1 Part 1

Pedotransfer functions after Riley (1996)

Regression equations to calculate soil moisture retention

2 Org Vol0= 54.4 + 0.69*SOM - 0.0041*SOM2 3 Clay Vol0= 42.3 + 3.1*SOM - 0.24*Sand 4 Loam Vol0= 41.7 + 2.8*SOM - 0.13 *SAND - 0.15*GRUS 5 Silt Vol0= 39.5 + 2.6*SOM - 0.34*GRUS - 0.42*Leir + 0.08*Silt 6 Sand Vol0= 66.2 + 2.6*SOM - 0.19*GRUS - 0.44*Silt - 0.28 *SAND

2 Org Vol13= 34.1 + 1.22*SOM - 0.0095*SOM2 3 Clay Vol13= 60.9 - 18.5F + 0.19*Leir - 0.24*GRUS + 0.72*SOM 4 Loam Vol13= 54.6 - 14.3F - 0.30*GRUS + 1.0*SOM + 0.20*Leir 5 Silt Vol13= 63.9 - 14.3F - 0.18 *SAND - 0.16*GRUS + 0.59*SOM 6 Sand Vol13= 26.1 + 1.8*SOM + 0.28*Silt - 0.18*GRUS - 5.0F + 0.25*Leir

2 Org Vol2= 28.6 + 1.17*SOM - 0.0089*SOM2 3 Clay Vol2= 51.8 - 14.3F + 0.21*Leir - 0.32*GRUS + 0.78*SOM 4 Loam Vol2= 40.8 - 7.9F - 0.36*GRUS + 1.2*SOM + 0.27*Leir 5 Silt Vol2= 28.6 + 0.24*Silt - 6.5F + 0.94*SOM - 0.15*GRUS 6 Sand Vol2= 11.5 + 1.9*SOM + 0.34*Silt - 0.17*GRUS + 0.24*Leir

2 Org Vol3= 18.8 + 1.25*SOM - 0.0114*SOM2 3 Clay Vol3= 36.4 - 7.6F + 0.25*Leir - 0.35*GRUS + 0.73*SOM 4 Loam Vol3= 20.6 + 1.2*SOM - 0.30*GRUS + 0.37*Leir 5 Silt Vol3= 5.4 + 1.9*SOM + 0.76*Leir - 0.09 *SAND - 0.15*GRUS + 6.7F 6 Sand Vol3= - 1.2 + 0.65*Leir + 1.8*SOM - 0.14*GRUS + 0.14*Silt + 5.2 F

3 Clay Vol35= 17.8 + 0.40*Leir - 3.2F - 0.19*GRUS + 0.80*SOM + 0.07*Silt 4 Loam Vol35= 15.2 + 1.0*SOM - 0.23*GRUS + 0.50*Leir - 0.04*Silt 5 Silt Vol35= - 0.2 + 0.79*Leir + 1.6*SOM - 0.04 *SAND + 5.6F - 0.11*GRUS 6 Sand Vol35= - 1.5 + 0.71*Leir + 1.4*SOM - 0.11*GRUS + 4.0F + 0.07*Silt

2 Org Vol42= - 2.03 + 1.74*SOM - 0.0506*SOM2 + 4.2e – 4 *SOM3 3 Clay Vol42= - 11.5 + 0.47*Leir + 10.2F - 0.15*GRUS 4 Loam Vol42= - 11.3 + 0.48*Leir + 8.3F + 0.70*SOM - 0.07*GRUS 5 Silt Vol42= - 5.4 + 0.37*Leir + 0.82*SOM + 4.8F 6 Sand Vol42= - 3.4 + 1.0*SOM + 0.31*Leir - 0.08*GRUS + 4.2F

Regression equation for the calculation of aircapacity at pF = 2 (AIRCAP)

3 Clay Aircap2= 27.4 – 12.6 * F + 0.29 * GRUS – 0.10 * Leir 4 Loam Aircap2= 39.2 – 20.3 * F + 0.33 * GRUS – 0.89 * SOM 5 Silt Aircap2= 36.9 + 0.20 * SAND – 22.3 * F – 0.95 * SOM + 0.12 * GRUS 6 Sand Aircap2= 69.7 – 0.36 * Silt – 27.4 * F – 1.8 * SOM + 0.12 * GRUS

