Stratified drought analysis using a stochastic ensemble of simulated and in-situ soil moisture observations

Abstract This study proposes a multi-wavelet Bayesian ensemble of two Land Surface Models (LSMs) using in-situ observations for accurate estimation of soil moisture for Contiguous United States (CONUS). In the absence of a continuous, accurate in-situ soil moisture dataset at high spatial resolution, an ensemble of Noah and Mosaic LSMs is derived by performing a Bayesian Model Averaging (BMA) of several wavelet-based multi-resolution regression models (WR) of the simulated soil moisture from the LSMs and in-situ volumetric soil moisture dataset obtained from the U.S. Climate Reference Network (USCRN) field stations. This provides a proxy to the in-situ soil moisture dataset at 1/8th degree spatial resolution called Hybrid Soil Moisture (HSM) for three soil layers (1–10 cm, 10–40 cm and 40–100 cm) for the CONUS. The derived HSM is used further to study the layer-wise response of soil moisture to drought, highlighting the necessity of the ensemble approach and soil profile perspective for drought analysis. A correlation analysis between HSM, the long-term (PDSI, PHDI, SPI-9, SPI-12 and SPI-24) and the short-term (Palmer Z index, SPI-1 and SPI-6) drought indices is carried out for the nine climate regions of the U.S. indicating a higher sensitivity of soil moisture to drought conditions for the Southern U.S. Furthermore, a layer-wise soil moisture percentile approach is proposed and applied for drought reconstruction in CONUS with a focus on the Southern U.S. for the year 2011.

[1]  J. D. Tarpley,et al.  The multi‐institution North American Land Data Assimilation System (NLDAS): Utilizing multiple GCIP products and partners in a continental distributed hydrological modeling system , 2004 .

[2]  K. Trenberth.  Some Effects of Finite Sample Size and Persistence on Meteorological Statistics. Part I: Autocorrelations , 1984 .

[3]  Adrian E. Raftery,et al.  Bayesian model averaging: a tutorial (with comments by M. Clyde, David Draper and E. I. George, and a rejoinder by the authors , 1999 .

[4]  V. Lakshmi,et al.  Characterizing subpixel variability of low resolution radiometer derived soil moisture using high resolution radar data , 2008 .

[5]  J. D. Tarpley,et al.  Implementation of Noah land surface model advances in the National Centers for Environmental Prediction operational mesoscale Eta model , 2003 .

[6]  Amir AghaKouchak,et al.  A baseline probabilistic drought forecasting framework using standardized soil moisture index: application to the 2012 United States drought , 2014 .

[7]  Tiago M. Fragoso,et al.  Bayesian Model Averaging: A Systematic Review and Conceptual Classification , 2015, 1509.08864.

[8]  A. Aghakouchak.  A multivariate approach for persistence-based drought prediction: Application to the 2010–2011 East Africa drought , 2015 .

[9]  D. Lawrence,et al.  Regions of Strong Coupling Between Soil Moisture and Precipitation , 2004, Science.

[10]  K. Mitchell,et al.  A parameterization of snowpack and frozen ground intended for NCEP weather and climate models , 1999 .

[11]  Hamid Moradkhani,et al.  A Bayesian Framework for Probabilistic Seasonal Drought Forecasting , 2013 .

[12]  George E. P. Box,et al.  Time Series Analysis: Forecasting and Control , 1977 .

[13]  K. Mitchell,et al.  Impact of Atmospheric Surface-layer Parameterizations in the new Land-surface Scheme of the NCEP Mesoscale Eta Model , 1997 .

[14]  Eric F. Wood,et al.  Uncertainties, Correlations, and Optimal Blends of Drought Indices from the NLDAS Multiple Land Surface Model Ensemble , 2014 .

[15]  Amir AghaKouchak,et al.  A Nonparametric Multivariate Multi-Index Drought Monitoring Framework , 2014 .

[16]  K. Mitchell,et al.  Assessment of the Land Surface and Boundary Layer Models in Two Operational Versions of the NCEP Eta Model Using FIFE Data , 1997 .

