INCO-CT-2004-509091

OPTIMA

Optimisation for Sustainable Water Resources Management Instrument type: Specific targeted research or innovation project Priority name: SP1-10

D12.1 Case Study: Gulf of Tunis Due date: 31/07/06 Actual submission date: 11/07/06 Start date of project: 01/07/2004 Duration: 36 months Lead contractor of deliverable: CNTD Revision: vs 1

Project co-funded by the European Commission within the Sixth Framework Programme (2002-2006) Dissemination level PU Public X PP Restricted to other programme participants (including the Commission Services) RE Restricted to a group specified by the consortium (including the Commission

Services)

CO Confidential, only for members of the consortium (including the Commission Services)

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Table of Contents Table of Contents .......................................................................................................................... 2 LIST OF FIGURES........................................................................................................................ 3 LIST OF TABLES.......................................................................................................................... 4 I INTRODUCTION......................................................................................................................... 5

I.1 Study area ............................................................................................................................ 5 I.2 Geology ................................................................................................................................ 6 I.3 Hydrogeology........................................................................................................................ 6

Water supply .......................................................................................................................... 6 Exploitation............................................................................................................................. 6

II CLIMATOLOGICAL DATA ......................................................................................................... 7 II. 1 Temperature ....................................................................................................................... 7 II. 2 Precipitation ........................................................................................................................ 8

III Socio-economic data................................................................................................................. 9 III. 1 Legislation: Legislative and regulatory accomplishments.................................................. 9 III.2 Social indicators................................................................................................................ 11 III.3 Economic indicators.......................................................................................................... 12

IV STAKEHOLDERS................................................................................................................... 14 IV.1 Stakeholders data base.................................................................................................... 14 IV.2 Local networks, user group .............................................................................................. 16

V GEOGRAPHIC DATA BASE ................................................................................................... 18 VI LAND USE CHANGE.............................................................................................................. 23

VI.1 Introduction....................................................................................................................... 23 VI.2 Methodology adopted for the cartography of the Land Use map ..................................... 24 VI.3 Land Use map (Years 1988 & 2000)................................................................................ 25 VI.4 Land use statistics............................................................................................................ 26 VI.5 Land Use Change methodology....................................................................................... 27 VI.6 Land Use Change statistics.............................................................................................. 28

VII RAINFALL RUNOFF MODEL (RRM) .................................................................................... 30 VII.1 Model components .......................................................................................................... 30 VII.2 Implementation of the RRM scenario .............................................................................. 33 VII.3 Results ............................................................................................................................ 37

VIII WATER RESSOURCES MODEL (WRM)............................................................................. 40 VIII.1 Case study description ................................................................................................... 40 VIII.2 Data collected................................................................................................................. 40 VIII.3 Implementation of the WRM........................................................................................... 42

VIII.3.1 Implementation of the Times Series data ................................................................ 42 VIII.3.2 Topologic model of the Melian basin ....................................................................... 43

VIII.4 Results of the WRM ....................................................................................................... 46 VIII.4.1 Annual mass budget summary ................................................................................ 46 VIII.4.2 Annual sectoral demand .......................................................................................... 47 VIII.4.3 Annual groundwater mass budget ........................................................................... 48

IX CONCLUSION........................................................................................................................ 49 ANNEXES ................................................................................................................................... 50

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LIST OF FIGURES Figure 1: Digital Model Elevation and Drainage network .............................................................. 5 Figure 2: Tunisia Stakeholders.................................................................................................... 14 Figure 3: Institutions analysis ...................................................................................................... 15 Figure 4: Land Use map (1988 & 2000) ...................................................................................... 25 Figure 5: Land use change.......................................................................................................... 27 Figure 6: Digital Elevation Model................................................................................................. 30 Figure 7: Parameters of the RRM ............................................................................................... 35 Figure 8: Introduction of the precipitation, temperature and inflow ............................................. 35 Figure 9: Hypsometric curve of the Melian basin ........................................................................ 36 Figure 10: Land use coefficient of the Melian basin .................................................................... 36 Figure 11: Detail results of the RRM ........................................................................................... 37 Figure 12: Detail results of RRM ................................................................................................. 38 Figure 13: Detail results of RRM ................................................................................................. 39 Figure 14: WaterWare node charts ............................................................................................. 41 Figure 15: WRM scenario............................................................................................................ 42 Figure 16: Implementation of time series data ............................................................................ 42 Figure 17: Topological model of the Melian basin....................................................................... 43 Figure 18: Creation of the Base line scenario of the Melian basin .............................................. 44 Figure 19: Parameters of the Hma reservoir ............................................................................... 45 Figure 20: Parameters of the demand node................................................................................ 45 Figure 21: Annual Mass budget summary................................................................................... 46 Figure 22: Annual Sectoral Demand ........................................................................................... 47 Figure 23: Annual Groundwater Mass Budget ............................................................................ 48

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LIST OF TABLES Table 1: Mean temperatures for the year 2003 ............................................................................. 7 Table 2: Mean pluviometry for the year 2003................................................................................ 8 Table 3: Social indicators ............................................................................................................ 11 Table 4: Economic indicators ...................................................................................................... 12 Table 5: Water consumption ....................................................................................................... 12 Table 6: Local networks, user group ........................................................................................... 17 Table 7: Descriptive GIS data ..................................................................................................... 21 Table 8: Institutions analysis ....................................................................................................... 22 Table 9:Land use statistics.......................................................................................................... 26 Table 10: Land Use Change statistics......................................................................................... 28 Table 11: Rainfall Runoff Model parameters............................................................................... 32 Table 12: RRM- Scenario selection............................................................................................. 33 Table 13: Daily time series of inflow measured at TUBURBO MAJUS station ........................... 34 Table 14: Daily time series of precipitation measured at Kallat Andalous Station ...................... 34 Table 15: Environmental Indicators............................................................................................. 51

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I INTRODUCTION

I.1 Study area The subcatchment of Melian, our study area, has its source in Sminja, situated 5 kilometers from the ouest region of Zaghouan. The study area extends to Rades city and it’s limited by the sea. The subcatchment is characterized by a huge plain, called Mornag plain, which receives water from the mountainous areas in the vicinity. Mornag plain is the downstream part of the hydrologic basin of Melian river. This plain has a hot and dry summer and a mild winter. The inter-annual mean pluviometry is about 490mm. This plain is principally crossed by Melian river with is main affluent, El Hma river.

