Environ Earth Sci DOI 10.1007/s12665-015-4073-8
ORIGINAL ARTICLE
Subsidence and liquefaction analysis in Mexicali, Mexico, during the Cucapa earthquake (April 4, 2010) using Envisat/Asar and Spot images Ramiro Rodriguez • Jorge Lira
Received: 12 June 2013 / Accepted: 20 January 2015 Ó Springer-Verlag Berlin Heidelberg 2015
Abstract An earthquake, 7.2° moment magnitude, occurred on April 4, 2010. Its epicenter was located in southern Cucapa Range, Northern Baja California Peninsula, Mexico, in the confluence of a set of active tectonic faults. Two additional hazards after the earthquake affected population: subsidence and liquefaction. Farmer communities and agriculture lands located in southern Mexicali City were flooded due to the liquefaction phenomenon. Great volumes of fine sediments and water sprouted in different points, flooding agricultural lands and some small communities. The fault displacement during the earthquake damaged roads and buildings. Land subsidence was observed in some areas. More than 35,000 inhabitants and 60,000 ha of agricultural lands were affected. To analyze the consequences of such an earthquake, two multi-spectral and two panchromatic Spot images (before and after the earthquake) were acquired by means of the National Commission of Water, the Mexican Government Water Agency. In addition to these optical images, three interferometric pairs from Envisat/Asar radar sensor were acquired on the grounds of the project C1P6926 with the European Space Agency (ESA). A red, green, blue (RGB) false color composite of the multi-spectral images, before and after the earthquake, shows the inundated areas caused by the liquefaction phenomenon. The two panchromatic images form a stereoscopic pair. These images were integrated into multi-spectral images to derive the texture relief caused by the liquefaction phenomenon. An interferometric R. Rodriguez (&) J. Lira Instituto de Geofı´sica, Universidad Nacional Auto´noma de Me´xico, Cd. Universitaria, 04510 Me´xico, DF, Mexico e-mail:
[email protected] J. Lira e-mail:
[email protected]
analysis was applied to the three interferometric pairs. The coherence images and the digital elevation model (DEM) were calculated as well. The interferometry, the amplitude and the DEM were overlaid. This overlay shows subsidence occurrence in the area of study due to the earthquake. From results and field data, it was possible to identify subsidence-affected areas as well as flooded areas due to the liquefaction phenomenon. Keywords Subsidence Liquefaction Earthquakes Interferometry Multi-spectral images
Introduction An earthquake affected Mexicali Valley on April 4, 2010. The perceived shaking was classified as violent and the potential damage as heavy. The peak ground velocity was 116 cm/s. The seismic activity was characterized by large accelerations, 65–124 % g (SSN 2010), and the prevalence of shallow layers of saturated fine sediments originated soil liquefaction, causing flooding in large areas. Intense abstraction regimes in areas where aquifers are composed of aquitard formations (clay and clayey units) induce differential vertical displacement of terrains, subsidence (BinLin et al. 2003). Subsidence can cause terrain fracturing and faulting of small dimensions. Ground deformation of Mexicali Valley was reported for the time span September 1993–2006 (Sarychikhina et al. 2007). The process can be altered by terrain sinking due to earthquakes (Berardi et al. 1991; Holzer et al. 1999). The extension of affected areas can be recognized, in a relatively short time, by the use of remote sensing techniques. Remote sensing represents the application of techniques to identify and differentiate spectral and
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morphologic parameters from liquefaction and subsidence processes. Mexicali is an agricultural zone where irrigation systems are based on channels due to rain scarcity. Subsidence alters channel slope and breaks channels locally causing flooding of agriculture terrains in the vicinity of the channels. Area zoning can avoid or minimize risks in case of future earthquakes. A detailed review of different types of liquefaction related to earthquake activity can be found in the article by Huang and Yu (2013). The damages in soils and construction are provided as well. A description of the physical effects of liquefaction originated by the Wenchuan earthquake has been published in the scientific literature (Huang and Jiang 2010). Huang et al. (2012) carried out an analysis of geological hazards after the Wenchuan earthquake. Secondary geological hazards such as landslide and rockfall, surface fracture and debris flow are discussed as well. A geotechnical field investigation of liquefaction of soil and a detailed account of the aspects of the Tohoku earthquake can be found in the literature (Bhattacharya et al. 2011). Surface liquefaction was observed in many locations. The liquefied and ejected soil consisted of pure sand, gray silt sand and dredged recycled material. Subsidence and liquefaction phenomena affected inhabitants of farmer communities located in southern Mexicali. To identify risk zones, this investigation focuses on the use of Envisat/Asar interferometric images and multi-temporal optical Spot images of Mexicali Valley. There is a great