# Ground Deformations around the Toktogul Reservoir, Kyrgyzstan, from Envisat ASAR and Sentinel-1 Data—A Case Study about the Impact of Atmospheric Corrections on InSAR Time Series

^{1}

^{2}

^{*}

## Abstract

**:**

^{3}) from 2004–2009, whereas, for 2014–2016, the net water level increased by approximately 51 m (∼11.2 km

^{3}). The individual Small BAseline Subset (SBAS) interferograms were heavily influenced by atmospheric effects that needed to be minimized prior to the time-series analysis. We tested several approaches including corrections based on global numerical weather model data, such as the European Centre for Medium-Range Weather Forecasts (ECMWF) operational forecast data, the ERA-5 reanalysis, and the ERA-Interim reanalysis, as well as phase-based methods, such as calculating a simple linear dependency on the elevation or the more sophisticated power-law approach. Our findings suggest that, for the high-mountain Toktogul area, the power-law correction performs the best. Envisat descending time series for the period of water recession reveal mean line-of-sight (LOS) uplift rates of 7.8 mm/yr on the northern shore of the Toktogul Reservoir close to the Toktogul city area. For the same area, Sentinel-1 ascending and descending time series consistently show a subsidence behaviour due to the replenishing of the water reservoir, which includes intra-annual LOS variations on the order of 30 mm. A decomposition of the LOS deformation rates of both Sentinel-1 orbits revealed mean vertical subsidence rates of 25 mm/yr for the common time period of March 2015–November 2016, which is in very good agreement with the results derived from elastic modelling based on the TEA12 Earth model.

## 1. Introduction

^{2}, and a maximum depth of 200 m [12]. As the water level decreases, the eastern elongated part, where the Naryn River enters the lake, goes dry (Figure 2b). Toktogul is the largest artificial water reservoir in the Syr Darya Basin, with a maximum capacity of 19.5 km

^{3}[13]. Its main purposes are power generation for the Kyrgyz population in winter time and irrigation of agricultural areas located downstream in Uzbekistan and Kazakhstan in summer time [13,14]. These activities lead to a trans-boundary water policy conflict, which resulted in an exaggerated use of water in some years that could not be compensated by the incoming amount of water until the beginning of the following winter season (Figure 2).

^{3}), and a time series of Sentinel-1 data for the time period 2014–2016, in which the net water level increased by approximately 51 m (∼11.2 km

^{3}) (Figure 2). We expect that these large load changes on the ground lead to an uplift of the surrounding area in the case of water recession and to a subsidence response in the case of water replenishing.

## 2. Materials and Methods

#### 2.1. Lake Altimetry

^{2}= 0.9998), which can be used for converting all water height levels into reservoir volumes. These data can then be used to verify the accuracy of the RA-derived water heights, which is approximately ±0.3 m [24].

#### 2.2. DInSAR Processing of Envisat ASAR and Sentinel-1 Data

#### 2.3. Atmospheric Correction

#### 2.3.1. Tropospheric Delays from Numerical Weather Models

#### 2.3.2. Phase-Based Tropospheric Delays

#### 2.4. Deformation Decomposition of Sentinel-1 Data

#### 2.5. Modelling of Elastic Surface Deformations

## 3. Results

#### 3.1. Atmospheric Corrections

#### 3.2. Ground Deformation

^{2}= 0.85) and S1d (R

^{2}= 0.88) time series compared to the S1a (R

^{2}= 0.62) time series. From the Sentinel-1 data, it is clear that intra-annual LOS deformation changes appear simultaneously with the water level changes, which indicates an elastic response of the surface. At location P1, these intra-annual LOS deformation variations are on the order of 30 mm and more.

^{2}= 0.52), −10.4 mm/yr (R

^{2}= 0.51), and −9.7 mm/yr (R

^{2}= 0.54) for Envisat, S1d and S1a, respectively, which convert to 0.38 mm, −0.43 mm and −0.54 mm per 1 m water level change.

^{2}) are consistently below 0.2.

^{2}= 0.47) during the water recession phase captured by Envisat data and mean LOS uplift rates of 6.9 mm/yr (0.29 mm per 1 m water level change and R

^{2}= 0.67) in the S1d time series that cover a water replenishing phase. Compared to S1d, S1a LOS deformation is less explicit and also only yields a low water level fit correlation value of R

^{2}= 0.1.

