Using satellite rainfall products to assess the triggering conditions for hydro-morphological processes in different geomorphological settings in China

Abstract Hydro-morphological processes (HMP, i.e. all processes contained within the spectrum defined between debris flows and flash floods) initiate in response to intense rainfall events. Efficient HMP hazard assessment over large regions is often hindered because of limited rainfall observations over mountainous areas. Real-time and easily accessible satellite rainfall products offer new opportunities to address the observational coverage problem in ungauged catchments. In this work, two satellite rainfall products, Global Precipitation Measurement (GPM) and Climate Hazards Group Infrared Precipitation with Station Data (CHIRPS), are investigated by taking the ground measurements as a reference. Based on a close agreement between GPM and rain gauge data, daily rainfall together with a series of antecedent rainfall values were calculated to investigate the spatio-temporal distribution of HMP occurred from 2001 to 2015 across the whole Chinese territory. Ultimately, rainfall thresholds for HMP initiation within different geomorphological settings in China were obtained by: (1) building antecedent rainfall sequences consisting of HMP and non-HMP via 100 nonparametric bootstrapped replicates; (2) testing several percentiles of the rainfall distribution as thresholds for HMP occurrence; (3) optimizing rainfall thresholds for six geomorphological macro-regions in China. This study confirmed the ability of satellite data in defining the rainfall conditions for the triggering of HMP, acknowledging the potential underestimation and/or bias that characterize any satellite rainfall products. Our findings provides new insight on rainfall conditions responsible for HMP initiation at the Chinese national scale.

[1]  Yang Hong,et al.  Have satellite precipitation products improved over last two decades? A comprehensive comparison of GPM IMERG with nine satellite and reanalysis datasets , 2020 .

[2]  Y. Hong,et al.  The TRMM Multisatellite Precipitation Analysis (TMPA): Quasi-Global, Multiyear, Combined-Sensor Precipitation Estimates at Fine Scales , 2007 .

[3]  Quan J. Wang,et al.  A review of advances in flash flood forecasting , 2011 .

[4]  Boleslo E. Romero,et al.  A quasi-global precipitation time series for drought monitoring , 2014 .

[5]  Dong-Jun Seo,et al.  An Intercomparison Study of NEXRAD Precipitation Estimates , 1996 .

[6]  W. Briggs.  Statistical Methods in the Atmospheric Sciences , 2007 .

[7]  D. Kirschbaum,et al.  Satellite‐Based Assessment of Rainfall‐Triggered Landslide Hazard for Situational Awareness , 2018, Earth's future.

[8]  Jian Zhou,et al.  Comprehensive evaluation of latest GPM era IMERG and GSMaP precipitation products over mainland China , 2020 .

[9]  D. Stephenson.  Use of the “Odds Ratio” for Diagnosing Forecast Skill , 2000 .

[10]  M. Rossi,et al.  Comparison of Satellite Rainfall Estimates and Rain Gauge Measurements in Italy, and Impact on Landslide Modeling , 2017 .

[11]  R. Scofield,et al.  Status and Outlook of Operational Satellite Precipitation Algorithms for Extreme-Precipitation Events , 2003 .

[12]  D. Easterling,et al.  Changes in climate extremes and their impacts on the natural physical environment , 2012 .

[13]  L. Brocca,et al.  How far are we from the use of satellite rainfall products in landslide forecasting? , 2018, Remote Sensing of Environment.

[14]  Sandeep Kumar,et al.  PMT: New analytical framework for automated evaluation of geo-environmental modelling approaches. , 2019, The Science of the total environment.

[15]  A. Badoux,et al.  Rainfall intensity–duration thresholds for bedload transport initiation in small Alpine watersheds , 2012 .

[16]  S. L. Gariano,et al.  How much does the rainfall temporal resolution affect rainfall thresholds for landslide triggering? , 2019, Natural Hazards.

[17]  Victor G. Jetten,et al.  Integration of two-phase solid fluid equations in a catchment model for flashfloods, debris flows and shallow slope failures , 2018, Environ. Model. Softw..

[18]  Dalia Kirschbaum,et al.  A dynamic landslide hazard assessment system for Central America and Hispaniola , 2015 .

[19]  Max Tegmark,et al.  Pareto-Optimal Data Compression for Binary Classification Tasks , 2020, Entropy.

[20]  Gottfried Kirchengast,et al.  Evaluation of GPM IMERG Early, Late, and Final rainfall estimates using WegenerNet gauge data in southeastern Austria , 2017 .

[21]  M. Borga,et al.  Estimation of debris flow triggering rainfall: Influence of rain gauge density and interpolation methods , 2015 .

[22]  David W. Hosmer,et al.  Applied Logistic Regression , 1991 .

[23]  F. Guzzetti,et al.  Space-time landslide predictive modelling , 2020 .

