The Normalized Difference Infrared Index (NDII) as a proxy for soil moisture storage in hydrological modelling

Sriwongsitanon, Nutchanart; Gao, Hongkai; Savenije, Hubert; Maekan, Ekkarin; Saengsawang, Sirikanya; Thianpopirug, Sansarith

doi:10.5194/hessd-12-8419-2015

Cited by 20 publications

(12 citation statements)

References 44 publications

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“…The NDII also exhibited a similar pattern with the NDVI and precipitation, suggesting that the reduction of tree activity in 2015 was related to a water deficit as a result of the strongest El Niño period, which is believed to have induced drier conditions [66] and altered vegetation reflectance spectra [69]. This reaffirms Sriwongsitanon's [31] finding that the NDII is a robust indicator of the interaction between precipitation, soil moisture, and plant water content. This further highlights the stronger influence of precipitation on tree activity [70].…”

Section: Discussionsupporting

confidence: 65%

Drought Influence on Forest Plantations in Zululand, South Africa, Using MODIS Time Series and Climate Data

Xulu

Peerbhay

Gebreslasie

et al. 2018

Forests

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South Africa has a long history of recurrent droughts that have adversely affected its economic performance. The recent 2015 drought has been declared the most serious in 26 years and impaired key agricultural sectors including the forestry sector. Research on the forests’ responses to drought is therefore essential for management planning and monitoring. The effects of the latest drought on the forests in South Africa have not been studied and are uncertain. The study reported here addresses this gap by using Moderate Resolution Imaging Spectroradiometer (MODIS)-derived normalized difference vegetation index (NDVI) and precipitation data retrieved and processed using the JavaScript code editor in the Google Earth Engine (GEE) and the corresponding normalized difference infrared index (NDII), Palmer drought severity index (PDSI), and El Niño time series data for KwaMbonambi, northern Zululand, between 2002 and 2016. The NDVI and NDII time series were decomposed using the Breaks for Additive Seasonal and Trend (BFAST) method to establish the trend and seasonal variation. Multiple linear regression and Mann–Kendall tests were applied to determine the association of the NDVI and NDII with the climate variables. Plantation trees displayed high NDVI values (0.74–0.78) from 2002 to 2013; then, they decreased sharply to 0.64 in 2015. The Mann–Kendall trend test confirmed a negative significant (p = 0.000353) trend between 2014 and 2015. This pattern was associated with a precipitation deficit and low NDII values during a strong El Niño phase. The PDSI (−2.6) values indicated severe drought conditions. The greening decreased in 2015, with some forest remnants showing resistance, implying that the tree species had varying sensitivity to drought. We found that the plantation trees suffered drought stress during 2015, although it seems that the trees began to recover, as the NDVI signals rose in 2016. Overall, these results demonstrated the effective use of the NDVI- and NDII-derived MODIS data coupled with climatic variables to provide insights into the influence of drought on plantation trees in the study area.

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Section: Discussionsupporting

confidence: 65%

Drought Influence on Forest Plantations in Zululand, South Africa, Using MODIS Time Series and Climate Data

Xulu

Peerbhay

Gebreslasie

et al. 2018

Forests

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“…Also, diverse works show that the longer the wavelength in the optical domain (400-2,500 nm), the better potential to detect soil moisture (e.g., Sriwongsitanon et al, 2015;Zhu et al, 2010). Thus, Band 2 (NIR) is an appropriate alternative to identify not only moist soil but also flooded areas (Amani, Parsian, Mirmazloumi, & Aieneh, 2016;Brakenridge & Anderson, 2006;Gao et al, 2013).…”

Section: Study Areamentioning

confidence: 99%

Surface moisture area during rainfall–run‐off events to understand the hydrological dynamics of a basin in a plain region

