A GIS-Based Approach to the Management of Tropical
Land areas often ‘have spatially varying characteristics which affect agricultural production, resource conservation and management, e. g. different soil types, fertility levels, and opography. Stocking (1988) observes that the complexity of tropical farming systems necessitates a vastly greater effort- to establish cropping management and conservation practice factors, ‘ for example, than required elsewhere. Proper management of tropical agricultural watersheds must recognize this complexity’ and spatial variability, by customizing conservation practices as well as inputs, such as fertilizers, herbicides and irrigation, in every part of the watershed, in order to ensure optimum yields with
minimum costs and environmental impacts. computerized data management systems such as Geographic Information Systems ( G I s )
provide a basis for customization in watershed management.
A GIs can be used for the collection, management, analysis, and display of spatially registered (georeferenced) multi-attribute data. The distinctive feature of a GIs above other databases is the spatial nature of data in it. It can create separate data planes or layers for land use, soil type, property boundaries, water-table depth, hydrography, etc., to be referenced to one another, while a layer containing information on best management strategy is the result of a user-driven analysis. Powerful cross-layer analyses can be performed to create layers for essentially any spatially distributed attribute of interest, and multiple layers of the same attribute can be used to show time-series relationships.
The accuracy of these analyses and resultant management information depends on the design resolution of the GIs and on the care taken
in data capture. This paper presents the important considerations for a practical application of GIs to the management of tropical agricultural watersheds, keeping to a minimum the technical aspects of GIs which are usually described in the manuals of GIs packages.
According to Stocking (1988), the complexity of tropical farming systems necessitates a vastly greater research effort to stablish parameters of cropping management and structural practices for soil conservation planning, than has already been done elsewhere. Given this coatplexity, and the distinctively marked seasonality of hydrometeorological phenomena in the tropics (Balek, 1983), the management of tropical agricultural watersheds will be greatly facilitated and. enhanced by a GIs–based approach. Geographic Information systems ( G I s ) ‘have been used for a Y variety of applications such as evaluation of groundwater pollution and non-point source pollinator~ of surface waters, aircraft navigation and global positioning, and military purposes.
For example, the Geographic Resource Analysis Support System (GRASS) i~a GIs application by the 3.S. Army, Hodgs et al., 1988. The development of a GIs-based, management system for tropical agricultural watersheds will require the following related activities, representing thc Y G U ~ Purifications of’ u CIS
(a) Data Capture/Acquisi L i a n – the collection and input of spatial data by digitization of existing maps, and Prom remotelysensed images, aerial photographs, field studies and other records ;
(b) Data Management, Storage and Retrieval – a hardware and software configuration to control the data structure and allow for the integration of tabular and graphical data, as well as updates and modification of the database; Manipulation and Spatial Analysis – enables map layers to be combined, compared and manipulated in many ways which , represent the. true value of the GIs; and, Product Genera5ion and Display of Results – communicates the
results of an analysis in any form required by the user, tabular or graphical, including generation of a multidimensional display. For example, to plan soil conservation activities on the watershed, the USLE (Wischmeier and Smith, 1978) can be easily implemented.Layers of data within the GIs are used to represent values of each of the USLE factors, A map of erosion susceptibility is developed by multiplying the values in each layer together.
Similarly, distributed-parameter watershed models used in resource management, such as the WRM model (Mbajiorgu, l995a), have computational features that make representation with a GIs valuable as an information source. The same grid used to solve the finite difference formulation of overland flow and other hydrologic/ transport processes may be represented by a raster of pixels or a set of ,polygonal map ef&nents showing both the solution of the modelled process and the input parameters used to arrive at the solution. Thus model integration with GIs can facilitate the planning of management activities.
Examples of this integration in other parts of the world have been reported by Jett et al. (1979), Wolfe and Neale (1988), Hodge et al. (1988), Smith* et al. (1990) and Evans and Myers (1990). 2. State-of-the-Art Consideration on G I s Application
.1. GIS Database Development:
The two i n i t i a l . ‘ a c t i v i t i e s in t h e development of a GIs-based“ watershed management . system, namely, cla-tct a c q u i s i t i o n and data management, r e q u i r e t h e g r e a t e s t e f f o r t . spatial data of h y d r o l o g i c a l relevance f roin topographic and thematic maps, p o i n t d a t a and d a t a Prom high r e s o l u t i o n e a r t h o b s e r v a t i o n s a t e l l i t e s c o n s t i t u t e t h e input f o r GIS operatj-ons. These s p a t i a l data from v a r i o u s sources have t o be made compatible i n terms of citographic s c a l e and p r o j e c t i o n s . F i g , 1 shows a t y p i c a l d a t a flow in GI6 from r e a l world s i t u a t i o n t o d e s i r e d product, after Meijerink et. i& (1994).
