subterranean water extracted is used for agriculture, … · of irrigated lands is settled over the aquifer system 08-29 ... surfaces. The integration of ... EXPLOITATION. WATER CONSUMPTION

Use of a GIS tool for sustainable management

of aquifer 08-29 resources in La Mancha,

Spain

A. Calera, J. Medrano, C. Martinez & J.R. Ruiz

Institute de Desarrollo Regional UCLM.Av. Campus Universitario sn. 02071 Albacete Spain.

jmedrano@idr-ab. uclm. es

Abstract

Geographic Information Systems enable us to manage projects ascomplex as the sustainable exploitation of subterranean aquifers foragricultural use. This is the case of the extensive hydrologic system 08-29, located on the eastern side of La Mancha (Spain). The integration ofRemote Sensing into the GIS, which allows us to identify, discriminateand study irrigated crops in the semiarid environment of this area, is doneby the intersection of a classified image with the polygon layer of therural cadastre.This union of Remote Sensing and GIS, using the rural cadastre as ageographic base, proves to be highly useful as it combines thecapabilities of both tools.

1 Introduction

The irrigation agriculture of La Mancha (Spain) is almost exclusivelybased on the exploitation of subterranean waters through wells that crossthe permeable beds of the underlying aquifer system. The decisions aboutthe volume of water to be extracted depend on the individual landowners,and are a function of the crop, the meteorological conditions and theirrigation systems used. Currently, the extractions for agriculturalpurposes (mainly irrigation) clearly represent the highest waterconsumption. This way, in the 08-29 aquifer system, an area withsemiarid climate where this study has been carried out; 92.4% of the

Transactions on Information and Communications Technologies vol 18, © 1998 WIT Press, www.witpress.com, ISSN 1743-3517

64 GIS Technologies and their Environmental Applications

subterranean water extracted is used for agriculture, and the remaining7.6% for urban supply and industrial uses.

This aquifer located on eastern side of La Mancha and considered oneof the most important in Spain MOPTMA [1], has more than 100,000 haof irrigated lands is settled over the aquifer system 08-29 (with a surfaceof 8500 Km2). (figure. 1). Presently, most of the sectors implied insubterranean water management, such as farmers, administration and

society as a whole, are convinced that preservation of such a valuable

natural resource as water is truly needed, specially in this areacharacterised by a semiarid climate, and seriously threatened bydesertification. This goal can only be achieved by means of sustainable

exploitation.For the sustainable exploitation of an aquifer, planning and control

methods allowing the integration of a great amount of spatial andtemporal variables are needed. Currently, the Geographic InformationSystems (GIS) are a quickly spreading technology in several scientificfields and applications. The GIS capabilities to integrate spatially

georeferenced data from different sources, with diverse formats,

structures, projections or resolution levels, constitute the main feature ofthese systems Goodchild, [2]. These features make the GIS a useful toolwhen making decisions for improved management of the available waterresources.

In this study, a set of GIS tools have been developed which respond tothe specific management needs of the JCRMO, the farming associationco-responsible for aquifer management. In this process, the experienceobtained from the application of exploitation plans from previous years,which were the first attempt at regulation of extracted volumes, has given

us highly valuable information.

Figure 1. - Location of the study area, also showing the pilot area.


GIS Technologies and their Environmental Applications 65

Special attention has been paid to the integration of Remote Sensing inthis GIS, this technology being very useful for crop identification and

control in real time Moran et al [3] when dealing with relatively extensive

surfaces. The integration of these two techniques increases the

capabilities of each Menenti et al. [4].

2 GIS description

FLOW CHART FOR THE AREAS WITH AVAILABLE DIGITAL CADASTER

REMOTE SENSING

LAND USE CLASSIFICATION(IRRIGATED CROPS)

EXTRACTION OF \NFORMATION AND ITS PLOT

REFERENCE(CARTOGRAPHIC BASE: DIGITAL

CADASTER) J

CROP SPATIALANALYSIS

IRRIGATIONSYSTEMS

IRRIGATIONSYSTEMS SPATIALANALISYS

ALPHANUMERIC DATABASE

DIGITAL CADASTER

PLOTCROP DIGITAL MAPPING(CROPS AND IRRIGATION SYSTEMS)