Medjerda

Main river

Drainage network

0-100-200-300-400-500-600-700->80

Elevation in meters

Case Study: Melian basin, TUNISIA Figure 1: Digital Model Elevation and Drainage network

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I.2 Geology The Mornag plain represents a huge depression downstream Melian and Hma rivers. It’s a synclinal basin (Schoeller, 1932) limited in the NW and SE by an anticlinal. This area includes Sidi Salem, Ressas and Bou Kornine mountains. This basin is surrounded by quaternary deposits. The center of the basin is also covered by quaternary sediments but they are more recent than those in the surroundings. The NW limit is made up from M’hamdia anticlinal and Khlidia synclinal. This one is characterized by a subsidence of its axis to the sea, which represents the hydraulic limit of the system. The geological structures met in the region are:

• Oligocenous outcrops stretching out on a huge area (Khlidia) among 14 km². It is an alternation of coarse sandstone with some clay banks which sometimes are distant the ones from the others. The total thickness can reach 500m

• The Miocene is composed by sandstone marl which has a thickness of 400m. • The quaternary which is dominant in the plain is composed by sandy clay, sand, gravel,

pebbles and silt. Near the wadi, the pebbles are dominant. From the lithological point of vue, the basin is essentially composed by an alternation of sand and clay with a predominance of sand along the edge.

I.3 Hydrogeology The Mornag plain contains a complex aquifer system in which there is a deep table represented by an aquifer containing in one hand, quaternary series in the center of the basin and in the other hand oligocenous sandstone series which surmount clay from superior Eocene and this constitutes the most interesting level of the aquifer in the system. The sandstones from Oligocene represent an important mass which can reach 500m of thickness. This characteristic allows a big water accumulation. The clay banks and marl aren’t numerous and don’t constitute an obstacle for water circulation. There is no lithologic discontinuity between quaternary and Oligocene structures. These ones are lying over the clayey roof of the superior Eocene.

Water supply The aquifer supply is assured by a direct percolation of rainfall in the sandstone outcrops of the aquifers in Khlidia, Ettella, Rouf and Rades. Water supply is also coming from rain water and from the hydrographic network. The stock of the water table is about 38.5 106 m3/year.

Exploitation The exploitation was in the beginning oriented towards surface wells and after towards drills which exploit deeper waters. The intensification of table exploitation has as a consequence a drop in the piezometric levels and an increasing of the salinity of underground waters especially in the areas near the outlet (sea and lacks). The aquifer exploitation for the year 2003 is as follow:

• 2460 surface wells, with 1449 wells equipped with an exploitation of 22 106 m3/year.

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• 494 deep drills exploiting 26.1 106 m3/year. The aquifer system of Mornag is exploited at the rate of 48.11 106 m3 with an overexploitation of 9.6 106 m3/year which is directly taken from the geological stock of the water table.

II CLIMATOLOGICAL DATA Our region belongs to the Mediterranean Bioclimatical class, which is semi-arid and characterized by warm winter. Like all the Mediterranean regions, the climate has got 4 seasons. Ben Arous region is characterised by a hot summer and a warm winter with an irregular pluviometry.

II. 1 Temperature The averaged temperatures as well as the maxima and minima recorded in the Tunis_Carthage station are detailed in the table below. The annual averaged temperature is 19.7°C.

Month Min Max January 7.2 15.7 February 7.4 16.5 March 8.3 18.1 April 10.4 20.7 May 13.7 24.9 June 17.3 29 July 20 32.6 August 20.8 32.7 September 19 29.7 October 15.5 25.2 November 11.3 20.5 December 8.2 16.7

Source: INM, 2003 (www.meteo.tn)

Table 1: Mean temperatures for the year 2003 The maxima are recorded from June to September. The minima correspond to the period from December to march (see figure below). We notice that the extreme temperature can reach 32.6°C in August in the Tunis_Carthage station. The extreme minus temperatures reach 7.2°C in January. The temperatures show a thermic contrast between a hot and dry summer and a cold and humid winter.

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II. 2 Precipitation The rainiest months in our case study are those going from September to May whereas the driest months are June, July and August.

Month Min Max January 59 12 February 57 12 March 47 11 April 38 9 May 23 5 June 10 3 July 2 1 August 7 2 September 36 6 October 66 9 November 54 10 December 63 12

Source:INM, 2003 (www.meteo.tn)

Table 2: Mean pluviometry for the year 2003

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III Socio-economic data Socio-Economic Framework and Guidelines Water is essential to all life forms. It is the most precious resource because it is both rare and fragile. Although Tunisia is situated on the Mediterranean, much of the country’s land surface falls within the arid zone. Tunisia has limited water resources, unevenly distributed in geographical and seasonal terms. Population growth and socio-economic development have meant a corresponding growth in water needs. The result is an increasing pressure on the country’s capacity to provide this rare resource in sufficient quantities. For the future generations, the country has been developing skills to manage water scarcity resources in order to satisfy demand without having to ration water, even during the most severe droughts. Nevertheless, water is a priority, and it is clearly the key to future sustainable development across the country. Tunisia realized a complex and diversified hydraulic infrastructure all over the country to mobilize and manage all water resources and implemented a management system and a progressive legislation in purpose to answer to all social and economic needs. The issue of sewage techniques and management clearly goes beyond the question of environmental protection and public health. The resource must be recycled in order to maintain a healthy water balance.

