Upload
celina-napp
View
218
Download
0
Embed Size (px)
Citation preview
F. Fussi(1), L. Fumagalli(1), T. Bonomi(1), F. Fava(1), B. Di Mauro(1), C.H. Kane(2), M. Faye(3), S. Wade(3), G. Faye(3), B. Hamidou (4) , R. Colombo(1)
(1) University Milano Bicocca, (2) University of Thies, (3)University Cheik Anta Diop – Dakar, (4) SNAPE - Conakry
contact: [email protected]
Use of remote sensing and terrain modeling to identify suitable zones for manual drilling in Africa and support low cost water supply
Groundwater, poverty and development, Overseas Development Institute, London 28/11/2014
STRUCTURE OF THE PRESENTATION
Introduction to manual drillingPrevious studies on suitable zones for manual drillingThe research projectGeneral research approachHydrogeological data processingRemote SensingResults achieved and next steps
Groundwater, poverty and development, Overseas Development Institute, London 28/11/2014
Introduction to manual drilling
MANUAL DRILLING techniques of drilling boreholes for groundwater exploitation using
human or animal power (not mechanized equipment).
These techniques are well known in countries with large alluvial deposits (India,
Nepal, Bangladesh, etc)
High quality hand drilled wells can provide sustainable and
clean water supply
Groundwater, poverty and development, Overseas Development Institute, London 28/11/2014
Introduction to Manual Drilling
Advantages and limitations
Advantages of manual drilling
Cheaper than mechanized boreholesEasy to implement with locally made equipment“manual work intensive” and not “capital intensive” ; source of income for local groups
Limitations of manual drilling
Manual drilling is feasible only under hydrogeological suitable conditionsSoft unconsolidated shallow geological layers Water level not too deep Good hydraulic conductivity of shallow porous aquifers
IT IS IMPORTANT TO IDENTIFY THOSE ZONES WHERE HYDROGEOLOGICAL CONDITIONS ARE SUITABLE FOR
MANUAL DRILLING
Introduction to Manual Drilling
Groundwater, poverty and development, Overseas Development Institute, London 28/11/2014
Previous maps of suitablezones for manual drilling
BENIN BURUNDICENTRAL AFRICAN REPUBLICCHADGUINEA IVORY COAST LIBERIA MADAGASCAR MALI MAURITANIA NIGER SENEGAL SIERRA LEONE TOGO ZAMBIA
Since 2008 UNICEF has produced maps of suitable zones for manual drilling in 15 countries in Africa:
Previous studies on suitable zones
Groundwater, poverty and development, Overseas Development Institute, London 28/11/2014
http://www.unicef.org/wash/index_54332.html
Previous method to identify suitable conditions for manual drilling (UNICEF)
Previous studies on suitable zones
Data sources:EXISTING MAPSNATIONAL DATABASE OF WATER POINTSQUALITATIVE EXPERIENCE OF WATER EXPERTS IN THE COUNTRY
Limitations:Input data are limited and often at very broad scale,inadequate for reliable interpretation (where data are limited) and more detailed studyNot systematic and structured procedure for data analysis. Difficult to compare results from different countries
Groundwater, poverty and development, Overseas Development Institute, London 28/11/2014
COMBINED ANALYSIS OF 3 PARAMETERS:
THE UPGRO RESEARCH PROJECT
University Milano Bicocca (Italy)
University Cheik Anta Diop (Senegal)
SNAPE (Guinea)
UNICEF (Guinea and Senegal)
PARTNERS
FUNDED BY:
Groundwater, poverty and development, Overseas Development Institute, London 28/11/2014
Use of remote sensing and terrain modeling to identify suitable zones for manual drilling in Africa and support low cost water supply
Main goal of the research
OBJECTIVE OF THE RESEARCHIntegration of direct hydrogeological information from existing database with indirect parameters from Remote Sensing and terrain modeling to characterize shallow aquifers and identify suitable zones for manual drilling
DURATIONNovember 2013 – April 2015
Groundwater, poverty and development, Overseas Development Institute, London 28/11/2014
The research project
Research study area
REGION OF KANKAN AND FARANAH (EAST GUINEA)
REGION OF LOUGA – KEBEMER (NORTH WEST SENEGAL
Groundwater, poverty and development, Overseas Development Institute, London 28/11/2014
The research project
Scientific approach
Geo-Environmental indicators (Geology, Soil, Morphometry, Vegetation dynamics, Soil moisture,
Thermal Inertia)
Thematic maps, Remote Sensing (optical, radar), Digital terrain model
(Geo)Statistical model
Borehole logs interpretation, pump test, geophysics
Map of suitable zones for manual
drilling
Hydrogeological features at observation points
Groundwater, poverty and development, Overseas Development Institute, London 28/11/2014
General research approach
Methodological approach
Geology, Sols, etc
Topography &Geomorp
hology
Vegetation Type &
Persistence
Thermal Inertia
Soil Moisture
Base maps
STRM/ASTER DEM
MODIS Veg. Ind.