PLOTCROPRJUQS

\

I

I'

WATERCONSUMPTION

CHART

EFFICIENCY CHART

f*0? ANALISYS BLOCK(DIGITAL MAP OF WATER CONSUMPTION PER PLOT) CROP

SPATIAL ANALISYSCONSUMPTION IN APARTICUIARZONEMEDIOOWBAL

ANALISYS BYADMINISTRATIVEEXPLOITATION. ANALISYS BY

HYDRAULICEXPLOITATION.WATER CONSUMPTIONPER WELL

ACQUIFER MODELLING

Figure 2



The basic aspects this GIS deals with are Calera et al. [5]:a) Capability to integrate and process spatial and temporal information

coming from different sources such as field work, remote sensing or

administrative files.b) Capability of displaying data on maps for easy visualisation and

handling by the users, allowing individualised queries. This tool isintended to be handled by the users in the JCRMO; thus it is

necessary to develop a user-friendly environment,c) Capability of aquifer monitoring and control in real time.d) Capability of scenery generation allowing for resource planning and

management. This GIS must allow for spatial and temporalestimations of the extracted volumes, so that it performs the input for

the hydrologic aquifer model that is being developed in other parallel

projects.In Figure 2, the above mentioned GIS features and working scheme

are shown, emphasising the Remote Sensing-derived information. Thedigital rural cadaster is the georeferenced base layer, and thus all theother layers will refer to it. The cadastrial subplot is regarded as the

elementary unit. Its cadastrial identifier is the field that both provides the

geographical location and allows for correlation with other layers. Thisway attributes such as administrative owner, surface, irrigation system,system efficiency, multiannual crop evolution, water source, waterconsumption estimation, etc., can be linked to the identifier. The basicmanagement unit is the agrarian exploitation, where the owner isresponsible for yearly crop planning. The exploitation is then defined asthe aggregation of subplots belonging to the same owner.

3 Remote Sensing and GIS

It is usual to operate with the support of a GIS in order to improve theclassification results in crop discrimination .In this study, RemoteSensing is a source of information, monitoring and control for irrigatedcrops that, integrated in a GIS, results in a highly useful tool.

3.1 Landsat TM images classification

An irrigated crop classification has been established for theagricultural year 1997. It has been accomplished using Landsat TMimages, georreferenced with control points using second-degreepolynomials and cubic convolution resampling. The classificationprocedure has followed multitemporal supervised classification by



Table I. Classes used in the classification.

Name of class

SPRIR (spring irrigated crops)

SUMIRSC (short cycle summer irrigated

crops)

SUMIRLC (long cycle summer irrigated

crops)

DOUBHAR (two harvests a year)

ALFALFA (perennial leguminous)

Crops

barley, wheat,garlic, peas, etc.

onions, sunflowers,potatoes, etc.

corn, sugar beet.

peas/corn,

barley/green beans,

etc.

alfalfaTable II. Confusion matrix for the 1998 classified image pilot area.

5 P R IR

SUMIRLCA L F A L F A

Not irrigated

Satelite image classification

1716Z 71 61

230

299705 7

093

221 3

2195B

1 7

361 3

2705791 01

67

11830

99767 85

341 200

to ta I1 90811063087604

2 1 231231

combining maximum likelihood algorithms with decision-tree criterions.

The crop map obtained displays the classes shown in Table I. The classselection followed the criterion of grouping into a single class those cropswith similar temporal evolution and equivalent water consumption.

A pilot area with 34000 ha. of surface, 14000 of them being irrigatedlands (figure 1), has been selected for this study as representative enoughof the whole aquifer Martin de Santaollalla, [6]. The fieldwork done inthis area has allowed checking and verifying of the classified image. Theconfusion matrix obtained by comparing the fieldwork data with theclassified image is shown in Table II. The classification accuracy reaches84.4%. Only 3% of pixels in the image have been misclassified (drylands as irrigated or vice versa).