## 4. Discussion

#### 4.1. Atmospheric Corrections

#### 4.2. Ground Deformation

^{2}is also high in the Envisat case, intra-annual variations are less obvious due to the much lower temporal sampling. The area in the west (P2), close to the Talas-Fergana Fault, is also prone to the same intra-annual deformation, but at lower rates. Here, the slopes of the high mountains are much steeper than at P1 and even reach the shoreline (Figure 9b).

## 5. Conclusions

## Acknowledgments

## Author Contributions

## Conflicts of Interest

## References

- Simpson, D.W.; Leith, W.; Scholz, C. Two types of reservoir-induced seismicity. Bull. Seismol. Soc. Am.
**1988**, 78, 2025–2040. [Google Scholar] - Kaufmann, G.; Amelung, F. Reservoir-induced deformation and continental rheology in vicinity of Lake Mead, Nevada. J. Geophys. Res.-Solid Earth
**2000**, 105, 16341–16358. [Google Scholar] [CrossRef] - Bevis, M.; Kendrick, E.; Cser, A.; Smalley, R. Geodetic measurement of the local elastic response to the changing mass of water in Lago Laja, Chile. Phys. Earth Planet. Inter.
**2004**, 141, 71–78. [Google Scholar] [CrossRef] - Wahr, J.; Khan, S.A.; van Dam, T.; Liu, L.; van Angelen, J.H.; van den Broeke, M.R.; Meertens, C.M. The use of GPS horizontals for loading studies, with applications to northern California and southeast Greenland. J. Geophys. Res.-Solid Earth
**2013**, 118, 1795–1806. [Google Scholar] [CrossRef] - Cavalié, O.; Doin, M.P.; Lasserre, C.; Briole, P. Ground motion measurement in the Lake Mead area, Nevada, by differential synthetic aperture radar interferometry time series analysis: Probing the lithosphere rheological structure. J. Geophys. Res.
**2007**, 112, B03403. [Google Scholar] [CrossRef] - Nof, R.N.; Ziv, A.; Doin, M.P.; Baer, G.; Fialko, Y.; Wdowinski, S.; Eyal, Y.; Bock, Y. Rising of the lowest place on Earth due to Dead Sea water-level drop: Evidence from SAR interferometry and GPS. J. Geophys. Res.-Solid Earth
**2012**, 117, B05412. [Google Scholar] [CrossRef] - Zhao, W.; Amelung, F.; Doin, M.P.; Dixon, T.H.; Wdowinski, S.; Lin, G. InSAR observations of lake loading at Yangzhuoyong Lake, Tibet: Constraints on crustal elasticity. Earth Planet. Sci. Lett.
**2016**, 449, 240–245. [Google Scholar] [CrossRef] - Furuya, M.; Wahr, J.M. Water level changes at an ice-dammed lake in west Greenland inferred from InSAR data. Geophys. Res. Lett.
**2005**, 32, L14501. [Google Scholar] [CrossRef] - Doin, M.P.; Twardzik, C.; Ducret, G.; Lasserre, C.; Guillaso, S.; Jianbao, S. InSAR measurement of the deformation around Siling Co Lake: Inferences on the lower crust viscosity in central Tibet. J. Geophys. Res.-Solid Earth
**2015**, 120, 5290–5310. [Google Scholar] [CrossRef] - Gahalaut, V.; Yadav, R.K.; Sreejith, K.M.; Gahalaut, K.; Bürgmann, R.; Agrawal, R.; Sati, S.; Kumar, A. InSAR and GPS measurements of crustal deformation due to seasonal loading of Tehri reservoir in Garhwal Himalaya, India. Geophys. J. Int.
**2017**, 209, 425–433. [Google Scholar] [CrossRef] - Simpson, D.W.; Hamburger, M.W.; Pavlov, V.D.; Nersesov, I.L. Tectonics and seismicity of the Toktogul Reservoir Region, Kirgizia, USSR. J. Geophys. Res.