Keyboard e n t r y of tables and d i g i t i z i n g of maps are t h e conventional requirements for data a c q u i s i t i o n i n s u i t a b l e d i g i t a l formats. Often the GIs sof t.uare package i n c l u d e s d i g i t a l image p r o c e s s i n g software f o r t h e conversion of spectral d a t a into h y d r o l o g i c a l l y relevant. t e r r di ant a . Hy d r o l o g i c a l t i m e series; need t o be checked for c o n s i s t e n c y , g r a p h i c a l l y inspected by p l o t t i n g hydro graphs and applying corxbections where necessary, followed by hydro-graph s a p s r a t i o n and frequency a n a l y s i s ; t h e s e curl be done by u s i n g an e x t e r n a l spreadsheet.
For d a t a management, thoreries s p e c i a l G I S pnclwges t h a t can r a p i d l y store, r e t r i e v e and d i s p l a y hydrographic information, including d i g i t i z e d photographs, end access data f i l e s of hydrologic time s e r i e s . But, c o n v e n t i o n a l l y , d a t a management is done i n a s e p a r a t e hydrological database t h a t is l o o s e l y coupled t o t h e G I s database. A GIs database is a collection of spatially referenced data that acts as a model of reality. Spatial data have three characteristic components, namely: geographic position, attributes or properties, and time.
The positional component can be described in an. absolute manner, using a coordinate system e.g. Cartesian (X,Y,Z) or global geographic (latitude, longitude, altitude). It’ can also be described in a relative manner, with reference to some
.other object, e.g. topologic position or directional references (N, S, W, E, below, above, left, right). On the other hand, attributes of data can be nominal, as described ‘by names with no specific order ( e . g . agricultural, urban, etc. ) ; .ordinal, as described by an inherent order or ranking ( e . g . first, second, etc.); or interval, as described by a natural sequence (e.g. equal intervals on a scale with an arbitrary zero point); and/or a rati~ with the same . . characteristics as an interval but with a natural zero or starting point. Finally, the temporal component of data can be described in terms of time duration, temporal resolution (time interval, e. g . hourly or daily rainfall) and/or temporal frequency.
Spectral data generated by earth observation satellites contain spatial information about the surface and near-surface
features of the earth. Aerial photography and satellite imagery, together known as aerospace imagery, constitute an important source of thematic spstial that can be merged with other data using GIS operations. Land cover maps derived from remote sensing have become the basis of hydrologic response units as multispectral classification of land covers was one of the first established a p p l i c a t i o n s of remote sensing t o water resources (Rango, 1990).
An understanding of t h e hydrol.ogg of t r o p i c a l watersheds, with very l i t t l e a v a i l a b l e d a t a , ~:,requires your close look i n t o t h e d i s t r i b u t i o r ~ of physical c h a r z c t e r i s t i c s of %ha wtzterslleds. Notable among -[.he
charcrct,erist.ics ~yhich can lir depicted by imager;, as produced hy image processing techfiiques, arc cover type:; such ss arecrs with dense v e g e t a t i o n , water bodies, and areas with bare s i o i l s or. rock o u t c r o p s . The vegetnt . ion p a t t e r n i n ?l u e n c e s i n t c ~ c e p to~ni, runof’C , evaporation and e v a p o t r c ~ n s p i r a t i o n .
A GIS-Based Approach to the Management of Tropical
Density of vcgetat.ion i n ijrtlas ccin .provide information on serzsonnl and s p a t i a l r a i n f a l l p a t t e r n s ,
e. g . t h e isohyet-form mapping i.n northern Kenya ( M e i j c r i n k 8 t a1. ,
3.994 ) . Remote oensj.ng c o n t r i b u t i o n s t o watershed hydro1.ogj.c
information r e q u i r e techniques of bringing o u t t,hc s p a t i a l p a t t e r n s
i n the land and t h e nature of r e l a t i o n s h i p s between hy-drologic
v a r i a b l e s and t h e spectral p a t t e r n s .