3.2 GIS attribute securing using RemoteSensing

The information obtained with Remote Sensing through theclassification process is a raster map where each pixel is assigned to oneof the classes shown in Table I. In the case of the Landsat images used,the pixel size is 30x30 m., which is the TM sensor spatial resolution. Thisinformation must be processed in order to expedite its integration into theGIS, together with the other information layers with vectorial format that



are linked to the administrative data (cadastrial subplots) and also have ageographical location, allowing them to be grouped into exploitations.This way, a process to extract information from a raster layer and to

integrate it in a vector layer has been developed. This process has beenapplied to the crossing of the classified raster map and the digital rural

cadaster vector map.These operations, with their flow chart displayed in figure 3, have

been implemented over ArcVIEW, using a script that, executed over thissoftware, obtains a spatial database, i.e. which means a vector layer thatintegrates the raster information. The process inputs are, besides theirrigated crop map and the polygon layer corresponding to the digital

cadaster, a table with the description of the codes assigned to each class

in the raster map. The code table is used during the process for designingthe database linked to the output layer, so that each one of the createdfields in this output layer has an identifier obtained as a function of pixel

values in the raster map.The output is a polygon layer with the same geographic base as the

input polygon layer. The difference between these layers is the

alphanumeric database linked to the output layer, which will be built by

those fields in the input layer selected by the user, the fields with the

cadastrial identification, and also a number of fields equal to the numberof classes appearing in the raster map. The information stored in thesefields is, for each polygon, the number of pixels belonging to each classidentified in the raster map that are included within the polygon limits.

Figure 3


This process is displayed if figure 4, where, starting from theclassified image raster map 4(a), crossed with the polygon map shown in

4(b), an alphanumeric database is obtained. In figure 4(c) the database for

the three circular plots in the centre of the image is listed. For thisprocess, a user-friendly interface has been designed 4(d). Thecombination of this database with the polygon map allows us to displayin this layer the major irrigated crop for each plot, figure 4(b), althoughinternally the system operates with the linked database.

This tool has proved to be highly useful and manageable for obtainingand processing information about a particular zone from a raster map andfor its integration in a GIS. By automatically assigning the crop or cropsidentified in the classified image to a cadastrial subplot, and monitoringtheir annual evolution, the GIS and Remote Sensing capabilities areenhanced. The process described is not only limited to the above

Figure 4a

v irrigated crop I.e.-_._..2r irrigated crop s.c.

Figure 4b

Hdaite harvest/Walfas

POLIGON181818

PLOT51717

SUBPLOT1A1A10

SUMIRLC0,00000,00000,0000

SUMIRSC625,0000

448750,00000,0000

ALFALFA0,00000,00000,0000

SPRIR363750,00008750,0000

496875,0000

SPRIR70000,00008125,00002500,0000

DOUBHAR113125,00004375,0000

0,0000

3a«ciond Mapa uatf K&OQJPaile97 jd

Selecciona la capa catatbal

j Gin97fin.shp jsJ

Figure 4cCampos d@ enliadaArea •*PerimeterSubiu035_Subpaice

nadaRegrVeCtRetf/eCCRegPriA;- -H

s

.

Campo* tte $alidaPoliaono •*Parcela

......

MapadesaWa j»n\gesrrxAano97\abacete shp

Exptow |

TaWadocuftivo* j d:\juan\gesmo\ano97Melcult

Cancel*

Figure 4d



mentioned layers, but can be extended to any raster or vector map, or

even two vector maps with the geographic intersection criterion.

4 Temporal evolution of subterranean water

extraction

One of the GIS capabilities is the estimation of aquifer water

extraction for agricultural uses, which represents most of the totalextracted volume. This is an especially relevant datum for sustainable

aquifer management and constitutes in itself an input for the

hydrogeologic model. Within these estimations, an important parameter

is the interannual variation produced by changes in the surface destinedfor each type of crop, and the agrometeorological conditions thatdetermine the water demands for each campaign. It is also important toconsider the annual evolution during the agrarian campaign, regardingthe date when the water extractions are made, which is a function of thecrop water demands. In figure 5, the water extraction annual evolution in

the pilot area for the 1997 campaign is given. The estimations shown inthis figure are based on the knowledge of hydric needs for each crop(quantified week by week), calculated by the Irrigation Advisory Service

belonging to Diputacion de Albacete Lopez [7] on the basis of the crop

Figure 5



phenology, agrometeorological conditions and the direct monitoring of alarge number of control plots. The surfaces estimated for each different

crop are those identified by Remote Sensing, thus the same calculation

can be accomplished for any zone in the aquifer where images are

available.

