scholarly journals The Effect of Climatic Changes on Vertical Moisture Exchange in Soils

2021 ◽  
pp. 47-66
Author(s):  
Keyword(s):  
Soil Moisture ◽  
Moisture Transfer ◽  
Water Vapor Pressure ◽  
Weather Conditions ◽  
Climatic Changes ◽  
Weather Factors ◽  
Moisture Exchange ◽  
Groundwater Levels ◽  
The Impact

The effect of climatic changes on surface and underground runoff cannot be explained without studying such changes on such processes of moisture transfer in soils as infiltration, evaporation, migration of moisture to the frost front. These processes are components of moisture exchange in soils and almost completely determine the mechanisms of runoff formation and its climatic interconformity. The paper discloses the main links of vertical moisture exchange in soils with environmental factors such as temperature, precipitation, wind speed and water vapor pressure. On the example of the Volga basin, changes in moisture flows in soils over the past decades are considered. Methods. To reveal the patterns of moisture exchange, a physically sound mathematical model of vertical heat-moisture transfer in soils and snow cover was used. Numerical experiments were carried out to assess the impact of all the main weather factors that cause long-term changes in vertical moisture flows in soils for the period 1952-2019. Results. Calculations showed that in the 1970s there were significant changes in soil moisture flows. There was a preferential increase in downstream flows and a decrease in upstream flows, which under certain weather conditions led to an increase in the level of groundwater. In recent decades, the growth of descending soil moisture flows in the river basin. Volga and, accordingly, groundwater levels have slowed down.

Evaluation of 2018 drought and effectiveness of adaptation measures in the Netherlands

2020 ◽  
Author(s):  
Marjolein H.J. van Huijgevoort ◽  
Janine A. de Wit ◽  
Ruud P. Bartholomeus
Keyword(s):  
Soil Moisture ◽  
The Netherlands ◽  
Capillary Rise ◽  
Hydrological Drought ◽  
Water Levels ◽  
Severe Drought ◽  
Drought Event ◽  
Groundwater Levels ◽  
The Impact

<p>Extreme dry conditions occurred over the summer of 2018 in the Netherlands. This severe drought event led to very low groundwater  and surface water levels. These impacted several sectors like navigation, agriculture, nature and drinking water supply. Especially in the Pleistocene uplands of the Netherlands, the low groundwater levels had a large impact on crop yields and biodiversity in nature areas. Projections show that droughts with this severity will occur more often in the future due to changes in climate. To mitigate the impact of these drought events, water management needs to be altered.</p><p>In this study, we evaluated the 2018 drought event in the sandy regions of the Netherlands and studied which measures could be most effective to mitigate drought impact. We have included meteorological, soil moisture and hydrological drought and the propagation of the drought through these types. Droughts were determined with standardized indices (e.g. Standardized Precipitation Index) and the variable threshold level method. Investigated measures were, for example, higher water levels in ditches, reduced irrigation from groundwater, and increased water conservation in winter. We also studied the timing of these measures to determine the potential for mitigating effects during a drought versus the effectiveness of long term adaptation. The measures were simulated with the agro-hydrological Soil–Water–Atmosphere–Plant (SWAP) model for several areas across the Netherlands for both agricultural fields and nature sites.</p><p>As expected, decreasing irrigation from groundwater reduced the severity of the hydrological drought in the region. Severity of the soil moisture drought also decreased in fields that were never irrigated due to the effects of capillary rise from the groundwater, but, as expected, increased in currently irrigated fields. Increasing the level of a weir in ditches had a relatively small effect on the hydrological drought, provided water was available to sustain higher water levels. This measure is, therefore, better suited as a long term change than as ad hoc measure during a drought. The effectiveness of the measures depended on the characteristics of the regions; for some regions small changes led to increases in groundwater levels for several months, whereas in other regions effects were lost after a few weeks. This study gives insight into the most effective measures to mitigate drought impacts in low-lying sandy regions like the Netherlands.</p>

scholarly journals Global Atmospheric Evaporative Demand over Land from 1973 to 2008