**1981**, 86, 345–358. [Google Scholar] [CrossRef] - Tibaldi, A.; Corazzato, C.; Rust, D.; Bonali, F.; Pasquarè Mariotto, F.; Korzhenkov, A.; Oppizzi, P.; Bonzanigo, L. Tectonic and gravity-induced deformation along the active Talas–Fergana Fault, Tien Shan, Kyrgyzstan. Tectonophysics
**2015**, 657, 38–62. [Google Scholar] [CrossRef] [Green Version] - Savoskul, O.; Chevnina, E.; Perziger, F.; Vasilina, L.; Baburin, V.; Danshin, A.I.; Matyakubov, B.; Murakaev, R. Water, climate, food, and environment in the Syr Darya Basin. In Contribution to the Project ADAPT; Savoskul, O.S., Ed.; The Pennsylvania State University: State College, PA, USA, 2003. [Google Scholar]
- Keith, J.E.; McKinney, D.C. Options Analysis of the Operation of the Toktogul Reservoir. Available online: http://www.ce.utexas.edu/prof/mckinney/papers/aral/Issue7.html (accessed on 15 December 2017).
- Kyrgyzstan Disaster Risk Data Platform. Available online: http://geonode.mes.kg (accessed on 10 March 2017).
- Ghose, S.; Mellors, R.J.; Korjenkov, A.M.; Hamburger, M.W.; Pavlis, T.L.; Pavlis, G.L.; Omuraliev, M.; Mamyrov, E.; Muraliev, A.R. The M
_{S}= 7.3 1992 Suusamyr, Kyrgyzstan, Earthquake in the Tien Shan: 2. Aftershock Focal Mechanisms and Surface Deformation. Bull. Seismol. Soc. Am.**1997**, 87, 23–38. [Google Scholar] - Dovgan, V. Seismometric Monitoring of Toktogul Hydroelectric Power Station. In Proceedings of the IV International Conference “Problems of Cybernetics and Informatics” (PCI’2012), Baku, Azerbaijan, 12–14 September 2012; pp. 81–84. [Google Scholar]
- Zebker, H.A.; Rosen, P.A.; Hensley, S. Atmospheric effects in interferometric synthetic aperture radar surface deformation and topographic maps. J. Geophys. Res.-Solid Earth
**1997**, 102, 7547–7563. [Google Scholar] [CrossRef] - Fialko, Y. Interseismic strain accumulation and the earthquake potential on the southern San Andreas fault system. Nature
**2006**, 441, 968–971. [Google Scholar] [CrossRef] [PubMed] - Puysségur, B.; Michel, R.; Avouac, J.P. Tropospheric phase delay in interferometric synthetic aperture radar estimated from meteorological model and multispectral imagery. J. Geophys. Res.
**2007**, 112, B05419. [Google Scholar] [CrossRef] - Bekaert, D.P.S.; Hooper, A.; Wright, T.J. A spatially variable power law tropospheric correction technique for InSAR data. J. Geophys. Res.-Solid Earth
**2015**, 120, 1345–1356. [Google Scholar] [CrossRef] - Birkett, C.M. Radar altimetry: A new concept in monitoring lake level changes. Eos Trans. Am. Geophys. Union
**1994**, 75, 273–275. [Google Scholar] [CrossRef] - Crétaux, J.F.; Abarca-del Río, R.; Bergé-Nguyen, M.; Arsen, A.; Drolon, V.; Clos, G.; Maisongrande, P. Lake Volume Monitoring from Space. Surv. Geophys.
**2016**, 37, 269–305. [Google Scholar] [CrossRef] - Schöne, T.; Dusik, E.; Illigner, J.; Klein, I. Water in Central Asia: Reservoir Monitoring with Radar Altimetry Along the Naryn and Syr Darya Rivers. In Proceedings of the International Symposium on Earth and Environmental Sciences for Future Generations, Prague, Czech Republic, 22 June–2 July 2015; Springer: Cham, Switzerland, 2017; Volume 147, pp. 349–357. [Google Scholar]
- CA WATER Info. Available online: www.cawater-info.net (accessed on 31 January 2017).