Regression equation for the calculation of Ksat = f( Aircap2)

3 Clay Ksat = 0.017 * e^(0.42 * Aircap2) 4 Loam Ksat = 0.064 * e^(0.33 * Aircap2) 5 Silt Ksat = 0.128 * e^(0.20 * Aircap2) 6 Sand Ksat = 0.462 * e^(0.17 * Aircap2)

82 STRIVER Deliverable D7.1 Part 1

F = dry bulk density, calculated as; F= 1.522 -0.065*SOM+0.0064 *GRUS+0.0026*depth(cm)-0.0016*Silt + 0.0022*Leir Depth of soil horizon is set to 25 cm.

Variable Meaning Identity meaning vol0, vol13, etc moisture content at pF = 0, 1.3, etc 1 rock som soil organic matter 2 organic grus gravel 3 clay leir clay 4 loam F dry bulk density 5 silt 6 sand 9 not classified

83 STRIVER Deliverable D7.1 Part 1

Reported data on discharges from scattered dwellings and industry in Hunnselva and Lena

Scattered dwellings/population, tonnes/year P Municipality Municipality _no totP_2000 totP_2001 totP_2002 totP_2003 totP_2004 totP_2005 totP_2006 Gjovik 502 0.828 0.863 2.150 1.007 0.883 0.740 0.729 Østre Toten 520 1.862 1.313 1.481 2.041 3.511 3.511 3.231 Vestre_Toten 529 1.435 1.439 1.746 1.746 1.475 1.475 1.474

Scattered dwellings/population, tonn/year N Municipality Municipality _no totN_2000 totN_2001 totN_2002 totN_2003 totN_2004 totN_2005 totN_2006 Gjovik 502 24.2 20.3 23.7 24.2 20.3 17.0 16.8 Østre Toten 520 25.7 27.5 21.3 25.7 26.6 28.9 26.6 Vestre_Toten 529 14.0 10.3 14.0 14.0 10.6 10.6 10.5

Industry, tonnes/year P Ind_ID Ind_Name X33 Y33 totP_2000 totP_2001 totP_2002 totP_2003 totP_2004 totP_2005 0502.010.01 HUNTON FIBER AS, Gjøik 265991 6747864 0.1 0.1 0.2 0.2 0.1 0.1 0502.020.01 O. Mustad & Sø A.S, Brusveen 264587 6747077 0.0 0.0 0.0 0.0 0.0 0.0 0529.006.01 Eidsiva Servicepartner 260436 6741003 0.7

Industry, tonnes/year N Ind_ID Ind_Name X33 Y33 totN_2000 totN_2001 totN_2002 totN_2003 totN_2004 totN_2005 0502.010.01 HUNTON FIBER AS, Gjøik 265991 6747864 0.7 0.5 1.2 1.1 0.1 0.1 0502.020.01 O. Mustad & Sø A.S, Brusveen 264587 6747077 2.0 2.0 2.0 2.0 2.5 2.5 0529.006.01 Eidsiva Servicepartner 260436 6741003

