Seasonal and interannual relations between precipitation, surface soil moisture and vegetation dynamics in the North American monsoon region

Méndez-Barroso, Luis A.; Vivoni, Enrique R.; Watts, Christopher J.; Rodríguez, Julio

doi:10.1016/j.jhydrol.2009.08.009

Cited by 125 publications

(113 citation statements)

References 51 publications

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“…Because autumn rainfall is relatively low, increasing precipitation in September can enhance plant growth or prevent vegetation from early withering. A 1-month temporal lag between vegetation response and precipitation variation has also been reported by many previous studies (e.g., Weiss et al 2004;Nezlin et al 2005;Piao et al 2006;Fabricante et al 2009;Méndez-Barroso et al 2009;Cui and Shi 2010;Zhong et al 2010).…”

Section: Correlations Between Monthly Ndvi and Precipitationsupporting

confidence: 82%

“…The regional and seasonal difference of precipitation, to a certain extent, determines the vegetation pattern. Since the 1980s, a number of researchers have examined the correlations between vegetation characteristics and precipitation at regional or national scales (e.g., Roerink et al 2003;Nezlin et al 2005;Bates et al 2006;Piao et al 2006;Suzuki et al 2007;Méndez-Barroso et al 2009;García-Romero et al 2010;Zhong et al 2010;Meng et al 2011). However, few studies have documented their relationships at fine temporal and spatial scales.…”

Section: Introductionmentioning

confidence: 99%

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Interannual variability and correlation of vegetation cover and precipitation in Eastern China

Jiang

Zhang

et al. 2013

Theor Appl Climatol

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Based on the SPOT/VEGETATION Normalized Difference Vegetation Index (NDVI) data and daily precipitation data of 357 meteorological stations, the spatial and temporal variability of vegetation cover, measured by NDVI, and precipitation as well as their relationships are investigated in Eastern China, which is portioned into three subregions (regions I, II, and III), for the period 1998-2010. The results show that high NDVI values appear mainly in Northeastern China and in August while high precipitation (PRETOT) occurs in Southeastern China and in July (June for Southern China). Extreme precipitation days (RD95p) and amount (EPRETOT) coincide well with PRETOT. Extreme precipitation intensity (RINTEN) has a similar spatial variability to PRETOT but with a smaller seasonal variation than PRETOT. Growing season NDVI is positively correlated with PRETOT in 11.7 % of the study area (mostly in arid to subhumid regions of Northern China), where precipitation is a limiting factor for vegetation growth. In contrast, a negative correlation between growing season NDVI and PRETOT is found in 4.8 % of the study area, mostly in areas around the Yangtze River and deep Northeastern China. No significant correlations between these two variables are found for the other regions because vegetation response to precipitation is affected by other factors such as temperature, radiation, and human disturbance. On a monthly scale, there is a positive correlation between NDVI and PRETOT in May (for region II) and September (all subregions except region I). NDVI variations lag 1 month behind PRETOT in June (for region I) and October. Correlations between NDVI and RD95p, EPRETOT are similar to that with PRETOT, but the relationships between NDVI and RINTEN are relatively weaker than with PRETOT. This study provides the technical basis for agriculture development and ecological construction in Eastern China.

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Section: Correlations Between Monthly Ndvi and Precipitationsupporting

confidence: 82%

Section: Introductionmentioning

confidence: 99%

Interannual variability and correlation of vegetation cover and precipitation in Eastern China

Jiang

Zhang

et al. 2013

Theor Appl Climatol

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“…Most commonly, precipitation and soil moisture have been used as defining variables (Chen et al, 2014;Huxman, 2004;Méndez-Barroso et al, 2009;Wang et al, 2007). Both of these have shown generally meaningful correlations with ecosystem performance (by various measures such as the normalised difference vegetation index, NDVI, and above-ground net primary production).…”

Section: Introductionmentioning

confidence: 99%

Large-scale vegetation responses to terrestrial moisture storage changes

Andrew

Guan

Batelaan

2017

Hydrol. Earth Syst. Sci.

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Abstract. The normalised difference vegetation index (NDVI) is a useful tool for studying vegetation activity and ecosystem performance at a large spatial scale. In this study we use the Gravity Recovery and Climate Experiment (GRACE) total water storage (TWS) estimates to examine temporal variability of the NDVI across Australia. We aim to demonstrate a new method that reveals the moisture dependence of vegetation cover at different temporal resolutions. Time series of monthly GRACE TWS anomalies are decomposed into different temporal frequencies using a discrete wavelet transform and analysed against time series of the NDVI anomalies in a stepwise regression. The results show that combinations of different frequencies of decomposed GRACE TWS data explain NDVI temporal variations better than raw GRACE TWS alone. Generally, the NDVI appears to be more sensitive to interannual changes in water storage than shorter changes, though grassland-dominated areas are sensitive to higher-frequencies of water-storage changes. Different types of vegetation, defined by areas of land use type, show distinct differences in how they respond to the changes in water storage, which is generally consistent with our physical understanding. This unique method provides useful insight into how the NDVI is affected by changes in water storage at different temporal scales across land use types.

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“…However, the direct relationships between these components have not been intensively studied owing to the paucity of regional datasets (Méndez-Barroso et al 2009). Remote sensing by making use of satellite imagery has been recognized as a successful tool for monitoring ecological and hydrological variables such as soil moisture, ET, and vegetation grossness with different spatial resolutions (Schmugge et al 2002).…”

Section: Introductionmentioning

confidence: 99%

“…Most of the previous studies on this relationship have pointed out a time lag between NDVI and hydrologic variables. Investigations of the relationships between ecological variables and hydrologic components have thus far been limited to the few local regions with mostly semi-arid climatic conditions (Schultz and Halpert 1993;Nicholson and Farrar 1994;Farrar et al 1994;Szilagyi et al 1998;Wang et al 2001Wang et al , 2007Adegoke and Carleton 2002;Nagler et al 2005;Kurc and Small 2007;Suzuki et al 2007;Méndez-Barroso et al 2009;Nandintsetseg et al 2010;Zribi et al 2010). We estimate the relationships between soil moisture and ET in this study with MODIS NDVI at 132 stations located on different continents around the world ( Fig.…”

Section: Introductionmentioning

confidence: 99%

Ecosystem-dynamics link to hydrologic variations for different land-cover types

Choi¹,

Mu²,

Kim³

et al. 2017

Terr. Atmos. Ocean. Sci.

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The soil moisture and evapotranspiration (ET) influence on ecosystem dynamics has been studied only in a limited way owing to the lack of large-scale measurements. The Normalized Difference Vegetation Index (NDVI) data retrieved using the Moderate Resolution Imaging Spectroradiometer (MODIS) was successfully used in this study to identify the ecological relationships that involve soil moisture and ET at 132 sites located on different continents around the world. Optimal relationships exist between NDVI and soil moisture within time lags of 10 days at forest and grassland sites, and 25 days at cropland and shrub land sites. The ecological correlations between NDVI and the hydrological variables are affected mainly by the land-cover type. The densely vegetated areas show shorter time lags for NDVI to ET owing to canopy evaporation and plant transpiration, which are almost simultaneous with NDVI.

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Seasonal and interannual relations between precipitation, surface soil moisture and vegetation dynamics in the North American monsoon region

Cited by 125 publications

References 51 publications

Interannual variability and correlation of vegetation cover and precipitation in Eastern China

Interannual variability and correlation of vegetation cover and precipitation in Eastern China

Large-scale vegetation responses to terrestrial moisture storage changes

Ecosystem-dynamics link to hydrologic variations for different land-cover types

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