III. 1 Legislation: Legislative and regulatory accomplishments Tunisia is currently considered as being fairly advanced along the process of development of its legal nomenclature in the field of the environment. Following the set up of the National Agency for the Protection of the Environment (ANPE), it has not ceased to revise the various instruments established as to renew its legislation with the evolution of the environmental context. Accordingly, following the Rio Conference, Tunisia undertook, in the 1990s, to promulgate a certain number of legislative texts related to the environment and the conservation of the natural heritage, such as:

• Law N° 94 – 1223, November 28, 1994, the promulgation of the Code for Land Planning and Urbanization;

• Law N° 95 – 72, July 24, 1995, bearing the creation of the Agency for the Protection and Land Use of the Coastline (APAL);

• Law N° 95 – 73, July 24, 1995, related to the Maritime Public Domain; • Law N° 96 – 29, April 3, 1996, concerning the setting up of a national Emergency Plan

for Combating Marine Pollution; • Law N° 96 – 41, related to wastes, the control of their management and of their

elimination. The various texts have been accompanied by many implementation texts of a regulatory nature. The areas concerned by the implementation texts issued during the 2001 are:

• Sanitation; • Water saving and non conventional water resources; • Management of wastes; • Energy management.

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Soil and water conservation

• Law 75/16 (31 March 1975), relative to the Water Code. • Law (17 July 1995) regarding soil and water conservation • Law 95-70 on the National Council for the Conservation of Water and Soil

Waste water management

• Decree 86-56 (2 January 1986) related to the on regulations of discharges into the environment

• Decree 79-768 (8 September 1979) completed by Decree 94-1885 (12 September 1994), laying down regulations on conditions for discharging residual water, other than household, waste water, into the public sewage network located in areas where the ONAS is responsible for sewage services.

• Decree 94-2050 (3 October 1994), laying down the conditions for connection to the public sewage network located in the areas under the responsibility of ONAS for sewage services.

• Law N°75-16 (31 March 1975): concerning the waste water for agricultural use which is only authorized after appropriate purification in treatment stations.

• Decree N°93-2447 (13 December 1993) modifying Decree N°89-1047 (28 July 1989): lays down the use conditions for treated waste water subject to authorization as well as the physico-chemical analyses to be undertaken.

• Circular of 21 June 1995: provides a list of crops which may be irrigated with treated waste water.

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III.2 Social indicators • Resident population : 481960 inhabitants (2003) • Population density : 629 inhabitants/km² (2003)

Social indicators Value Year National average or % of national value Source

Population structure by slices of age

00-04 years 36200 inhab 2002 4.64% 05-19 years 134600 inhab 2002 4.45% 20-59 years 262500 inhab 2002 5.16% >60 years 34000 inhab 2002 3.81% Synthetic Index of fertility 1.66 child 2001 2.05 child

population density 628.65 inhab per km² 2003 64.16 inhab per km²

Internal migration rate 37508 2004

National institute of statistics

% of connection to drinkable water

95.0% 2003 84.90% SONEDE-DGGR-INS

% of householders connected to electric network

99.00% 2003 96.30%

Density of telephone network 19 Tel per 100 inhab 2003 12.6 Tel per 100 inhab

Urbanization rate 90.85% 2003 63.57% Illiteracy rate 12.50% 2003 22.4%

Number of active women per 100 men

38.87 1999 32.65

Unemployment rate 16.80% 1999 15.80%

National institute of statistics

Mortality rate 4.9 death per 1000 hab 2002 5.8 death per 1000

inhab Number of inhabitants per doctor 1307 2003 1208

Number of beds in hospital for 1000 inhabitants

0.08 2002 1.71

Ministry of public breath

Source: PRE, Ben Arous Table 3: Social indicators

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III.3 Economic indicators

Economic indicators Value Year National average or % of national value

Source

Cultured land areas by cultivation type Cereal 11000 ha 2003 0.72% DGPA Fodder 5610 ha 2003 1.39% DGPA grains 280 ha 2003 0.40% DGPA Market gardening 970 ha 2003 0.65% DGPA Arboriculture 15850 ha 2003 0.74% DGPA Industrial cultures and others 20 ha 2003 0.09% DGPA

Irrigated land use rate 91% 2003 79% DGEDA

Intensification rate 91% 2003 88% DGEDA Livestock size Bovine 15950 units 2003 2.35% DGEDA Ovine 41330 units 2003 0.62% DGEDA goat 11340 units 2003 0.82% DGEDA

Source: PRE, Ben Arous

Table 4: Economic indicators Water consumption per sector

Agriculture 81,5 m3/year

Industry 5,93 m3/year

Domestic 16,58 m3/year

Tourism 0,33 m3/year

Table 5: Water consumption

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Water costs are calculated as follows: 0 - 20 m3 =0,130 DT/ m3 / term (0.089 €) 21 - 40 m3 = 0,200 DT/ m3 / term (0.136 €) 41 - 70 m3 =0,400 DT/ m3 / term (0.273 €) 71 - 150 m3 = 0,605 DT/ m3 / term (0.414 €) 150 m3 = 0,740 DT/ m3 / term (0.506 €) This system is implemented nationally Tourism: 0.740 DT/ m3 (unique price) (0.506 €) Agriculture: 0.060 DT/ m3 (unique price) (0.041 €)

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IV STAKEHOLDERS

IV.1 Stakeholders data base

Figure 2: Tunisia Stakeholders

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Figure 3: Institutions analysis Figure 3: Institutions analysis