84 STRIVER Deliverable D7.1 Part 1

Waste Water Treatment Plants (WWTP) in Hunnselva og Lena ID_Ri ID_S verRe ewa Komm Catch EAST NORTH totP_2 totP_2 totP_2 totP_2 totP_2 totP_2 totP_2 totN_2 totN_2 totN_2 totN_2 totN_2 totN_2 totN_2 ach ge Name_ Regine une ment _33 _33 000 001 002 003 004 005 006 000 001 002 003 004 005 006 21000 0502 002.DC Hunns 26392 674665 00 AL03 Osbakken Pe A0 502 elva 0 6 5.3 5.3 5.3 5.3 5.3 7.3 149 112 112 112 112 112 175 1117 20723 0528 002.DC Hunns 27156 673333 93 AL31 Lena 4B0 528 elva 2 5 381.8 7 6 29.5 22 49 73 13528 5470 9362 9362 9362 9362 548 20743 0529 002.DC Hunns 26176 671949 66 AL26 Blaakorshjem 4BZ 529 elva 9 3 2.4 0.3 0.3 6.4 0 0.3 35 263 246 246 246 246 246 261 20738 0529 002.DC Hunns 26136 674287 50 AL50 Breiskallen C1 529 elva 1 3 1392.4 642 341.2 409.6 547 410.7 313 43913 41347 37027 41698 41698 41698 2345 20736 0528 002.DC 26808 672791 56 AL30 Fjellvold 4B0 528 Lena 1 8 12 5 7 2 3 3.2 3 465 131 443 443 443 444 22 20734 0528 002.DC 27754 672541 64 AL32 Skjeppsjoen 4A0 528 Lena 7 3 2.2 0.1 0.1 0.2 0.2 0.2 7 263 16 16 16 16 16 175 20705 0528 002.DC 26792 673109 99 AL72 Kolbu 4B0 528 Lena 0 5 52.9 5 20 6.8 12 8.5 75 3515 2300 2300 3367 3367 3367 565 20714 0528 002.DC 26648 672637 50 AL73 Lund_Ruud 4BZ 528 Lena 3 6 6.9 2 3 1.4 4 2.7 143 701 476 719 719 719 719 1073 20741 0529 002.DC 25911 672984 14 AL51 Eina C5 529 Lena 0 6 36.7 11 12.5 5.1 7 5.8 14 2610 2488 2488 2593 2593 2593 326

Reported non-treated storm water runoff (overløp) at WWTP Name of WWTP Resipient Q_m3ar Qoverlop_m3ar C_SS Susp_SS C_totP totP Fjellvold Lena Elv 9125 0 0.00 0.00 0.29 2.67 Lena Lena Elv 313535 0 0.00 0.00 0.08 25.16 Skjeppsjø Slukelva 0 0 0.00 0.00 0.00 0.00 Skreia Mjøsa 367366 0 0.00 0.00 0.16 60.44 Kolbu Lenaelva 133568 0 0.00 0.00 0.07 8.74 Lund/Ruud Lenaelva 17489 0 0.00 0.00 0.07 1.36 Blåkorshj Einavanne 5876 0 0.00 0.00 0.13 0.51 Breiskall Hunnselva 2363463 69578 0.00 0.00 0.13 393.48 Eina Hunnselva 114378 0 0.00 0.00 0.08 9.35 Osbakken Mjøsa 0 0 0.00 0.00 0.00 0.00

85 STRIVER Deliverable D7.1 Part 1

Annex to Chapter 4

A) CPCB Guidelines Values for Different Classes of Inland Surface Water

Class A: Drinking water surface Without conventional treatment but after disinfection Class B: Outdoor bathing (organized) Class C: Drinking water source with conventional treatment followed by disinfection Class D: Propagation of wild life, fisheries Class E: Irrigation, industrial, cooling, controlled waste disposal

No. Characteristics A B C D E 1. Dissolved Oxygen, mg/L, Min 6 5 4 4 - 2. Biochemical Oxygen Demand, mg/L, Max 2 3 3 - - Total Coli form Organisms* MPN/100 ml, 3. 50 500 5000 - - Max 4. Total Dissolved Solids mg/L, Max 500 - 1500 - 2100 5. Chlorides (as CL), mg/L, Max 250 - 600 - 600 6. Colour, Hazen Units, Max 10 300 300 - - 7. Sodium Absorption Ratio, Max - - - - 26 8. Boron (as B), mg/L, Max - - - - 2 9. Sulphates (as SO4), mg/L, Max 400 - 400 - 1000 10. Nitrates (as NO3), mg/L, Max 20 - 50 - - 11 Free Ammonia (as N), mg/L, Max - - - 1.2 - 12. Conductivity at 25°C, micromhos/cm, Max - - - 1000 2250 13. pH value 6.5-8.5 6.5-8.5 6.5-8.5 6.5-8.5 6.5-8.5 14. Arsenic (as As), mg/L, Max 0.05 0.2 0.2 - - 15. Iron (as Fe), mg/l, Max 0.3 - 50 - - 16. Fluorides (as F), mg/L, Max 1.5 1.5 1.5 - - 17. Lead (as Pb), mg/L, Max 0.1 - 0.1 - - 18. Copper (as Cu), mg/L, Max 1.5 - 1.5 - - 19. Zinc (as Zn), mg/L, Max 15 - 15 - - * If the coliform is found to be more than the prescribed tolerance limits, the criteria for coliform shall be satisfied if not more than 20 percent of samples show more than the tolerance limit specified, and not more than 5 percent of samples show values more than 4 times the tolerance limits. Further, the faecal coliform should not be more than 20 percent of the coliform. From Indian Standard (IS: 2296-1982). Source: http://www.wbphed.gov.in/guidelinevalues.html