Ares

Holzman

Entraigas

et al. 2018

Hydrological Processes

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The understanding of the hydrology of plain basins may be improved by the combined analysis of rainfall–run‐off records and remote sensed surface moisture data. Our work evaluates the surface moisture area (SMA) produced during rainfall–run‐off events in a plain watershed of the Argentine Pampas Region, and studies which hydrological variables are related to the generated SMA. The study area is located in the upper and middle basins of the Del Azul stream, characterized by the presence of small gently hilly areas surrounded by flat landscapes. Data from 9 rainfall–run‐off events were analysed. MODIS surface reflectance data were processed to calculate SMA subsequent to the peak discharge (post‐SMA), and previous to the rainfall events (prev‐SMA), to consider the antecedent wetness. Rainfall–run‐off data included total precipitation depth (P), maximum intensity of rainfall over 6 hr (I6max), surface run‐off registered between the beginning of the event and the day previous to the analysed MODIS scene (R), peak flow (Qp), and flood intensity (IF). In contrast with other works, post‐SMA showed a negative relationship with the R. Three groups of cases were identified: (a) Events of low I6max, high prev‐SMA, and low R were associated with slow and weakly channelized flow over plain areas, leading to saturated overland flow (SOF), with large SMA; (b) events of high I6max, low prev‐SMA, and medium to high R were rapidly transported along the gentle slopes of the basin, related to Hortonian overland flow (HOF) and low post‐SMA; and (c) events of medium to high I6max and prev‐SMA with medium R were related to heterogeneous input‐antecedent‐run‐off conditions combined: Local spatial conditions may have produced HOF or SOF, leading to an averaged response with medium SMA. The interactions between the geomorphology of the basin, the characteristics of the events, and the antecedent conditions may explain the obtained results. This analysis is relevant for the general knowledge of the hydrology of large plains, whose functioning studies are still in their early stages.

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“…NDII is defined similarly to the NDVI, but using the shortwave infrared reflectance (ρSWIR) as (ρNIR − ρSWIR)/(ρNIR + ρSWIR). NDII can be used to detect water shortage using the property of shortwave infrared reflectance, which is negatively related to leaf water content due to the large absorption by the leaf e.g., [57,58].…”

Section: Remote-sensing Datamentioning

confidence: 99%

Recent Drought-Induced Vitality Decline of Black Pine (Pinus nigra Arn.) in South-West Hungary—Is This Drought-Resistant Species under Threat by Climate Change?

Móricz

Garamszegi

Rasztovits

et al. 2018

Forests

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This paper analyses the recent recurring dieback and growth decline of Black pine (P. nigra Arn. var austriaca) in the Keszthely mountains of south-west Hungary, and their relations to water deficits due to droughts. These relations were studied in five stands with low soil water storage capacity for the period 1981-2016. The vitality was assessed using 60 tree-ring samples and changes in remotely sensed vegetation activity indices, i.e., the normalized difference vegetation index (NDVI) and the normalized difference infrared index (NDII). Water deficit was estimated by using meteorological drought indices such the standardized precipitation-evapotranspiration index (SPEI) and the forestry aridity index (FAI), as well as the relative extractable water (REW), calculated by the Brook90 hydrological model. Results revealed a strong dependency of annual tree ring width on the amount of water deficit as measured by all the above estimators, with the highest correlation shown by the summer REW. Droughts also showed a long-term superimposed effect on tree growth. NDII seemed to be more sensitive to drought conditions than NDVI. The robust dependency of tree growth on the summer water availability combined with the projected increasing aridity might lead to decreasing growth of Black pine in Hungary towards the end of the century. We thus argue that the suggestion by several papers that Black pine can be a possible substitute species in the Alpine and Mediterranean region in the future should be revisited.

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The Normalized Difference Infrared Index (NDII) as a proxy for soil moisture storage in hydrological modelling

Cited by 20 publications

References 44 publications

Drought Influence on Forest Plantations in Zululand, South Africa, Using MODIS Time Series and Climate Data

Drought Influence on Forest Plantations in Zululand, South Africa, Using MODIS Time Series and Climate Data

Surface moisture area during rainfall–run‐off events to understand the hydrological dynamics of a basin in a plain region

Recent Drought-Induced Vitality Decline of Black Pine (Pinus nigra Arn.) in South-West Hungary—Is This Drought-Resistant Species under Threat by Climate Change?

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