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IV.2 Local networks, user group Institution Acronym Address Tel/ Fax/e-mail Contact

person Agency for Coastal Protection and Management APAL

2 Rue Md Rachid Ridha - Tunis Belvédère BP 200 - 2045 Tunis

T:216 71 840 177 F: 216 71 848 660 boc@apal.nat.tn

Walid REFAI Imen BOUAZIZ

Société d'Etude et de Conseil Tunisie SECT

App C3 Résidence Badr El Manar I CP 1004

T:216 98 22 28 55 F: 216 71 255 217 y.belkhiria@gnet.tn

Yacine BELKHIRIA

Regional Commissariat for Agriculture Development (Zaghouan)

CRDA Zaghouan

Av. Hédi Chaker - Zaghouan 1100

T:216 72 675 911 F:216 72 675 419

Néjib ELLOUZ Ali ETTABOURI

Institut National Agronomique de Tunis (National Agronomic Institute of Tunis)

INAT

43, Avenue Charles Nicolle 1082 Mahrajène

T :216 71 892 785 F :216 71 799 391

Zohra LILI CHABAANE

Direction Générale des Ressources en Eau DGRE

43 Rue essaida Manoubia - 1008 Tunis Cedex

T :216 71 560 000 F :216 71 391 549

Yosra BEN SALAH Md Néjib KACHOURI

National Centre for Remote sensing (Centre National de Télédétection) CNTD

Route de la Marsa. BP 200 1080 Tunis Cedex

T :216 761 333 F :216 760 890 cnt.dg@cnt.nat.tn

Myriam HAFFANI Ahmed EZZINE Emna KOCHLEF

National Sanitation Board (Office National de l'Assainissement) ONAS

32, Rue Hédi Nouira - 1001 Tunis

T :216 71 343 200 F :216 71 350 411 boc@onas.nat.tn

Khalil ATTIA Jamel LAABIDI Adel MAZLOUT

National Agency for Environment Protection ANPE

12 rue du Cameroun BP 52 1002 Tunis Belvédère

T : 216 71 847 122 F : 216 71 848 069 anpe.boc@anpe.nat.tn

Jamil SAADANI Mounira HAMDI

General Direction of Dams and Large hydraulic works (Direction Générale des barrages et des grands travaux hydrauliques)

DGBGTH

30, rue Alain Savary 1002 Tunis

T :216 71 840 289 F : 216 71 840 289 geore@iresa.agrinet.tn

Hédi BEL HADJ

Laboratoire Eau et Environnement, Institut INRST BP 95

2050 Hamam Lif T : 216 71 430 044 F : 216 71 430 934

Makram ANNANE

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National de Recherche Scientifique et Technique

Tunisie webmaster@inrst.rnrt.tn

Tunisian National School of Engineers (Ecole Nationale des Ingénieurs de Tunis) ENIT

BP 37 le Belvedère Campus Universitaire Tunis - 1002

T : 216 71 873 180 F : 216 71 872 729 enit@enit.rnu.tn

Kaies EJEDIDI

Faculty of Science of Tunis (Faculté des Sciences de Tunis) FST

Faculté des Sciences de Tunis 1060 Tunis

T :216 71 882 099 F: 216 71 885 480

Moez JAOUED

Tunisian Union of Agriculture and Fishery ( union Tunisienne de l’Agriculture et de la Pêche)

UTAP

Rue Alain Savary 1003 Cité El Khadhra

T : 216 71 800 800 F : 216 71 807 041 Utap.tunis@email.ati.tn

Mokhtar BARBOUCH

Regional Commissariat for Agriculture Development CRDA

Immeuble Sprols N.Médina -2063(Ben Arous)

T : 216 71 310 037 F :216 71 310 577

Md Lotfi NACEF Lassaad AGAL

Ministry of Agriculture and Hydraulic Resources (Ministère de l'Agriculture et des Ressources Hydrauliques)

MA

30 Rue Alain Savary - 1002 - Tunis

T: 216 71 786 833 F: 216 71 766 107 mag@ministeres.tn

Wadi ELLEUCH

National Research Institute of rural engineering and forestry (Institut National de la Recherche en Génie rural)

INGREF

Rue Hédi Karray BP 10 2080 Ariana

T: 216 71 719 630 F: 216 71 717 951

Noureddine GAALOUL

unis International Center for Environnemental Technologies

CITET Boulevard de l'Environnement - 1080 Tunis Cedex

T :216 71 770 938 F: 216 71 772 255 boc@citet.nat.tn

Habib GHANNOUCHI

Table 6: Local networks, user group

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V GEOGRAPHIC DATA BASE The geographic data was digitized from topographic maps in the 1:25.000 scale

• Tunis (NE-NO-SE-SO) • Bir M’charga (NE-NO-SE-SO) • Grombalia (NO-SO) • La goulette (NO-SO) • Zaghouan (NO-NE) • Bouficha (NO)

The projection system: Universal Transverse Mercator (UTM) Datum: Clarke 1880 Origin: Carthage The vector layers that will be integrated in the GIS as coverage were digitized from scanned and geometrically corrected maps. We have 13 coverages in Shp format (ArcView) and their associated descriptive data. [See table]

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Complete Noun

Kind of object Scale Acquisition

method theme Data date Distributor Attributes

Settlement Polygon 1/25000 from Land

use Cadastral

Topographic map, edited in may 1997

by Office de Topographie et de Cartographie (OTC)

CNT Id, Code, Surface_Ha

Villages Point 1/25000 digitalization Cadastral

Topographic map, edited in may 1997

by Office de Topographie et de Cartographie (OTC)

OTC

X_coor, Y_coor, Village_id, Cc_village, vill_char, pop_94

Elevation points Point 1/25000 digitalization Topography

Topographic map, edited in may 1997

by Office de Topographie et de Cartographie (OTC)