86 STRIVER Deliverable D7.1 Part 1

B) Bureau of Indian Standard/Specification for Drinking Water (BIS: 10500/1991)

Permissible Requirem limit in the Sl. Substance or ent Undesirable effect outside absence of Remarks No. characteristic (Desirabl the desirable alternate e limit) Source Essential Characteristic Extended to 25 only if toxic Colour Hazen Above 5, consumer Substance are not 1. 5 25 Units, Max acceptance decreases suspect in absence of alternate sources a) test cold and Unobjecti when heated b) 2. Odour - - onable test are several dilutions Test to be Agreeabl conducted only 3. Taste - - e after safely has been established Turbidity (NTU), Above 5, consumer 4. 5 10 - Max acceptance decreases Beyond this range the water will after the mucous 5. pH value 6.5 to 8.5 No relaxation - membrane and/or water supply system Encrustation in water Total Hardness supply structure and 6. 300 600 - (mg/L) CaCO3 adverse effects on domestic use Beyond this limit taste/appearance are affected; has adverse 7. Iron (mg/L Fe), Max 0.3 1.0 - effects on domestic uses and water supply structure and promotes iron bacteria Chlorides 250 Beyond effects outside the 8. 250 1000 - (mg/L, Cl), Max desirable limit To be applicable only when water is chlorinated. Tested at Residual free customer end. 9. Chlorine (mg/L), 0.2 - - When protection Max against viral infection is required, it should be min. 0.5 mg/L. Desirable Characteristics Beyond this, palatability Dissolved solids 10. 500 decreases and may cause 2000 - (mg/L), Max gastrointestinal irritation. Calcium (mg/L, Ca), Encrustation in water 11. 75 200 - Max. supply structure and

87 STRIVER Deliverable D7.1 Part 1

adverse effects on domestic use. Encrustation in water Magnesium (mg/L, supply structure and 12. 30 100 - Mg), Max adverse effects on domestic use. Astringent taste discoloration and corrosion Copper (mg/L, Cu), 13. 0.05 of pipes fittings and 1.5 - Max utensils will be caused beyond this. Beyond this limit taste/appearance are Manganese (mg/L, 14. 0.1 affected, has advers effect 0.3 - Mn), Max on domestic use and water supply structure May be extended Beyond this causes gastro upto 400 provided Sulphate (mg/L, intestinal irritation when 15. 200 400 magnesium (as SO4), Max magnesium or sodium are Mg) does not present exceed 30 Nitrate (mg/L, NO3) Beyond this methaemo ? 16. 45 100 - Max. globinemia takes place. Fluoride may be kept as Fluoride (mg/L, F) low as possible. High 17. 1.0 1.5 - Max. fluoride may cause fluorosis. Phenolic Beyond this, it may cause 18. Compounds (mg/L 0.001 objectionable taste and 0.002 - C6H5OH) Max. odour To be tested when Mercury (mg/L Hg) Beyond this the water No 19. 0.001 pollution is Max becomes toxic Relaxation. suspected To be tested when Cadmium (mg/L, Beyond this the water No 20 0.01 pollution is Cd), Max becomes toxic Relaxation. suspected To be tested when Selenium (mg/L, Se) Beyond this the water No 21. 0.01 pollution is Max becomes toxic. Relaxation. suspected To be tested when Arsenic (mg/L, As), Beyond this the water No 22. 0.05 pollution is Max becomes toxic Relaxation suspected To be tested when Beyond this the water No 23. Cyanide 0.05 pollution is becomes toxic Relaxation suspected To be tested when Lead (mg/L Pb), Beyond this the water No 24. 0.05 pollution is Max. becomes toxic Relaxation suspected Beyond this limit it can To be tested when Zinc (mg/L, Zn) 25. 5 cause astringent taste and 15 pollution is Max an opalescence in water suspected Anionic detergents To be tested when Beyond this limit it can 26. (mg/L, MBAS), 0.2 1.0 pollution is cause a light froth in water Max suspected 27. Chromium (mg/L, 0.05 May be carcinogenic - -