[24]  Olga Mavrouli,et al.  Satellite-derived rainfall thresholds for landslide early warning in Bogowonto Catchment, Central Java, Indonesia , 2020, Int. J. Appl. Earth Obs. Geoinformation.

[25]  Tom Fawcett,et al.  An introduction to ROC analysis , 2006, Pattern Recognit. Lett..

[26]  O. Dewitte,et al.  Towards a Transferable Antecedent Rainfall—Susceptibility Threshold Approach for Landsliding , 2019, Water.

[27]  Viviana Maggioni,et al.  Assessment of Level-3 Gridded Global Precipitation Mission (GPM) Products Over Oceans , 2019, Remote. Sens..

[28]  M. Jakob,et al.  Hydrogeomorphic response to extreme rainfall in headwater systems: Flash floods and debris flows , 2014 .

[29]  P. Martin Mai,et al.  Presenting logistic regression-based landslide susceptibility results , 2018, Engineering Geology.

[30]  Marco Borga,et al.  Radar hydrology modifies the monitoring of flash‐flood hazard , 2003 .

[31]  J. Salas,et al.  Revisiting the Concepts of Return Period and Risk for Nonstationary Hydrologic Extreme Events , 2014 .

[32]  Dawen Yang,et al.  Establishing a rainfall threshold for flash flood warnings in China’s mountainous areas based on a distributed hydrological model , 2016 .

[33]  Yang Hong,et al.  Can Near-Real-Time Satellite Precipitation Products Capture Rainstorms and Guide Flood Warning for the 2016 Summer in South China? , 2017, IEEE Geoscience and Remote Sensing Letters.

[34]  Chengguang Lai,et al.  Evaluation of the GPM IMERG satellite-based precipitation products and the hydrological utility , 2017 .

[35]  H. Lü,et al.  The Assessment and Comparison of TMPA and IMERG Products Over the Major Basins of Mainland China , 2019, Earth and Space Science.

[36]  Yang Hong,et al.  Assessing the potential of satellite-based precipitation estimates for flood frequency analysis in ungauged or poorly gauged tributaries of China's Yangtze River basin , 2017 .

[37]  J. Janowiak,et al.  The Global Precipitation Climatology Project (GPCP) combined precipitation dataset , 1997 .

[38]  P. Taylor,et al.  The spatial distribution of rainfall extremes and the influence of El Nino Southern Oscillation , 2017 .

[39]  Misako Kachi,et al.  Global Precipitation Map Using Satellite-Borne Microwave Radiometers by the GSMaP Project: Production and Validation , 2006, IEEE Transactions on Geoscience and Remote Sensing.

[40]  Changjiang Li,et al.  An effective antecedent precipitation model derived from the power-law relationship between landslide occurrence and rainfall level , 2014 .

[41]  I. Jolliffe,et al.  Forecast verification : a practitioner's guide in atmospheric science , 2011 .

[42]  S. Sorooshian,et al.  Evaluation of PERSIANN system satellite-based estimates of tropical rainfall , 2000 .

[43]  L. Lombardo,et al.  Accounting for covariate distributions in slope-unit-based landslide susceptibility models. A case study in the alpine environment , 2019, Engineering Geology.

[44]  Thomas Glade,et al.  Applying Probability Determination to Refine Landslide-triggering Rainfall Thresholds Using an Empirical “Antecedent Daily Rainfall Model” , 2000 .

[45]  A. Hou,et al.  The Global Precipitation Measurement Mission , 2014 .

[46]  Yang Hong,et al.  Flood and landslide applications of near real-time satellite rainfall products , 2007 .

[47]  F. Wei,et al.  Determination of effective antecedent rainfall for debris flow forecast based on soil moisture content observation in Jiangjia Gully, China , 2008 .

[48]  J. Janowiak,et al.  CMORPH: A Method that Produces Global Precipitation Estimates from Passive Microwave and Infrared Data at High Spatial and Temporal Resolution , 2004 .

[49]  Warren. Viessman.  Introduction to hydrology , 1972 .

[50]  Diogo Olivetti,et al.  Seasonal Effect on Spatial and Temporal Consistency of the New GPM-Based IMERG-v5 and GSMaP-v7 Satellite Precipitation Estimates in Brazil’s Central Plateau Region , 2019, Water.

[51]  Chenghu Zhou,et al.  Geomorphological regionalization theory system and division methodology of China , 2020, Journal of Geographical Sciences.

[52]  Aiwen Lin,et al.  Evaluation of the TRMM 3B42 and GPM IMERG products for extreme precipitation analysis over China , 2019, Atmospheric Research.

[53]  E. Freitas,et al.  An improved rainfall-threshold approach for robust prediction and warning of flood and flash flood hazards , 2020, Natural Hazards.

