“Methodological approach for a better estimation of water erosion in the watershed of OUED NAKHLA ”

Mr.JABBAR Tahar

Supervised by:Pr. Mounir F.Pr. SABIR M.Mr. EZZINE H.

Realised by:

PLAN

Methodology2

Conclusion4

Results33

Introduction31

water

2000 1000 m3/hab./y

2030 500 m3/hab./an

1/5 of world population has no access to drinking water

In Morocco:

Strategic issue

Quantity Quality

Introduction Méthodology Results Conclusion

Water needs(3% /y)

Water resources

- L’extension urbanistique et touristique - Industrial progress- The extension of irrigated land

- Siltation of the dams

- Pollution (agricultural & industrial)

- Climate change

Insistent & global vision

integrated approachat the level of the WS

to mitigate the Causes of deterioration of water resources in the watershed.

Introduction Méthodology Results Conclusion

- Irrational irrigation

An assessment of the annual soil loss in the Nakhla watershed

Introduction Méthodology Results Conclusion

Objectives

The Comparison of three models(SWAT,USL E& IMPELERO) of water erosion to the Moroccan conditions

Spain

Northern Morocco

Spain

P Factor

LS factor

K Factor

R factor

C Factor

map of soil losses

USLE

A = R*K*LS*C*P

satellite image

meteorological data

geomorphological mapGeological map granulometric data

ASTER GDEM

Assessment of water erosion :I

landuse

rainfall erosivity

Soil erodibility

Pertes en sol délivrées à l’exutoire

Introduction Methodology Results Conclusion

USLE

ImpelERO

Introduction Zone d’étude Methodology Results Conclusion et recommandations

An hybrid model of expert-decision trees and artificial neural networks

input/output & application modelinput

Model aplicationIntroduction Methodology Results Conclusion

SWAT (Soil and Water Assessment Tool )Based on the modified Universal Soil Loss Equation (MUSLE)

A Several versions have been created since 1994. The version used for our work is that of 2009

Introduction Methodology Results Conclusion

DEMDelineation of WS

Delineation of subWS

Soil map

landuse

Hydrologic Response Unit

Subwatershed

(HRU)

Map of soil loss

Climate data

Scenarios of agricultural practices

Introduction Methodology Results Conclusion

A= * K* LS* C

* PRIntroduction Méthodology Results Conclusion

R=143 log (P* P224*10-6) + 89,7

Heusch _1970

R K

100*K = 2.1*10-4*M1,14(12-a) + 3.25

(b-2) + 2.5 (c-3)Barril (1988)

LS

LS = (L/22,15)m *(65,41sin2S + 4,56 sin S + 0,065)

Wischmeier & Smith (1978)C

P

50%

13%

21%

16%

Area(%)0 – 10 10 – 50 50 – 100 >100

13,35 t/ha/an DR 38 %.

SWATSed =11.8 x (Qsurf x qpeak x SHRU) 0.56 x KUSLE x CUSLE x PUSLE x LSUSLE

500000,000000

500000,000000

505000,000000

505000,000000

510000,000000

510000,000000

5250

00,0

0000

0

5250

00,0

0000

0

5300

00,0

0000

0

5300

00,0

0000

0

5350

00,0

0000

0

5350

00,0

0000

0

5400

00,0

0000

0

5400

00,0

0000

0

Carte des pertes en sols par SWAT(t/ha/an)

Légende

0 - 10

10 - 50

50 - 100

>100

±

0 990 1 980 2 970 3 960495Meters1:70 000

Sep Oct Nov Dec jan Fev Mars Avril Mai Juin Jllet Août0

5

10

15

20

25

non pratiques Terrasses zero-labour Scénario de base

pert

es e

n so

ls(t/

ha)

70t/ha/y 39t/ha/y 140 t/ha/y 55t/ha/y

Introduction Méthodology Results Conclusion

ImpelERO

Qualitative results by decion tree

Quantitative results by expert neural network

Introduction Méthodology Results Conclusion

Runoff

Relief Erodibility

Qualitative resultsQuantitative results

Horizon_20yHorizon_50yHorizon_100y

Introduction Méthodology Results Conclusion

Reduction of prodectivity

Introduction Méthodology Results Conclusion

21%40%7%

28%

Comparison of soil losses estimated and observed

Data analysis

Observation(t/ha/y) USLE(t/ha/y) ImpelERO(t/ha/y) SWAT(t/ha/y)

Average 0 ,9963 17,62 11,29 15

R 0,61 0.964 0,79

ME -1,2 0,28 0 ,12

Standard error

of the estimate

0,89 0,21 0,44

experimental parcels

So we can wonder where is the problem . Is it in the modelisation process or/and in the experimental design ?

Conclusion

Introduction Méthodology Results Conclusion

Training In KTU

•Strengthen the knowledge in the forest management planning;

•Acquire the knowledge and skills in GIS and remote sensing;

•Use of geomatics sciences to estimate a soil loss in the watershed;

•Erosion models used in the Mediterranean basin and their integration into the GIS software;

•Forest management through the web mapping

Objectives :

AGORA Project

•Ecosystem-based multi-purpose planning ; Pr. Ali İHSAN KADIOGULLARI;

•Ecological modeling; Pr. BİLGİLİ E.;

•Forest management ; Pr. ZEKİ BAŞKENT E.;

•Forest and biodiversity ; Pr. TERZİOĞLU S.;

•Geographic information system (GIS) ; Pr. EMİN ZEKİ BAŞKENT.

•Use of remote sensing in the naturelle ressources field ; Pr.KARAHIL U.,

Training In KTU Program

Conferences

Theoretical courses & practical works:Theoretical courses & practical works:

Visits to the forest department

At the end of 45 days of training, we were able to benefit from knowledge

and expertise and learn from the experiences of our Turkish friends

برشآ ! شكرا

Merci pour l'attention Votre !

Thank you for your attention !Ilginiz için teşekkür ederim !

obrigado pela vossa atenção

آف بز !! شكرا