88 STRIVER Deliverable D7.1 Part 1

Cr6+) above this limit Polynuclear Aromatic 28. - May be carcinogenic - - Hydrocarbons (mg/l, PAH), Max Beyond this limit, To be tested when undesirable taste and odour 29. Mineral oil (mg/L) 0.01 0.03 pollution is after chlorination takes suspected place Pesticides (mg/L), 30. Absent Toxic 0.001 - Max Radioactive materials Alpha emitters 31. - - 0.1 - (Bq/L), Max Beta emitters Pci/L 32. - - 1.0 - Max Alkalinity (mg/L), Beyond this limit, taste 33. 200 600 - Max becomes unpleasant Aluminum (mg/L, Cumulative effect is 34. 0.03 0.2 Al), Max reported to cause dementia 35. Boron (mg/L), Max 1.0 - 5.0 - From Source: http://www.wbphed.gov.in/Bureau%20of%20Indian.html

89 STRIVER Deliverable D7.1 Part 1

Pollution monitoring trends in nine stations on the Tuungabhadra (progression downstream)

pH Values

Honnali Bridge - pH values

10 9.5 9 8.5 8

pH 7.5 7 6.5 6 5.5 5 2006 2004 2003 2002 2001 2000 1999 1998 1997 1995 1994 1993 1992 1991 1990 1989 1988 1987 1985 Year

Max of pH Min of pH

Harihar Intake Point - pH values

10 9.5 9 8.5 8

7.5 pH 7 6.5 6 5.5 5 2006 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1988 1987 Year

Max of pH Min of pH

90 STRIVER Deliverable D7.1 Part 1

Harihar jackwell point - pH values

10 9.5 9 8.5 8

7.5 pH 7 6.5 6 5.5 5 2006 2005 2004 2003 2002 2001 2000 1999 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 1987 Year

Max of pH Min of pH

U/s of Harihar Poly Fibres - pH values

10 9.5 9

8.5 8

7.5 pH 7 6.5

6 5.5 5 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1989 1988 1987 1986 1985 Year

Max of pH Min of pH

91 STRIVER Deliverable D7.1 Part 1

D/s of Harihar Poly Fibres - pH values

9.5

9

8.5

8

7.5 pH 7

6.5

6

5.5

5 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 1987 Year

Max of pH Min of pH

Harihar New Bridge - pH values

10 9.5 9

8.5 8

7.5 pH 7 6.5

6 5.5 5 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 Year

Max of pH Min of pH

92 STRIVER Deliverable D7.1 Part 1

Haralahalli Bridge - pH values

10 9.5 9 8.5 8

7.5 pH 7 6.5 6 5.5 5 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1995 1994 1993 1992 1991 1990 1988 1987 1985 Year

Max of pH Min of pH

Ullanur - pH values

10 9.5 9

8.5 8

7.5 pH 7 6.5

6 5.5 5 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1995 1994 1993 1991 1990 1989 1988 1987 1985 Year

Max of pH Min of pH

93 STRIVER Deliverable D7.1 Part 1

D/s of Gangavati

10 9.5 9 8.5 8

7.5 pH 7 6.5 6 5.5 5 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1994 1993 1990 1989 1988 1987 Year

Max of pH Min of pH

94 STRIVER Deliverable D7.1 Part 1

Dissolved Oxygen (DO) Values

Honnali Bridge - DO values

10 9 8 7 6 5

DO mg/lDO 4 3 2 1 0 2006 2004 2003 2002 2001 2000 1999 1998 1997 1995 1994 1993 1992 1991 1990 1989 1988 1985 Year

Max of DO mg/l Min of DO mg/l

Harihar Intake Point - DO values

10 9 8 7 6 5

DO mg/lDO 4 3 2 1 0 2006 2005 2004 2003 2002 2001 2000 1999 1997 1996 1995 1994 1993 1992 1991 1990 1988 1987 Year