Conclusions

The GIS has proved to be a suitable tool for managing complexsystems, where a great number of variables whose main feature is spatiallocation are involved. Such is the case of aquifer system 08-29 describedin this study. Remote Sensing has been useful for producing land use

maps in which the different irrigated crops are identified and

discriminated by a multitemporal classification process in which images

from different dates are used.The integration of Remote Sensing in the GIS has been accomplished

by a process that assigns the crop or crops previously identified as classesto each cadastrial plot. This process consists in the intersection of apolygon layer (the digital cadaster) with the classified image raster map.Each polygon corresponds to a spatially delimited subplot, the

assignment of other attributes also being possible.This integration process notably increases the GIS and Remote

Sensing tool capabilities and usefulness. The GIS capabilities increasebecause it accesses and manages a great amount of information whoseacquisition would be economically unapproachable by other ways, sinceit deals with large land surfaces. Furthermore, it facilitates the checkingof fieldwork plot by plot, and the plots can be grouped as exploitations,which are the elementary aquifer management units, allowing themonitoring of exploitations interannually. Remote Sensing also increasesits potential as an information source for the monitoring and control of

irrigated crops.One of the basic GIS utilities is the aquifer water extraction estimation

for agricultural purposes that represent a percentage higher than 80% ofthe total subterranean water extractions. This analysis needs informationabout the crop water needs. It is made spatially, either at the level of thewhole aquifer or other smaller units, making it possible to monitor thetemporal evolution of subterranean water extractions for agriculturaluses, either between years or within the agricultural campaign.



Acknowledgements

This research is financed by the CICYT project n° HID96-1373. Our

acknowledgement specially to the JCRMO ( General Board of Irrigation

Users of Eastern La Mancha).

References

[1]MOPTMA, 1995. Libro bianco de las aguas subterraneas. Ed.

Ministerio de Obras Publicas, Transposes y Medio Ambiente y

Ministerio de Industria y Energfa, Madrid, 135 pp.

[2]Goodchild, M. F., 1993. The state of GIS for environmental problem-solving. In: M. F. Goodchild, B.O. Parks, L.T. Steyaert (Editors),Environmental Modeling with GIS. Oxfor University Press, pp 8-15.

[3]Moran, M. S. , Inoue, Y., and Barnes, E. M., 1997. Opportunities and

limitations for image-based remote sensing in precision crop

management. Remote Sens. Environm., 61:319-346

[4]Menenti, M.; Azzali, S.; d'Urso, G., 1996. Remote Sensing, GIS andHidrological Modelling for Irrigation Management. In: L.S. Pereira; R.A. Feddes; J.R. Gilley and B. Lesaffre (Editors), Sustainability ofIrrigated Agriculture, Kluwer Academic Publishers, Dordrech, pp 453-

472

[5]Calera, A.; Medrano, J.; Vela, A.;Castano, S.. GIS Tool Applied to theSustainable Management of Hydric Resources. Application to theAquifer System 08-29. Agri. Water Management. Special Issue of theWorkshop "The Use of Water in Sustainable Agriculture"2-4 June 1997,Albacete, Spain

[6]Martin de Santaolalla Manas, F.; Brasa Ramos, A.; Fabeiro Cortes, C.;Fernandez Gonzalez D.; Lopez Corcoles, H. Integrated managementsystem of an aquifer in Castilla La Mancha, Spain. The role of IrrigationAdvisory Service of Albacete. Agric. Water Manag. Special Issue of theWorkshop "The Use of Water In Sustainable Agriculture" 2-4 June 1997,Albacete, Spain (submitted)

[7] Lopez, P. and Lopez, H., 1993. Servicio de asesoramiento de riegos.In: Agronomia del Riego, Ed. Mundi Prensa, Madrid.


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subterranean water extracted is used for agriculture, … · of irrigated lands is settled over the aquifer system 08-29 ... surfaces. The integration of ... EXPLOITATION. WATER CONSUMPTION