Gert A. Schultz

Remote Sensing in Hydrology and Water Management

From the contents: Overview and Basic Principles Physical Principles and Technical Aspects of Remote Sensing Processing Remotely Sensed Data: Hardware and Software Considerations Integration of Remotely Sensed Data into Geographical Information Systems Remote Sensing in Hydrological Modeling Precipitation Land-use and Catchment Characteristics Evaporation Soil Moisture Remote Sensing of Surface Water Snow and Ice Soil Erosion Water Quality Groundwater Introduction to and General Aspects of Water Management with the Aid of Remote Sensing Flood Forecasting and Control Irrigation and Drainage Computation of Hydrological Data for Design of Water Projects in Ungauged River Basins Detection of Land Cover Change Tendencies and their Effect on Water Management Future Perspectives.

Remote sensing in hydrology

Abstract The “Electronic Age” offers new and attractive opportunities to hydrologists for remote sensing (RS) of hydrological data. A discussion of hydrologically relevant platforms and sensors and the type of electromagnetic signals used by such sensors is followed by an analysis of the structure of mathematical hydrologic models which use RS information either as input or to provide a basis for model parameter estimation. Three examples of RS application in hydrological modeling are given: (1) model parameter estimation with the aid of multispectral Landsat satellite data; (2) computation of historic monthly runoff for design purposes with the aid of a lumped system model using NOAA infrared satellite data as input; and (3) real-time flood forecasting applying a distributed system model using radar rainfall measurements as input. Further applications of RS information in hydrology are discussed in the field of evapotranspiration, soil moisture, rainfall, surface water, snow and ice, sediments and water quality. A brief discussion of RS data availability and the hardware and software required is followed by an assessment of future opportunities. The potential of passive and active microwave sensors for hydrological applications is emphasized.

Remote sensing applications to hydrology: runoff

Abstract Since no remote sensing (RS) devices have been developed allowing the measurement of river runoff directly, information from RS sources is used to compute runoff values indirectly. This is done with the aid of hydrological models, where RS data are used in two different ways: (1) in the form of model input data; and (2) for model parameter estimation. Three types of models are discussed, the parameters of which are estimated—at least partially—with the aid of RS information. A mathematical model is demonstrated, which reconstructs monthly river runoff volumes on the basis of IR data obtained by the Meteosat geostationary satellite. The second model computes flood hydrographs with the aid of a distributed system rainfall/runoff model. A major model parameter, viz. the soil water storage capacity, which varies in space, is determined on the basis of Landsat imagery and digital soil maps. The third model discussed is a water balance model which computes all relevant variables of the water balance eq...

Application of a geographic information system for conceptual rainfall-runoff modeling.

Abstract Geographic information systems (GIS) offer many new opportunities for hydrological modeling. They can be used to form spatially distributed models of watershed. However, some problems of this approach, e.g. the parameterization of physically based models, are not resolved yet. Conceptual models of the meso-scale still have a great practical importance. In this paper one approach is presented: how statistical descriptions of distributed catchment characteristics could be used to consider spatial heterogeneity within conceptual models. Three semi-distributed modules are presented. The three components are combined to a hydrological model including feedback components between surface flow and infiltration and between subsurface return flow and surface flow in saturated areas. The model was set up to use spatially distributed information about catchment characteristics for the estimation of its parameters. By a direct estimation of some model parameters from a GIS-based analysis of the catchment characteristics, the number of calibration parameters can be reduced. In the second part it is shown how the application of this model to different catchments within a region can benefit from boundary conditions for optimization, which are derived from a GIS considering the differences of catchment characteristics.

Meso-scale modelling of runoff and water balances using remote sensing and other GIS data

Abstract For about two decades remote sensing (RS) data in the form of multi-spectral air photography, ground based weather radar as well as geostationary and polar orbiting satellite data have been available for use in hydrology. It is the intention of this paper to advocate the use of RS data in the field of hydrological modelling. It is shown that the main field of application of RS data in hydrological modelling lies in the meso-scale. The potential of RS in the framework of GIS is shown along with three examples. The first example shows the use of RS data for rainfall/runoff modelling in the lower meso-scale. A model was developed which used the high spatial resolution of Landsat polar orbiting satellites (30m × 30 m) for model parameter estimation. The second example shows the use of geostationary satellite data for the computation of long time series of monthly runoff values in the upper meso-scale. It was applied in West Africa for the purpose of water resources planning. In the third example, a w...

Filling gaps in runoff time series in West Africa

Abstract Design and operation of water resources management systems in many countries, particularly in the developing world, very often suffer from inadequate hydrological data. Consequently, many water resources management projects in the Third World do not function as optimally as they are supposed to since long uninterrupted time series of data are often not available for the assessment of the performance and reliability of the projects. Besides data inaccuracy, inadequate data may comprise the total absence or incompleteness (in terms of length of records) of data or irregular observation periods, leading to a number of gaps or discontinuities in the series. Infilling of missing sections of data is often necessary prior to the practical use of hydrological time series. It was the aim of this research study to find the most effective ways of infilling the numerous missing runoff data most commonly associated with Third World data based on a simple Decision Support System (DSS) valid in West Africa.

