Dr. Coulibaly Naga
Prof. Umesh Bellur
Prof. Nandlal L. Sarda
Presentation plan
1. Introduction
2. Methodology
3. Results
4. Conclusion
2
Introduction
The development of almost all socio-economic
sectors depends on water resources.
Water resources are mobilized to satisfy various
uses like domestic, agricultural, industrial, livestock,
tourism, leisure etc.
water resources are not available in sufficient
quantity and quality anytime, anywhere.
Creation of a tools which allows management and
analysis of current and historical data.
3
Introduction
General Objective:
Design and create a prototype of open source (Spatial
Decision Support System (SDSS) for water resources
management in a watershed.
Specifics Objectives:
•Collect
water
resources,
environmental data,
socio-economic
and
•Design and implement a database,
•Create a Spatial Decision Support System for water
management
4
Methodology
5
Materials – Software
1. Desktop GIS : Quantum GIS (QGIS)
a)
b)
c)
Creation of plugins in Python (PyQGIS with PyQt)
Customization of QGIS interface from source code
Adding GRASS functionalities
2. A Cartographic server : Mapserver
3. RDBMS : PostgreSql / PostGIS
- The tool uses PostGreSQL database with PostGIS analysis tools.
6
Materials - Data
7
Soil Loss Evaluation
Universal Soil Loss Equation (USLE)
Topographic map
DEM
LS Factor map
Meteorologic data
Statellite data
Soil map
K Factor map
Landuse / landcover
C Factor map
P Factor map
R Factor map
USLE Soil Erosion Model (A=R.K.LS.C.P)
Soil Loss rate
A=R.K.LS.C.P
The result (A) is the average annual soil loss
(mass/area/year)
8
Soil Loss Evaluation
sub-watershed sensibility prioritization
assessment
Soil Loss rate of the
basin
Mask map by
sub-basin
Soil Loss rate of a
sub-basin
Sum Soil Loss by subbasin
Sub-basin polygon
Sub-basin sensibility
prioritization`s map
Figure: Flow chat for sub-watershed sensibility prioritization
assessment
9
Water security
Water security = Availability - Demand
Water availability evaluation
Water resources are evaluated by the water balance equation.
A simple from of water balance equation is as follows:
P = Q + E ± ∆S
Where, P is precipitation,
Q is runoff,
E is evaporation
∆S = is the storage in the soil, aquifers or reservoirs.
10
Water security
Global Water demand
The Water demand for each use will be assessed from the
product of the specific consumption by the population
(effective) involved or the planned production. Thus, the Global
water demand (Dg) in m3 is modeled by the equation:
Dg = Ddom+ Dagri + Dlstk + Dind
Where: Ddom , Domestic water demand,
Dagri , Agricultural water demand,
Dlstk , Livestock water demand,
Dind , Industrial water demand.
11
Water security
Domestic water demand
Domestic water demand is estimated by multiplying the
population with the specific water consomption.
The average specific consumption is per day per person is 40
liters in urban areas, rural and semi-urban areas, it’s respectively
15 and 20 l / day / person (BAD, 1993).
Agricultural water demand
Agricultural water demand is a function of crop type and
agricultural practices and also of the climatic region
12
Water security
Livestock water demand
Water requirements depend on the livestock species, the
forage quality and climate. According to the Inter-State
Hydraulic Study (CIEH) the values are:
- Cattle: 39.2 l / day / head
- Sheep: 4.3 l / day / head
- Goats: 4.3 l / day / head
Industrial water demand.
The industrial water demand for each industry equals to the
product of production with the corresponding water-demand per
a production unit .
13
Water vulnerability
Multi-criteria Evaluation (MCE)
 The most commonly used decision rule is the
weighted linear combination
 where:






S = ∑wixi x ∏cj
S is the composite suitability score
xi – factor normalised
wi – weights assigned to each factor
ci – constraints (or boolean factors)
∑ -- sum of weighted factors
∏ -- product of constraints (1-suitable, 0-unsuitable)
Example: With a GIS raster calculator
S =((F1 * 0.67) + (F2 * 0.06) + (F3 * 0.27)) * cons_boolean
14
Water vulnerability
Groundwater vulnerability Criteria
1. Pesticide application Method (foliar, soil surface
or incorporation),
2. Risk of lixiviation caused by soil type (estimated
from the soil organic matter rate, texture or
depth of soil),
3. Human toxicity estimated from the acceptable
daily intake (ADI),
4. Quantity applied per hectare,
5. Depth of groundwater,
15
Water vulnerability
Surface vulnerability Criteria
1. Runoff generated by the characteristics of the plot (slope,
length, texture, surface condition),
2. Rate of drift from the application of the product (estimated
from the distance of the parcel to the watercourse),
3. Mode of application,
4. Pesticide persistent,
5. Toxicity on target organisms (people, algae, crustaceans,
fish, ...),
6. Quantity molecule applied per hectare,
7. Drainage density weighted.
16
Results
17
System architecture
SERVEUR
Spatial DBMS
- PostGis
CLIENT
Desktop GIS
- QGIS
INTERNET
INTRANET
Web Map Server
- Mapserver
GRASS
Client interface
developed with
Quantum GIS 1.6 shell
enhanced with GRASS
functionalities.
Web Server
- Apache
Figure: Functional structure of the system
18
Desktop GIS tool
Application
19
Todo
1. Develop USLE, vulnerability and water security
functions
2. Customize some queries and graphs ; map
composer.
3. Write the report and 1 paper for publication
20
Conclusion
This study is aims at creating a Spatial
Decision Support System (SDSS) prototype
for
the
integrated
water
resources
management for various uses.
This Spatial tool will be an institutional spatial
tool for decision making and for concertations
between all the water resources actors (users,
managers, NGO, …) for a sustainable
management of water.
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End
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