Short-Term Waterlogging Depresses Early Growth of Sunflower (Helianthus annuus L.) on Saline Soils with a Shallow Water Table in the Coastal Zone of Bangladesh

Sunflower (Helianthus annuus L.), which is widely grown globally for its high-quality edible oil, is reasonably salt and drought tolerant but it is susceptible to waterlogging. In the saline coastal zone of the Ganges delta, sunflower is often exposed to sudden heavy rainfall during early growth but plant tolerance to such events is not known. Hence, we evaluated the effect of short-term soil inundation (referred to as waterlogging) for 0, 24, 48 and 72 h on sunflower at emergence, 2-leaf, and 4-leaf stages in early- and late-sown crops under field conditions (saline, clay-textured soil, and shallow groundwater). Waterlogging for 24 h did not affect sunflower at any stage but waterlogging for 48 and 72 h suppressed emergence and growth at the 2 and 4-leaf stages. Waterlogging for 72 h completely prevented the emergence for early sowing, whereas emergence was less affected for later sowing. Shoot and root dry weight were most affected at the emergence and 2-leaf stage, not at the 4-leaf stage. In conclusion, waterlogging caused by more than 24 h soil inundation at up to the 4-leaf stage severely depressed emergence and growth, indicating the need for effective drainage at sowing of sunflower in the low-lying coastal saline zone of Bangladesh.

Detecting rice inundation status for water saving and methane emission mitigation measures using Sentinel-1 & ALOS-2/PALSAR-2 Data

<p>Approximately 90% of the world total paddies area and annual output of the rice production are concentrated in monsoon Asia, which has no more land/water resources for further expansion of cultivation. Most rice grows under lowland conditions where currently facing to the fresh water scarcity due to sea-water intrusion accelerated by sea-level rise and land-subsidence, and decelerating freshwater supply by upstream-dam construction. Since the rice production also requires large amount of water (3,000-5,000 L kg<sup>-1</sup> rice), water-saving irrigation practice (e.g., Alternate Wetting and Drying, a.k.a., AWD) is desirable to be implemented in this region to save the water-demand sustainably, and irrigation status need to be evaluated for the decision making on sustainable food security. In addition to the significance of AWD’s role as an adaptation to drought risks, AWD also has a potential to act as an important mitigation-measure by reducing methane emission from paddy soils. This function is very important since rice cropping is responsible for approximately 11% of global anthropogenic CH<sub>4</sub> emissions, and rice has the highest greenhouse gas intensity among the main food crops.</p><p>In order to implement AWD in Asian rice paddies as a mitigation-measure based on a carbon pricing scheme, it is important to evaluate the spatial distribution of AWD paddy fields in the target region. For the detection of AWD-fields versus continuously-flooding fields, it is essential to develop method using EO data to detect soil inundation under rice plants at various growth stages.  In this study, ALOS-2/PALSAR-2 and Sentinel-1 data were used to combine the penetration capacity of L-band SAR data with C-band data capacity to monitor rice growth status with their high temporal resolution.</p><p>The study was conducted in triple rice cropping systems in the Vietnamese Mekong delta (5 sites: Thot Not in Can Tho city; Chau Thanh, Cho Moi, Thoai Son and Tri Ton in An Giang Province, where AWD field campaign was conducted from 2012 to 2017. EO data consisted of ALOS-2/PALSAR-2 every 14 days in 2017/2018 in An Giang province at high resolution observation mode (3-6m resolution) and ScanSAR observation mode (25-100m resolution) every 42 days over the Mekong delta.</p><p>As the result of the classification using the dual-polarization ALOS-2/PALSAR-2 data, soil inundation status could be detected during various rice growth stages. To evaluate rice productivity and GHG emissions from rice fields, we developed a simulation system based on the DeNitrification-Decomposition (DNDC) model which can assimilate PALSAR-2 inundation map and ground observed GHG -flux and rice growth status data on a pixel basis. For spatial extension, rice map, together with rice calendar (sowing date, rice growth status), required as inputs by DNDC are provided by the GeoRice project, based on the use of Sentinel-1 6-day time series. This paper presents the performance of multi-sensor data fusion to realize sustainable agricultural management by mitigating the GHGs emission while maintaining or improving regional fresh water use efficiency for stable food production under climate change pressure.</p>

Estimation of Methane Emissions from Rice Paddies in the Mekong Delta Based on Land Surface Dynamics Characterization with Remote Sensing

In paddy soils in the Mekong Delta, soil archaea emit substantial amounts of methane. Reproducing ground flux data using only satellite-observable explanatory variables is a highly transparent method for evaluating regional emissions. We hypothesized that PALSAR-2 (Phased Array type L-band Synthetic Aperture RADAR) can distinguish inundated soil from noninundated soil even if the soil is covered by rice plants. Then, we verified the reproducibility of the ground flux data with satellite-observable variables (soil inundation and cropping calendar) and with hierarchical Bayesian models. Furthermore, inundated/noninundated soils were classified with PALSAR-2. The model parameters were successfully converged using the Hamiltonian–Monte Carlo method. The cross-validation of PALSAR-2 land surface water coverage (LSWC) with several inundation indices of MODIS (Moderate Resolution Imaging Spectroradiometer) and AMSR-2 (Advanced Microwave Scanning Radiometer-2) data showed that (1) high PALSAR-2-LSWC values were detected even when MODIS and AMSR-2 inundation index values (MODIS-NDWI and AMSR-2-NDFI) were low and (2) low values of PALSAR-2-LSWC tended to be less frequently detected as the MODIS-NDWI and AMSR-2-NDFI increased. These findings indicate the potential of PALSAR-2 to detect inundated soils covered by rice plants even when MODIS and AMSR-2 cannot, and show the similarity between PALSAR-2-LSWC and the other two indices for nonvegetated areas.

Responses of Pinushalepensis seedlings to flooding

Pinushalepensis Mill, seedlings adapted poorly to flooding. Soil inundation up to 40 days induced stem swelling and splitting and inhibited dry weight increment of seedlings. Flooding decreased dry weight increment of shoots, largely by inhibiting formation of secondary needles. However, flooding had much greater inhibitory effects on root growth. Flooding inhibited root growth almost completely and also caused some deterioration of the original root system.