scholarly journals Investigation of rootzone salinity with field monitoring system at tsunami affected rice fields in Miyagi, Japan

2016 ◽  
Author(s):  
Ieyasu Tokumoto ◽  
Katsumi Chiba ◽  
Masaru Mizoguchi ◽  
Hideki Miyamoto
Keyword(s):  
Soil Moisture ◽  
Monitoring System ◽  
Groundwater Level ◽  
Saltwater Intrusion ◽  
High Salinity ◽  
Sea Water ◽  
Soil Surface ◽  
Field Monitoring ◽  
Aquifer Management ◽  
Miyagi Prefecture

Abstract. After the 2011 Tohoku earthquake, thirteen thousand hectares of farmlands were damaged by massive Tsunami near coastal sites in Miyagi, Japan. Some eighty percent of the damaged farmlands have been recovered in 2014, but subsidence and high salinity groundwater make it difficult to completely remove salinity from the soil. To solve the problem, management of saltwater intrusion plays an important role in rootzone salinity control with the Field Monitoring System (FMS), which is remote sensing technology of wireless real-time soil data through the internet data sever to investigate high soil moisture and high salinity in tsunami affected fields. Using the FMS with the time domain transmission system, we monitored soil moisture, electrical conductivity (EC), groundwater level, and EC of groundwater at tsunami damaged paddy fields. The field measurements of the FMS were conducted at two sites of tsunami damaged farmlands in Iwanuma and Higashimatsushima of Miyagi prefecture, Japan. After the Tohoku disaster, co-seismic subsidence of 17–21 cm and 50–60 cm of the land was reported at the sites, respectively. Our findings were high EC of groundwater (> 35 dS m−1) due to intrusion of sea water into groundwater in 2013. Although the shallow groundwater provided salinity to the soil surface in 2014, the FEM allowed us to monitor high EC (< 6 dS m−1) even in saturated soil condition. Rainfall facilitated desalination process, but the saline groundwater level reached the soil surface after heavy rainfall, suggesting that coastal zone aquifer management is essential to prevent saltwater intrusion into groundwater.

Distribution of moisture and salinity under deficit irrigation and irrigation water salinity in an alternative trickle irrigation system of tape

2013 ◽  
Vol 13 (2) ◽  
pp. 394-402
Author(s):  
Jahangir Abedi-Koupai ◽  
Mojtaba Khoshravesh ◽  
Mohammad Ebrahim Zanganeh
Keyword(s):  
Soil Moisture ◽  
Crop Yield ◽  
Deficit Irrigation ◽  
High Salinity ◽  
Irrigation System ◽  
Soil Surface ◽  
Water Requirement ◽  
Plant Water ◽  
Trickle Irrigation ◽  
Salinity Levels

This study was performed to investigate the horizontal and vertical distribution of soil moisture and salinity using an alternative trickle irrigation system of drip tape. Four main treatments consisting of 100, 80, 70, and 60% of the plants’ water requirements and three sub-treatments of 2.1, 4.6, and 10.2 dS/m, were conducted. Following irrigation, the soil moisture and salinity distribution around the emitters were measured every 24 h. The results showed that the accumulation of salts in the soil reduced the evaporation from the soil surface in treatments with high salinity. Therefore, in treatments with a low plant water requirement and high salinity levels, the volume of water in the soil is greater than in treatments with a high plant water requirement and low salinity levels. Although the crop yield is reduced with deficit irrigation, the saved water can be used to increase the area under cultivation, leading to increases in the overall crop yield.

scholarly journals Variation in Soil Properties Regulate Greenhouse Gas Fluxes and Global Warming Potential in Three Land Use Types on Tropical Peat

Atmosphere ◽  
2018 ◽  
Vol 9 (12) ◽  
pp. 465 ◽  
Author(s):  
Kiwamu Ishikura ◽  
Untung Darung ◽  
Takashi Inoue ◽  
Ryusuke Hatano
Keyword(s):  
Global Warming ◽  
Soil Moisture ◽  
Groundwater Level ◽  
Global Warming Potential ◽  
C:N Ratio ◽  
Co2 Flux ◽  
Nitrate Content ◽  
N2o Flux ◽  
Ch4 Flux ◽  
In The Beginning