Max of DO mg/l Min of DO mg/l

95 STRIVER Deliverable D7.1 Part 1

Harihar Jackwell Point - DO values

12

10

8

6 DO mg/lDO 4

2

0 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 1987 Year

Max of DO mg/l Min of DO mg/l

U/s of Harihar Poly Fibres - DO values

10

9

8

7

6

5

DO mg/l DO 4

3

2

1

0 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1989 1988 1987 1985 Year

Max of DO mg/l Min of DO mg/l

96 STRIVER Deliverable D7.1 Part 1

D/s of Harihar Poly Fibres - DO values

12

10

8

6 DO mg/l DO

4

2

0 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 1987 1986 1985 Year

Max of DO mg/l Min of DO mg/l

Harihar New Bridge - DO valuies

10

9

8

7

6

5

DO mg/lDO 4

3

2

1

0 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 Year

Max of DO mg/l Min of DO mg/l

97 STRIVER Deliverable D7.1 Part 1

Haralihalli Bridge - DO values

12

10

8

6 DO mg/l DO

4

2

0 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1995 1994 1993 1992 1991 1990 1989 1988 1987 1985 Year

Max of DO mg/l Min of DO mg/l

Ullanur - DO values

14

12

10

8

6 DO mg/lDO

4

2

0 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1995 1994 1993 1991 1990 1989 1988 1987 1985 Year

Max of DO mg/l Min of DO mg/l

98 STRIVER Deliverable D7.1 Part 1

D/s of Gangavati - DO values

14

12

10 DO mg/l 8

6

4

2

0 2006 2005 2004 2002 2001 2000 1999 1998 1997 1996 1994 1993 1990 1989 1988 1987 1986 Year

Max of DO mg/l Min of DO mg/l

99 STRIVER Deliverable D7.1 Part 1

Biological Oxygen Demand (BOD) Values

Honnali Bridge - BOD values

6

5

4

3 BOD mg/lBOD 2

1

0 2006 2004 2003 2002 2001 2000 1999 1998 1997 1995 1994 1993 1992 1991 1990 1989 1988 1987 1985 Year

Max of BOD mg/l Min of BOD mg/l

Harihar Intake Point - BOD values

16

14

12

10

8

BOD mg/lBOD 6

4

2

0 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1988 1987 Year

Max of BOD mg/l Min of BOD mg/l

100 STRIVER Deliverable D7.1 Part 1

Harihar Jackwell Point - BOD values

45

40

35

30

25

20

BOD mg/l BOD 15

10

5

0 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 1987 Year

Max of BOD mg/l Min of BOD mg/l

U/s of Harihar Poly Fibres - BOD values

7

6

5

4

3 BOD mg/lBOD

2

1

0 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1989 1988 1987 1986 1985 Year

Max of BOD mg/l Min of BOD mg/l

101 STRIVER Deliverable D7.1 Part 1

D/s of Harihar Poly Fibres - BOD values

20

18

16

14

12

10

8 BOD mg/lBOD

6

4

2

0 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 1987 1986 1985 Year

Max of BOD mg/l Min of BOD mg/l

Harihar New Bridge - BOD values

12

10

8

6 BOD mg/lBOD 4

2

0 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1995 1994 1993 1992 1991 1990 1989 1988 Year

Max of BOD mg/l Min of BOD mg/l

102 STRIVER Deliverable D7.1 Part 1

Haralihalli Bridge - BOD values

12

10

8

6 BOD mg/lBOD 4

2

0 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1995 1994 1993 1992 1991 1990 1989 1988 1987 1986 1985 Year

Max of BOD mg/l Min of BOD mg/l

Ullanur - BOD values

14

12

10

8

6 BOD mg/lBOD

4

2

0 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1995 1994 1993 1991 1990 1989 1988 1987 1985 Year

Max of BOD mg/l Min of BOD mg/l

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D/s of Gangavati - BOD values

14

12

10

8

6 BOD mg/lBOD

4

2

0 2006 2005 2004 2003 2002 2001 2000 1999 1998 1997 1996 1994 1993 1990 1989 1988 1987 1986 Year

Max of BOD mg/l Min of BOD mg/l

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A preliminary set of basin indicators, their scoring systems and justification