2012 ◽  
Vol 25 (23) ◽  
pp. 8353-8361 ◽  
Author(s):  
Kaicun Wang ◽  
Robert E. Dickinson ◽  
Shunlin Liang
Keyword(s):  
Sunshine Duration ◽  
Water Vapor Pressure ◽  
Evaporative Demand ◽  
Term Trend ◽  
Direct Measurements ◽  
Arid And Semiarid Areas ◽  
Water Vapor Pressure Deficit ◽  
The Impact ◽  
Long Term Trend

Abstract Pan evaporation (EP), an index of atmospheric evaporative demand, has been widely reported to have weakened in the past decades. However, its interpretation remains controversial because EP observations are not globally available and observations of one of its key controls, surface incident solar radiation Rs, are even less available. Using global-distributed Rs from both direct measurements (available through the Global Energy Balance Archive) and derived from sunshine duration, the authors calculated the potential evaporation from 1982 to 2008 from approximately 1300 stations. The findings herein show that the contribution of water vapor pressure deficit (VPD) to monthly variability of EP is much larger than that of other controlling factors, of Rs, wind speed (WS), and air temperature Ta. The trend of the aerodynamic component of EP, which includes contributions of VPD, WS, and Ta, accounted for 86% of the long-term trend of EP. The aerodynamic component was then calculated from 4250 globally distributed stations and showed a negligible averaged trend from 1973 to 2008 because the reduction in WS canceled out the impact of the elevated VPD. The long-term trend of WS dominates the long-term trend of the aerodynamic component of EP at the 4250 stations. Atmospheric evaporative demand increased in most arid and semiarid areas, indicating a decrease in water availability in those areas.

scholarly journals The impact of drought stress on the yields and food value of selected forage grasses

2016 ◽  
Vol 69 (2) ◽  
Author(s):  
Mariola Staniak
Keyword(s):  
Soil Moisture ◽  
Water Stress ◽  
Drought Stress ◽  
Dry Matter ◽  
Nutritional Value ◽  
Lolium Multiflorum ◽  
Grass Species ◽  
Forage Grasses ◽  
The Impact

<p>The aim of the study was to compare yields and nutritional value of selected species and cultivars of forage grasses under the optimal moisture conditions and long-term drought stress. The regenerative capacity of plants after dehydration was also assessed. The pot experiment was conducted in years 2009–2010 in IUNG-PIB’s greenhouse in Puławy, Poland. Nine cultivars of four species: <em>Dactylis glomerata</em> (‘Amera’, ‘Minora’), <em>Festuca pratensis</em> (‘Skra’, ‘Fantazja’), <em>Festulolium braunii</em> (‘Felopa’, ‘Agula’, ‘Sulino’), and <em>Lolium multiflorum</em> (‘Gisel’, ‘Lotos’) were investigated in well-watered conditions (70% field water capacity – FWC) and under a long-term drought stress (40% FWC).</p><p>The study showed that stress caused by soil moisture deficiency significantly reduced yields of <em>D. glomerata</em>, <em>F. pratensis</em>, <em>F. braunii</em>, and <em>L. multiflorum</em>. The total yield of dry matter under stress conditions was about 31% lower, compared to the performance achieved on the optimally moisturized treatment. The smallest reduction in dry matter yield under the conditions of water deficit was recorded for <em>D. glomerata</em>, which makes it the most resistant to stress, followed by <em>F. pratensis</em>. The resistance of <em>F. braunii</em> and <em>L. multiflorum</em> to stress was similar and significantly lower. There was a various response of different grasses to the water stress. On the basis of the value of the DSI (drought susceptibility index), the tested cultivars were ranked depending on the sensitivity to drought, starting with the most resistant cultivar: ‘Minora’, ‘Skra’, ‘Fantazja’, ‘Amera’, ‘Sulino’, ‘Agula’, ‘Gisel’, ‘Lotos’, and ‘Felopa’. The digestibility of dry matter and nutrient value of the grasses depended on both the level of soil moisture and grass species. Under the water stress, the digestibility and protein value increased compared to the control objects. <em>Lolium multiflorum</em> and <em>F. braunii</em> had the best nutritional value, while <em>D. glomerata</em> – the weakest.</p>

scholarly journals Використання нечіткої логіки для автоматизації функціонування зрошувальних систем