[54]  Kuolin Hsu,et al.  Assessing the Efficacy of High-Resolution Satellite-Based PERSIANN-CDR Precipitation Product in Simulating Streamflow , 2016 .

[55]  Development of a new rainfall‐triggering index of flash flood warning‐case study in Yunnan province, China , 2020, Journal of Flood Risk Management.

[56]  Jing Wu,et al.  Accuracy of CHIRPS Satellite-Rainfall Products over Mainland China , 2018, Remote. Sens..

[57]  Fei Yuan,et al.  Applications of TRMM- and GPM-Era Multiple-Satellite Precipitation Products for Flood Simulations at Sub-Daily Scales in a Sparsely Gauged Watershed in Myanmar , 2019, Remote. Sens..

[58]  Liguang Jiang,et al.  How do GPM IMERG precipitation estimates perform as hydrological model forcing? Evaluation for 300 catchments across Mainland China , 2019, Journal of Hydrology.

[59]  Shuangshuang He,et al.  Rainfall Event–Duration Thresholds for Landslide Occurrences in China , 2020 .

[60]  Martin Schlather,et al.  Models for Stationary Max-Stable Random Fields , 2002 .

[61]  Lorenzo Marchi,et al.  Impact of uncertainty in rainfall estimation on the identification of rainfall thresholds for debris flow occurrence , 2014 .

[62]  S. Sorooshian,et al.  Effective and efficient algorithm for multiobjective optimization of hydrologic models , 2003 .

[63]  Pengfei Jia,et al.  Application of the GPM-IMERG Products in Flash Flood Warning: A Case Study in Yunnan, China , 2020, Remote. Sens..

[64]  I. Nistor,et al.  Climate change impacts on extreme floods I: combining imperfect deterministic simulations and non-stationary frequency analysis , 2012, Natural Hazards.

[65]  M. Borga,et al.  Flash flood warning based on rainfall thresholds and soil moisture conditions: An assessment for gauged and ungauged basins , 2008 .

[66]  An assessment of global satellite‐based precipitation datasets in capturing precipitation extremes: A comparison with observed precipitation dataset in India , 2019, International Journal of Climatology.

[67]  M. Borga,et al.  Satellite Rainfall Estimates For Debris Flow Prediction: An Evaluation Based On Rainfall Accumulation–Duration Thresholds , 2017 .

[68]  Hendrik Boogaard,et al.  Evaluation of Satellite Rainfall Estimates for Drought and Flood Monitoring in Mozambique , 2015, Remote. Sens..

[69]  Y. Hong,et al.  Recent global performance of the Climate Hazards group Infrared Precipitation (CHIRP) with Stations (CHIRPS) , 2020 .

[70]  Zhenshan Yang,et al.  Spatiotemporal evolution and driving factors of China’s flash flood disasters since 1949 , 2018, Science China Earth Sciences.

[71]  Zhe Li,et al.  Incorporation of Satellite Precipitation Uncertainty in a Landslide Hazard Nowcasting System. , 2020, Journal of hydrometeorology.

[72]  Zheng Duan,et al.  Assessment of GPM and TRMM Precipitation Products over Singapore , 2017, Remote. Sens..

[73]  Matjaž Mikoš,et al.  Copula-based IDF curves and empirical rainfall thresholds for flash floods and rainfall-induced landslides , 2016 .

[74]  G. Huffman,et al.  Integrated Multi-satellitE Retrievals for GPM (IMERG) Technical Documentation , 2015 .

[75]  S. L. Gariano,et al.  Changes in climate patterns and their association to natural hazard distribution in South Tyrol (Eastern Italian Alps) , 2020, Scientific Reports.

[76]  Chen Cheng,et al.  Analysis of the relationship of landslide occurrence with rainfall: a case study of Wudu County, China , 2014, Arabian Journal of Geosciences.

[77]  J. Michaelsen,et al.  The climate hazards infrared precipitation with stations—a new environmental record for monitoring extremes , 2015, Scientific Data.

[78]  Qiuhong Tang,et al.  Evaluating the performances of satellite-based rainfall data for global rainfall-induced landslide warnings , 2019, Landslides.

[79]  C. Doswell,et al.  Flash Flood Forecasting: An Ingredients-Based Methodology , 1996 .

[80]  Thomas J. Schmugge,et al.  Estimation of Soil Moisture with Api Algorithms and Microwave Emission , 1981 .

[81]  J. Susskind,et al.  Global Precipitation at One-Degree Daily Resolution from Multisatellite Observations , 2001 .

[82]  J. Moya,et al.  Critical rainfall conditions for the initiation of torrential flows: results from the Rebaixader catchment (Central Pyrenees) , 2016 .

[83]  D. M. Green,et al.  Signal detection theory and psychophysics , 1966 .