Indicator Range Score Justification in the Context of Environmental Flow Assessment Indicators Related to Ecological Value (Importance and Sensitivity) Very The total number of rare and endangered species can be expressed 5 High as a percentage of the total number of species in a country, region or basin — depending on the scale of analysis. These percentages Rare and High 4 may be related to the range and to the score. The more rare and endangered Moderate 3 endangered aquatic biota is present in the basin, the more sensitive aquatic biota Minor 2 the rivers generally are to flow changes (e.g., to reduction). Consequently the more effort is needed to maintain the flow in a None 1 river at least at existing levels. Very The number of unique (endemic) species can be expressed as a 5 High percentage of the total number of species in a country, region or High 4 basin—depending on the scale of analysis. These percentages may Unique be related to the range and to the score. The assumption is that the aquatic biota Moderate 3 more unique aquatic biota is present in the basin, the more Minor 2 important it is to ensure that they do not get affected by flow modifications. Therefore, more flow and more flow variability None 1 needs to be preserved in a river. Very Can be estimated either by professional judgment or a more 5 High quantitative approach, e.g., by identifying different habitat types in High 4 representative river reaches and then calculating the representative value for a basin. Example of habitats include runs (rapidly flowing Moderate 3 water with a gradient over 4% with no surface turbulence), pools, Minor 2 glides (a shallow stream reach with a maximum depth of under 5% of the average, and without surface turbulence), pocket water (one Diversity of None 1 or a series of small pools in a section of flowing water containing aquatic numerous obstructions), backwater (abandoned channel that habitats remains connected to the active main river or secondary channel in which the inlet is blocked with deposition at low water velocities but the outlet remains connected with the active main channel), floodplains and marshes (including mangroves), etc. The assumption is that the more habitat types are present, the more incentives should exist to preserve them to ensure the aquatic biodiversity as well. Presence of > 10 % 5 protected 5 - 10 % 4 areas of natural 3 – 5 % 3 Based on the IUCN aim of 10% of the basin area to be protected. heritage and 1 – 3 % 2 The more area that is protected, pristine or ‗a must to be preserved,‘ pristine areas < 1 % 1 the more flow is likely to be necessary to be left in rivers, or to be which are released into them for maintenance of aquatic life. crossed by the main watercourse in the basin Very Can be evaluated using professional judgment and knowledge of a 5 High river. A limited decrease in flow in some rivers may result in Sensitivity of particular habitat types (e.g., floodplains, riffles, brackish costal aquatic High 4 wetlands, estuaries) becoming unsuitable for biota, compared to ecosystems to Moderate 3 other rivers, e.g., smaller rivers versus larger rivers, rivers in drier flow Minor 2 areas versus those in more humid ones, etc. The assumption is that reduction highly sensitive ecosystems need more water to maintain them in None 1 the current or desired condition.

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Percentage of 70 -100% 5 Can be estimated using RS images, from literature sources or watershed 50 – 70 % 4 based on field surveys. These are measures of the extent to which remaining natural vegetation communities have persisted in a watershed or 30 – 50 % 3 under natural a floodplain. An area that retains a high proportion of natural vegetation 10 – 30 % 2 cover types may be expected to also have many essential cover types < 10 % 1 ecosystem services, such as flood control, still intact. Because it stil contains ‗natural capital‘ in the form of natural communities, 70 -100% 5 the ecological structures and functions of such a watershed or 50 – 70 % 4 Percentage of floodplain would also be expected to be more sustainable, and floodplain 30 – 50 % 3 their resilience and ability to cope with anthropogenic and natural remaining 10 – 30 % 2 stress would be greater. The assumption is that the higher the under natural values of both indicators, the more biodiversity is likely to be vegetation preserved and the more the basin is insured against the functional cover types < 10 % 1 degradation. If the natural capital is important to maintain at existing conditions, the higher EMC will be necessary and more environmental flows will be required. > 100 % 1 The first indicator is the total dam storage in a basin as a 50 – 100 % 2 percentage of the mean flow, the second—the catchment area Degree of upstream of dams as a percentage of the total catchment area. flow 20 – 50 % 3 These are important determinants of the habitat condition and regulation 10 – 20 % 4 aquatic biodiversity. Many riverine species move large distances 0 – 10 % 5 through channel networks as part of their life history requirements. Dams and weirs disrupt longitudinal connectivity 70 -100% 1 and fragment populations leading to decline in aquatic Percentage of 50 – 70 % 2 biodiversity. Migratory species often form the basis of productive the watershed 30 – 50 % 3 fisheries and are typically the most affected by such barriers. A closed to 10 – 30 % 4 high density of impoundments prevents biota from migrating to movement of preferred habitats such as upstream spawning beds. As these aquatic biota ecological processes are degraded, the sustainability and coping by capacity of the system is reduced. Environmental flows should be anthropogenic < 10 % 5 allocated to cater for longitudinal and lateral connectivity. The structures more the river system is fragmented, the lower is the ecological status, hence a lower environmental management class is achievable. This indicator is an alternative to the above one. The ranges are