OTC

X_coor, Y_coor, Elev_id, Elev

Drainage networks Line 1/25000 digitalization Hydrogeology

Topographic map, edited in may 1997

by Office de Topographie et de Cartographie (OTC) 1997

OTC

Fnode_, Tnode_, Hyl_typ , Dr_if, Drlength,

OTCCc_dr_, Dr_name

Road networks Line 1/25000 digitalization Cadastral

Topographic map, edited in may 1997

by Office de Topographie et de Cartographie (OTC)

OTC

Fnode_, Tnode_,

Road_len, Cc_road_, Road_cat,

Road_id, Classe

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Contours Line 1/25000 digitalization Topography

Topographic map, edited in may 1997

by Office de Topographie et de Cartographie (OTC)

OTC

Cont_id, Fnode_,Tnode_,

Cont_elev, C_length, Cc_cont_, Cont_int

Area location polygon 1/200000 digitalization Topography

Topographic map, edited in may 1997

by Office de Topographie et de Cartographie (OTC)

CNT

Study_id, Study_ar, Study_pe, Cc_study

Cadastral/ municipality boundaries

polygon 1/200000 digitalization Cadastral

Topographic map, edited in may 1997

by Office de Topographie et de Cartographie (OTC)

OTC

Nom_del, Mun_id,

Mun_area, Mun_prm, Cc_mun

Bioclimatic polygon 1/25000 digitalization Meteorology

Bioclimatic map edited by (Centre National de

Recherche Scientifique (CNRS) Paris 1967 1997

Institut National de

la Météorologie

(INM)

Pluv_id, Pluv_area, Pluv_prm, Pluv_int, Cc_pluv_

Soil polygon 1/25000 digitalization Pedology Pedological Map of Tunisia,

edited in ,,,,,,, by Ministere de l'agriculture

Direction des sols

Sol_desc, Sol_area,

Sol_prm, Sol_id

Groundwater polygon 1/25000 digitalization Hydrogeology Groundwater Map of Tunisia, edited in 1990 by CNT

Direction Generale

des ressources

en eau (DGRE),

CNT

code, Résidu_sec

Geology digitalization geology Geological Map of Tunisia,

edited in 1985 by Office National des Mines

Office National des

Mines

Geo_code, Geo_facies, Geo_area,

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(ONM) Geo_prm

Land use (1988) polygon 1/25000

photo interpretation

and classification

land use 2006 CNT Classe, Cont,

Lu_prm, Lu_area

Land use (2000)

photo interpretation

and classification

land use 2006 CNT Cont, Lu_prm, Lu_area

Table 7: Descriptive GIS data

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Table 8: Institutions analysis

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VI LAND USE CHANGE

VI.1 Introduction The land use change was realized with two land use maps:

• Land use map of 1988 • Land use map of 2000

Each land use has 12 layers obtained from satellite imagery (1988) and from aerial photography (2000). The Corine legend was adopted in the two classifications. The layers obtained are: a- Artificial Surface

• 11: Urban fabric • 12: Industrial, commercial and transport units • 13: Mine, dump and construction sites

b- Agricultural Area

• 21: Arable land • 22: Permanent crops • 23: Pastures • 24: Heterogeneous agricultural areas

c- Forest and Semi-natural area

• 31: Forest • 32: Shrubs and/or herbaceous vegetation associations • 33: Open spaces with little or no vegetation

d- Water Bodies

• 51: Inland waters • 52: Marine waters

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VI.2 Methodology adopted for the cartography of the Land Use map

Natural areas

Arable land Permanent crops

Pastures Heterogeneous agricultural

Aerial photography

Photo-interpretation and classification

Corine land cover legend

Agricultural areas Artificial Surface

Urban fabric

Industrial, commercial area Dump and mine

Forest Water bodies

LAND USE MAP

Spot XS

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VI.3 Land Use map (Years 1988 & 2000)

Land use

Land use

Figure 4: Land Use map (1988 & 2000)

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VI.4 Land use statistics Area (Km²) Area (%)

Classes Code 1988 2000 1988 2000

11: Urban fabric 21293116 23422292 3,79 4,12 12: Industrial, commercial and transport units 999699 20937925 0,18 3,68 Artificial Surface

13: Mine, dump and construction sites 2049048 5413689 0,37 0,95 21: Arable land 510320 13155173 0,09 2,31 22: Permanent crops 435999932 364134746 77,7 64,07 23: Pastures 0 3114568 0 0,55

Agricultural Area

24: Heterogeneous agricultural areas 6739353 8887165 1,2 1,56 31: Forest 42495422 41423570 7,57 7,2932: Herbaceous vegetation association 32890461 56813002 5,86 10 Forest and natural area

33: Open spaces with little or no vegetation 96096 286228 0,02 0,05 51: Inland waters 8033936 14797447 1,43 2,6 Water Bodies 52: Marine waters 1805042 454963 0,32 0,08

Area (Km²) Area (%)

Classes 1988 2000 1988 2000

Artificial Surface 24,341863 49,773906 4,40 9,00 Agricultural Area 443,249606 389,291651 80,17 70,42 Forest and natural area 75,481979 98,522800 13,65 17,82 Water Bodies 9,838978 15,252411 1,78 2,76

Table 9:Land use statistics

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VI.5 Land Use Change methodology The land use change between the two years 1988 and 2000 was obtained using the Arcview 3.2 software. The steps followed are:

a) Intersection of the two land use maps using Arcview geoprocessing wizard b) Creation of a new field named LUC in the attribute table of the result map c) We put “0” if there is not change and “1” if there is one d) A new classification (land use change) based on the new field named LUC

NO change Change

Figure 5: Land use change

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VI.6 Land Use Change statistics