- JSC “Electric Stations”. Available online: www.energo-es.kg (accessed on 31 January 2017).
- Förste, C.; Bruinsma, S.; Abrykosov, O.; Flechtner, F.; Dahle, C.; Neumayer, K.H.; Barthelmes, F.; König, R.; Marty, J.-C.; Lemoine, J.M.; et al. EIGEN-6C3—The newest high resolution global combined gravity field model based on the 4th release of the GOCE Direct Approach. In Proceedings of the 2013 IAG Scientific Assembly, 150th Anniversary of the IAG, Potsdam, Germany, 1–6 September 2013. [Google Scholar]
- Werner, C.L.; Wegmüller, U.; Strozzi, T.; Wiesmann, A. GAMMA SAR and Interferometric Processing Software. In Proceedings of the ERS-ENVISAT Symposium, Gothenburg, Sweden, 16–20 October 2000. [Google Scholar]
- Prats, P.; Marotti, L.; Wollstadt, S.; Scheiber, R. Investigations on TOPS interferometry with TerraSAR-X. In Proceedings of the 2010 IEEE International Geoscience and Remote Sensing Symposium (IGARSS), Honolulu, Hawaii, 25–30 July 2010; pp. 2629–2632. [Google Scholar] [CrossRef]
- Prats-Iraola, P.; Scheiber, R.; Marotti, L.; Wollstadt, S.; Reigber, A. TOPS Interferometry With TerraSAR-X. IEEE Trans. Geosci. Remote Sens.
**2012**, 50, 3179–3188. [Google Scholar] [CrossRef] [Green Version] - Scheiber, R.; Moreira, A. Coregistration of interferometric SAR images using spectral diversity. IEEE Trans. Geosci. Remote Sens.
**2000**, 38, 2179–2191. [Google Scholar] [CrossRef] - Wegmüller, U.; Werner, C.; Strozzi, T.; Wiesmann, A.; Frey, O.; Santoro, M. Sentinel-1 IWS mode support in the GAMMA software. Procedia Comput. Sci.
**2016**, 100, 431–436. [Google Scholar] [CrossRef] - Berardino, P.; Fornaro, G.; Lanari, R.; Sansosti, E. A new algorithm for surface deformation monitoring based on small baseline differential SAR interferograms. IEEE T. Geosci. Remote
**2002**, 40, 2375–2383. [Google Scholar] [CrossRef] - Hooper, A.J.; Bekaert, D.; Spaans, K.; Arıkan, M. Recent advances in SAR interferometry time series analysis for measuring crustal deformation. Tectonophysics
**2012**, 514–517, 1–13. [Google Scholar] [CrossRef] - Hooper, A. A multi-temporal InSAR method incorporating both persistent scatterer and small baseline approaches. Geophys. Res. Lett.
**2008**, 35, L16302. [Google Scholar] [CrossRef] - Hooper, A.J.; Zebker, H.A. Phase unwrapping in three dimensions with application to InSAR time series. J. Opt. Soc. Am.
**2007**, 24, 2737–2747. [Google Scholar] [CrossRef] - Marinković, P.; Larsen, Y. On Resolving the Local Oscillator Drift Induced Phase Ramps in ASAR and ERS1/2 Interferometric Data—The Final Solution. In Proceedings of the Fringe 2015 workshop (ESA SP-731), Frascati, Italy, 23–27 March 2015. [Google Scholar]
- Bekaert, D.; Walters, R.; Wright, T.; Hooper, A.; Parker, D. Statistical comparison of InSAR tropospheric correction techniques. Remote Sens. Environ.