Hydrological modeling based on remote sensing information

Abstract Starting with the water balance equation the various terms of the equation are briefly discussed and the question, how far these parameters can be estimated with the aid of remote sensing data. The difference in use of RS data for the estimation of parameters of hydrological models and the use of such data as model input is discussed. For the modeling of hydrological processes single processes are discussed, i.e. the values of a hydrological variable are determined from RS data of one source only, while in combined processes the values of a desired hydrological variable are determined indirectly with the aid of some other information. Examples for both conditions are given. A major part of the paper is devoted to the question of modeling at different scales. Problems in hydrological modeling at micro-scale, meso-scale and macro-scale are discussed. A model for the micro-scale is presented which uses remote sensing data as well as digital elevation model data for the estimation of model parameters. The structure of the model is such that the hydrologic computations are done for all the Landsat pixels within a catchment area and the flow is routed downhill and eventually down the river by mathematical procedures. The technique is presented for rainfall runoff modeling in the Volme river in Germany. Also for the meso-scale hydrological modeling an approach is presented which uses the principle of overlays and generates aggregated Hydrologically Similar Units, for which the relevant flow computations are carried out. The chapter closes with a few remarks on hydrological macro-scale modeling within the context of coupled Atmospheric General Circulation models with ocean and hydrological models. A more detailed presentation follows dealing with the question of mathematical structures of hydrological models using remote sensing data either as input or for model parameter estimation. Conventional concepts like lumped vs. distributed models, linear vs. nonlinear models and deterministic vs. stochastic models are discussed with the focus on their suitability for use of RS data. The paper concludes with a discussion of expected future developments, both in the field of hydrological modeling as well as in the field of new remote sensing platforms and sensors.

Potential of Modern Data Types for Future Water Resources Management

Abstract Presently a change of paradigm in the field of planning and operation of water management schemes can be observed. The introduction of the principle of sustainable development by the United Nations and the principle of integrated river basin management postulated by the European Union play a major role in this context. Introduction of these new principles requires development of new planning tools, which in turn require a much better data basis than available hitherto. This paper deals with new data types already partly available now, partly to be expected to be developed in the medium-range future. The present data situation is discussed, along with the obvious deficits of conventional data. New data types will not be limited to point measurements, but rather must comprise information covering large areas with a higher resolution in time and space than presently available. Remote sensing data will play a more important role in the future. Furthermore, digital maps, digital elevation models, etc. are also of growing importance and will be processed, together with remote sensing and other data, within Geographical Information Systems of future generations also exposing the potential for working with multi-temporal imagery. In the paper it is shown that in the future more accurate data will be available, not only in terms of data quality, but also resolution in time and space. It is shown how the new types of hydrometeorological data postulate new types of hydrological models. Here, distributed system models are of growing importance. Furthermore, it is shown how the combination of remote sensing with other information leads to new data types that allow integrated planning of water resources systems. The potential of real time data is highlighted, particularly in the context of real time operation of water resources systems, especially for flood control. The potential of large-scale data schemes in the context of regional and continental water management schemes is discussed. Global atmospheric models coupled to hydrological models are discussed, and their potential to consider long-distance effects of certain phenomena (e.g., El Niño) are mentioned. For sustainable development of water resources, the potential of long-term data prediction scenarios is evaluated, and an example of this principle for planning future water supply systems is presented. The paper ends with a vision of future developments in planning water management schemes on the basis of new data types

Monthly runoff generation by non-linear model using multispectral and multitemporal satellite imagery

Abstract A monthly cloud cover index (CCI) is determined as a function of the threshold cloud top temperature (IR channel), the “reflectivity” of the cloud (VIS channel) and the state of the environmental mean relative humidity in the upper troposphere (WV channel) using multispectral and multitemporal satellite imagery and is transformed into monthly area precipitation. Consequently the rainfall based on satellite information is transformed into monthly runoff values with the aid of the non-linear Volterra series model. The approach is tested in West Africa, in the Tano river basin in Ghana, which cover an area of about 16.000 sq. km.

Low-Flow and Flood Control: Distributed Versus Lumped Reservoir Model

Abstract Two possible approaches to the problem of optimal operation of a reservoir system are applied, namely a distributed model in which each reservoir is individually considered and a lumped model with only one equivalent reservoir to be ope-rated. These models yield near optimal solutions to the reservoir operation problem. The solutions are then analysed under various criteria: operating rules, marginal value of storage, computational aspects, stochastic considerations, environmental factors and multicriteria analysis. As a practical application the Wupper River Reservoir System, consisting of six major multipurpose reservoirs, is operated to meet three objectives, namely low-flow augmentation, flood control and recreation.