Soil moisture change analysis under watershed management practice using in situ and remote sensing data in a paired watershed

Kazemzadeh, Majid; Salajegheh, Ali; Malekian, Arash; Liaghat, Abdolmajid; Hashemi, Hossein

doi:10.1007/s10661-021-09078-y

Cited by 4 publications

(5 citation statements)

References 82 publications

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“…The upper and lower thresholds of land surface temperature are represented on both sides of the characteristic space, and the calculated TVDI values are subsequently used to infer the degree of drought, which can more accurately determine the SM. A significant negative correlation was found between the TVDI and SM in different arid and semi-arid regions (Guo et al, 2009; Rev Bras Cienc Solo 2022;46:e0220113 Kazemzadeh et al, 2021). Due to the discrepancies in climate and soil environment in different regions, the feature space (Vis-TVDI) and LST that constitute the TVDI were modified in a suitable manner, summarized as follows: (a) replaced NDVI and used the modified soil adjusted VI (MSAVI), soil adjusted VI (SAVI), and enhanced VI (EVI) for evaluation (Zhang et al, 2014a;Ma et al, 2017;Wu et al, 2019); (b) modified the soil line and increased the combination of shortwave infrared (SWIR), near-infrared (NIR), and red light bands to reduce the sensitivity of VI to the soil background (Feng et al, 2011a;Chen et al, 2019;Liu et al, 2021b); (c) considered the influence of factors such as terrain (digital elevation model, DEM) and environmental data on the LST and made corrections to the LST (Ran et al, 2005;Sun et al, 2010;Liu et al, 2013).…”

Section: Introductionmentioning

confidence: 93%

Inversion of soil moisture and its feedback on ecological restoration in arid and semi-arid areas of northwest China

Liu¹,

Yuanyuan²,

Zhou³

et al. 2022

Revista Brasileira De Ciência Do Solo

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Soil moisture (SM) plays an important role in regulating the global water cycle, especially in arid areas, and is one of the main indicators of ecological environmental health. Although traditional methods can accurately measure SM at a single sample site, they are limited in large-scale and dynamic SM monitoring. Therefore, we used the Landsat images as the data source and the soil adjusted vegetation index (SAVI) to build the adjusted SAVI (aSAVI) index by modifying the soil adjustment parameter L and introducing the short-wave infrared band. According to the theory of temperature vegetation dryness index (TVDI) and feature space, we introduced a model, combined the measured SM data (Minqin Basin, China) through a comparative analysis of four vegetation indices (NDVI, SAVI, MSAVI, aSAVI) determine the optimal model. Taking the Minqin Basin as the study area, the spatiotemporal variation characteristics of SM in three sub-regions (the entire study area, irrigated region, and periphery of the irrigated regions) were quantitatively analyzed and compared in four different periods: pre-Comprehensive Treatment Program of the Shiyang River Basin (pre-CTSRB) (2000)(2001)(2002)(2003)(2004)(2005), CTSRB I (2006-2010), CTSRB II (2011-2016), and CTSRB-end (2017-2021) to evaluate the ecological restoration effects of treatment programs from the SM perspective. The results showed that: 1) SM values derived from TVDI inversion and the aSAVI were more accurate, and the model sensitivity decreased with soil depth; 2) the mean value of SM fluctuated across the four periods but decreased slightly over the entire time series. The spatial variations of the SM were characterized by a "descending then ascending" trend. Soil moisture increased in 21.35 % of areas at 0.00-0.10 m in the past 22 years, and 59.66 % at 0.10-0.20 m. There was a negative correlation between the mean variation trend of SM and the percentage of area where SM fell in different periods; 3) the treatment program positively affected the ecological restoration of the Minqin Basin from the SM perspective. The area where SM increased was larger than that of decreasing SM, especially in 0.10-0.20 m soil layer. The increase can promote growth and confer resistance to desertification.

