Vol. V, No. 4, July-August, 2014

López-de la Cruz and Francés,

Figure 4. Summary of the results obtained using the external covariables model at six representative stations. The results

show the calculated quantiles for different non-exceedance probabilities (0.025, 0.25, 0.50, 0.75, 0.95).

graphs for the

quantiles without trends,

obtained from the review of the normality of

the residuals.

Returning to the inspection of the results in

Figure 4, the calculation of the middle quantile

(with an exceedance probability of 0.50) tended

to be less affected by climate variability.

Nevertheless, the effects are significant in the

calculation for the higher quantiles. Another

point to be noted is that in spite of an adequate

fit of the models, some noise in the results of the

model can be observed, which reflects the non-

linearity in the response of the flood regimes to

natural climate-forced variability.

The main objective of the study of floods in

operational hydrology is to calculate growth

events for an exceedance probability defined

in order to obtain flood maps, design

protection measures or establish flood risk

management plans. In fact, in Mexico and

many parts of the world, legislation related

to the risk of floods is based on the analysis

of the frequency of floods to calculate design

floods associated with different time periods

(for example, 20, 50 and 100 years ). These

return periods are related to the need for sound

structures.

Figure 6 shows the results from the

analysis of the frequency of floods in stationary

conditions and non-stationarity conditions for

an exceedance probability of 0.01 (that is, a

return period of 100 years). The graphs show

the problem with assuming stationarity in

the calculation of the flood events. As can be

observed, the non-stationary models indicate

the existence of important periods duringwhich

the flood calculated under non-stationarity is

above that obtained with the stationary model.

Focusing on the analysis of the results for

station 10027, based on the trend model, the

flood for an annual exceedance probability of

0.01 for 58 years of records has ranged from

a minimum value of 640.40 m

3

/s in 1996 to a

maximum of 1 730.52 m

3

/s in 1966. Based on

the covariables model, the minimum value was

295.51 m

3

/s in 1988 and the maximum was 3

508.08 m

3

/s in 1969.

Analyzing the results from the modeling of

the flood events in the non-stationary scenario

with the covariables model and the stationary

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