**2015**, 170, 40–47. [Google Scholar] [CrossRef] - Doin, M.P.; Lasserre, C.; Peltzer, G.; Cavalié, O.; Doubre, C. Corrections of stratified tropospheric delays in SAR interferometry: Validation with global atmospheric models. J. Appl. Geophys.
**2009**, 69, 35–50. [Google Scholar] [CrossRef] - Jolivet, R.; Agram, P.S.; Lin, N.Y.; Simons, M.; Doin, M.P.; Peltzer, G.; Li, Z. Improving InSAR geodesy using Global Atmospheric Models. J. Geophys. Res.-Solid Earth
**2014**, 119, 2324–2341. [Google Scholar] [CrossRef] - Barnhart, W.D.; Lohman, R.B. Characterizing and estimating noise in InSAR and InSAR time series with MODIS. Geochem. Geophys.
**2013**, 14, 4121–4132. [Google Scholar] [CrossRef] - Jolivet, R.; Grandin, R.; Lasserre, C.; Doin, M.P.; Peltzer, G. Systematic InSAR tropospheric phase delay corrections from global meteorological reanalysis data. Geophys. Res. Lett.
**2011**, 38, L17311. [Google Scholar] [CrossRef] - Dee, D.P.; Uppala, S.M.; Simmons, A.J.; Berrisford, P.; Poli, P.; Kobayashi, S.; Andrae, U.; Balmaseda, M.A.; Balsamo, G.; Bauer, P.; et al. The ERA-Interim reanalysis: Configuration and performance of the data assimilation system. Q. J. R. Meteorol. Soc.
**2011**, 137, 553–597. [Google Scholar] [CrossRef] - Fialko, Y.; Simons, M.; Agnew, D. The complete (3-D) surface displacement field in the epicentral area of the 1999 M W 7.1 Hector Mine Earthquake, California, from space geodetic observations. Geophys. Res. Lett.
**2001**, 28, 3063–3066. [Google Scholar] [CrossRef] - Motagh, M.; Shamshiri, R.; Haghshenas Haghighi, M.; Wetzel, H.U.; Akbari, B.; Nahavandchi, H.; Roessner, S.; Arabi, S. Quantifying groundwater exploitation induced subsidence in the Rafsanjan plain, southeastern Iran, using InSAR time-series and in situ measurements. Eng. Geol.
**2017**, 218, 134–151. [Google Scholar] [CrossRef] - Farrell, W.E. Deformation of the Earth by surface loads. Rev. Geophys.
**1972**, 10, 761–797. [Google Scholar] [CrossRef] - Dill, R.; Klemann, V.; Martinec, Z.; Tesauro, M. Applying local Green’s functions to study the influence of the crustal structure on hydrological loading displacements. J. Geodyn.
**2015**, 88, 14–22. [Google Scholar] [CrossRef] - Dziewonski, A.M.; Anderson, D.L. Preliminary reference Earth model. Phys. Earth Planet. Inter.
**1981**, 25, 297–356. [Google Scholar] [CrossRef] - Tesauro, M.; Audet, P.; Kaban, M.K.; Bürgmann, R.; Cloetingh, S. The effective elastic thickness of the continental lithosphere: Comparison between rheological and inverse approaches. Geochem. Geophys. Geosys.
**2012**, 13, Q09001. [Google Scholar] [CrossRef] - Haiden, T.; Janousek, M.; Bauer, P.; Bidlot, J.; Dahoui, M.; Ferranti, L.; Prates, F.; Richardson, D.; Vitart, F. Evaluation of ECMWF forecasts, including 2014–2015 upgrades. In ECMWF Technical Memoranda; European Centre for Medium-Range Weather Forecasts: Reading, UK, 2015; Volume 765, pp. 1–51. [Google Scholar]
- Havenith, H.B.; Torgoev, I.; Torgoev, A.; Strom, A.; Xu, Y.; Fernandez-Steeger, T. The Kambarata 2 blast-fill dam, Kyrgyz Republic: Blast event, geophysical monitoring and dam structure modelling. Geoenviron. Disasters
**2015**, 2, 11. [Google Scholar] [CrossRef] - Abdrakhmatov, K.; Havenith, H.B.; Delvaux, D.; Jongmans, D.; Trefois, P. Probabilistic PGA and Arias Intensity maps of Kyrgyzstan (Central Asia). J. Seismol.
**2003**, 7, 203–220. [Google Scholar] [CrossRef] - Bindi, D.; Abdrakhmatov, K.; Parolai, S.; Mucciarelli, M.; Grünthal, G.; Ischuk, A.; Mikhailova, N.; Zschau, J. Seismic hazard assessment in Central Asia: Outcomes from a site approach. Soil Dyn. Earthq. Eng.
**2012**, 37, 84–91. [Google Scholar] [CrossRef]