possibility that other earthquakes can occur in Mexicali Valley. Previous knowledge of affected zones of flooding by liquefaction can help local authorities to implement programs to support the affected population (Berardi et al. 1991; Gallagher 2000; Baise et al. 2006). The phenomenon of subsidence due to underground water extraction has been studied using a number of interferometric pairs (Lo´pez-Quiroz et al. 2009). The unwrapping process was performed by means of a stack of the best interferograms to compute an average of deformation rate for a certain time span. The rate of subsidence of Mexico City was calculated on the grounds of such a process Lo´pez-Quiroz et al. (2009). The subsidence associated with the extraction of water from geothermal fields was estimated using an interferometric pair from European Remote Sensing (ERS) and Envisat/Asar satellites (Hole et al. 2007). Considerable deformation was corroborated with field data for five geothermal sites located in the Taupo Volcanic Zone in New Zealand. Operational monitoring of such deformation requires more suitable interferometric pairs of the geothermal zone. A general discussion on the use of interferometry and differential interferometry to quantify landform attributes, mass movement, landslide and surface ground deformation has been published in the scientific literature
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(Berardino et al. 2003; Catani et al. 2005; Stramondo et al. 2007; Samsonov et al. 2008; Prati et al. 2010). The subsidence caused by groundwater extraction has been reported in many sites around the world (Toma´s et al. 2010; Wang et al. 2008; Rodrı´guez and Schroeder 2010). The main objectives of our research were: (1) identification of recent vertical displacements and faulting related to subsidence by means of optical and radar image analysis; (2) identification of subsidence zones and fractures and faults related to terrain sinking due to the earthquake; (3) assessment of flooding and liquefaction susceptible areas.
Materials and methods Materials One set of optical images and one set of radar images were considered in our research. Two multi-spectral and two panchromatic images from Spot satellite were obtained by means of the National Commission of Water, a Mexican government agency. Three interferometric pairs from Envisat/Asar radar sensor were acquired on the grounds of the project C1P6926 with the European Space Agency (ESA). Tables 1, 2 and 3 provide basic technical parameters for such images. The optical multi-spectral data from Spot satellite was used to assess the extension of the liquefaction phenomenon. A stereoscopic pair was formed by the panchromatic images. Such a pair was integrated into the multi-spectral images to derive the texture relief (Lira and Rodriguez 2006) of the study area. The radar data were used to quantify the degree and extension of subsidence. The study area was located in a quadrangle with coordinates: north-west [3, 614, 649 N, 654, 214 W] and southeast [3, 564, 648 N, 705, 254 W]. From the multi-spectral images, a subset was extracted that covered the study area. Figure 1 shows a map where the location of the study area is depicted. In addition to satellite images, we used field data. With this data (soil, rocks, geo-positioning by GPS, well location, fault and fracture orientation), a set of thematic maps of the study area was integrated (fractures and faults, geothermal and agriculture wells, flooding areas, liquefaction zones). Geological framework and hydrogeology of the study area The study area is located in the Salton Basin (Fig. 1). The basin was filled with sediments (clay, sands, clayey sands) reaching a thickness of 2,000 m (Lippmann et al. 1991). Three sedimentary environments were identified: fluvial,
Environ Earth Sci Table 1 Basic parameters of Spot multi-spectral images
Date
Pixel size (m2)
Image dimensions (pixels)
January 1, 2010
10 9 10
7,398 9 7,278
Bands (lm) 0.50–0.59 0.61–0.68 0.79–0.89 1.58–1.75
April 9, 2010
10 9 10
7,552 9 7,176
0.50–0.59 0.61–0.68 0.79–0.89 1.58–1.75
Table 2 Basic parameters of Spot panchromatic images Date
Pixel size (m2)
Image dimensions (pixels)
Band (lm)
January 1, 2010
2.5 9 2.5
29,573 9 29,183
0.48–0.71
April 9, 2010
2.5 9 2.5
30,230 9 28,554
0.48–0.71
Table 3 Basic parameters of Envisat/Terra interferometric pairs Pair First Second Third
Date
Pixel size (m2)
Dimension (pixels) 5,172 9 4,553
February 21, 2010
Azimuth: 24
March 28, 2010
Range: 20
March 9, 2010
Azimuth: 24
April 13, 2010
Range: 20
April 13, 2010
Azimuth: 24
May 2, 2010
Range: 20
Looks
Mode
Baseline (m)
Azimuth: 6
Ascending
262.71
Descending
262.71
Descending
262.71
Range: 1 5,171 9 4,551
Azimuth: 6 Range: 1
5,171 9 4,546