[17]  K. Mo,et al.  Model-Based Drought Indices over the United States , 2008 .

[18]  Arun Kumar,et al.  Long‐range experimental hydrologic forecasting for the eastern United States , 2002 .

[19]  Yi Liu,et al.  A three-dimensional gap filling method for large geophysical datasets: Application to global satellite soil moisture observations , 2012, Environ. Model. Softw..

[20]  J. Kurths,et al.  Wavelet Spectrum and Self-Organizing Maps-Based Approach for Hydrologic Regionalization -a Case Study in the Western United States , 2016, Water Resources Management.

[21]  M. Steel,et al.  Model uncertainty in cross-country growth regressions , 2001 .

[22]  Ankit Agarwal,et al.  Hydrologic regionalization using wavelet-based multiscale entropy method , 2015 .

[23]  F. Robertson,et al.  Thresholds in atmosphere–soil moisture interactions: Results from climate model studies , 2002 .

[24]  Yanjun Wang,et al.  Spatiotemporal variations of soil moisture in the Tarim River basin, China , 2016, Int. J. Appl. Earth Obs. Geoinformation.

[25]  V. Singh,et al.  A review of drought concepts , 2010 .

[26]  Venkat Lakshmi,et al.  Soil moisture as an indicator of weather extremes , 2004 .

[27]  Wensheng Wang,et al.  Wavelet Network Model and Its Application to the Prediction of Hydrology , 2003 .

[28]  Dara Entekhabi,et al.  NASA's Soil Moisture Active Passive (SMAP) Mission and Opportunities for Applications Users , 2013 .

[29]  Qiang Zhang,et al.  On the potential application of land surface models for drought monitoring in China , 2017, Theoretical and Applied Climatology.

[30]  Tsegaye Tadesse,et al.  Assessing the evolution of soil moisture and vegetation conditions during the 2012 United States flash drought , 2016 .

[31]  A. Dai.  Drought under global warming: a review , 2011 .

[32]  Ingrid Daubechies,et al.  The wavelet transform, time-frequency localization and signal analysis , 1990, IEEE Trans. Inf. Theory.

[33]  S. Mallat.  A wavelet tour of signal processing , 1998 .

[34]  T. Barnett,et al.  Origins of the midlatitude Pacific decadal variability , 1999 .

[35]  J. Overpeck,et al.  Exploring drought and its implications for the future , 2004 .

[36]  Peter J. Webster,et al.  The annual cycle of persistence in the El Nño/Southern Oscillation , 1998 .

[37]  Zachary A. Holden,et al.  Tracking Interannual Streamflow Variability with Drought Indices in the U.S. Pacific Northwest , 2014 .

[38]  Dennis P. Lettenmaier,et al.  Uncertainties in North American Land Data Assimilation Systems over the Contiguous United States , 2012 .

[39]  Chandranath Chatterjee,et al.  A wavelet-based non-linear autoregressive with exogenous inputs (WNARX) dynamic neural network model for real-time flood forecasting using satellite-based rainfall products , 2016 .

[40]  Michael Manga,et al.  VARIATION IN THE RELATIONSHIP BETWEEN SNOWMELT RUNOFF IN OREGON AND ENSO AND PDO 1 , 2004 .

[41]  Dennis P. Lettenmaier,et al.  Multimodel Ensemble Reconstruction of Drought over the Continental United States , 2009 .

[43]  Alain Dassargues,et al.  Conceptual model uncertainty in groundwater modeling: Combining generalized likelihood uncertainty estimation and Bayesian model averaging , 2008 .

[44]  S. Quiring,et al.  On the utility of in situ soil moisture observations for flash drought early warning in Oklahoma, USA , 2015 .

[45]  Daniel W. Goldberg,et al.  The North American Soil Moisture Database: Development and Applications , 2016 .

[46]  Jan Adamowski,et al.  Multiscale streamflow forecasting using a new Bayesian Model Average based ensemble multi-wavelet Volterra nonlinear method , 2013 .

