GIS and Remote Sensing Technologies for Efficient Agricultural Water Use
Professor Shahbaz Khan
CSIRO Land and Water Division,
Locked Bag 588, Wagga Wagga, NSW 2678
International Centre for Water,
Charles Sturt University, Locked Bag 588, Wagga
Wagga, NSW 2678, Australia
Shahbaz.khan@csiro.au
Cooperative Research Centre for Irrigation Futures
Abstract
Efficient water use is the key for sustainable management of water resources. In
inefficient rice growing areas, groundwater recharge is caused by inefficient irrigation
practices, high leakage rates from light textured soils, poor surface and groundwater
drainage and inappropriate crop rotations. Shallow watertable and secondary soil
salinisation have a major impact on the long term sustainability of these areas. Land
and Water Management Plans have been developed in these irrigation areas to
address sustainability issues by implementation of on-ground works and community
actions to control waterlogging and salinity. The proposed on-ground works and
community actions can achieve the desired benefits only if their effectiveness can be
assessed prior to implementation, restrictions on rice areas can be quantified and
resulting changes in environmental conditions can be measured on the landscape.
This paper describes how GIS databases, remote sensing and hydrological
modelling techniques are helping land and water management actions in the rice
growing regions.
1. Introduction
The major rice based irrigation areas in Australia are situated in southern NSW
comprising of a total area of around 150,000 hectares situated in the Murrumbigdee,
Coleambally, Murray Valley Irrigation areas and districts and along the rivers and
creeks (Humphreys, 1999). The rice growing areas are experiencing rising
watertables and soil salinity, which threaten the sustainability of irrigated agriculture.
Due to the limited unconfined storage, discontinuous nature of underlying aquifers
and limited regional groundwater discharge it is necessary to limit rice growing to
suitable lands which do not effect surrounding areas significantly. Currently rice
growing area restrictions are in place to reduce recharge to groundwater (Humphreys
et al, 1994).
In addition to rice area restrictions, Land and Water Management Plans (LWMPs) are
currently being developed and implemented to address sustainability issues. These
plans enlist specific sustainability targets for a 30 years period such as:
- Sustainable productivity of farms
- Achievement of on farm water balance bench marks
- Extent of saline areas to be less than a certain proportion of total irrigation
area by a certain number of years
- Levels of salinity in the drainage waters at key locations
In order to achieve these targets a number of actions such as adoption of best
management practices, growing of rice on only suitable lands, on-farm and regional
management activities and education and extension endeavours are planned.
Currently rice growing areas in the Murray Valley and Irrigation Districts are being
monitored using satellite images and GIS methods. The GIS offers unique
opportunities to integrate spatial data from different sources with the natural
resources management models (Goodchild, 1993). Digital description of these rice
growing areas with the hydrological models in a GIS environment can be used to
assess and differentiate climatic and management impacts on shallow watertables
and soil salinity. These models can also be used to evaluate the local and
downstream impacts of a number of management concepts e.g. drainage,
conjunctive water use and sustainable hydraulic loading.
2. Measurement of Rice Growing Areas
Barrs et al. (1994) gave details of rice classifying methods using satellite imagery,
with varying degrees of accuracy stated. De Soyres (1989) showed 25-50 percent
reduction in costs over the conventional techniques for medium-scale line maps and
further reductions in costs for digital elevation mapping, ortho-images and spatiomaps
when satellite images (Landsat) were used. Gastellu-Etchegorry (1990)
analysed SPOT and Landsat capabilities for spatial feature determination and
concluded that Landsat-MSS (TM) data (30 m pixel size) can allow identification of
features larger than 5 hectares and whereas SPOT-XS (P) data (10 m pixel size) can
allow analysis of features larger than 0.16 hectares for length to width ratios less than
4.
Prior to 1996/97 irrigation season, Murray Irrigation Ltd (MIL) were using hard copy
aerial photographs and planimeters to measure rice crop areas. To record the history
of areas sown to rice, measured areas were transferred to a file system by hand
colour coding for every irrigation season thus a drawing or photocopy was produced
for each of the 1580 rice growing farms. At this stage a visual comparison was done
to verify the crop was grown on suitable soil. Measured areas were then keyed into a
data base and hydraulic loading (amount of water applied per unit area) was
calculated using meter readings from dethridge water measuring outlets. This entire
process used to take around 6 to 8 weeks for 3 people to complete. MIL has now
adopted digitisation of satellite imagery for quantification of rice areas.
Timing of rice growing activities is dependent on crop variety and climate. Rice bays
are filled and sown from late September to early December. The crop emergence
varies due to climate, variety, water management and turbidity. Draining begins late
February for early varieties and harvest can continue into June. The purpose of rice
area measurement is to assess whether rice is being grown on the suitable land and
within the allowable rice area limits Therefore irrigation companies need to measure
the total amount of ponded water regardless of crop density or coverage.
The optimum timing for satellite data acquisition for rice area measurement is mid
December to early February. The Murray Irrigation Area is split across two Landsat
flight paths. The revisit interval of Landsat could mean a large change in crop
development between scenes or data could be missed entirely due to cloud cover.
Off nadir viewing capability of SPOT gives excellent revisit opportunity during periods
of cloud cover. SPOT imagery has higher spatial resolution and could be used by the
irrigation company for other larger scale mapping applications.
Two remote sensing methods were considered for rice area measurement:
- Classification of Landsat imagery with Normalised Vegetation Index
(NDVI).
- On screen digitising of Spot Panchromatic imagery
Identification of Rice Paddocks Using Landsat Data
Landsat band 3 (Red, 0.63-0.69 µm wavelength) and band 4 (Near Infrared, 0.76-
0.90 µm wavelength) were used to construct normalised vegetation index (NDVI) i.e.