Authored by Bahman Ansari*
Abstract
Unique water level variations make the Caspian Sea a suitable case for investigating seismic responses, analogous to the problem of Reservoir Induced Seismicity (RIS) which is an interesting issue in civil, geotechnical and earthquake engineering. An analysis using past data demonstrates that the seismicity of the Caspian Sea region changed with changing sea water level and changes in the b-value of the Gutenberg-Richter Relation have had an inverse correlation with sea level changes. It is conventionally assumed that, the b-value can show the stress level in a region, hence, additional loads on the earth crust, represented by sea level changes, affect the b-value and change seismic regime. It is not possible to calculate b-values for all time periods due to limitations in the past data and therefore, an explicit non-linear function is proposed to approximate the obtained correlation using a genetic algorithm and an RBF (Radial Basis Function) neural network. This function can estimate b-values where there is not enough data for a definitive evaluation of the b- value..
Keywords: Seismicity; Sea level changes; Function approximation; Genetic algorithms; Neural network
Introduction
Inland water bodies are highly sensitive to environmental changes in their hinterlands. As the largest lake on the Earth, the Caspian Sea has a number of unique features. Not least of there is the considerable water level fluctuations during the 20th century due to changes in the volume of water in the sea. The water surface area in the Caspian Sea is around 380,000 km2 depending on the water level. It washes five different countries along almost 7000 km length of coastline, namely Iran, Turkmenistan, Kazakhstan, Azerbaijan and Russia. It is believed that it is a remnant of the Tethys Ocean that became landlocked about 5.5 M years ago, along with the Aral Sea and the Black Sea [1]. It is a sea with no outlets and no tides. Its salinity is only one third of that of the main oceans (up to 13 g/l), decreasing from the north, where the Volga river flows into the sea, to the south basin and also from the west to the east due to fresh water coming from rivers [2,3]. It is conventional to consider the basin of the Caspian Sea as having three parts [4,5]: a northern part, with water depths of only a few meters; a central part, where the water depth increases in a southerly direction with a maximum depth of 788m; and a southern part wherein the water depth increases to over 1000m. Based on the known bathymetry and depending on the water level, the volume of water in the sea is around 78,200 km3. It measures 1,170 km North-South (between latitudes 36° and 47°) and as much as 470 km East-West (between longitudes 49° and 54°) as shown in Figure (1). As a landlocked body of water, the Caspian Sea level (CSL) is controlled by the interplay of the influx of water from a number of rivers, of which the largest is the Volga, and the outflux due to net evaporation. It is believed that the net volume contribution from seepage either into or out of the sea is negligible [6]. The Caspian Sea water balance has been documented in various publications and generally riverine inflow and evaporation from the sea surface are believed to be the major factors [6,7]. River runoff mostly comes from the Volga River. The Volga River Basin is situated within the Russian Plain and this river drains an area of around 1,380,000 km2 with a length of about 3700 km and discharges into the northern part of the Caspian Sea (Figure 1). Its annual discharge has been observed to be varied between 212 and 310 km3 [8] (Figure 1).
The Caspian Sea has experienced considerable fluctuations in its water level during the past century. In 1900, the Caspian Sea level (CSL) was about -25.5m relative to global sea level, and it had fluctuated a little around -26m for the previous three decades. In the 1930s, the CSL began to decline rapidly by around 2m, followed by a longer period ending in 1977 at which time CSL was about -29m. By the year 1995, CSL had largely recovered, increasing to about -26.6m. Subsequently it has slightly fluctuated around -26.5m. These profound water level changes in the Caspian Sea have had several impacts on the region: Changed coastal morphology [5,9] seriously affected many national economy branches [10], and even changed the seismic regime [11]. The last of these effects is similar to the problem of Reservoir Induced Seismicity (RIS) (Figure 2).
RIS was detected for the first time in Lake Mead (Hoover Dam) in the United States in 1940s. After that, around a hundred worldwide cases have been reported by researchers such as Gupta, Beck, Simpson, Kalpan and Chander, Awad and numerous others. Many studies were carried out to achieve a better understanding of correlation between dam site conditions with RIS. It is observed that in some cases, Triggered earthquakes occurred by impounding a small reservoir whereas water filling in some other large reservoirs has been not followed by induced earthquakes. Both the Geological setting and the reservoir characteristics are important factors in assessing potential of sites among which the maximum height of water column has a significant effect. There are a number of reservoirs in which RIS has been observed several years after impounding and the earthquakes that occurred have been even larger, both in number and magnitude, than those shaking the region at the time of initial impoundment. This type of RIS can also be related to the lake level oscillations seen in some sites such as Koyna in India, Lake Mead in United States, and Lake Jocassee together with Monticello reservoir both in South Carolina. In the case of Induced earthquakes, given the gradual accumulation of energy in faults of a region, any change in the stress level will stimulate faults, and act as a catalyst to impact the seismic regime. The b-value parameter (see below and equation 1) of the Gutenberg and Richter equation [12] provides a leading seismic source of information in a region [13,14]. Most b-value investigations result in a correlation between this parameter and the physical properties in an area [13]. For example, spatial variations of b-value demonstrate stress variations in an area [13,15]. Scholz [16] showed that the magnitude of the b-value depends on the stress level. Several highquality seismic catalogues were analysed by Schorlemmer et.al [17]. They found that the highest, lowest, and intermediate amounts of b- value belong to the normal, thrust, and strike-slip faulting types of earthquakes, respectively.
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