MODIS LST &
ALBEDO
RADAR ASAR
P, K, T, suitability class(estimated)
Classification (e.g. CART)
Borelogs - TANGAFRIC
Training set (P, K, T, class)
Testing set (P, K, T, class)
P, K, T, suitability class(observed)
Accuracy assessment
(e.g. Q2, RMSE)
cal
val
Spatial maps
Groundwater, poverty and development, Overseas Development Institute, London 28/11/2014
General research approach
Definition of a 2 steps procedure toestimate suitability for manual drilling
Groundwater, poverty and development, Overseas Development Institute, London 28/11/2014
Feasibility: It depends on-depth of hard rock- depth of water level- thickness of hard lateritic layers
Potential for exploitation-It is obtained from assigning class of potential based on hydraulic transmissivity of porous unconsolidated aquifer from 0 to 50 m (considered the maximum epth for manual drilling) Estimation potential
General research approach
Development of a specific software andcodification of hydrogeological data
DATABASE OF WATER POINTS SENEGAL AND GUINEA
STANDARDIZATION OF DATABASE STRUCTURE
IDENTIFICATION OF MOST FREQUENT CATEGORIES
ASSIGNING STRATIGRAPHIC CODES
Groundwater, poverty and development, Overseas Development Institute, London 28/11/2014
Hydrogeological data processing
Processing of stratigraphic data
Groundwater, poverty and development, Overseas Development Institute, London 28/11/2014
PROCESSING OF STRATIGRAPHIC AND PIEZOMETRIC DATA
Hydrogeological data processing
Bonomi, T., (2009): Database development and 3D modeling of textural variations in heterogeneous, unconsolidated aquifer media: Application to the Milan plain. Computers & Geosciences 35 (2009) 134–145
Processing of hydrogeological data have been based on previous experience in Italy (Bonomi, 2009) and adapted to the context of Senegal and Guinea
Processing of stratigraphic data
Groundwater, poverty and development, Overseas Development Institute, London 28/11/2014
EXTRACTION OF:
Each 2 m intervals:TEXTUREHYDRAULIC CONDUCTIVITY
For the whole log:DEPTH OF HARD ROCK,DEPTH OF WATER TABLETHICKNESS OF HARD LATERITIC LAYERSHYDRAULIC CONDUCTIVITY (K) OF UNCONSOLIDATED LAYERTRANSMISSIVITY
Processing of textural data at intervals of 2 m (Tangram software)
Hydrogeological data processing
Extraction of hydrogeologicalparameters at borehole logs position
Groundwater, poverty and development, Overseas Development Institute, London 28/11/2014
Depth of water
Depth of hard rock
Thickness of laterite
Average K (in exploitable layers)
Hydrogeological data processing
Estimating feasibility and potentialfor manual drilling at logs position
Groundwater, poverty and development, Overseas Development Institute, London 28/11/2014
Hydrogeological data processing
SENEGAL STUDY AREA
Multitemporal analysis of ATI
Thermal Inertia (TI) is related to the characteristics of the surface materials as well as surface water content. Apparent Thermal Inertia (ATI) [K-1]can be estimated using solely remote sensing optical and thermal data (Van Doning et al., 2012 IJAEG).
