Changes of soil moisture during apple growth based on TVDI index

Based on MODIS data, soil moisture data and field survey data from 2014 to 2018, the consistency of temperature vegetation drought index (TVDL), normalized vegetation water content index (NDWL), vegetation water supply index (VSWI) and soil moisture at 15cm depth (SM) in apple growth in Fuxian county was investigated. Results showed that the spatial and temporal consistency between VSWI and SM calculated by the enhanced vegetation index (EVI) was best; the sensitivity of remote sensing indexes to soil moisture was different in different apple growth stages. The sensitivity of VSWI was the most obvious in different growth stages, and the sensitivity of soil moisture was higher than that of germination, flowering, fruit expansion and maturity. The research findings were consistent with the law of water demand in different growth stages of apple in Fuxian county and the characteristics of precipitation and drought in Fuxian county. The present results could provide a reference for soil moisture monitoring of apple growth by remote sensing. Bangladesh J. Bot. 50(3): 955-961, 2021 (September) Special

Drought Monitoring over West Africa Based on an Ecohydrological Simulation (2003–2018)

In Africa, droughts are causing significant damage to human health and the economy. In West Africa, a severe decline in food production due to agricultural droughts has been reported in recent years. In this study, we simulated ecohydrological variables using the Coupled Land and Vegetation Data Assimilation System, which can effectively evaluate the hydrological water cycle and provide a dynamic evaluation of terrestrial biomass. Using ecohydrological variables (e.g., soil moisture content, leaf area index and vegetation water content) as a drought indicator, we analyzed agricultural droughts in the Sahel-inland region of West Africa during 2003–2018. Results revealed reasonable agreement between the simulated values and the pearl millet yield, and produced a successful quantification of severe droughts in the Sahel-inland region.

Reconstructing Continuous Vegetation Water Content To Understand Sub-daily Backscatter Variations

Microwave observations are sensitive to vegetation water content (VWC). Consequently, the increasing temporal and spatial resolution of spaceborne microwave observations creates a unique opportunity to study vegetation water dynamics and its role in the diurnal water cycle. However, we currently have a limited understanding of sub-daily variations in VWC and how they affect passive and active microwave observations. This is partly due to the challenges associated with measuring internal VWC for validation, particularly non-destructively and at timescales of less than a day. In this study, we aimed to (1) use field sensors to reconstruct diurnal and continuous records of internal VWC of corn, and (2) use these records to interpret the sub-daily behaviour of a 10-day time series of polarimetric L-band backscatter with high temporal resolution. Sub-daily variations of internal VWC were calculated based on the cumulative difference between estimated transpiration and sap flow rates at the base of the stems. Destructive samples were used to constrain the estimates and for validation. The inclusion of continuous surface canopy water estimates (dew or interception) and surface soil moisture allowed us to attribute hour-to-hour backscatter dynamics to either internal VWC, surface canopy water or soil moisture variations. Our results showed that internal VWC varied with 10–20 % during the day in non-stressed conditions, and the effect on backscatter was significant. Diurnal variations of internal VWC and nocturnal dew formation affected vertically polarized backscatter most. Moreover, on a typical dry day, backscatter variations were 1.5 (HH-pol) to 3 (VV-pol) times more sensitive to VWC than to soil moisture. These results demonstrate that radar observations have the potential to provide unprecedented insight into the role of vegetation water dynamics in land-atmosphere interactions at sub-daily timescales.

Validation of SMAP Soil Moisture at Terrestrial National Ecological Observatory Network (NEON) Sites Show Potential for Soil Moisture Retrieval in Forested Areas

Soil moisture influences forest health, fire occurrence and extent, and insect and pathogen impacts, creating a need for regular, globally extensive soil moisture measurements that can only be achieved by satellite-based sensors, such as NASA’s Soil Moisture Active Passive (SMAP). However, SMAP data for forested regions, which account for ~20% of land cover globally, are flagged as unreliable due to interference from vegetation water content, and forests were underrepresented in previous validation efforts, preventing an assessment of measurement accuracy in these biomes. Here we compare over twelve thousand SMAP soil moisture measurements, representing 88 site-years, to in-situ soil moisture measurements from forty National Ecological Observatory Network (NEON) sites throughout the US, half of which are forested. At unforested NEON sites, agreement with SMAP soil moisture (unbiased RMSD: 0.046 m³ m^-3) was similar to previous sparse network validations (which include inflation of the metric due to spatial representativeness errors). For the forested sites, SMAP achieved a reasonable level of accuracy (unbiased RMSD: 0.06 m³ m^-3 or 0.053 m³ m^-3 after accounting for random representativeness errors) indicating SMAP is sensitive to changes in soil moisture in forest ecosystems. Moreover, we identified that both an index of vegetation water content and canopy height were related to mean difference, which incorporates measurement bias and representativeness bias, and suggests a potential approach to improve SMAP algorithm parameterization for forested regions. In addition, expanding the number and extent of soil moisture measurements at forested validation sites would likely further reduce mean difference by minimizing representativeness errors.