lacustrine and alluvial. The intense regional tectonism has given rise to a complex fault system such as the Cerro Prieto, Michoaca´n and Imperial faults with a main orientation of North-West–South-East (Fig. 2) and the Volcano and Hidalgo faults perpendicular to the cited faults (Lira 2005). Surface soil fractures associated with subsidence has been detected in some areas. Three aquifer units compose the aquifer system: a shallow, an intermediate and a deep formation. Differences in chemical composition and hydraulic head support the aquifer system differentiation. The fault system is hydraulic connecting the three formations. The composition is mainly formed of fine to gross sediments. In spite of the scarce precipitation, the aquifer system is recharged by infiltrations of the Colorado River, leakages from channels and from irrigation water. The water table is very shallow: between 4 and 8 m in depth. Methods The optical images and the radar images require different procedure analyses. Optical multi-spectral images are used to evaluate the liquefaction phenomenon. This evaluation is obtained by means of an RGB false color composite of the multi-spectral images for both, before and after the
Azimuth: 6 Range: 1
earthquake. The panchromatic images are integrated into the multi-spectral images to derive the texture relief of the study area. This integration produces expanded multispectral images. The texture relief is produced by the application of a divergence operator to the first two principal components of the expanded images (Lira and Rodriguez 2006). Radar images are used to derive a subsidence map of the areas affected by the earthquake. The subsidence is generated employing differential interferometric analysis. In the following paragraphs we explain the procedure of the analysis. Identification of liquefaction spots We used optical images to derive the spectral changes the scene experienced because of the liquefaction phenomenon. To this aim, the Spot images were orthorectified and co-registered. The Spot images before and after the seismic activity must be geocoded and co-registered to evaluate scene changes. The procedure to evaluate such changes is as follows. The study area is identified (Fig. 1) in both multispectral Spot images. An image sub-set covering the study area is extracted for both images. An RGB false color
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Fig. 1 Study area. The big block indicates the area covered by radar imagery. The small block is the study area covered by Spot and radar imagery
Fig. 2 RGB false color composite of bands 1, 2, 3 of Spot image before the earthquake. The blocks indicate two zones inundated by the earthquake. Communities: Durango (1), Delta Station (2), Cucapa Indigena (3), Cucapa Mestizo (4), Cucapa Mayor (5), Mosqueda (6) and Chimi (7)
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Fig. 3 RGB false color composite of bands 1, 2, 3 of Spot image after the earthquake
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composite of bands 1, 2 and 3 is obtained (Figs. 2, 3) for both images. Field data are then integrated into such RGB composites. A block diagram of such a procedure is given in Fig. 4. The geographic location of the inundated areas caused by the liquefaction phenomenon was used to verify the results, and the liquefaction spots were identified in the RGB false color composite after the earthquake. Two blocks marked in Figs. 2 and 3 indicate two liquefaction areas. In Figs. 2 and 3 crop fields appear in red, roads in medium gray, bare fields in medium gray and water bodies in dark gray. An amplification of such blocks is shown in Fig. 5. Texture relief of liquefaction spots To assess texture changes due to the liquefaction phenomenon, a procedure was designed, which is as follows.
Fig. 4 Block diagram of the analysis of Spot multi-spectral imagery for liquefaction assessment
Fig. 5 A liquefaction-affected area. Water with fine sediments was ejected through the small holes
The study area is identified (Fig. 1) in both Spot panchromatic images. Both images are orthorectified and coregistered. An image sub-set covering the study area is extracted for both images. The technical details of the stereoscopic pair are given in Table 2. The multi-spectral image and the panchromatic image are co-registered. The multi-spectral image has four bands. Both images are resampled to have the same pixel size. The panchromatic image is then integrated into the multi-spectral image as a fifth band; this is an expanded image. Such integration was done for the images before and after the earthquake. Principal component analysis is applied to the expanded multi-spectral images; only the two first principal components are retained. A divergence operator (Lira and Rodriguez 2006) is then applied to the first two components. This operator is designed to extract the texture relief of the images. Therefore, the output of this operator is the texture relief of the study area. The subtle traces left by the flooding modify the texture relief of the inundated spots. The smoothness of the ground surface is a consequence of the inundation in the flooded areas. As Fig. 5 depicts, fine sediments ejected by liquefaction were deposited in the affected areas. These sediments smoothen the surface and flatten the texture as a consequence. Therefore, the inundated spots appear with a smooth texture. Instead, the crop fields show a medium and rough texture due to the physical arrangement of the plantation. The smooth texture is depicted as dark gray tones with increasing lightness toward the rough texture (Fig. 6). Our research studies the texture change of the areas inundated by liquefaction. Nonetheless, Fig. 6 shows the same texture change for inundated areas and for flooding in the channels. Both the flooding from the channels and the inundated areas carry a mixture of water and sediments.
