Multi-scale Remote Sensing of Ground and surface Water Interactions.
Tim R Mc Vicar1, David LB Jupp1, Alex Hel1, V.K. Choubey2 and Li Lingtao3
1Division of Water Resource CSIRO, Canberra, ACT Australia.
2National Institute of Hydrology, Roorkee, Uttar Pradesh, India.
3North-West Institute of Soil and Water Conscrvation, CAS, yangling, Shaanxi Province, PR China.
1 Introduction
The Loddon-Campaspe catchments (LCC) in northern Victoria, Australia, cover an area of 19400 km2. Land use in primarily agricultural including dryland and irrigation for crop and pasture production. Remnant stands of deeper rooted native woodland and forest cover 10% of the LCC. Changes to landcover by clearing for agriculture has altered the gydrologic balance. Subsequent rises in local and regional water tables are expressed on the surface as waterlogging and soil salinisation.
A collaborative project involving staff from CSIRO Division of Water Resources. CSIRO Centre for Environmental Mechanics and the Victorian Department of Conservation and Natural Resuurces has been established to understand round and surface water interactions for the prediction of water response to a prefect. For overviews of the environmental conditions in these catchments see Campaspe CWG (1992).
To comprehend the complexities the completies of water movement through the landscape and its expression at the surface, as either waterlogging or salinisation, multi-scale remotely sensed imagery is being liked with hydrologic process models, Remotely sensed data is providing insights into the spatial and temporal variations of water presence and movement, modelling is enabling us the comprehend variations in remotely For example, providing land use maps. Rate of land use change and regional estimates use change and regional estimates of LAI. Data used in (LANDSAT MSS & TM) and regional (AHRR), these are detailed in Section 3.
2. Monitorin Ground - Surface Water Interactions in a Water Balance
Waterlogging in the LCC occurs when saturated local or regional groundwater intersectios the upper metre of the soil column. Salinisation occurs when this water mobilises soil salt and when the water evaporates the salt is left at the soil surface. Changing vegetation management practices, by a combination of reducting amounts entering the groundwater aquifers or intercepting groundwater with deeper rooted vegetation, wil enable future waterlogging and salinisation the be minimised. The presence and movement of water in the landscape is the most improtant parmeter to the understanding and prediction of waterlogging and salinisation. The water budget for the root zone of the soil column can be written:
¶W/¶t=(P+I) - E - R + D - G (1)
Where W is water content of the root zone, p is Precipitation, I is Irrigation, E is Evaportranspiration, R is Runof D is dDischarge from the groundwater' and G is Recharge to the groundwater, all uniits in cm. Ignoring, for the moment, irigation, recharge and discharge, this rate equation can be integrated over days or weeks to ederive a simple difference equation for the incremental change in the soil water storage:
Wt - Wt-1 = Pt - Et - Rt (2)
Soil moisture increments by the net of rainfall (Pt) minus evapotranspiration (Et) and runoff (Rt) over the time period from t-1 to t resulting in a total at time t of Wt Typically, an information system for estimating soil moisture will utilise meteorological data to provide rainfall and the atmospheric demand for water, This demand can be estimated in various ways from records of air temperature, solar radiation, humidity and windspeed It can then be used with allowance for land cover type and condition to compute a potential evaportranspiration (Ep) This is the response of the land surface to the atmospheric demand for
Presented at the 15th Asian Conference on Remote Sensing, Bangalore, India, November 17-23, 1994. Water if soil water is not limiting. A water balance can be computed if an initial storage is known (W0) and if operating characteristics, for the area are known which define relationships between the water balance moisture availability (ma (WB)) and runoff fraction (rr) and soil moisture. For example:
ma(WB)=E/EP=f(Wt/Wmax)
and (3)
rr=R/P=g(Wt/Wmax)
Here, Wmax is the water which whould be available at field capacity. I gnoring recharge and discharge, the application of Equation (2) results in a time series for the water available in the root zone While this water balance model does not incorporate surface and ground water interactions these will be observed by thermal remote sensing. The aim is to bring the meteorological driven water balance model into agreement with indices obtained from thermal remote sensing and to analyse the spatial and temporal residuals in the remotely sensed derived indices to profile indications of ground and surface water interactions.
3. Role And Description of Remotely Sensed Data Sets
3.1 Catchment Scale (Airborne Data)
Airborne scanning devices offer flexible paramenterisation of geometric, radiomtric and temporal resolution. In the past two years we have gained considerable experience in all aspects of airborne remote sensing, including instrument operation, flight planning, image modelling, development of radiometric and geometric correction algrithms and coupling the rmote science with field based measurement science (Jupp et al. 1992b, Held and Juppp 1994, Jupp et al 1994b.)
The Compact Airborne Spectrographic Imager (CASI) a pushbroom imaging spectrugraph intended for acquisition of Visible and Near Infra-Red multispectral imagery from light aircraft. A " reflection diffraction grating spectrograph" disperses the light along the Charge Coupled Device to create the 288 spectral channels covering 379nm to 894nm spectrum. Each spectral channel (or array element) is in the order of 2nm wide. The CASI is operated in two preferred modes of imaging, spatial or spectral. Spatial mode collects image data limited to up to 19 user defined spectral channels. Spectral mode images the full spectral array response on a few nominated ground pixels. For further technical details of the CASI see Anger et al (1990) and Babey and Anger (1989).
Recently, narow-band reflectance indices sensitive to plant physiological conditions have been proposed (Gamon et al. 1990) Epoxidation state of leaf xanthophyll pigments produces a detectable changes in leaf reflectance at 531 nm this is closely related to changes in photosynthetic light use at the leaf and canopy levels. The 'physiological reflectance index (PRI) takes advantage of this absorption feature to map photosynthetic efficiency at various levels of water and nutrient stress.