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Section: Introductionmentioning

confidence: 93%

Inversion of soil moisture and its feedback on ecological restoration in arid and semi-arid areas of northwest China

Liu¹,

Yuanyuan²,

Zhou³

et al. 2022

Revista Brasileira De Ciência Do Solo

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“…In recent decades, remote sensing techniques have been developed to estimate soil moisture (Moran et al, 2004;Amani et al, 2016;Mohamed et al, 2020;Kazemzadeh et al, 2021;). Radiation including nearinfrared (NIR), visible light (VIS), thermal infrared (TIR), soil moisture ocean salinity (SMOS), short wave infrared (SWIR) reflectance, soil moisture active passive (SMAP), and microwave are used to retrieve soil moisture data from the topsoil.…”

Section: Introductionmentioning

confidence: 99%

“…Integration of coarse spatial resolution microwave data with an optical/thermal infrared retrieval using a downscaling factor is the most extensively used satellite-based approach (Moran et al, 2004;Mobasheri, 2016;Gao et al, 2017;Amazirh et al, 2018) Serrano et al, 2004;Amazirh et al, 2018). TVDI is frequently utilized due to its great precision and ease in monitoring soil moisture (Younis and Iqbal, 2015;Paddies, 2016;Peng et al, 2020;Kazemzadeh et al, 2021). TVDI is an optical/thermal remote sensing metric related to soil moisture fluctuation.…”

Section: Introductionmentioning

confidence: 99%

“…TVDI can accurately reflect soil moisture under diverse tree species, they found. Several studies have employed TVDI as a soil moisture indicator and shown good performance in different locations of the world (Peng et al, 2020;Kazemzadeh et al, 2021). The NDVI measures chlorophyll and vegetation cover.…”

Section: Introductionmentioning

confidence: 99%

“…Soil moisture interacts with various hydrological variables, including surface water, groundwater, and evaporation, and is affected by terrain, climate, soil texture, and vegetation cover. Soil moisture is vital to hydrological processes including the energy-water exchange cycle (Dong et al, 2019;Bartels et al, 2021;Kazemzadeh et al, 2021). While remote sensing is considered an alternative approach for the estimation of the environmental factors at a watershed scale, the results need to be validated with ground-based measurement.…”

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

Soil Moisture Estimation Using Multitemporal Remote Sensing Data in Tabunio Watershed

2022

Int. J. Biosci.

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Soil moisture, vegetation cover, and land surface temperature influence water energy balance, eco-hydrological processes, and water resources management. This research focused on the spatial and temporal variability of soil moisture, vegetation cover, land surface temperature, and Temperature Vegetation Dryness Index (TVDI) in Tabunio watershed. In this research, soil moisture and vegetation cover data were recorded and statistically evaluated from 2005 until 2020 using remote sensing data. Soil moisture, vegetation cover, and land surface temperature were significantly different over the research period. Increased vegetation cover had an inverse influence on land surface temperature and TVDI while directly affecting soil moisture. TVDI averages were 0 -0.83. Decreased soil dryness in the period 2022 can increase water availability by controlling water resources.Proper watershed management can improve soil moisture and water availability. Vegetation cover protection and biological activities can be used to restore the watersheds. The approach combination of LST and NDVI to calculate TVDI is able to estimate the soil moisture as its estimation is extremely important for the evaluation of the overall ecological setting as well as the monitoring of the moisture content of wetland environments.

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Characterization of dominant factors on evapotranspiration with seasonal soil water changes in two adjacent forests in the semiarid Loess Plateau

Chen

Liu²,

Lyu³

et al. 2022

Journal of Hydrology

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Soil moisture change analysis under watershed management practice using in situ and remote sensing data in a paired watershed

Cited by 4 publications

References 82 publications

Inversion of soil moisture and its feedback on ecological restoration in arid and semi-arid areas of northwest China

Inversion of soil moisture and its feedback on ecological restoration in arid and semi-arid areas of northwest China

Soil Moisture Estimation Using Multitemporal Remote Sensing Data in Tabunio Watershed

Characterization of dominant factors on evapotranspiration with seasonal soil water changes in two adjacent forests in the semiarid Loess Plateau

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