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Environ Earth Sci Fig. 6 Texture relief of two inundated areas identified in Fig. 3. The gray scale depicts the association of gray tone and texture roughness. a Texture before earthquake. b Texture after earthquake. c Smoothtexture spots produced by liquefaction. Areas before and after liquefaction are marked by circles
The consequence is a flat surface that appears with a smooth texture. Figure 6c shows the texture change experienced by the liquefaction and by the flooding. Radar imagery The use of differential interferometric techniques to assess subsidence in the Mexicali Valley has been reported (Sarychikhina et al. 2007, 2011). To quantify the subsidence in the study area, an analysis of differential interferometry was undertaken using Envisat/Asar interferometric pairs. Three interferometric pairs from Envisat/Asar radar satellite were acquired on the grounds of the project C1P6926 approved by the European Space Agency (ESA). The radar images forming such pairs were resampled to have an approximately square pixel. Table 3 shows basic technical data of such pairs. The first pair was acquired in ascending mode, while the second and third pairs were acquired in descending mode. Due to this, only the second and third pairs were used in the interferometric analysis. The radar images that form the second interferometric pair were acquired before and after the earthquake
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(Table 3); this is a pair dubbed through the earthquake. The third interferometric pair was acquired after the earthquake (Table 3). These two pairs were co-registered and resampled. The three acquired pairs are the most close in time to the earthquake date. From the pairs we calculated the following: (1) the interferogram, (2) the digital elevation model (DEM), (3) the coherence and (4) the amplitude image. The interferogram was filtered by means of a Goldstein interferometric filter (Goldstein and Werner 1998). Figure 7 is a block diagram of the analysis of the radar imagery. Figure 8a depicts the interferogram through the earthquake and Fig. 9a the interferogram after the earthquake. Upon these images, field data were considered. In the section of results, we discuss the effects of subsidence depicted in such image composites. The pixel size of the radar images used in our research is 24 m in azimuth and 20 m in range. The DEM generated from the interferometric pair has a resolution in x, y and z of the same order of magnitude as the pixel size. The subsidence detected by differential interferometry is of the order of centimeters. Such subsidence is clearly visible in the interferogram of Fig. 8. A difference in DEM from the
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earthquake and after the earthquake does not depict the subsidence due to the relatively low resolution of the radar images that form the interferometric pair. The integration of field data Field data include detailed account of fault structures and the identification of flooding zones in the study area (Figs. 3, 5). The basic goal of the field data is to correlate spectral scene change and differential interferometry with the stress caused by the faults. The Mexican Electric Company is currently extracting geothermal water and
vapor for the sake of electricity generation. The geothermal wells are located in the study area, specifically in the zone where part of the subsidence occurred (Fig. 9b). The integration of field data with differential interferometry aims to investigate a possible correlation of subsidence with such geothermal activity. In areas around geothermal wells with intense extraction, there are terrain sinkings. The orientation and regional trends of faults and fracturing can be used to know the possible occurrence of other faults and fractures (Hitchcoc et al. 1999). The assessment of subsidence areas will be used for channel leveling. The subsidence alters the slope of terrain in local spots, and the occurrence of new earthquakes can damage channels and provoke local flooding of agricultural lands. Generation of thematic maps of the study area of scene change analysis (Figs. 3, 6), differential interferometry and field data (Fig. 8) can help local authorities to move affected people to a safe environment.
