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Drought is one of the natural disasters having the highest degrees in comparison to the other natural disasters in terms of rate, intensity, incident duration, region expansion, life losses, economic damages, and long-term effects. Hence, the prediction of drought as a meteorological phenomenon should be evaluated to determine the groundwater exploitation strategies in agriculture. The present study aims at investigating the impact of the drought duration and severity on soil moisture supplement for agricultural activities in Baghmalek plain, Khuzestan province, Iran. For this objective, a non-dimensional index of precipitation depth was defined for quantifying the drought characteristics. Furthermore, marginal distribution functions, correlation coefficients and joint functions were incorporated to a probabilistic decision-making framework to predict the variables in different return periods from 2-year to 100-year periods. Results showed that t copula was the best function for constructing the multivariate distribution in the study area based on the goodness-of-fit tests. Moreover, soil moisture content in the root zone achieved by the predetermined amounts of precipitation could be increased in the seasonal average. HIGHLIGHTS A new probabilistic framework was developed for sustainable water allocation.; Fuzzy particle swarm optimization was employed for generating the optimal solution.; A daily time-step model was simulated using mathematical formulation of crop growth process.; Developed framework increased the water use efficiency in the cropping pattern of Baghmalek as the study area.

Climate change and the erratic and uneven rainfall distribution are the causes of reduced water available in the soil for plant needs to the transpiration process. This study aimed to determine coffee transpiration rate on dry land with rain harvesting techniques during the dry season, transition season, and rainy season and the factors that influence it. This study used field observation and laboratory analysis with two treatments, i.e. a bench terrace as a control (P1) and an L-shaped silt pit (P2). The variables observed were soil moisture content, transpiration rate, soil water potential, leaf water potential, and microclimate, especially temperature and sunlight intensity. The results showed that the transpiration rate of coffee plants was significantly different in the two treatments. The highest transpiration rate was found in P2 as much as 13.17 mm week-1 or equivalent to 1.88 mm day-1 during the dry season. Application of the L-shaped silt pit (P2) increased soil moisture content compared to the control (P1). This increase was followed by an increase in soil water potential and leaf water potential, which could reach the highest values of 0.18 bar and 0.49 bar, respectively. The transpiration decreases with the change of seasons from the dry season to the transitional season and the rainy season. This decrease is caused by changes in the microclimate, especially the temperature and sunlight intensity. Both are the most variables that affect the rate of transpiration.

In order to solve the problem of low accuracy and efficiency of soil moisture content prediction in tea plantations and improve the level of soil water content prediction, a soil moisture content prediction model for tea plantations based on the support vector machine (SVM)‐optimised bald eagle search (BES) algorithm (BES‐SVM) is proposed. Soil data and environmental data of tea plantations were transmitted to the server using sensor nodes and weather station nodes. The prediction models of soil moisture content and natural environmental parameters such as soil electrical conductivity, soil temperature, air temperature, air humidity, light intensity, and rainfall were developed using the SVM model optimised by the bald eagle search algorithm, and the mean square error (MSE) and coefficient of determination (R2) were calculated to evaluate the model performance. Meanwhile, the performance of the BES‐SVM model is compared with the particle swarm algorithm optimisation SVM (PSO‐SVM) and genetic algorithm optimised SVM (GA‐SVM) models. Results show that the proposed model has a mean coefficient of determination of 95.65%, and the prediction performance is better than the PSO‐SVM and GA‐SVM model, indicating that the BES‐SVM model has good performance and is a feasible prediction method for soil water content prediction and guiding irrigation and fertilisation management in tea plantations.

For thousands of years, terracing has been one of the most important systems for preventing soil erosion, conserving water, and increasing agricultural production. Despite having a long history, the wide-ranging effects and mechanisms of terracing are poorly understood owing to large-scale spatial and temporal distribution patterns and the challenges related to assessing the ecosystem services of terraced landscapes. Thus, our study aims to review comprehensively the effect of terraces by describing the mechanisms behind terraced systems. Terraces provide many ecosystem services, including the reduction of runoff and sediment by over 41.9% and 52%, respectively, and the improvement of grain yields and soil moisture content by 44.8% and 12.9%, respectively. In addition, terracing can also contribute toward the conservation of plant biodiversity on a local scale. However, as terraces age, a number of disadvantages gradually emerge, including interference with water circulation and the development of serious environmental problems caused by poorly designed or mismanaged terraces, where the average runoff and soil loss can be 1–5 times that of well-managed terraces. Although understanding the complexity and multifaceted effects of terracing is vital for terrace construction and management, the negative effects of terracing are often not considered, and existing studies have several shortcomings. Within this context, this paper aims to describe both the benefits and disadvantages of terracing, investigate the gaps in current research, as well as discuss preventive and remedial measures so as to negate the possible bad impacts of terracing.