This study investigated spatial factors controlling CO2, CH4, and N2O fluxes and compared global warming potential (GWP) among undrained forest (UDF), drained forest (DF), and drained burned land (DBL) on tropical peatland in Central Kalimantan, Indonesia. Sampling was performed once within two weeks in the beginning of dry season. CO2 flux was significantly promoted by lowering soil moisture and pH. The result suggests that oxidative peat decomposition was enhanced in drier position, and the decomposition acidify the peat soils. CH4 flux was significantly promoted by a rise in groundwater level, suggesting that methanogenesis was enhanced under anaerobic condition. N2O flux was promoted by increasing soil nitrate content in DF, suggesting that denitrification was promoted by substrate availability. On the other hand, N2O flux was promoted by lower soil C:N ratio and higher soil pH in DBL and UDF. CO2 flux was the highest in DF (241 mg C m−2 h−1) and was the lowest in DBL (94 mg C m−2 h−1), whereas CH4 flux was the highest in DBL (0.91 mg C m−2 h−1) and was the lowest in DF (0.01 mg C m−2 h−1), respectively. N2O flux was not significantly different among land uses. CO2 flux relatively contributed to 91–100% of GWP. In conclusion, it is necessary to decrease CO2 flux to mitigate GWP through a rise in groundwater level and soil moisture in the region.

scholarly journals Mapping the Groundwater Level and Soil Moisture of a Montane Peat Bog Using UAV Monitoring and Machine Learning

2021 ◽  
Vol 13 (5) ◽  
pp. 907
Author(s):  
Theodora Lendzioch ◽  
Jakub Langhammer ◽  
Lukáš Vlček ◽  
Robert Minařík
Keyword(s):  
Machine Learning ◽  
Soil Moisture ◽  
Spatial Data ◽  
Groundwater Level ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Sampling Strategy ◽  
Peat Bog ◽  
Strong Impact ◽  
Ground Truth Data

One of the best preconditions for the sufficient monitoring of peat bog ecosystems is the collection, processing, and analysis of unique spatial data to understand peat bog dynamics. Over two seasons, we sampled groundwater level (GWL) and soil moisture (SM) ground truth data at two diverse locations at the Rokytka Peat bog within the Sumava Mountains, Czechia. These data served as reference data and were modeled with a suite of potential variables derived from digital surface models (DSMs) and RGB, multispectral, and thermal orthoimages reflecting topomorphometry, vegetation, and surface temperature information generated from drone mapping. We used 34 predictors to feed the random forest (RF) algorithm. The predictor selection, hyperparameter tuning, and performance assessment were performed with the target-oriented leave-location-out (LLO) spatial cross-validation (CV) strategy combined with forward feature selection (FFS) to avoid overfitting and to predict on unknown locations. The spatial CV performance statistics showed low (R2 = 0.12) to high (R2 = 0.78) model predictions. The predictor importance was used for model interpretation, where temperature had strong impact on GWL and SM, and we found significant contributions of other predictors, such as Normalized Difference Vegetation Index (NDVI), Normalized Difference Index (NDI), Enhanced Red-Green-Blue Vegetation Index (ERGBVE), Shape Index (SHP), Green Leaf Index (GLI), Brightness Index (BI), Coloration Index (CI), Redness Index (RI), Primary Colours Hue Index (HI), Overall Hue Index (HUE), SAGA Wetness Index (TWI), Plan Curvature (PlnCurv), Topographic Position Index (TPI), and Vector Ruggedness Measure (VRM). Additionally, we estimated the area of applicability (AOA) by presenting maps where the prediction model yielded high-quality results and where predictions were highly uncertain because machine learning (ML) models make predictions far beyond sampling locations without sampling data with no knowledge about these environments. The AOA method is well suited and unique for planning and decision-making about the best sampling strategy, most notably with limited data.

