Evaluating the Operational Application of SMAP for Global Agricultural Drought Monitoring

Over the past two decades, remote sensing has made possible the routine global monitoring of surface soil moisture. Regional agricultural drought monitoring is one of the most logical application areas for such monitoring. However, remote sensing alone provides soil moisture information for only the top few centimeters of the soil profile, while agricultural drought monitoring requires knowledge of the amount of water present in the entire root zone. The assimilation of remotely sensed soil moisture products into continuous soil water balance models provides a way of addressing this shortcoming. Here, we describe the assimilation of NASA's soil moisture active passive (SMAP) surface soil moisture data into the United States Department of Agriculture Foreign Agricultural Service (USDA FAS) Palmer model and assess the impact of SMAP on USDA FAS drought monitoring capabilities. The assimilation of SMAP is specifically designed to enhance the model skill and the USDA FAS drought capabilities by correcting for random errors inherent in its rainfall forcing data. The performance of this SMAP-based assimilation system is evaluated using two approaches. At global scale, the accuracy of the system is assessed by examining the lagged correlation agreement between soil moisture and the normalized difference vegetation index (NDVI). Additional regional-scale evaluation using in situ-based soil moisture estimates is carried out at seven of the SMAP core Cal/Val sites located in the USA. Both types of analysis demonstrate the value of assimilating SMAP into the USDA FAS Palmer model and its potential to enhance operational USDA FAS root-zone soil moisture information.

• Publication year

  2019

• Venue

  IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing

• Publication date

  2019-07-09

• Fields of study

  Agricultural and Food Sciences, Computer Science, Environmental Science

• Identifiers
  DOI 10.1109/JSTARS.2019.2923555
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

• Validation of SMAP surface soil moisture products with core validation sites

  2017cited by this paper
• Validation of SMAP soil moisture for the SMAPVEX15 field campaign using a hyper‐resolution model

  2017cited by this paper
• The Error Structure of the SMAP Single and Dual Channel Soil Moisture Retrievals

  2017cited by this paper
• Development and assessment of the SMAP enhanced passive soil moisture product

  2017cited by this paper
• A Comparative Study of the SMAP Passive Soil Moisture Product With Existing Satellite-Based Soil Moisture Products

  2017cited by this paper
• Evaluating the application of microwave-based vegetation observations in an operational soil moisture data assimilation system

  2015cited by this paper
• Response of plants to water stress

  2014cited by this paper
• Benchmarking a Soil Moisture Data Assimilation System for Agricultural Drought Monitoring

  2014cited by this paper
• The Optimality of Potential Rescaling Approaches in Land Data Assimilation

  2013cited by this paper
• Improved prediction of quasi‐global vegetation conditions using remotely‐sensed surface soil moisture

  2012cited by this paper
• On the utility of land surface models for agricultural drought monitoring

  2012cited by this paper
• An improved approach for estimating observation and model error parameters in soil moisture data assimilation

  2010cited by this paper
• On the Nature of Soil Moisture in Land Surface Models

  2009cited by this paper
• Technical Note: Comparing and ranking soil drought indices performance over Europe, through remote-sensing of vegetation

  2009cited by this paper
• Performance Metrics for Soil Moisture Retrievals and Application Requirements

  2009cited by this paper
• A new data assimilation approach for improving runoff prediction using remotely-sensed soil moisture retrievals

  2008cited by this paper
• Data assimilation methods in the Earth sciences

  2008cited by this paper
• A new data assimilation approach for improving hydrologic prediction using remotely-sensed soil moisture retrievals

  2008cited by this paper
• Initializing numerical weather prediction models with satellite‐derived surface soil moisture: Data assimilation experiments with ECMWF's Integrated Forecast System and the TMI soil moisture data set

  2007cited by this paper
• Crop model data assimilation with the Ensemble Kalman filter for improving regional crop yield forecasts

  2007cited by this paper
• Using the satellite-derived NDVI to assess ecological responses to environmental change.

  2005cited by this paper
• Global assimilation of satellite surface soil moisture retrievals into the NASA Catchment land surface model

  2005cited by this paper
• Bias reduction in short records of satellite soil moisture

  2004cited by this paper
• The Ensemble Kalman Filter: theoretical formulation and practical implementation

  2003cited by this paper
• Further validation of a new methodology for surface moisture and vegetation optical depth retrieval

  2003cited by this paper
• How plants cope with water stress in the field. Photosynthesis and growth.

  2002cited by this paper
• III. Measuring surface soil moisture using passive microwave remote sensing

  1993cited by this paper
• Adaptation of plants to water and high temperature stress

  1980cited by this paper

• Climate and soil moisture variability and cropland exposure in Western Yemen: a spatiotemporal analysis using satellite and reanalysis time series from 2000 to 2024

  2026cites this paper
• Spatial–Frequency Residual-Guided Dynamic Perceptual Network for Remote Sensing Image Haze Removal

  2025cites this paper
• Evaluating different drought products for assessing drought and implications on agriculture in Nepal

  2025cites this paper
• Advancements in Agricultural Microwave Remote Sensing: An Overview From Indoor to Space-Borne Platforms

  2025cites this paper
• Above the Clouds: New Software Challenges in Space Computing

  2025cites this paper
• Exploring Hydrological Variable Interconnections and Enhancing Predictions for Data‐Limited Basins Through Multi‐Task Learning

  2025influential citation
• Understanding discrepancies in soil moisture from SMAP and AMSR2: insights into performance and dry-down behavior

  2025cites this paper
• A Soil Moisture and Vegetation-Based Susceptibility Mapping Approach to Wildfire Events in Greece