- α0 is the albedo estimated from MODIS satellite optical data (MCD43B3 – 16 day – 1km)
- A is the amplitude of the diurnal cycle of the land surface temperature estimated from day/night MODIS thermal observations (MOD11C1/MYD11C1 – daily (4 overpass/day) – 1km).
- C is a solar correction factor.
Van Doninck J., Peters J., De Baets B., De Clercq E.M., Ducheynec E., Verhoesta N.E.C. (2011). The potential of multitemporal Aqua and Terra MODIS apparent thermal inertia as a soil moisture indicator. Int. J. App. Earth Obs. Geoinf. 13, 934–941
Remote Sensing
Groundwater, poverty and development, Overseas Development Institute, London 28/11/2014
Multitemporal analysis of ATI
Daily time series of ATI (2012)
MODIS DATA (1km)MOD11C1/MYD11C1 +
MCD43B3
Data selection: no precipitation/clouds
Dry season ATI map
LOUGA
0.2 0.4 [K-1]
Dry ATI map 2012 (1km) - Northern Senegal
N
50 km
Groundwater, poverty and development,28/11/2014, Overseas Development Ini
Remote Sensing
Vegetation Dynamics The abundance, type and seasonal variations of vegetation are dependent from nutrient and water availability. Especially in drylands, vegetation can thus be related to water availability across the landscape.
Vegetation persistence or poor sensitivity from precipitation patterns may reflect the presence of shallow water and/or substrates suitable for deep plant roots development. Normalized Difference Vegetation Index (NDVI) time series were analysed to assess phenological indicators of vegetation cover and persistence during the dry season.
2007 2009 2010 2011 20122008YEAR
Remote Sensing
Groundwater, poverty and development, Overseas Development Institute, London 28/11/2014
Vegetation Dynamics
MOD13Q1 (TERRA/AQUA MODIS - 16 day - Vegetation Indices, 250 m) 2008-2012
Filtering and smoothing procedure
Extraction of phenological metrics. Start of season, End of season, maximum, minimun, seasonal mean, etc
Vegetation persistence indicators (5 years average)- Mean dry season NDVI- Rate of NDVI decreas- Dry season lenght
LOUGA
DRY SEASON LENGHT (Number of days)
200-220220-240240-260260-280280-300
LOUGA
DRY SEASON MEAN NDVI
0.1 0.25
Remote Sensing
Groundwater, poverty and development, Overseas Development Institute, London 28/11/2014
SOIL MOISTURE DYNAMICSSoil moisture dynamics may indicate areas with high water holding capacity or water accumulation.
ENVISAT-ASAR radar data (Global mode -1km) between 2008 and 2012 in C-band are used to estimate soil moisture by inversion of the radiative transfer model proposed by Karam et al., 1992.
Biomass maps derived from SPOT vegetation were used to separate the contribution of vegetation and soil moisture on the radar signal.
Karam M.A., Fung A.K., Lang R.H. and Chauhan N.S., 1992 : Microwave scattering model for layered vegetation, IEEE Trans. Geosci. Remote Sens., 30:767-784.
LOUGA
SOIL MOISTURE (%)
0 100
June 2010
Remote Sensing
Groundwater, poverty and development, Overseas Development Institute, London 28/11/2014
Results achieved and next stepsMAIN RESULTS ACHIEVEDElaboration of a specific software to organize and process hydrogeological data based on the inventory of Senegal and GuineaDefinition of a structured method to estimate suitability for manual drillingProduction of maps of hydrogeological parameters and suitability for manual drilling at borehole logs positions in SenegalDefinition of procedures and generation of maps of soil moisture, phenology and ATI from optical and radar dataFirst set of direct field data (geophysics, pump test) collected and intepreted in SenegalNEXT STEPSCompleting field data collection in Senegal. And (depending from Ebola outbreak) in Guinea.Validation of hydrogeological interpretation with field informationDefinition of geostatistical model and integrated analysis of dataSpatialisation of hydrogeological interpretation from borehole logs position to the whole areaGenerating maps of suitability for manual drilling
Groundwater, poverty and development, Overseas Development Institute, London 28/11/2014
Groundwater, poverty and development, Overseas Development Institute, London 28/11/2014
Thanks very much for the attention