Digital image processing for large scale irrigation management and monitoring
Janet E. Nichol
Department of Geography, National University of Singapore
Introduction
Accurate monitoring of the social and environmental impacts of large dams in often still only a minor concern in total project design (Adams, 1985: Barrow, 1987: Nichol, 1987). One of the frequently cited explanations for this shortcoming is a lack of data coupled with the difficulty of obtaining it. Project implementation is often the main concern of governments, funding agencies and contractors. Post-project appraisals are therefore often subjective and lack empirical evidence (Barrow, 1987, p. 134).
Te types of data required for impact assessment and management are not easily obtained by conventional methods since they demand observations at regular intervals over long periods, often covering catchments thousands of square kilometers in extent. These types of data include soil erosion, sediment yield, and changes in the water regime and vegetation cover. Increased human activity in an area frequently follows dam construction, and these impacts are likely to be observed throughout the upstream as well as downstream catchments.
Hydrologic impacts of dam building are usually long term, requiring observation for a subsequent period of several years. Land downstream previously subject, to annual flooding may take several years to dry out completely. Thus associated changes in vegetative intensity may not e apparent immediately. On the other hand geomorphic changes such as gull eying and soil erosion tent to occur most dramatically in the year immediately following dam construction.
Since changes in the type and amount of vegetation are intimately associated with all the major environmental factors surrounding water resource development schemes, vegetation monitoring is seen as a key factor in impact assessment.
This study describes technique of using digital satellite data fro measuring changes in vegetation intensity in a reservoir catchment, and for obtaining data on water surface area for input into hydrological models.
Compared with other data sources, satellite data is relatively cheap, once image processing equipment has been obtained. Since the levels of detail increasingly ressemble those obtainable from air photos, land cover of large areas can be rapidly and cheaply monitored. The data is digital and quantifiable, thus objective comparisons can be made between different time periods if other factors are constant.
The study area
The study was carried out in Kano State of Northern Nigeria, where numerous earth filled dams were constructed in the late 1970s and early 1980s. due to its accessibility and proximity to Kano City, a case study was carried out of the Jakara Catchment,
(figure 1) from the edge of Kano city to the river's disappearance in the sediments of the Chad Formation, approximately 40 Kilometers tot eh north-east. This was accomplished using a 512 x 512 pixel extract from LANDSAT MSS path 202, Row 52 covering can area o 1,600 square kilometers, for which two dates were available : 10.1.76
(Plate 1), and 19.11.1978.
The Jakara catchment, an area of 559 sq. kms is located within the Sudan Savanna zone of northern Nigeria, a region of semi-arid climate with an average of 800mm rainfall in the May to September we season. Thus non-irrigated cultivation is limited tot eh wet season except in the seasonally flooded fadama (flood plain) areas. The fadama areas which comprise less than 10% of the total land area in northern Nigeria therefore constitute a very important resource whose continued productivity is vital to the local economy.
Figure 1. Study Area
Plate 1. Vegetation enhanced false colour
composite January
1976 (pre-dam).
Kano city in bottom left