  2024cites this paper
• Retrieving forest soil moisture from SMAP observations considering a microwave polarization difference index (MPDI) to -ω model

  2024cites this paper
• WSN-Driven Advances in Soil Moisture Estimation: A Machine Learning Approach

  2024cites this paper
• Miscellaneous methods for determination of unfrozen water content in frozen soils

  2024cites this paper
• On the Use of SMAP Soil Moisture for Forecasting NDVI Over CONUS Cropland Regions

  2024influential citation
• Utilization of satellite data for landslide disaster mitigation in extreme event: a case study June 18, 2016, landslide in Banjarnegara Regency, Indonesia

  2024cites this paper
• Evaluation of a combined drought indicator against crop yield estimations and simulations over the Argentine Humid Pampas

  2024cites this paper
• Hydrologic Consistency of Multi-Sensor Drought Observations in Forested Environments

  2024cites this paper
• Detection of vegetation drying signals using diurnal variation of land surface temperature: Application to the 2018 East Asia heatwave

  2023cites this paper
• Do limits exist on potential woody cover of Brazilian savanna?

  2023cites this paper
• Variations in Global Soil Moisture During the Past Decades: Climate or Human Causes?

  2023cites this paper
• Fine Resolution Mapping of Soil Organic Carbon in Croplands with Feature Selection and Machine Learning in Northeast Plain China

  2023cites this paper
• Structural-optimized sequential deep learning methods for surface soil moisture forecasting, case study Quebec, Canada

  2022cites this paper
• Understanding root-zone soil moisture in agricultural regions of Central Mexico using the ensemble Kalman filter, satellite-derived information, and the THEXMEX-18 dataset

  2022influential citation
• Assimilation of SMAP Products for Improving Streamflow Simulations over Tropical Climate Region - Is Spatial Information More Important Than Temporal Information?

  2022cites this paper
• Retrieval of Soil Moisture from FengYun-3D Microwave Radiation Imager Operational and Recalibrated Data Using Random Forest Regression

  2022cites this paper
• Quasi-global machine learning-based soil moisture estimates at high spatio-temporal scales using CYGNSS and SMAP observations

  2022cites this paper
• The global pattern and development trends & directions on the drought monitoring research from 1983 to 2020 by using bibliometric analysis

  2022cites this paper
• Crop-CASMA: A web geoprocessing and map service based architecture and implementation for serving soil moisture and crop vegetation condition data over U.S. Cropland

  2022cites this paper
• Advances in the Quality of Global Soil Moisture Products: A Review

  2022cites this paper
• Detecting a Declining Trend of Multidepth Soil Moisture Over the Mongolian Plateau From 1950 to 2020 Using ERA5-Land Reanalysis Datasets

  2022cites this paper
• An Agenda for Land Data Assimilation Priorities: Realizing the Promise of Terrestrial Water, Energy, and Vegetation Observations From Space

  2022cites this paper
• SI-SA GAN: A Generative Adversarial Network Combined With Spatial Information and Self-Attention for Removing Thin Cloud in Optical Remote Sensing Images

  2022cites this paper
• Flash Drought Onset and Development Mechanisms Captured With Soil Moisture and Vegetation Data Assimilation

  2022cites this paper
• Contrastive Haze-Aware Learning for Dynamic Remote Sensing Image Dehazing

  2022cites this paper
• Is land degradation worsening in Northern China? Quantitative evidence and enlightenment from satellites

  2022cites this paper
• Remote Sensing of Environment

  2021cites this paper
• Regional drought risk assessment in the Central Highlands and the South of Vietnam

  2021cites this paper
• Progress, Challenges, and Opportunities in Remote Sensing of Drought

  2021cites this paper
• Global Flash Drought Monitoring Using Surface Soil Moisture

  2021cites this paper
• Performance analysis of regional AquaCrop (v6.1) biomass and surface soil moisture simulations using satellite and in situ observations

  2021cites this paper
• Satellite Flood Inundation Assessment and Forecast Using SMAP and Landsat

  2021cites this paper
• Assessing Disaggregated SMAP Soil Moisture Products in the United States

  2021cites this paper
• Assimilation of SMAP and ASCAT soil moisture retrievals into the JULES land surface model using the Local Ensemble Transform Kalman Filter

  2021cites this paper
• Assessing the Impact of ENSO on Agriculture Over Africa Using Earth Observation Data

  2020cites this paper
• Soil Moisture–Evapotranspiration Overcoupling and L-Band Brightness Temperature Assimilation: Sources and Forecast Implications

  2020cites this paper
• Exploring Spatiotemporal Relations between Soil Moisture, Precipitation, and Streamflow for a Large Set of Watersheds Using Google Earth Engine

  2020cites this paper
• SMAP Soil Moisture Product Validity in Heterogeneous Irrigated Regions

  2020cites this paper
• Synergistic use of SMAP and OCO-2 data in assessing the responses of ecosystem productivity to the 2018 U.S. drought

  2020cites this paper
• Monitoreo de sequías en El Salvador mediante variables teledetectadas usando la plataforma Google Earth Engine

  2020cites this paper
• Agricultural Drought Monitoring via the Assimilation of SMAP Soil Moisture Retrievals Into a Global Soil Water Balance Model

  2020influential citation
• Soil moisture / evapotranspiration over-coupling and L-band brightness 1 temperature assimilation : sources and forecast implications 2 3

  2020cites this paper
• Impact of model coupling bias on water flux estimates acquired from a land data assimilation system

  2020cites this paper
• How Satellite Soil Moisture Data Can Help to Monitor the Impacts of Climate Change: SMAP Case Studies

  2020cites this paper
• Assimilation of SMAP Products for Improving Streamflow

  year unknowncites this paper