1988 2000 LUC/total Classes area(m²) area(m²) %

Urban fabric 21293116 23422292 0,39 Industrial, commercial and transport units 999699 20937925 3,61 Mine, dump and construction sites 2049048 5413689 0,61 Arable land 510320 13155173 2,29 Permanent crops 435999932 364134746 -13,00 Pastures 0 3114568 0,56 Heterogeneous agricultural areas 6739353 8887165 0,39 Forest 42495422 41423570 -0,19 Shrubs and/or herbaceous vegetation associations 32890461 56813002 4,33 Open spaces with little or no vegetation 96096 286228 0,03 Inland waters 8033936 14797447 1,22 Marine waters 1805042 454963 -0,24

Classes 1988 area(m²)

2000 area(m²) LUC /total (%)

Artificial Surface 24341863 49773906 4,60 Agricultural Area 443249606 389291651 -9,76 Forest and Semi-natural area 75481979 98522800 4,17 Water Bodies 9838978 15252411 0,98

Table 10: Land Use Change statistics

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-0,24

1,22

0,03

4,33

-0,19

0,390,56

-13,00

2,29

0,61

3,61

0,39

-16

-14

-12

-10

-8

-6

-4

-2

0

2

4

6

Var

iabl

e in

dex

Urban fabric

Industrial, commercial and transport units

Mine, dump and construction sites

Arable land

Permanent crops

Pastures

Heterogeneous agricultural areas

Forest

Shrubs and/or herbaceous vegetationassociationsOpen spaces with little or no vegetation

Inland waters

Marine waters

Figure 6:Land use change distribution areas

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VII RAINFALL RUNOFF MODEL (RRM) We used the Melian catchment as a start node in our scenario for the RRM model.

Figure 7: Digital Elevation Model

VII.1 Model components The rainfall-runoff model is a dynamic (daily) lumped water budget model for small to medium-sized basins. Time-series data are required for the model. The majority of the model components lie within three parameter groups. They are: Catchments’ parameters Describe the dimensional elements and drainage characteristics of the catchment. This is in addition to Land use/Land cover classification. Model parameters They primarily tackle the climatic conditions and major hydrologic elements. Thus, that involves several hydrologic elements controlling water percolation from surface into subsurface media. This is expressed by initial conditions and groundwater parameters. Basin specific Model Constants Include constants relating to basin and land use parameters. Main among them are root zones, interception storage and infiltration rate.

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Basin Parameters

Catchment Size km2 553 Minimum elevation masl 0 Maximum elevation masl 720 Channel Length km 56 Drainage Length km 1598

Model Parameters Precipitation factor %/100m 3 Precipitation scale 1 Adiabatic lapse rate deg/100m 0.5 Temperature shift deg 0 Field capacity mm/m 200 Maximum percolation rate mm/day 10

Initial Conditions Initial condition: snow mm 0 Initial condition: interception mm 0 Initial condition: soil moisture % 40 Initial condition: shallow groundwater mm 200 Initial condition: deep groundwater mm 50

Groundwater Parameters

Shallow groundwater: drainage coefficient 0.001 Shallow groundwater: drainage exponent 1.0

Deep groundwater drainage: half time days 120 Deep percolation mm/m/day 0.01

Basin specific Model Constants Degree Day: interception mm/deg 1 Degree Day: snowmelt mm/deg 0.3 Heavy rain limit mm 10 PEVT reduction factor 0.6 Infiltration reduction factor 0.6 Percolation reduction factor 0.8 Minimum temperature evapotranspiration deg 4 Warm rain effect on snowmelt mm/mm*deg 2 Agriculture Specific Constants Root zone agriculture m 1.5 Degree Day: agriculture mm/deg 0.3 Interception storage agriculture mm 2 Maximum infiltration: agriculture mm/day 50

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Forest Specific Constants Root zone forest m 1.5 Degree Day: forest mm/deg 0.3 Interception storage forest mm 3 Maximum infiltration: forest mm/day 60

Pasture Specific Constants Root zone pastures m 0.5 Degree Day: pastures mm/deg 0.3 Interception storage pastures mm 2 Maximum infiltration: pastures mm/day 40

Residual Specific Constants Root zone residual m 0.25 Degree Day: residual mm/deg 0.3 Interception storage residual mm 1 Maximum infiltration: residual mm/day 20

Table 11: Rainfall Runoff Model parameters

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VII.2 Implementation of the RRM scenario We have implemented the RRM scenario of the Melian catchment.

Table 12: RRM- Scenario selection

The RRM model also requires as input, a daily value of precipitation and temperature, so we used:

Day Sept Octo Nove Dece Jan Feb March April May June July August1 0 0.002 0 0 0 0.001 0 0 0 0 0 0 2 0 0.002 0 0 0 0.001 0 0.002 0 0 0 0 3 0 0.002 0 0 0 0.001 0 0.002 0 0.001 0 0 4 0 0.001 0 0 0 0.001 0 0.001 0 0.001 0 0 5 0 0.001 0 0 0 0.001 0 0.001 0 0 0 0 6 0 0 0 0 0 0.001 0 0.001 0 0 0 0 7 0 0 0 0 0 0.015 0 0.001 0 0 0 0 8 0 0 0 0 0 0.003 0 0.001 0 0 0 0 9 0.32 0 0 0 0 0.001 0 0.001 0 0 0 0