**Figure 1.**Location of the Toktogul Reservoir, city and dam with the outlines of the cut SAR data frames that are used for the final analysis. The alignment of the Talas-Fergana Fault is based on vector data from the Kyrgyzstan Disaster Risk Data Platform [15]. The dashed outline denotes the estimated area of the main deformation. The inset shows the location of the area within Kyrgyzstan.

**Figure 2.**(

**a**) Toktogul water level change between 2002 and 2016 obtained from satellite radar altimetry. Red, purple and green highlighted periods correspond to Envisat and Sentinel-1 ascending (S1a) and Sentinel-1 descending (S1d) acquisition times, respectively. The corresponding regression lines denote the average water increase per year for each of the three SAR time series (note that differences between S1a and S1d are due to different covered time periods). The red asterisks correspond to the reservoir extents at low and high water levels, which are shown by Landsat-8 images from (

**b**) 11.04.2015 and (

**c**) 07.11.2016, respectively.

**Figure 3.**Small BAseline Subset (SBAS) networks after offending interferograms are removed for (

**a**) Envisat descending; (

**b**) Sentinel-1 descending and (

**c**) Sentinel-1 ascending time series. Red dots denote the time of the image acquisitions, and black lines show the interferograms.

**Figure 4.**Mean line-of-sight (LOS) deformation values for various atmospheric corrections of the (

**1**) Envisat descending; (

**2**) Sentinel-1 descending and (

**3**) Sentinel-1 ascending time series. (

**a**) no atmospheric correction applied; (

**b**) best results of the power-law technique; (

**c**) linear dependency on the topography; (

**d**) correction with the operational weather model (opECMWF) analysis; (

**e**) ERA-I weather model correction; (

**f**) the ERA-5 1 h temporal resolution solution and (

**g**) the ERA-5 6 h temporal resolution solution. The black asterisks show the location of the reference point.

**Figure 5.**Variances of the LOS deformation in time for all applied atmospheric corrections. The location of the exemplary point P1 is shown in Figure 6. For better visualization, deformation markers have been connected with lines, although this does not imply that we expect linear deformation in between.

**Figure 6.**Power-law-corrected mean LOS deformation maps for (

**a**) Envisat; (

**b**) S1d and (

**c**) S1a SAR time series. Points 1-4 show the locations of the deformation time series shown in Figure 7, and the black asterisk denotes the reference point used in the time series. The red triangle area in the southeast corner of the S1d time series shows an unwrapping artifact that we did not correct for.

**Figure 7.**(

**a**) Envisat; (

**b**) S1d and (

**c**) S1a power-law-corrected LOS deformation in time (black triangles) for points 1-4 as in Figure 6. The red lines indicate the annual mean LOS deformation for the investigated time period. The blue lines in the bottom diagrams show the true Toktogul water level change, whereas the blue lines in the point figures represent the best fit of this water level to the shown deformation.

**Figure 8.**(

**a**) vertical and (

**b**) horizontal (east/west) components of the decomposed Sentinel-1 ascending and descending LOS deformations for the time period March 2015–November 2016. Input data for the decomposition are the power-law-corrected mean LOS deformation maps; (

**c**) vertical deformation from elastic modelling with the TEA12 Earth model; and (

**d**) residuals from Sentinel-1 minus modelled vertical deformation. Negative values in the vertical case refer to subsidence, and blue values refer to uplift. In the horizontal case, positive values denote a motion towards the east, and negative values denote a motion towards the west. The black asterisk shows the location of the reference point. Measured and modelled vertical deformation rates for profiles $\overline{A{A}^{\prime}}$ and $\overline{B{B}^{\prime}}$ are given in (

**e**,

**f**), respectively.

**Figure 9.**Vertical deformation extracted from Sentinel-1 decomposition around (

**a**) point P1 and the Toktogul city area; (

**b**) point P2; (

**c**) alluvial fans at point P3 and (

**d**) the Naryn River entrance area at point P4. For the locations of the points (refer to Figure 6). Background imagery provided by Google

^{®}Earth.

**Table 1.**SAR data specifications and summary of the amount of images used in the final networks. The covered time period that could be reliably unwrapped is as follows for the individual time series: Envisat: 24.10.2004–05.07.2009, Sentinel-1, descending (desc.): 23.03.2015–12.11.2016, ascending (asc.): 24.10.2014–18.11.2016.

