چكيده لاتين :
Introduction
There is a mutual relationship between the characteristics of geomorphology and
flood conditions; therefore morphometric properties of river plays an important role
in the hydraulic estimation of development and passing of flood waves. For example,
using LFH index, including morphometric parameters of river channel, the probability
of flood occurrence in meandering channels is predictable. The results of the flood
prediction, applying morphometric and geomorphic features, are often presented as
the flood zoning maps. These maps are mainly based on hydrological and
geomorphological approaches. As a matter of fact, various hydrological models are
presented to predict the flow in channels, although the hydraulic model HEC-RAS has
been widely applying in recent years. However, this model is often considered costly
and time-consuming, for it needs a wide field data gathering. Moreover, applying the indices such as LFH index accelerates the estimation of the river part flooding.
However, these indices are only a potential expression of flooding, applying the
factors like the rate of meander sinuosity and levee distance of channel sides, and do
not show the zones based on the return period. Therefore, the present study aims at
recognizing the flood zones with different return periods using HEC-RAS model that
would go with LFH index. As a result, a model can be achieved to predict the flood
zone, using LFH index, for each bend with a determined return period for the basin
without gauging stations.
Materials and Methods
In order to study the relationship between LFH index, evaluating the possibility of
flooding in meandering rivers by using some morphometric characteristics, and flood
zones in different return periods, at first, the area of natural levees was determined
during a field visit by GPS devices. After that, the river plans were drawn according to
the maps with a scale of 1: 2000. Then, the value of LFH index was calculated for 31
river bend. In the next stage, using HEC-RAS model and HEC-GeoRAS Extension, flood
zones were identified for 2, 5, 10, 25, 50 and 100-year return periods and the maps
for different return periods were prepared in GIS environment. Finally, flood zones
association with LFH index values was analyzed by using Pearson correlation in SPSS
software.
Discussion and Conclusion
The findings revealed that there is no significant correlation between the flood zones
and the values of LFH index. Replacing flood zones with the intervals between natural
levees in LFH index and considering other parameters fixed, separate LFH return
values were calculated for each period. Besides, their relationship with measured LFH
index was tested. The results showed that the highest correlation is with 2-year computational LFH. Besides, the 2-year flood zone can be predicted indirectly by
second degree polynomial regression model.
Conclusion
In this study, LFH index proved that about 70 percent of the river bends have
moderate-to-low flooding, although a poor and reverse communication {.465 - = r}
exists between LFH index values and the distance among natural levees. This finding
seems reasonable, for as the distance of levees increases, the flooding needs more
return time. However, the lack of relationship between LFH index and flood zones,
obtained from HEC-RAS model, depends on other fundamental factors that need LFH
changes for practical purposes. LFH index is used in meandering river while HEC-RAS
model is handled in the rivers with different patterns. The aforesaid index, using
geometric characteristics of river, shows the flooding potential of each bend
separately which is considered as its advantage in the basins with no hydrologic data.
Whereas, the hydraulic characteristics, HEC-RAS model shows the flow of flood zones
in all parts of the river continuously. Moreover, this model predicts the flood zones in
different return periods accurately, while LFH index shows the probability of flooding
along the river on the other side of barriers, such as natural levees, which is as a
result of insufficient capacity for water transmission during flooding. However, it is
not clear enough to guess the return period that water comes out of levees. Thus, if
the distance between the river levees in LFH index, reflecting passage of flood, is
assumed instead of various flood zones obtained by HEC-RAS, it can be said that LFH
index is the same as HEC-RAS and can predict one flood zone at least. Therefore, in
order to use LFH index instead of HEC-RAS model, first some changes must be made
in LFH index factors and then some searches should be done on morphometric
factors, so that the index can predict even in direct channels. Replacing flood zones with the intervals between natural levees (d) in LFH index and
taking other parameters fixed, the present study aims at obtaining a computational
LFH for each return period. The results showed that there is a significant correlation
between real LFH and computational LFH, although these relationships appear
differently in different return periods. For prediction purposes only two-year flood
zones with second degree polynomial regression model is predictable and this is
logical; because the area of flood zone is congruent in two-year return period which
has more agreement with the natural levees location.
This finding leads to two significant results: first, morphometry index of the rivers
such as the width of the meander belt, actual meander amplitude, width of the active
floodplain in intervals of natural levees and the tare of channel adjustment has an
important role in the hydraulic estimation of development and the passing of flood
waves. Second, based on the morphometric data, it is possible not only to enhance
the prediction up to advance as well as complicated models such as HEC-RAS, but
also to define a new index beyond the channel morphometry by replacing
morphometry of floodplains; this new index can be a substitution for complicated
models dealing with flooding zone with various return periods.