2018 ◽  
pp. 153-157
Author(s):  
Л. І. Лєві
Keyword(s):  
Fuzzy Logic ◽  
Soil Moisture ◽  
Moisture Content ◽  
Moisture Transfer ◽  
Control Object ◽  
Climatic Conditions ◽  
Agricultural Crops ◽  
Weather Factors ◽  
Rational Use ◽  
Moisture Management

Розглянуто підхід до автоматизації процесу керування зрошувальними системами із застосуванням нечіткої логіки. Потужність та інтуїтивна простота нечіткої логіки як методології вирішення проблем гарантує її успішне застосування в системах контролю та аналізу інформації. При цьому відбувається підключення людської інтуїції та досвіду оператора. Запропонований підхід дозволяє підвищити точність керування вологістю ґрунту, забезпечити отримання планових врожаїв сільськогосподарських культур, економити водні та енергетичні ресурси за рахунок їх раціонального використання. The highest yield of agricultural crops is achieved with the optimal amount of moisture, nutrition, heat, air and light. In this case, the necessary water regime for agricultural crops is created by the appropriate irrigation regime, which establishes the norms, timing and number of irrigation, depending on the biological characteristics of crops, natural and economic conditions. In determining the flow of water to irrigation take into account water consumption or total evaporation, which depends on climatic conditions, the amount of thermal energy that enters the surface, soil moisture, species and yield of the crop. Therefore, the issues of adaptation and self-studying of automated systems for controlling soil moisture in the conditions of the action of random weather factors, changes in the characteristics of the control object, improving the accuracy of control due to the operational consideration of the perturbations of the object, ensuring the receipt of planned yields of agricultural crops for the rational use of energy and water resources. In addition, modern water management systems for crops should not only provide sufficient management accuracy, but also forecast the need for plants in water for a certain period, minimize energy and water costs without loss of crop, be reliable and easy to operate, provide the operator with complete and timely information the value of all parameters and the state of the control system. A comprehensive solution to these problems is possible only through the development of modern technical means of automation, new mathematical models of moisture transfer in the unsaturated zone of soil and methods of managing moisture content of agricultural crops. Thus, the development of methods for automated management of moisture content of agricultural crops, taking into account perturbations, is an actual scientific and practical task. To solve these problems, the approach to automating the management of irrigation systems with the use of fuzzy logic is considered. The power and intuitive simplicity of fuzzy logic as a solution to problems ensures its successful application in information monitoring and analysis systems. At the same time there is a connection of human intuition and operator experience. The offered approach allows to improve the accuracy of soil moisture management, to ensure that planned crops are harvested, and to save water and energy resources at the expense of their rational use.

scholarly journals Reconciling Flagging Strategies for Multi-Sensor Satellite Soil Moisture Climate Data Records

2020 ◽  
Vol 12 (20) ◽  
pp. 3439
Author(s):  
Mendy van der Vliet ◽  
Robin van der Schalie ◽  
Nemesio Rodriguez-Fernandez ◽  
Andreas Colliander ◽  
Richard de Jeu ◽  
...  
Keyword(s):  
Soil Moisture ◽  
European Space Agency ◽  
Data Availability ◽  
Climate Data ◽  
Mountainous Regions ◽  
Soil Moisture Data ◽  
Climate Records ◽  
The Individual ◽  
The Impact