Seasonal activity and estivation of lumbricid earthworms in the midlands of Tasmania

Soil Research ◽  
1994 ◽  
Vol 32 (6) ◽  
pp. 1355 ◽  
Author(s):  
RB Garnsey
Keyword(s):  
Soil Moisture ◽  
Adult Development ◽  
Survival Rates ◽  
Soil Surface ◽  
Early Spring ◽  
Lumbricus Rubellus ◽  
Late Winter ◽  
Cocoon Production ◽  
Density And Biomass ◽  
Earthworm Activity

Earthworms have the ability to alleviate many soil degradational problems in Australia. An attempt to optimize this resource requires fundamental understanding of earthworm ecology. This study reports the seasonal changes in earthworm populations in the Midlands of Tasmania (<600 mm rainfall p.a.), and examines, for the first time in Australia, the behaviour and survival rates of aestivating earthworms. Earthworms were sampled from 14 permanent pastures in the Midlands from May 1992 to February 1994. Earthworm activity was significantly correlated with soil moisture; maximum earthworm activity in the surface soil was evident during the wetter months of winter and early spring, followed by aestivation in the surface and subsoils during the drier summer months. The two most abundant earthworm species found in the Midlands were Aporrectodea caliginosa (maximum of 174.8 m-2 or 55.06 g m-2) and A. trapezoides (86 m-2 or 52.03 g m-2), with low numbers of Octolasion cyaneum, Lumbricus rubellus and A. rosea. The phenology of A. caliginosa relating to rainfall contrasted with that of A. trapezoides in this study. A caliginosa was particularly dependent upon rainfall in the Midlands: population density, cocoon production and adult development of A. caliginosa were reduced as rainfall reduced from 600 to 425 mm p.a. In contrast, the density and biomass of A. trapezoides were unaffected by rainfall over the same range: cocoon production and adult development continued regardless of rainfall. The depth of earthworm aestivation during the summers of 1992-94 was similar in each year. Most individuals were in aestivation at a depth of 150-200 mm, regardless of species, soil moisture or texture. Smaller aestivating individuals were located nearer the soil surface, as was shown by an increase in mean mass of aestivating individuals with depth. There was a high mortality associated with summer aestivation of up to 60% for juvenile, and 63% for adult earthworms in 1993 in the Midlands. Cocoons did not survive during the summers of 1992 or 1994, but were recovered in 1993, possibly due to the influence of rainfall during late winter and early spring.

scholarly journals Potential Applications of GNSS-R Observations over Agricultural Areas: Results from the GLORI Airborne Campaign

2018 ◽  
Vol 10 (8) ◽  
pp. 1245 ◽  
Author(s):  
Mehrez Zribi ◽  
Erwan Motte ◽  
Nicolas Baghdadi ◽  
Frédéric Baup ◽  
Sylvia Dayau ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Signal To Noise Ratio ◽  
Soil Surface ◽  
Satellite System ◽  
Area Index ◽  
Vegetation Height ◽  
Study Sites ◽  
Global Navigation Satellite ◽  
Vegetation Characteristic ◽  
Agricultural Areas

The aim of this study is to analyze the sensitivity of airborne Global Navigation Satellite System Reflectometry (GNSS-R) on soil surface and vegetation cover characteristics in agricultural areas. Airborne polarimetric GNSS-R data were acquired in the context of the GLORI’2015 campaign over two study sites in Southwest France in June and July of 2015. Ground measurements of soil surface parameters (moisture content) and vegetation characteristics (leaf area index (LAI), and vegetation height) were recorded for different types of crops (corn, sunflower, wheat, soybean, vegetable) simultaneously with the airborne GNSS-R measurements. Three GNSS-R observables (apparent reflectivity, the reflected signal-to-noise-ratio (SNR), and the polarimetric ratio (PR)) were found to be well correlated with soil moisture and a major vegetation characteristic (LAI). A tau-omega model was used to explain the dependence of the GNSS-R reflectivity on both the soil moisture and vegetation parameters.