Validation of SMAP Soil Moisture at Terrestrial National Ecological Observatory Network (NEON) Sites Show Potential for Soil Moisture Retrieval in Forested Areas

Soil moisture influences forest health, fire occurrence and extent, and insect and pathogen impacts, creating a need for regular, globally extensive soil moisture measurements that can only be achieved by satellite-based sensors, such as NASA’s Soil Moisture Active Passive (SMAP). However, SMAP data for forested regions, which account for ~20% of land cover globally, are flagged as unreliable due to interference from vegetation water content, and forests were underrepresented in previous validation efforts, preventing an assessment of measurement accuracy in these biomes. Here we compare over twelve thousand SMAP soil moisture measurements, representing 88 site-years, to in-situ soil moisture measurements from forty National Ecological Observatory Network (NEON) sites throughout the US, half of which are forested. At unforested NEON sites, agreement with SMAP soil moisture (unbiased RMSD: 0.046 m³ m^-3) was similar to previous sparse network validations (which include inflation of the metric due to spatial representativeness errors). For the forested sites, SMAP achieved a reasonable level of accuracy (unbiased RMSD: 0.06 m³ m^-3 or 0.053 m³ m^-3 after accounting for random representativeness errors) indicating SMAP is sensitive to changes in soil moisture in forest ecosystems. Moreover, we identified that both an index of vegetation water content and canopy height were related to mean difference, which incorporates measurement bias and representativeness bias, and suggests a potential approach to improve SMAP algorithm parameterization for forested regions. In addition, expanding the number and extent of soil moisture measurements at forested validation sites would likely further reduce mean difference by minimizing representativeness errors.

Inferring the effects of surface canopy water on VOD estimation from L-band backscatter

<p>Quantification of vegetation parameters such as Vegetation Optical Depth (VOD) and Vegetation Water Content (VWC) can be used for better irrigation management, yield forecasting, and soil moisture estimation. Since VOD is directly related to vegetation water content and canopy structure, it can be used as an indicator for VWC. Over the past few decades, optical and passive microwave satellite data have mostly been used to monitor VWC. However, recent research is using active data to monitor VOD and VWC benefitting from their high spatial and temporal resolution.</p><p>Attenuation of the microwave signal through the vegetation layer is parametrized by the VOD. VOD is assumed to be linearly related to VWC with the proportionality constant being an empirical parameter b. For a given wavelength and polarization, b is assumed static and only parametrized as a function of vegetation type. The hypothesis of this study is that the VOD is not similar for dry and wet vegetation and the static linear relationship between attenuation and vegetation water content is a simplification of reality.</p><p>The aim of this research is to understand the effect of surface canopy water on VOD estimation and the relationship between VOD and vegetation water content during the growing season of a corn canopy. In addition to studying the dependence of VOD on bulk VWC for dry and wet vegetation, the effect of different factors, such as different growth stages and internal vegetation water content is investigated using time series analysis.</p><p>A field experiment was conducted in Florida, USA, for a full growing season of sweet corn. The corn field was scanned every 30 minutes with a truck-mounted, fully polarimetric, L-band radar. Pre-dawn vegetation water content was measured using destructive sampling three times a week for a full growing season. VWC could therefore be analyzed by constituent (leaf, stem, ear) or by height. Meteorological data, surface canopy water (dew or interception), and soil moisture were measured every 15 minutes for the entire growing season.</p><p>The methodology of Vreugdenhil et al.  [1], developed by TU Wien for ASCAT data, was adapted to present a new technique to estimate VOD from single-incidence angle backscatter data in each polarization. The results showed that the effect of surface canopy water on the VOD estimation increased by vegetation biomass accumulation and the effect was higher in the VOD estimated from the co-pol compared with the VOD estimated from the cross-pol. Moreover, the surface canopy water considerably affected the regression coefficient values (b-factor) of the linear relationship between VOD and VWC from dry and wet vegetation. This finding suggests that considering a similar b-factor for the dry and the wet vegetation will introduce errors in soil moisture retrievals. Furthermore, it highlights the importance of considering canopy wetness conditions when using tau-omega.</p><ul><li>[1] Vreugdenhil,W. A. Dorigo,W.Wagner, R. A. De Jeu, S. Hahn, andM. J. VanMarle, “Analyzing the vegetation parameterization in the TU-Wien ASCAT soil moisture retrieval,” IEEE Transactions on Geoscience and Remote Sensing, vol. 54, pp. 3513–3531, 2016</li> </ul>