Reliable soil moisture retrievals from passive microwave satellite sensors are limited during certain conditions, e.g., snow coverage, radio-frequency interference, and dense vegetation. In these cases, the retrievals can be masked using flagging algorithms. Currently available single- and multi-sensor soil moisture products utilize different flagging approaches. However, a clear overview and comparison of these approaches and their impact on soil moisture data are still lacking. For long-term climate records such as the soil moisture products of the European Space Agency (ESA) Climate Change Initiative (CCI), the effect of any flagging inconsistency resulting from combining multiple sensor datasets is not yet understood. Therefore, the first objective of this study is to review the data flagging system that is used within multi-sensor ESA CCI soil moisture products as well as the flagging systems of two other soil moisture datasets from sensors that are also used for the ESA CCI soil moisture products: The level 3 Soil Moisture and Ocean Salinity (SMOS) and the Soil Moisture Active/Passive (SMAP). The SMOS and SMAP soil moisture flagging systems differ substantially in number and type of conditions considered, critical flags, and data source dependencies. The impact on the data availability of the different flagging systems were compared for the SMOS and SMAP soil moisture datasets. Major differences in data availability were observed globally, especially for northern high latitudes, mountainous regions, and equatorial latitudes (up to 37%, 33%, and 32% respectively) with large seasonal variability. These results highlight the importance of a consistent and well-performing approach that is applicable to all individual products used in long-term soil moisture data records. Consequently, the second objective of the present study is to design a consistent and model-independent flagging strategy to improve soil moisture climate records such as the ESA CCI products. As snow cover, ice, and frozen conditions were demonstrated to have the biggest impact on data availability, a uniform satellite driven flagging strategy was designed for these conditions and evaluated against two ground observation networks. The new flagging strategy demonstrated to be a robust flagging alternative when compared to the individual flagging strategies adopted by the SMOS and SMAP soil moisture datasets with a similar performance, but with the applicability to the entire ESA CCI time record without the use of modelled approximations.

Weather factors affecting the development of maize from sowing to flowering

1972 ◽  
Vol 78 (2) ◽  
pp. 325-331 ◽  
Author(s):  
M. N. Hough
Keyword(s):  
Soil Moisture ◽  
Correlation Analysis ◽  
Linear Correlation ◽  
Weather Conditions ◽  
Weather Data ◽  
Weather Factors ◽  
Mean Values ◽  
Rate Of Development ◽  
Linear Correlation Analysis ◽  
The Mean

SUMMARYThe phenological development from sowing to flowering of the eaxly maize hybrid INRA 200 is related to the weather conditions. Plot trial data from Wytham, near Oxford, England, and weather information from that and nearby sites formed the basic data.The mean rate of development per day from sowing to emergence is related by linear correlation analysis to the mean values of soil temperature at 5 cm depth and soil moisture deficit. A range of temperature thresholds for emergence development exist, which depend upon the soil moisture, and which differ from the true physiological threshold.Between omergence and flowering the mean rate of development per day is related by linear correlation analysis to mean air temperature, solar radiation and potential transpiration estimated from weather data. All correlations are significant, but the parameters which combine radiation and temperature are statistically better.

Terrestrial Solar Radiation

2017 ◽  
pp. 191-293
Keyword(s):  
Solar Radiation ◽  
Horizontal Plane ◽  
Cloud Cover ◽  
Weather Conditions ◽  
Clear Sky ◽  
Solar Tracking ◽  
Sky Conditions ◽  
The Impact ◽  
Estimation Models

After shading a light on the extraterrestrial solar radiation in the chapter 3 it is important to evaluate the global terrestrial solar radiation and its components. The information on terrestrial solar radiation is required in several different forms depending on the kinds of calculations and kind of application that are to be done. Of course, terrestrial solar radiation on the horizontal plane depends on the different weather conditions such as cloud cover, relative humidity, and ambient temperature. Therefore, the impact of the atmosphere on solar radiation should be considered. One of the most important points of terrestrial solar radiation evaluation is its determination during clear sky conditions. Therefore, in this chapter, the equations that determine the air mass basing on available theories are given and the clear sky conditions are introduced with shading a light on the previous work in identifying clear sky conditions. Taking into consideration that, clear sky solar radiation estimation is of great importance for solar tracking, a detailed review of main available models is given in this chapter. As daily, monthly, seasonally, biannually and yearly mean daily solar radiations are required information for designing and installing long term tracking systems, different available methods are commented regarding their applicability for the estimation of solar radiation information in the desired format from the data that are available. An important accent is paid also on the assessment and comparison of monthly mean daily solar radiation estimation models.