A neutron field monitoring system for collider experiments

2017 ◽  
Vol 60 (2) ◽  
pp. 167-174 ◽  
Author(s):  
A. M. Gribushin ◽  
A. I. Demianov ◽  
A. A. Ershov ◽  
A. A. Kaminskiy ◽  
V. S. Lukanin ◽  
...  
Keyword(s):  
Monitoring System ◽  
Neutron Field ◽  
Field Monitoring

scholarly journals The environmental forming and productional functions of the haloxylon aphyllum in the Karnabchul desert

2019 ◽  
pp. 34-38
Author(s):  
E. Z. Shamsutdinova
Keyword(s):  
Soil Moisture ◽  
Outer Part ◽  
Soil Surface ◽  
Hydrothermal Conditions ◽  
Noticeable Effect ◽  
Soil Layers ◽  
Haloxylon Aphyllum ◽  
Aged State ◽  
Ephemeral Vegetation ◽  
Black Saxaul

We have conducted investigation of the environmental function of the desert tree of black saxaul (Haloxylon aphyllum) in the Karnabchul desert. As a result, it was found that different age plants of black saxaul had different effects on the degree of illumination. The greatest influence on the intensity of solar radiation was exerted by the saxaul plant of the black middle-aged state, the least the old generative individuals. Saxaul black had a significant impact on the temperature of the air: in the daytime, especially in the period 13-16 h, reducing the temperature under the crown and on the edge of the crown, and at night increasing it in the same areas. It also had a noticeable effect on the temperature of the soil. The temperature of the soil surface under the crown at night is higher, and during the day the warming was slower than in the outer part of the saxaul crown. Under the influence of black saxaul and soil moisture changed. Under the saxaul crown soil moisture is significantly higher compared to the control (open natural pastures). The highest soil moisture was observed in the upper soil layers at the base of the saxaul trunk. As a result, under the environmental action of black saxaul more favorable hydrothermal conditions for the growth and development of natural wormwood-ephemeral vegetation under the protection of strips and adjacent areas of pastures are formed. The result of production activities chemotaxonomic postbestowal bands consists of two following components: production of fodder mass of the Haloxylon and fodder productivity of wormwood-ephemeral vegetation of natural pastures. By increasing the yield of natural pastures under the protection of pasture protection strips and the harvest of the black saxaul fodder productivity of desert pastures increases more than twice.

scholarly journals Investigation of Sentinel-1 Derived Land Subsidence Using Wavelet Tools And Triple Exponential Smoothing Algorithm In Lagos, Nigeria

2021 ◽  
Author(s):  
Femi Emmanuel Ikuemonisan ◽  
Vitalis Chidi Ozebo ◽  
Olawale Babatunde Olatinsu
Keyword(s):  
Soil Moisture ◽  
Land Subsidence ◽  
Groundwater Level ◽  
Exponential Smoothing ◽  
Future Trend ◽  
Smoothing Algorithm ◽  
Groundwater Abstraction ◽  
Groundwater Level Fluctuations ◽  
History Of ◽  
Sbas Insar

Abstract Lagos has a history of long-term groundwater abstraction that is often compounded by the rising indiscriminate private borehole and water well proliferation. This has resulted in various forms of environmental degradation, including land subsidence. Prediction of the temporal evolution of land subsidence is central to successful land subsidence management. In this study, a triple exponential smoothing algorithm was applied to predict the future trend of land subsidence in Lagos. Land subsidence time series is computed with SBAS-InSAR technique with Sentinel-1 acquisitions from 2015 to 2019. Besides, Matlab wavelet tool was implemented to investigate the periodicity within land displacement signal components and to understand the relationship between the observed land subsidence, and groundwater level change and that of soil moisture. Results show that land subsidence in the LOS direction varied approximately between –94 and 15 mm/year. According to the wavelet-based analysis result, land subsidence in Lagos is partly influenced by both groundwater level fluctuations and soil moisture variability. Evaluation of the proposed model indicates good accuracy, with the highest residual of approximately 8%. We then used the model to predict land subsidence between the years 2020 and 2023. The result showed that by the end of 2023 the maximum subsidence would reach 958 mm which is approximately 23% increase.

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