2.2. $aalvtj.caI Cspabi litie-z-ann GIS ~eve10prne:n~Ttr_o-n- ds
The main u t i l i t y of a QTS i-n hydrology and watershed
management is to facj.1 i t a t e t h e a n a l y s i s , of spatial d a t a and t h e i r
a t t r i b u t e s contained in a database, thus a s s i s t i n g i n the
management of land and water resources. CIS-based watershed
a n a l y ~ i se nables t h e u s e r t o answe r q u e s t i o n s about t h e p r e s e n t
state of land and water . r e s o u r c e s and, if its database all-ows, the
p a s t state can be r e t r i e v e d . and in combination with the present
state, t r e n d s can be detected through t h e analysis of watershccl
chanfles. In a d d i t i o n , GIS may be used to p r e d i c t e f f e c t s tind
impacts of proposed watershed managernent/development activities.
Because a GIs database stores data in distinct spatial and
non-spatial categories, spatial and attribute data analyses are
also distinct. The details of GIs anal-ytical functions of queries,
generalization and calculations with respect to attribute data
analysis are given by Meijerink et al? (1994). The ability of GIs
to analyse spatial and non-spatial data simultaneously
distinguishe.~ them from computerized cartographic and mapping
systems. Integrated spatial and attribute data analysis is
performed by means of four groups of analytical functions, namely:
(1) Retrieval, (re)classification and measurement operations; (2)
Overlay operations; (3) Surface operations; and, (4) Connectivity
operations. Some of these groups have sub-divisions of more
specific analytical functions, details as given by Meijerink et a1.
The availability of better and cheaper computers has boosted
the development of GIs technology to such a high degree of
performance that, currently, data can be input in different
formats; interfaces between different digital databases are
available; advanced graphics utilities have been incorporated; the
systems have become more user-friendly; and the number of
analytical functions have greatly increased. However, with most
current systems still limited to 2-dimensional analysis, the GIs
development trend is towards systems that can perform real 3-
dimensional spatial analysis. Only pseudo 3-dimensional analysis
has been achieved, as in the perspective view or illumination
Punct ions. A l s o , the incorporation of the dynamic/lemporal aspects
of watershed changes in CIS becomes increasingly vital for
management. Time itmy be regarded as a fourth diuexision of spatial
date, and the three components of watershed data, namely, sp~tial
(locationnl.), non-spatial (attributes) and temporal, are required
for effective model1 ing. Las LLy, the different analytical functions
of G I s can be app1.i.ed out oi’ corl.l;e>;ti n existing systens arid there
is a need to incorporate intc!lligsnce. Kn~wledge-based GIs, xi th
part of the expected user’s knowledge in-but, ar.e in the
. development trend,
3 . I\i>pl ication of GIS l;o S C,i Lc-Spec i P i c R’esourct. Miailrraemcnt
The “mining” of agricultural watersheds flus lad to degrudaLio:;
of the environment m d cle!pletion of natural resources, fcr which
there is a growing national and international concern. Management
pratices are needed to minirniae er~vir*oameri~tal inpacis . ; i l s i l ~
production and watershed development, Iri the! humid t r o p i c a l
sout.heaute~~Nni g e r i a , for example, the devsstuti~nc aused by soil
erosion i s well known.
An on-f arm GTS can provide the informa tion uud arlalysis needed
to optimally manage agricultural watersheds. Input data for the G I S
would come from various sources includir,g f i e l d setisors;
Agric:ulturcil production inpuLs such as herbicides, fertilizers,
insecticides and irrigation could be tailored in t h c i k ayplicul-r :O l i
to localities using information from the GIs. For instance,
fertilizer costs could be reduced by tailoring fertilizer
application to the soil production potential from one location to
another in the watershed. Simi.Larly, GIs could be used to identify
management practices for reducing soil erosion and conserving water .
and nutrients in a site-specific manner.
The spatially varying soil types, fertility levels and
topographic characteristics of a watershed require, for optimum
management, that inputs to agricultural production and resource
conservation should be customized. Currently, agricultural
equipment are designed to apply chemicals .and plant crops at
uniform rates within’a field, without regard to changes in soil
characteristics. There is ‘a need to rapidly and accurately adjust, ‘
chemical application and seeding rates by soil characteristics
across a watershed. An automated agricultural equipment capable of
customiz~ng its operations with spatial variability will require .
information from an on-farm,GIS.
The overlaying feature of GIS, by which two or more data
planes/layers are combined to form a new plane/layer, has perhaps
the greatest potential for application to site-specific resource
management based on georeferenced data. For example, the ration’al
formula for prediction of peak runoff rates can be implemented
within a GIs in a few steps of table operations. The basic data
(i’) Digital remote sensing data to prepare a cover map;
(ii). A table for converting cover types into runoff coefficients;
(iii) A topographic map; and,
A GIS-Based Approach to the Management of Tropical