Satellite | Orbit | Path | Acquisition Time (UTC) | Mean Angle of Incidence | Heading Angle | Amount of Scenes | Amount of Interferograms |
---|---|---|---|---|---|---|---|

Envisat | desc. | 277 | 05:23 | 23.4° | −167.8° | 22 | 53 |

Sentinel 1 | desc. | 5 | 01:13 | 39.7° | −170.1° | 20 | 49 |

Sentinel 1 | asc. | 100 | 13:06 | 43.3° | 9.4° | 28 | 96 |

Model | Spatial Resolution | Temporal Resolution | Pressure Levels |
---|---|---|---|

opECMWF | 0.1° | 6 h | 25 |

ERA5 1 h | 0.1° | 1 h | 37 |

ERA5 6 h | 0.1° | 6 h | 37 |

ERA-I | 0.75° | 6 h | 37 |

**Table 3.**Root mean square errors for different power-law filtering bands. The best results are highlighted in bold. The area of main deformation (cf. Figure 1) is excluded from this estimation.

Band [km]: | 2–4 | 2–8 | 2–16 | 4–8 | 4–16 | 4–32 | 8–16 | 8–32 | 8–64 | 16–32 | 16–64 | 32–64 | 32–128 | 64–128 |
---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|

Envisat RMSE [mm]: | 8.5 | 8.2 | 8.1 | 8.3 | 8.1 | 8.2 | 8.2 | 8.1 | 8.0 | 9.0 | 8.1 | 8.2 | 8.2 | 9.3 |

S1d RMSE [mm]: | 7.1 | 7.3 | 7.3 | 7.2 | 7.2 | 7.0 | 7.5 | 7.1 | 7.0 | 7.5 | 7.3 | 7.6 | 7.2 | 7.6 |

S1a RMSE [mm]: | 10.7 | 10.6 | 10.8 | 10.6 | 10.8 | 10.8 | 10.9 | 10.9 | 11.1 | 11.1 | 11.2 | 11.4 | 11.2 | 11.6 |

**Table 4.**Root mean square errors for different atmospheric correction techniques. ERA-5 data cover only the Sentinel-1 acquisition period and thus cannot be used for improving the Envisat time series. The best results are highlighted in bold. The area of main deformation (cf. Figure 1) is excluded from this estimation.

Atmospheric Correction: | None | Best Power-Law | Linear | opECMWF | ERA-I | ERA-5 1 h | ERA-5 6 h |
---|---|---|---|---|---|---|---|

Envisat RMSE [mm]: | 8.8 | 8.0 | 8.0 | 13.1 | 11.5 | - | - |

S1d RMSE [mm]: | 9.9 | 7.0 | 7.5 | 10.1 | 10.7 | 12.0 | 11.3 |

S1a RMSE [mm]: | 12.6 | 10.6 | 11.0 | 12.9 | 13.4 | 13.8 | 14.0 |

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/).

## Share and Cite

**MDPI and ACS Style**

Neelmeijer, J.; Schöne, T.; Dill, R.; Klemann, V.; Motagh, M.
Ground Deformations around the Toktogul Reservoir, Kyrgyzstan, from Envisat ASAR and Sentinel-1 Data—A Case Study about the Impact of Atmospheric Corrections on InSAR Time Series. *Remote Sens.* **2018**, *10*, 462.
https://doi.org/10.3390/rs10030462

**AMA Style**

Neelmeijer J, Schöne T, Dill R, Klemann V, Motagh M.
Ground Deformations around the Toktogul Reservoir, Kyrgyzstan, from Envisat ASAR and Sentinel-1 Data—A Case Study about the Impact of Atmospheric Corrections on InSAR Time Series. *Remote Sensing*. 2018; 10(3):462.
https://doi.org/10.3390/rs10030462

**Chicago/Turabian Style**

Neelmeijer, Julia, Tilo Schöne, Robert Dill, Volker Klemann, and Mahdi Motagh.
2018. "Ground Deformations around the Toktogul Reservoir, Kyrgyzstan, from Envisat ASAR and Sentinel-1 Data—A Case Study about the Impact of Atmospheric Corrections on InSAR Time Series" *Remote Sensing* 10, no. 3: 462.
https://doi.org/10.3390/rs10030462