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Graphical abstract Highlights • Three groundwater domes are found in the center and eastern part of the Heitai terrace. • The hydrological processes are characterized by multi-temporal 2D ERT and sensors. • Landslide deposits block the seepage and result in local groundwater level rising. • Landslide type and magnitude are affected by groundwater seepage and movement. Abstract In the Heifangtai terrace, NW China, flooding irrigation is common for the cropland production and has increased the groundwater table by 20–30 m over the past five decades. It is believed that excessive irrigation has induced a large number of loess landslides in this area. However, these loess landslides responses to hydrological changes have still not been well understood. Therefore, 43 boreholes and 51 2D Electrical resistivity tomography (ERT) profiles with a total length of 40 km have been investigated to analyze the hydrological characteristics for the whole terrace and characterize the effects of hydrological changes on the occurrence of different types of loess landslides. Our main findings are as follows: (1) Three groundwater domes are found in the center and eastern part of the Heitai terrace and the groundwater table is gradually rising in the whole terrace based on the ERT results. (2) The rising rate of groundwater table at the center of the terrace is twice greater than that at the margin of the terrace and it takes approximately 4 months for irrigation water to penetrate from the top surface to the saturated layer. (3) Landslide deposits could block drainage channels of groundwater, increase the localized hydraulic gradient and result in rising of local groundwater table at the edge of the terrace. (4) The resultant hydraulic gradient impels the groundwater from the center to seep out on the eastern and southern margins and new landslides are prone to occur in the main scarp of landslides with rising groundwater table. The type and magnitude of landslides are affected by groundwater seepage and movement. In order to fundamentally control the occurrence of landslides, effective drainage system and the restrained amount of irrigation water are needed. [ABSTRACT FROM AUTHOR]

Agricultural irrigation has increased the groundwater level in the Heitai terrace (part of the Heifangtai terrace) by 20 m over nearly five decades, which causes 3–5 landslides each year at the edge of the terrace. The Heitai terrace is of great interest in the study of loess-related landslides; but there is no unanimous agreement on the types of either the landslides in this study site or the loess-related slope failures in general. On the basis of aerial images (res. 5 cm), Digital Elevation Model (res. 10 cm), and field investigations, we analyzed the distribution and failure mode of the landslides in Heitai. The geological structure and characteristics of 69 landslides (vol. 5 × 10 3 –6 × 10 6 m 3 ) are studied. The preliminary results of groundwater recharge in the terrace and formation of the apparent spring lines on the slope surface are analyzed to better understand the failure modes. We divided the landslides in Heitai into two groups based on the location of the failure surface, i.e. loess landslide and loess-bedrock landslide, of which the development is governed by the angle between the principle direction of slope deformation and the dip of bedrock bedding. We further analyzed the failure mode of each type observed in Heitai, defined as follows: loess-bedrock planar slide, loess-bedrock irregular slide, loess flowslide, loess slide, and loess flow. The proposed types of loess-related landslide are to be incorporated in the Varnes classification (Varnes, 1978) in consideration of the engineering properties of loess, and to provide backward compatibility for Heitai and potentially other regions in the Loess Plateau of China. [ABSTRACT FROM AUTHOR]

Real-time monitoring and intelligent early warning system are crucial and significant to take mitigation measures and reduce casualties and property losses related to landslides. It is difficult to obtain entire monitoring data in the accelerated deformation phase in a landslide event, and hard to issue early warning information using a traditional monitoring approach with fixed and low sampling frequency. Displacement increments of loess landslides induced by agriculture irrigation on the Heifangtai terrace could be sudden and extremely rapid. Typical landslide types include loess flowslides and loess falls. It is of practical significance to develop a self-adaptive data acquisition monitoring technique and establish a real-time landslide early warning system (LEWS) to meet the needs for risk mitigation of rapid sliding slopes on the Heifangtai terrace. The monitoring technique can wirelessly transmit displacement data and the LEWS was devised using the new artificial intelligence. The LEWS could automatically release the warning information in advance of the event once the early warning parameters exceed default thresholds. In this study, the early warning procedures, real-time monitoring approach, intelligent LEWS, a multiple criteria warning model, warning release and emergency mitigation measures, and performance are introduced in detail. Six loess landslides at Heifangtai and eight landslides in other regions of China have been successfully warned since its implementation in 2012. This study proposed an effective and practical solution for the early warning of loess landslides at Heifangtai. Two typical loess landslides that had successful early warnings at Heifangtai were presented. The successful implementation could serve as a reference for global rapid slope failure cases, considering the complex nature of landslide behaviors and failure mechanisms. • A self-adaptive data acquisition technique was successfully developed to monitor sudden failure of loess landslides. • 3D WebGIS-based platform developed by SKLGP becomes more intelligent and accurate. • Multiple alert criteria model including deformation rate, the rate increment, and tangential angle, is established. • The LEWS with multiple alert criteria model has successfully forecasted six loess landslides since its implementation in 2017. [ABSTRACT FROM AUTHOR]

The Heifangtai terrace located in Yongjing County of Gansu Province in northwest China is characterized by a large number of landslides with frequent failure events related to agricultural irrigation activities. Thus, it is a task of great importance to identify and monitor the active loess slopes and sort out the impact factors. In this study, we employed the time series InSAR method to map the active slopes in the Heifangtai terrace with two TerraSAR-X data stacks covering the year of 2016 and two Sentinel-1 data stacks from 2016 to 2018. The detected active spots are mainly distributed along the edges of the terrace. Time series displacements derived from TerraSAR-X and Sentinel-1 observations were validated by comparisons against GPS and crack gauge measurements. Good agreement between InSAR and GPS was achieved at slow moving locations, while unwrapping errors induced by sudden accelerations make InSAR underestimate the pre-failure displacements with respect to GPS measurements. The trends of InSAR-measured displacement and crack gauge measurements also match well with correlation higher than 0.75. InSAR-measured displacements at the Jiaojia landslide group were highly correlated with the bury of groundwater record, which suggested that the rising of groundwater level may seriously decrease the stability of loess slopes. • Unstable slopes in the Heifangtai terrace are mapped with TerraSAR-X and Sentinel-1 InSAR analyses from 2016 to 2018. • InSAR results are validated by comparisons with GPS and crack gauge measurements. • Displacement patterns of typical landslides within the study area are analyzed. • Intensive irrigation on the terrace significantly affects the stability of loess slopes. [ABSTRACT FROM AUTHOR]