[47]  Jiri Nekovar,et al.  Use of a soil moisture network for drought monitoring in the Czech Republic , 2011, Theoretical and Applied Climatology.

[48]  E. Wood,et al.  Probabilistic Seasonal Forecasting of African Drought by Dynamical Models , 2013 .

[49]  Dennis P. Lettenmaier,et al.  Soil Moisture Drought in China, 1950–2006 , 2011 .

[50]  O. Kisi,et al.  Wavelet and neuro-fuzzy conjunction model for precipitation forecasting , 2007 .

[51]  Venkat Lakshmi,et al.  Evaluating Bias‐Corrected AMSR‐E Soil Moisture using in situ Observations and Model Estimates , 2013 .

[52]  Paulin Coulibaly,et al.  Wavelet analysis of variability in annual Canadian streamflows , 2004 .

[53]  Thomas C. Peterson,et al.  Explaining Extreme Events of 2014 from a Climate Perspective , 2015 .

[54]  Edward E. Leamer,et al.  Specification Searches: Ad Hoc Inference with Nonexperimental Data , 1980 .

[55]  Sangdan Kim,et al.  Wavelet analysis of precipitation variability in northern California, U.S.A. , 2004 .

[56]  Zbigniew W. Kundzewicz,et al.  River Floods in the Changing Climate—Observations and Projections , 2010 .

[57]  K. Mo,et al.  Continental-scale water and energy flux analysis and validation for the North American Land Data Assimilation System project phase 2 (NLDAS-2): 1. Intercomparison and application of model products , 2012 .

[58]  P. Webster,et al.  Interdecadal changes in the ENSO-monsoon system , 1999 .

[59]  T. Piechota,et al.  Spatial and temporal soil moisture and drought variability in the Upper Colorado River Basin , 2009 .

[60]  S. Sorooshian,et al.  Multi-model ensemble hydrologic prediction using Bayesian model averaging , 2007 .

[61]  Mannava V. K. Sivakumar,et al.  Information systems in a changing climate: Early warnings and drought risk management , 2014 .

[62]  Vinit Sehgal,et al.  Effect of Utilization of Discrete Wavelet Components on Flood Forecasting Performance of Wavelet Based ANFIS Models , 2014, Water Resources Management.

[63]  Matthias Drusch,et al.  Global Automated Quality Control of In Situ Soil Moisture Data from the International Soil Moisture Network , 2013 .

[64]  J. Adamowski.  River flow forecasting using wavelet and cross‐wavelet transform models , 2008 .

[65]  Thomas R. Karl,et al.  Some Spatial Characteristics of Drought Duration in the United States , 1983 .

[66]  M. Steel,et al.  Benchmark Priors for Bayesian Model Averaging , 2001 .

[67]  Kevin E. Trenberth,et al.  Climate extremes and climate change: The Russian heat wave and other climate extremes of 2010 , 2012 .

[68]  Hamid Moradkhani,et al.  Toward reduction of model uncertainty: Integration of Bayesian model averaging and data assimilation , 2012 .

[69]  John Kochendorfer,et al.  U.S. Climate Reference Network Soil Moisture and Temperature Observations , 2013 .

[70]  Juan B. Valdés,et al.  NONLINEAR MODEL FOR DROUGHT FORECASTING BASED ON A CONJUNCTION OF WAVELET TRANSFORMS AND NEURAL NETWORKS , 2003 .

[71]  Ping Wang,et al.  Multiscale characteristics of the rainy season rainfall and interdecadal decaying of summer monsoon in North China , 2003 .

[72]  Damien Garcia,et al.  Robust smoothing of gridded data in one and higher dimensions with missing values , 2010, Comput. Stat. Data Anal..

[73]  Erick Fredj,et al.  Gap Filling of the Coastal Ocean Surface Currents from HFR Data: Application to the Mid-Atlantic Bight HFR Network , 2016 .

[74]  E. Wood,et al.  A simulated soil moisture based drought analysis for the United States , 2004 .