expressed in a number of structures per km of river length. 0 5 Naturally flowing river without structures. With/out upstream storage reservoirs and with possibilities of 0.001 – 0.01 4 Degree of movement upstream—like fish ladders—for aquatic fauna. flow With/out upstream storage reservoirs and with possibilities of 0.01 – 0.1 3 fragmentation movement upstream—like fish ladders—for aquatic fauna. With/out upstream storage reservoirs with/out possibility of 0.1 – 1 2 movement upstream—like fish ladders—for aquatic fauna. With/out upstream storage reservoirs with/out possibility of > 1 1 movement upstream—like fish ladders—for aquatic fauna. 0 % 5 Successful invasion by exotic species often incurs losses and 0 – 5 % 4 disruptions in ecosystem structures and functions (e.g., loss of Percentage biodiversity due to competitive exclusion and predation, aquatic biota 5 – 10 % 3 disruption and modification of food webs, loss of habitat for fish that are 10 – 20 % 2 and wildlife). Thus, the percentage of exotic species in a reach or exotics a basin provides information on its likely sustainability and > 20 % 1 coping capacity. The higher the proportion of exotic species the lower the achievable EMC is. Fish species Very High 5 Fish species relative richness, aquatic plant species relative relative High 4 richness, etc. Very High 5 These are measures of biodiversity richness, Moderate 3 remaining in a system and therefore—of its ecological capital

106 STRIVER Deliverable D7.1 Part 1 aquatic plant Minor 2 and ability to self-organize and sustain itself and cope with species None 1 Moderate 3 stressors. It is important to address relative richness, relative rather than just species counts because the baseline biodiversity richness, etc. of an area is conditional on habitat types, geographical locations, etc. Thus, the number of species that inhabit a watershed should be expressed as a percentage of the number that would be expected to occur there in the absence of human interventions. Xenopoulos et al. (2005) have shown that fish species numbers are reducing with reducing discharge. The reference condition is, however, very often difficult to establish and consequently the quantification of ranges is also difficult. As a surrogate for the percentage of some ‗natural‘ reference condition, the species richness may be quantified as a percentage of overall species in the country or geographical zone, or established by professional judgment. Human < 10 % 1 population 10 – 20 % 2 density in the Can be estimated using Census data. Districts located primarily entire river 20 – 40 % 3 in floodplain areas can be used to estimate population density in basin as a 40 – 60 % 4 floodplains, other districts - to estimate population density in the percentage of > 60 % 5 rest of the basin. It is assumed that this measure may be seen as the an aggregate indicator of human pressure on aquatic ecosystems population and as an indicator of disruption of lateral connectivity in river density in the basins. main floodplains Class A 5 National Indian categorization of water quality is used, where Class B 4 each class is characterized by certain ranges of constituents. Water in Class A can be used for drinking after disinfection; Overall water Class C 3 water in class B is only for swimming and bathing; water in quality in the Class D 2 Class C requires conventional treatment and disinfection before basin drinking; water in Class D is suitable for propagation of wildlife Class E 1 and fisheries; and water in class E is only suitable for such uses as irrigation and industry Adapted from Valdimir Smakhtin, Muthukumarasamy Arunachalam, Sandeep Behera, Archana Chatterjee, Srabani Das, Parikshit Gautam, Gaurav D. Joshi, Kumbakonam G. Sivaramakrishnan and K. Sankaran, Developing Procedures for Assessment of Ecological Status of Indian River Basins in the Context of Environmental Water Requirements, IWMI research report 114, IWMI, Colombo, www.iwmi.cgiar.org/Publications/IWMI_Research_Reports/PDF/PUB114/RR114.pdf

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