10 1.82 0 0 0 0 0.001 0 0.002 0 0 0 0 11 0.002 0 0 0 0 0.001 0 0.001 0 0 0 0 12 0.002 0 0 0 0.053 0.001 0 0.001 0 0 0 0 13 0.001 0 0 0 0.051 0.001 0 0.001 0 0 0 0 14 0.001 0 0 0 0.002 0 0 0.001 0 0 0 0 15 0.001 0 0 0 0.001 0 0 0.001 0 0 0 0 16 0.042 0 0 0 0.001 0 0 0.001 0 0 0 0 17 0.296 0 0 0 0.001 0 0 0.001 0 0 0 0 18 0.01 0 0 0 0.005 0 0 0.001 0 0 0 0.002 19 0.003 0 0 0 0.002 0 0 0.001 0 0 0 0.038 20 0.003 0 0 0 0.001 0 0 0.001 0 0 0 0 21 0.003 0 0 0 0.001 0 0 0 0 0 0 0 22 0.003 0 0 0 0.001 0 0 0 0 0 0 1.01 23 0.002 0 0 0 0.001 0 0 0 0 0 0 0.039 24 0.002 0 0 0 0.001 0 0 0 0 0 0 0 25 0.002 0 0 0 0.001 0 0 0 0 0 0 0.633

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26 0.002 0 0 0 0.624 0 0 0 0 0 0 1.05 27 0.002 0 0 0 0.018 0 0 0 0 0 0 0.15 28 0.002 0 0 0 0.005 0 0 0 0 0 0 0 29 0.002 0 0 0 0.003 0 0 0 0 0 0 0 30 0.002 0 0 0 0.002 0 0 0 0 0 0 0 31 0.002 0 0 0 0.002 0 0 0 0 0 0 0

Table 13: Daily time series of inflow measured at TUBURBO MAJUS station Day Sept Octo Nove Dece Jan Feb March April May June July August

1 0 0 0 7 0 0 0 0 0 0 0 0 2 0 1 0 0 0 0 0 0 0 0 0 0 3 0.21 34 0 0 0 3 0 0 0 0 0 0 4 0 16 0 0 0 0 0 12 0 0 0 0 5 0 0 0 0 0 0 0 0 0 0 0 0 6 0 0 0 0 1 0 0 0 0 6 0 0 7 0 0 0 0 4 0 0 0 8 1 0 0 8 0 3 0 10 0 0 0 0 5 0 0 0 9 1 0 0 2 0 0 0 2 2 0 0 0

10 0 0 0 0 4 0 0 2 0 0 0 0 11 0 0 0 0 10 0 0 28 0 0 0 0 12 1 0 0 0 40 0 0 0 2 1 0 0 13 0 0 0 0 0 0 0 0 0 0 0 0 14 0 2 0 0 0 0 0 0 0 0 0 0 15 0 2 0 0 0 0 0 0 0 0 0 0 16 0 0 0 2 0 0 0 0 0 0 0 0 17 0 0 01 0 0 16 0 1 0 0 0 0 18 0 0 1 0 5 0 0 0 0 0 0 0 19 0 0 0 2 0 0 0 0 0 0 0 0 20 0 0 2 0 0 0 3 0 0 0 0 0 21 0 0 2 0 0 0 0 0 0 0 0 0 22 0 0 0 0 0 0 0 0 0 0 0 0 23 0 0 0 0 0 5 0 0 0 0 0 0 24 0 0 0 0 0 0 0 0 0 1 0 0 25 0 0 0 11 11 0 0 0 1 1 0 0 26 0 0 0 6 4 0 0 0 6 6 0 0 27 0 0 5 4 0 0 0 0 0 0 0 0 28 0 0 0 0 0 0 0 0 0 0 0 0 29 0 0 0 0 0 0 0 0 0 0 0 0 30 0 0 1 1 0 0 0 0 0 0 0 0 31 0 0 0 0 0 0 0 0 0 0 0 0

Table 14: Daily time series of precipitation measured at Kallat Andalous Station

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Figure 8: Parameters of the RRM

Figure 9: Introduction of the precipitation, temperature and inflow

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Figure 10: Hypsometric curve of the Melian basin

Figure 11: Land use coefficient of the Melian basin

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VII.3 Results

Figure 12: Detail results of the RRM

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Figure 13: Detail results of RRM

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Figure 14: Detail results of RRM

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VIII WATER RESSOURCES MODEL (WRM)

VIII.1 Case study description The case study of WRM in Tunisia was applied on the largest coastal water basin in Tunisia (553 km2).

VIII.2 Data collected • Collection of 2460 wells built in the case study: complete information is available

concerning: wells depth, diameter, usage, exploitation, equipment, standing water level, dry residue…

• Dams: name, coordinates, sector, year of construction, storage capacity, irrigated area, inflow water, name of catchment…

• Collection of historic data related to observation wells in the groundwater • Mountains Lakes: name, coordinates, realization year, name of catchment, area of the

catchment, storage capacity, delegation… • Observation well: name, coordinates, year, dry residue, standing water level… • Collection of hydrologic, hydrogeologic and meteorologic data.

All this data are integrated in a GIS in order to determine the Water Ware Nodes (Fig. )

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Figure 15: WaterWare node charts

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VIII.3 Implementation of the WRM From Water Resources Model – Scenarios we created more than one scenario in order to test and perform our case study Model. (Fig. 18)

Figure 16: WRM scenario

VIII.3.1 Implementation of the Times Series data The Time Series data were introduced in the time series model (Fig.19), in order to implement the WRM and RRM models, these times series concern temperature, precipitation, the inflow observed per station and the demand water for each node.

Figure 17: Implementation of time series data

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VIII.3.2 Topologic model of the Melian basin In Melian case study, there are 60 major water nodes. These nodes are:

• 6 Start nodes (Melian basin, Melah basin, Rmel basin, Hma basin, Medjerda canal and Groundwater)

• 1 End node (Sea) • 1 Reservoir node (Hma reservoir) • 4 Demand nodes (irrigation, touristic, domestic and industry) • 1 Treatment plant • 6 Diversion nodes • 11 Confluence nodes

Number of Nodes: 30, Network Length: 54460 m All the related nodes was implemented in our topologic Model (Fig.20)

Industry

Domestic

Touristic

SeTreatment

Groundwate

Medjerda Hma

Hma Melah

Rmel Melian

Figure 18: Topological model of the Melian basin

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The nodes above are connected with 35 reaches, having 54460m of length. There are 5 reaches representing the main stream and the remaining 30 represent diversion reaches.