[75]  A. Raftery,et al.  Using Bayesian Model Averaging to Calibrate Forecast Ensembles , 2005 .

[76]  Jonggun Kim,et al.  Effective soil moisture estimate and its uncertainty using multimodel simulation based on Bayesian Model Averaging , 2013 .

[77]  V. Sridhar,et al.  Hydrological behaviour of grasslands of the Sandhills of Nebraska: water and energy‐balance assessment from measurements, treatments, and modelling , 2009 .

[78]  Laurence C. Smith,et al.  Stream flow characterization and feature detection using a discrete wavelet transform , 1998 .

[79]  T. Arkebauer,et al.  The development and evaluation of a soil moisture index , 2009 .

[80]  V. Sridhar,et al.  Development of the Soil Moisture Index to Quantify Agricultural Drought and Its “User Friendliness” in Severity-Area-Duration Assessment , 2008 .

[81]  Kiran Alapaty,et al.  UNCERTAINTY IN THE SPECIFICATION OF SURFACE CHARACTERISTICS: A STUDY OF PREDICTION ERRORS IN THE BOUNDARY LAYER , 1997 .

[82]  Randal D. Koster,et al.  The components of a 'SVAT' scheme and their effects on a GCM's hydrological cycle , 1994 .

[83]  J. Abatzoglou,et al.  Development of Soil Moisture Drought Index to Characterize Droughts , 2015 .

[84]  Melissa Widhalm,et al.  The Lincoln Declaration on Drought Indices: Universal Meteorological Drought Index Recommended , 2011 .

[85]  K. Hubbard,et al.  Soil Water Assessment Model for Several Crops in the High Plains , 1990 .

[86]  Rathinasamy Maheswaran,et al.  Comparative study of different wavelets for hydrologic forecasting , 2012, Comput. Geosci..

[87]  Luca Ridolfi,et al.  Preferential states of seasonal soil moisture: The impact of climate fluctuations , 2000 .

[88]  Vinit Sehgal,et al.  Wavelet Bootstrap Multiple Linear Regression Based Hybrid Modeling for Daily River Discharge Forecasting , 2014, Water Resources Management.

[89]  Qingyun Duan,et al.  An integrated hydrologic Bayesian multimodel combination framework: Confronting input, parameter, and model structural uncertainty in hydrologic prediction , 2006 .

[90]  Sethu Raman,et al.  Adopting drought indices for estimating soil moisture: A North Carolina case study , 2002 .

[91]  Min Chen,et al.  An Efficient Method of Estimating Downward Solar Radiation Based on the MODIS Observations for the Use of Land Surface Modeling , 2014, Remote. Sens..

[92]  M. Palecki,et al.  THE DROUGHT MONITOR , 2002 .

[93]  Chie-Ming Chou,et al.  On-line estimation of unit hydrographs using the wavelet-based LMS algorithm / Estimation en ligne des hydrogrammes unitaires grâce à l'algorithme des moindres carrés moyens à base d'ondelettes , 2002 .

[94]  Bruce A. Robinson,et al.  Treatment of uncertainty using ensemble methods: Comparison of sequential data assimilation and Bayesian model averaging , 2007 .

[95]  E. Wood,et al.  A Drought Monitoring and Forecasting System for Sub-Sahara African Water Resources and Food Security , 2014 .

[96]  D. Wilhite,et al.  CHAPfER2UNDERSTANDING THE DROUGHT PHENOMENON:THE ROLE OF DEFINITIONS , 1985 .

[97]  Syukuro Manabe,et al.  The influence of potential evaporation on the variabilities of simulated soil wetness and climate , 1988 .

[98]  Robert E. Dickinson,et al.  Time scales of land surface hydrology , 2004 .

[99]  V. Sridhar,et al.  Estimation of the Water Balance Using Observed Soil Water in the Nebraska Sandhills , 2010 .

[100]  R. Maheswaran,et al.  Wavelet–Volterra coupled model for monthly stream flow forecasting , 2012 .