Results and discussion
Fig. 7 Block diagram of the analysis of Envisatr/Asar radar imagery for subsidence assessment
Liquefaction flooding occurred in various small communities: Ejido Durango, Estacio´n Delta, Cucapa Indigena, Cucapa Mestizo, Cucapa Mayor, Mosqueda, Chimi and in agricultural fields (Figs. 2, 3). The identified flooded areas in the field are visible in Figs. 3, 5 and 6. Water bodies have the tendency to absorb the electromagnetic radiation in wavelengths of the visible spectrum. Therefore, in a false color composite of the visible bands of the multi-spectral image, water bodies appear dark in color (Figs. 3, 6). The flooded water and its sediments smooth the surface of terrain. The physical consequence of such phenomenon is the
Fig. 8 Interferometry through the earthquake. Second interferometric pair (a). Amplification of subsidence through the earthquake. Second interferometric pair (b)
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Fig. 9 Interferometry after the earthquake. Third interferometric pair (a). Amplification of subsidence after the earthquake. Third interferometric pair (b)
smoothness of the texture relief of the terrain. Therefore, a procedure that measures the texture relief of the terrain shall be able to identify the flooded spots by liquefaction. The results of such procedure are shown in Fig. 6. The earthquake provoked regional subsidence as can be observed in Figs. 8 and 9. The affected areas are mainly located to the east of the Cucapa Range. The main feature faults are displayed as yellow lines in Fig. 2. The affected area consists of a group of crop fields, smooth hills, a few roads and some small farmer settlements. Subsidence is identified as a differential interferogram of fringes present in the interferogram through the earthquake (Fig. 8), but absent in the interferogram after the earthquake (Fig. 9). A comparison of the fringes through and after the earthquake shows that fringes are apparent through the earthquake. The fringes that experiment no change in Figs. 8 and 9 describe the slope of the terrain. Before the earthquake, the fringes depict the slope of terrain. Subsidence is clearly visible to the East of a brine pool of the Mexican Electric Company. The pool is located at the center of the Figs. 8b and 9b. In particular, such fringes are absent in the pool area after the earthquake (Fig. 9b), but visible through the earthquake (Fig. 9b). A comparison of the interferograms (Figs. 8a, 9a) shows a disruption that appears on the slope of the hill located to the west of the pool (Figs. 8b, 9b). The subsidence close to the brine pool is partially caused by the geothermal water extraction, as reported by other authors (Sarychikhina et al. 2007, 2011). The whole area has few reference spots; there are a number of buildings with rigid structures in the geothermal extraction zone. Physical identification of subsidence in the field is difficult. In two spots, vertical displacements were observed in fractures crossing a road. Measured vertical displacements correspond with those obtained by means of the
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interferometric analysis: 9.5 cm. Because of the earthquake, a great cloud of dust was produced at the Cucapa Range as a result of the intense terrain movement. Tons of fine sediments of different granulometries to those ejected by liquefaction were displaced. The hill to the left of Figs. 8b and 9b was disrupted because of such terrain movement. The interferometric pattern was clearly modified.
Conclusions There were three basic achievements in our research: the identification of spectral response of liquefaction spot by means of an RGB color composite of multi-spectral images, the measurement of texture-relief changes produced by the liquefaction using a divergence operator and the identification of subsidence employing differential interferometric techniques. The use of interferometric radar imagery in areas affected by the earthquake allows the identification of subsidence. A differentiation between subsidence induced by tectonic and subsidence of anthropogenic origin was observed. Regional faults related to the San Andres Fault and terrain movement due to earthquakes cause tectonic subsidence. Local subsidence is caused by geothermal water abstraction by the thermoelectric plant. This subsidence affects only the plant terrains where wells are located. Subsidence outside this area is a geogenic process. The intensive agriculture practices in Mexicali Valley are identified by means of RGB false color composite of multi-spectral imagery. The bands used in the false color composite show the spectral response of agriculture fields and vegetation in red. The inundated areas and superficial water are depicted in dark blue. The application of color
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composite for images before and after the earthquake permits the delimitation of liquefaction-flooded areas. The multi-spectral image before earthquake was acquired 3 months and 4 days before the event. The multi-spectral image after earthquake was acquired only 5 days after the event. The interferometric pairs used in our research were acquired across the earthquake and after the earthquake. This timely acquisition of optical and radar images allows the identification of flooded areas and subsidence caused by the earthquake. Most of the flooding area is related to liquefaction. The irrigation channels rupture also flooded part of the agricultural lands; as observed in field surveys, the flooding area affected by the channel water was very small in comparison with the area flooded by liquefaction. The more affected areas are shown in some of the obtained figures. Instead, the second figure correspond to lands recently irrigated, not flooded by the liquefaction. In addition to this, the last map shows no subsidence after the earthquake. The high evapotranspiration quickly changes the soil humidity. The liquefaction water remains for only a few days; after that, the fine sediments carried by the liquefaction water can help to identify the affected areas. This is depicted in the texture-relief image. Our results can be used to obtain a zoning of the area. Areas near faults and soil fractures as well as flooded areas can be affected again if subsidence and liquefaction occur during a future earthquake. In the more susceptible areas, channels should be avoided. Acknowledgments The authors thank Dr. Felipe Arreguin of the National Commission of Water of Mexico (CONAGUA), for the images and the facilities offered for the fieldwork. The European Space Agency (ESA), through the project C1P6926, provided the interferometric pairs.
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