Satellite soil moisture for agricultural drought monitoring: Assessment of the SMOS derived Soil Water Deficit Index

被引:222
|
作者
Martinez-Fernandez, J. [1 ]
Gonzalez-Zamora, A. [1 ]
Sanchez, N. [1 ]
Gumuzzio, A. [1 ]
Herrero-Jimenez, C. M. [1 ]
机构
[1] Univ Salamanca, CIALE, Inst Hispano Luso Invest Agr, Duero 12, Villamayor 37185, Spain
关键词
Soil moisture; SMOS; Soil Water Deficit Index; Agricultural drought; Soil water parameters; ERS SCATTEROMETER; NEAR-SURFACE; VALIDATION; ASSIMILATION; NETWORK; SUPPORT; CLIMATE; STRESS; REGION; LIMIT;
D O I
10.1016/j.rse.2016.02.064
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Drought is a major cause of limited agricultural productivity and of crop yield uncertainty throughout the world. For that reason, agricultural drought research and monitoring are of increasing interest. Although soil moisture is the main variable to define and identify agricultural drought, the actual soil water content is rarely taken into account because this type of drought is commonly studied using methodologies based on either climatological data or hydrological modeling. Currently, it is possible to use remote sensing to obtain global and frequent soil moisture data that could be directly used for agricultural drought monitoring everywhere. For example, the SMOS (Soil Moisture and Ocean Salinity) satellite was launched in 2009 and provides global soil moisture maps every 1-2 days. In this work, the Soil Water Deficit Index (SWDI) was calculated using the SMOS 12 soil moisture series in the REMEDHUS (Soil Moisture Measurement Stations Network) area (Spain) during the period 2010-2014. The satellite index was thus calculated using several approaches to obtain the soil water parameters and was compared with the SWDI obtained from in situ data. One approach was based directly on SMOS soil moisture time series (using the 5th percentile as an estimator for wilting point and the 95th percentile and the minimum of the maximum value during the growing season as estimators for field capacity). In this case, the results of the comparison were good, but the temporal distribution and the range of the index data were unrealistic. Other approaches were based on in situ data parameters and pedotransfer functions estimation. In this case, the results were better, and the satellite index was able to adequately identify the drought dynamics. Therefore, the final choice to apply the index in one particular site will depend on the availability of data. Finally, a comparison analysis was made with the SMOS SWDI and two indices (Crop Moisture Index, CMI, and Atmospheric Water Deficit, AWD) commonly used for agricultural drought monitoring and assessment. In both cases, the agreement was very good, and it was proven that SMOS SWDI reproduces well the soil water balance dynamics and is able to appropriately track agricultural drought. (C) 2016 Elsevier Inc. All rights reserved.
引用
收藏
页码:277 / 286
页数:10
相关论文
共 50 条
  • [21] Agricultural Drought Monitoring via the Assimilation of SMAP Soil Moisture Retrievals Into a Global Soil Water Balance Model
    Mladenova, Iliana E.
    Bolten, John D.
    Crow, Wade
    Sazib, Nazmus
    Reynolds, Curt
    FRONTIERS IN BIG DATA, 2020, 3
  • [22] Assessing the soil moisture drought index for agricultural drought monitoring based on green vegetation fraction retrieval methods
    Wu, Rongjun
    Li, Qi
    NATURAL HAZARDS, 2021, 108 (01) : 499 - 518
  • [23] Assessing the soil moisture drought index for agricultural drought monitoring based on green vegetation fraction retrieval methods
    Rongjun Wu
    Qi Li
    Natural Hazards, 2021, 108 : 499 - 518
  • [24] Agricultural drought assessment based on multiple soil moisture products
    Baik, Jongjin
    Zohaib, Muhammad
    Kim, Ungtae
    Aadil, Muhammad
    Choi, Minha
    JOURNAL OF ARID ENVIRONMENTS, 2019, 167 : 43 - 55
  • [25] Agricultural drought monitoring based on soil moisture derived from the optical trapezoid model in Mozambique
    Mananze, Sosdito
    Pocas, Isabel
    Cunha, Mario
    JOURNAL OF APPLIED REMOTE SENSING, 2019, 13 (02)
  • [26] Design of an Optimal Soil Moisture Monitoring Network Using SMOS Retrieved Soil Moisture
    Kornelsen, Kurt C.
    Coulibaly, Paulin
    IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2015, 53 (07): : 3950 - 3959
  • [27] EVALUATION OF ASSIMILATED SMOS SOIL MOISTURE DATA FOR US CROPLAND SOIL MOISTURE MONITORING
    Yang, Zhengwei
    Shrestha, Ranjay
    Crow, Wade
    Bolten, John
    Mladenova, Iva
    Yu, Genong
    Di, Liping
    2016 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS), 2016, : 5244 - 5247
  • [28] An empirical standardized soil moisture index for agricultural drought assessment from remotely sensed data
    Carrao, Hugo
    Russo, Simone
    Sepulcre-Canto, Guadalupe
    Barbosa, Paulo
    INTERNATIONAL JOURNAL OF APPLIED EARTH OBSERVATION AND GEOINFORMATION, 2016, 48 : 74 - 84
  • [29] A New Soil Moisture Agricultural Drought Index (SMADI) Integrating MODIS and SMOS Products: A Case of Study over the Iberian Peninsula
    Sanchez, Nilda
    Gonzalez-Zamora, Angel
    Piles, Maria
    Martinez-Fernandez, Jose
    REMOTE SENSING, 2016, 8 (04):
  • [30] Random Forests with Bagging and Genetic Algorithms Coupled with Least Trimmed Squares Regression for Soil Moisture Deficit Using SMOS Satellite Soil Moisture
    Srivastava, Prashant K.
    Petropoulos, George P.
    Prasad, Rajendra
    Triantakonstantis, Dimitris
    ISPRS INTERNATIONAL JOURNAL OF GEO-INFORMATION, 2021, 10 (08)