scholarly journals Evaluating the impacts of environmental factors on soil moisture temporal dynamics at different time scales

2020 ◽  
Author(s):  
Qi Chai ◽  
Tiejun Wang ◽  
Chongli Di
Keyword(s):  
Soil Moisture ◽  
Environmental Factors ◽  
Time Scales ◽  
Temporal Dynamics ◽  
Soil Moisture Dynamics ◽  
Temporal Variance ◽  
The Impact ◽  
Moisture Dynamics ◽  
Different Time Scales

Abstract Soil moisture displays complex spatiotemporal patterns across scales, making it important to disentangle the impacts of environmental factors on soil moisture temporal dynamics at different time scales. This study evaluated the factors affecting soil moisture dynamics at different time scales using long-term soil moisture data obtained from Nebraska and Utah. The empirical mode decomposition method was employed to decompose soil moisture time series into different temporal components with several intrinsic mode functions (IMFs) and one residual component. Results showed that the percent variance contribution (PVC) of IMFs to the total soil moisture temporal variance tended to increase for the IMFs with longer time periods. It indicated that the long-term soil moisture variations in study regions were mainly determined by low-temporal frequency signals related to seasonal climate and vegetation variations. Besides, the PVCs at short- and medium-temporal ranges were positively correlated with climate dryness, while negatively at longer temporal ranges. Moreover, the results suggested that the impact of climate on soil moisture dynamics at different time scales might vary across different climate zones, while soil effect was comparatively less in both regions. It provides additional insights into understanding soil moisture temporal dynamics in regions with contrasting climatic conditions.

scholarly journals Low soil moisture predisposes field-grown chickpea plants to dry root rot disease: evidence from simulation modeling and correlation analysis

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Ranjita Sinha ◽  
Vadivelmurugan Irulappan ◽  
Basavanagouda S. Patil ◽  
Puli Chandra Obul Reddy ◽  
Venkategowda Ramegowda ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Root Rot ◽  
Disease Incidence ◽  
Maximum Temperature ◽  
Validation Dataset ◽  
Water Deficit Stress ◽  
Weather Factors ◽  
Rhizoctonia Bataticola ◽  
Average Maximum ◽  
The Impact

AbstractRhizoctonia bataticola causes dry root rot (DRR), a devastating disease in chickpea (Cicer arietinum). DRR incidence increases under water deficit stress and high temperature. However, the roles of other edaphic and environmental factors remain unclear. Here, we performed an artificial neural network (ANN)-based prediction of DRR incidence considering DRR incidence data from previous reports and weather factors. ANN-based prediction using the backpropagation algorithm showed that the combination of total rainfall from November to January of the chickpea-growing season and average maximum temperature of the months October and November is crucial in determining DRR occurrence in chickpea fields. The prediction accuracy of DRR incidence was 84.6% with the validation dataset. Field trials at seven different locations in India with combination of low soil moisture and pathogen stress treatments confirmed the impact of low soil moisture on DRR incidence under different agroclimatic zones and helped in determining the correlation of soil factors with DRR incidence. Soil phosphorus, potassium, organic carbon, and clay content were positively correlated with DRR incidence, while soil silt content was negatively correlated. Our results establish the role of edaphic and other weather factors in chickpea DRR disease incidence. Our ANN-based model will allow the location-specific prediction of DRR incidence, enabling efficient decision-making in chickpea cultivation to minimize yield loss.

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