This FRIEND project provides a forum for the development and application of methods of regional analysis in hydrology. The following topics have been addressed:
1. Techniques for mapping hydrological characteristics
2. The use of hydrological “maps” for validating hydrometeorological macro-models.
3. Spatial and temporal variability of hydrological regimes — role of global change and human impact.
4. Relationships between large-scale climatic and hydrologic anomalies and teleconnections.
An ambition in the group has been to define the context of “regional hydrology” and to work towards writing a textbook on this topic. The underlying approach of the group so far can be formulated as: “Let us allow hydrological data to speak for themselves.” Deductive models, so dominant in hydrological analyses, have been given a low priority in favour of inductive methods based on statistical theory. The present development of scientific hydrology calls for a change in the concept of regional hydrology and there are suggestions for broadening the base for the methods used in the future.
Many of the scientific results achieved by the group have been published in international scientific journals and conference proceedings. Summaries of scientific achievements can be found in Gottschalk & Krasovskaia (1998) for Topic 1; Krasovskaia (1996) for Topic 3, and Shorthouse (1999) for Topic 4. Sauquet (2000) has further developed Topics 1, 2 and 3. The three latter publications are doctoral theses completed under the framework of FRIEND.
Interpolation of hydrological information in space and time is an important topic in hydrology, relating to the problems of regionalisation and scaling of hydrological variables. Though runoff is measured at a point (at a gauging site), the value obtained is an integration of the whole river basin upstream of this point. Interpolation of such data demands consideration of the network structure to reflect the specific character of this information. The different nature of runoff characteristics demands different interpolation approaches. For mean discharges, a linear approach is necessary with discharges summed up at river junctions throughout the whole river system, whereas for index floods and low flows there is a non linear relationship with basin area which calls for a different approach. Interpolation algorithms, like those offered by GIS software, produce static colourful digital maps that often disregard both the river basin with its hydrographic net as the fundamental hydrological unit, and the water balance equation as the fundamental hydrological law. Hydrological maps need to be hydrological. The complexity of the interpolated hydrological information necessitates the use of a broad spectrum of interpolation techniques from statistical approaches, involving such aspects as dimensionality and scaling, to those based on physical models.
The study of large-scale variations implies the use of observations from large river basins, regions and continents. During recent years much of the research has therefore been conducted in close cooperation with AMHY FRIEND. Cooperation has also been initiated with the FRIEND/
AMIGO project for Mesoamerica and the Caribbean, where some of the approaches developed have been introduced for practical application.
Two studies, presented below, illustrate research into spatial and temporal variations of seasonal flow patterns (river flow regimes), which are still poorly understood.
Objective interpolation of flow regimes along a river
An approach for objective interpolation of flow regime patterns along a river net has been developed for south-eastern France in collaboration with AMHY FRIEND (Sauquet et al., 2000), based on an extensive monthly runoff record. The interpolation scheme suggested accounts for both the auto-correlation in time series and also considers the discharge record as an integrated value related to the upstream basin. The main river network (water paths) has been used as a logical background for the interpolation scheme. Monthly values were standard-ised to overcome scale dependence with basin size. An Empirical Orthogonal Function (EOF) procedure enabled each standardised time series to be interpreted as a linear combination of amplitude functions defined by weightings at the regional scale. Empirical dependencies related these weights to basin characteristics, with kriging applied for interpolation of weight
residuals. The derived seasonal flow patterns, interpreted within the framework of a simple regime classification scheme, enabled a hydrological map of flow regimes to be derived, as shown in Figure 2.6.
Spatial and temporal variability of seasonal flow patterns
A methodology for studying the spatial and temporal variability in seasonal flow patterns of river flow regimes has been developed by Gottschalk & Krasovskaia (2001). The dimensionality reduction based on EOF, outlined in the previous example, has been applied to a large sample of Scandinavian monthly flow values with a common record length of 74 years. The probability density functions of the weight coefficients in the reduced phase of the two first EOF has been constructed. These two-dimensional density functions (regime attractors) enable a possible change in the frequency of regime patterns over time to be traced. Figure 2.7 shows “regime attractors” for successive 25-year periods.
NE FRIEND
Figure 2.6 Flow regimes of the main rivers in south-eastern France and Corsica
a b c
Figure 2.7 Regime state vector (probability density function) PDF in the reduced space spanned by the two dominant EOF of monthly runoff over Scandinavia for (a) 1922-1945, (b) 1946-1970, and (c) 1971-1995. A point in the two dimensional space represents a regime pattern with stable rain regimes to the left and unstable rain regimes to the right. The graphs show a tendency for an increase in the frequency of stable rainfall regimes.