Figure 19: Creation of the Base line scenario of the Melian basin

We introduced all data concerning the different nodes of our topologic model (start node, demand node, treatment plant, end node, reservoir node, diversion node, confluence node). You see below an example of implemented data concerning Hma reservoir and Demand Node.

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Figure 20: Parameters of the Hma reservoir

Figure 21: Parameters of the demand node

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VIII.4 Results of the WRM After completing the correct connections and patterns of the different nodes and reaches, with all the detailed data and time-series, running the model can then be achieved. However, some basic data resulting from the WRM are necessary to show different aspects of the information on the water budget. The information expresses the water status for the year 2000, including the annual mass budget summary (Table 8), annual Sectoral demand (Table 9) and annual groundwater mass budget (Table 10). These informations are presented as follows:

VIII.4.1 Annual mass budget summary Table 8 shows a little error in the ratio (0.13%). The mass budget of our case study was estimated to 735.08 MCM; which is derived from the sum of inflow (49.49 MCM) and direct precipitation (0.71 MCM). The ratio of supply/demand is 98.54%. In addition, the total shortfall and unallocated water are respectively 0.39 MCM and 7.23 MCM.

Figure 22: Annual Mass budget summary

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VIII.4.2 Annual sectoral demand Different demand items in the Melian case study are those attributed to domestic, irrigation, industrial. For each use, several numeric values were calculated after running the model (Table 9). There is a loss value that is due to the domestic sector (1.85 million m3), which if is added to the other sectors, the sum will be come 8.74 million m3.

Figure 23: Annual Sectoral Demand

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VIII.4.3 Annual groundwater mass budget This deals directly with the groundwater balance, also in terms of input-output. The total input to the aquifer in the Melian case study is (10.59 MCM), while the output is (32.87 MCM). This means that there are 22.28 MCM positive net amounts.

Figure 24: Annual Groundwater Mass Budget

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IX CONCLUSION A bibliographic research and study on the Melian zone permitted us to identify and inventoriate many categories of data such as:

• Geologic; • Hydrologic; • Pedologic; • Geomorphologic; • Geographic; • Satellite images with different resolutions.

These data permitted to supply the different INPUT for The RRM and WRM (cf. annex). Realized works:

• Geographic database o 13 layers SHP and 6 raster data o Two Land use map (1988 & 2000) o Land Use Change map

• Hydrogeological database

o Information about 2460 wells (depth, standing water level, salinity,…) o Information about the groundwater (phreatic and profond) o Information about nodes o Lake, dam… o Observation well, bore hole…

• Vectors layers and raster data technical report • Hydrological technical report • Determination of the inputs user in WaterWare • Establish the Stakeholders database • Topologic model of the basin has been identified • Implementation of RRM and WRM model • GIS data sent to NCRS

Work in Progress:

• Identification and analysis of indicators (physical & socio-economic) and investigation of water quality related impacts

• Dissemination of experience and results on the local and international scales • Refinement and updating of GIS data base • Try to run the WRM model with new times series collecting from stakeholders

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ANNEXES

Environmental indicators Value Year National average or % of national value Source

Number of projects realized by private firms in the environmental field

Production of domestic wastes 700000 Tons3 2003 31.80%

% of domestic wastes treated in controlled discharges

100% 2003 38%

Number of « ECO-LEF » points 21 2003 23.33% Number of jobs created by « ECO-LEF» system

1011 2003 22.53%

ANGED

Connection rate to sanitation public network 84.40% 2003 84.00%

Number of popular districts connected to sanitation network

ONAS

Global volume of collected and treated used water

Water used volume 17.72 millions m3 2003 9.16

Collected used water volume 14.18 millions m3 2003 9.16

Treated used water volume 13.77 millions m3 2003 9.21

ONAS

Reuse of treated water for irrigation 326680 m3 2003 3.39% DGGR Drinkable water quality (% of samples not in accordance with norms) 0.80% 2003 1.60% SONEDE

Sea water quality (% of samples not in accordance with norms) 28% 2003 13%

Ministère de la Santé

Publique

% of agricultural areas equipped with water saving technology 97% 2003 74% DGGR

Superficial water resources mobilization

Water storage in dams by the 31st of august of every year

DGRE

Areas dedicated to biological agriculture 0 2003 0% DGPA

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Forest plantations pasture plantations 64 ha 2003 0.60% Forest plantations 130 ha 2003 1.37%

DGACTA /DGF

Green areas per inhabitant in urban environment

11.4 m2 2003 11.5 m2 DGEQV

Agricultural areas characteristics Maintenance 429 ha 2003 1.67% Mild techniques 0 2003 0% Mountain lakes 3 Units 2003 13.04%

Protected areas 1939 ha 2003 0.85% DGF/ DGEQV

% of built coast (artificial) 44.44% 0.85% APAL – CNT

Surface of industrial areas 424.41 ha 2003 27.99% AFI Renewable energy consumption Rural lightening with photovoltaic system 0 2003 0% Surface of sun panels 0m2 2003 0%

ANME

Rate of polluting industries 947 Units 2003 14.62% Total number of industrial units 347 Units 2003 0.86% Number of polluting industrial units

ONAS

% of industrial units connected to sanitation network

Number of polluting units in urban areas

Air quality Anarchic urbanization rate Vertical urbanization rate

ANPE

Evolution of bare lands in urban perimeters

Min Int and Loc Dev

Number of revised urban management plans % number of urban management plans Min. Equip and Terr manag

Table 15: Environmental Indicators

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