Articles | Volume 20, issue 8
https://doi.org/10.5194/hess-20-3361-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
https://doi.org/10.5194/hess-20-3361-2016
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
the Creative Commons Attribution 3.0 License.
Research article
| 
23 Aug 2016
Research article |
| 23 Aug 2016
Comparing the Normalized Difference Infrared Index (NDII) with root zone storage in a lumped conceptual model
Nutchanart Sriwongsitanon
Department of Water Resources Engineering, Faculty of Engineering, Kasetsart University, Bangkok, Thailand
Hongkai Gao
Water Resources Section, Delft University of Technology, Delft, the Netherlands
Hubert H. G. Savenije
CORRESPONDING AUTHOR
Water Resources Section, Delft University of Technology, Delft, the Netherlands
Ekkarin Maekan
Department of Water Resources Engineering, Faculty of Engineering, Kasetsart University, Bangkok, Thailand
Sirikanya Saengsawang
Department of Water Resources Engineering, Faculty of Engineering, Kasetsart University, Bangkok, Thailand
Sansarith Thianpopirug
Department of Water Resources Engineering, Faculty of Engineering, Kasetsart University, Bangkok, Thailand
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32 citations as recorded by crossref.
- WAYS v1: a hydrological model for root zone water storage simulation on a global scale G. Mao & J. Liu 10.5194/gmd-12-5267-2019
- MODIS-based modeling of evapotranspiration from woody vegetation supported by root-zone water storage G. Cui et al. 10.1016/j.rse.2024.114000
- Analysis of vegetation recovery surrounding a restored wetland using the normalized difference infrared index (NDII) and normalized difference vegetation index (NDVI) N. Wilson & L. Norman 10.1080/01431161.2018.1437297
- Extensive vegetation browning and drying in forests of India’s Tiger Reserves P. Koulgi et al. 10.1038/s41598-019-51118-8
- A longitudinal analysis of soil salinity changes using remotely sensed imageries S. Bandak et al. 10.1038/s41598-024-60033-6
- Multisource remote sensing data facilitate ecohydrological simulations without runoff calibration D. Yang et al. 10.1002/hyp.14773
- Drought Influence on Forest Plantations in Zululand, South Africa, Using MODIS Time Series and Climate Data S. Xulu et al. 10.3390/f9090528
- Mesoclimate regulation induced by landscape restoration and water harvesting in agroecosystems of the horn of Africa G. Castelli et al. 10.1016/j.agee.2019.02.002
- Vegetation fuel characterization using machine learning approach over southern Portugal F. Santos et al. 10.1016/j.rsase.2023.101017
- Evaluating Seasonal Wildfire Susceptibility and Wildfire Threats to Local Ecosystems in the Largest Forested Area of China X. Tang et al. 10.1029/2021EF002199
- Actual Evapotranspiration Estimates in Arid Cold Regions Using Machine Learning Algorithms with In Situ and Remote Sensing Data J. Mosre & F. Suárez 10.3390/w13060870
- Durum wheat ears perform better than the flag leaves under water stress: Gene expression and physiological evidence R. Vicente et al. 10.1016/j.envexpbot.2018.06.004
- Ecohydrologic separation alters interpreted hydrologic stores and fluxes in a headwater mountain catchment M. Cain et al. 10.1002/hyp.13518
- Using normalised difference infrared index patterns to constrain semi-distributed rainfall–runoff models in tropical nested catchments N. Sriwongsitanon et al. 10.5194/hess-27-2149-2023
- Forest age estimation using UAV-LiDAR and Sentinel-2 data with machine learning algorithms- a case study of Masson pine ( Pinus massoniana ) J. Chen et al. 10.1080/10095020.2024.2362752
- Time Series Analysis of MODIS-Derived NDVI for the Hluhluwe-Imfolozi Park, South Africa: Impact of Recent Intense Drought N. Mbatha & S. Xulu 10.3390/cli6040095
- Phenophase-based comparison of field observations to satellite-based actual evaporation estimates of a natural woodland: miombo woodland, southern Africa H. Zimba et al. 10.5194/hess-27-1695-2023
- Remotely Sensed Soil Moisture Assimilation in the Distributed Hydrological Model Based on the Error Subspace Transform Kalman Filter Y. Li et al. 10.3390/rs15071852
- Effect of traditional check dams (jessour) on soil and olive trees water status in Tunisia G. Castelli et al. 10.1016/j.scitotenv.2019.06.514
- Drought adaptability of phreatophytes: insight from vertical root distribution in drylands of China T. Wang et al. 10.1093/jpe/rtab059
- A comparative evaluation of arid inflow-dependent vegetation maps derived from LANDSAT top-of-atmosphere and surface reflectances I. Emelyanova et al. 10.1080/01431161.2018.1463114
- Comparison of Long-Term Changes in Non-Linear Aggregated Drought Index Calibrated by MERRA–2 and NDII Soil Moisture Proxies F. Mathivha & N. Mbatha 10.3390/w14010026
- Correlation analysis of different optical remote sensing indices for drought monitoring: a case study of Canton Sarajevo, Bosnia and Herzegovina M. Đidelija et al. 10.1007/s10661-023-11930-2
- Spatial prediction of soil organic carbon using machine learning techniques in western Iran H. Mahmoudzadeh et al. 10.1016/j.geodrs.2020.e00260
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- Twenty Years of Remote Sensing Applications Targeting Landscape Analysis and Environmental Issues in Olive Growing: A Review G. Messina & G. Modica 10.3390/rs14215430
- Wildfire Risk Assessment Based on Geospatial Open Data: Application on Chios, Greece N. Adaktylou et al. 10.3390/ijgi9090516
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- A Novel Teacher–Student Framework for Soil Moisture Retrieval by Combining Sentinel-1 and Sentinel-2: Application in Arid Regions N. Jarray et al. 10.1109/LGRS.2022.3168982
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- Use of time series Sentinel-1 and Sentinel-2 image for rice crop inventory in parts of Bangladesh M. Aziz et al. 10.1007/s12518-023-00501-2
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- Uncovering the Hidden Carbon Treasures of the Philippines’ Towering Mountains: A Synergistic Exploration Using Satellite Imagery and Machine Learning R. Altarez et al. 10.1007/s41064-023-00264-w
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Saved (preprint)
Latest update: 29 Jun 2024
Short summary
We demonstrated that the readily available NDII remote sensing product is a very useful proxy for moisture storage in the root zone of vegetation. We compared the temporal variation of the NDII with the root zone storage in a hydrological model of eight catchments in the Upper Ping River in Thailand, yielding very good results. Having a reliable NDII product that can help us to estimate the actual moisture storage in catchments is a major contribution to prediction in ungauged basins.
We demonstrated that the readily available NDII remote sensing product is a very useful proxy...