Potato (Solanum tuberosum L.) is important to the world population’s food security. However, potato production is implicated in several environmental problems, particularly soil loss due to crop harvest (SLCH). Moreover, a knowledge bias about this process exists given that most related studies are from Europe. Most studies compare SLCH differences among tuber and root characteristics of distinct crops but not the tuber morphologies, e.g., spherical and elongated ones, within the same crop. This study aimed to (a) estimate the SLCH in potatoes with contrasting morphologies in a very clayey soil; (b) test whether the potato morphology allied to soil moisture affects the sediment exportation. A total of 205 potatoes from four plots were collected for morphological and sediment exportation assessments. Several morphological characteristics were measured: weight (g), volume (cm3), axis dimension (mm), concavities (the number and volume), sediment adherence (g), and soil moisture (g kg−1). The spherical potatoes exported 1.28 kg sediment per ton−1 of harvested potato, whereas the elongated ones exported 20% more sediment (1.54 kg). The harvested field with a high soil moisture content (≈ 26%) exported three times more sediment than the field with the lowest moisture content (≈ 16%). The SLCH measured in the study area was lower (0.062 Mg ha−1 harvest−1) than most values reported in the literature. In addition, the potato morphological characteristics affected soil adherence at distinct soil moisture contents. The harvesting technique can be critical to reduce the SLCH.

The moisture retrieval depth is commonly held to be the approximately top 5 cm at L-band (~21-cm wavelength/1.41 GHz), which is seen as a limitation for hydrological applications. A widely held view is that this moisture retrieval depth increases with wavelength, ranging approximately from one-tenth to one-fourth of the wavelength. Accordingly, P-band (~40-cm wavelength/0.75 GHz) is under investigation for soil moisture observation over a deeper layer of soil. However, there is no accepted method for predicting the moisture retrieval depth, and there has been no study to confirm that the actual retrieval depth at P-band is indeed deeper than that achieved at L-band. Consequently, this research has estimated the moisture retrieval depth from theory and compared with empirical evidence from tower-based observations. Model predictions and experimental observations agreed that P-band has the potential to retrieve soil moisture over a deeper layer (~7 cm) than L-band (~5 cm) while maintaining the same correlation. However, an alternate interpretation of experimental results is that P-band has a larger correlation with soil moisture (accuracy of retrieval) than L-band but for the same 5-cm moisture retrieval depth. The results also demonstrated the increasing trend of the moisture retrieval depth for increasing wavelength, with the potential to achieving a moisture retrieval depth greater than 10 cm for P-band below 0.5 GHz. Importantly, model predictions showed that moisture retrieval depth was not only dependent on soil moisture content and observation frequency, but also the moisture gradient of the profile.

Movement of the soil particles during tillage operation is the result of the application of force by the tillage tools. The soil crushed due to the action of the applied force, and soil particles move in various directions. The extent of unnecessary soil movement by tillage tools during tillage practices will affect the rate of soil erosion. Moreover, there is a lack of experimental data concerning soil movement with currently used tillage tools and particularly the effect of repeated tillage over decades of time (Sharifat and Kushwaha, 1997). Under this study, a factorial experiment (2x3x3x3) with random design was used. The tool operating parameters were share shape, plowing speed and constant level of share depth. On the other hand, the soil parameters were soil moisture content and soil compaction. Soil movement was determined using the tracer method introduced by Turkelboom et al. (1996). Results of statistical analysis showed that there are highly significant differences were obtained for the soil movements in three directions with all factors and with the interaction between factors at P£ 0.01. It could be concluded that the use of shovel share instead of sweep share for the same job will reduce soil movement and consequently reduce the rate of soil erosion.

Soil moisture content (SMC) is an important element of the environment, influencing water availability for plants and atmospheric parameters, and its monitoring is important for predicting floods or droughts and for weather and climate modeling. Optical methods for measuring soil moisture use spectral reflection analysis in the 350–2500 nm range. Remote sensing is considered to be an effective tool for monitoring soil parameters over large areas and to be more cost effective than in situ measurements. The aim of this study was to assess the SMC of bare soil on the basis of hyperspectral data from the ASD FieldSpec 4 Hi-Res field spectrometer by determining remote sensing indices and visualization based on multispectral data obtained from UAVs. Remote sensing measurements were validated on the basis of field humidity measurements with the HH2 Moisture Meter and ML3 ThetaProbe Soil Moisture Sensor. A strong correlation between terrestrial and remote sensing data was observed for 7 out of 11 selected indexes and the determination coefficient R2 values ranged from 67%– 87%. The best results were obtained for the NINSON index, with determination coefficient values of 87%, NSMI index (83.5%) and NINSOL (81.7%). We conclude that both hyperspectral and multispectral remote sensing data of bare soil moisture are valuable, providing good temporal and spatial resolution of soil moisture distribution in local areas, which is important for monitoring and forecasting local changes in climate.

The West Liaohe Plain is a typical semi-arid area, where the process of rainfall infiltration to replenish groundwater is a key link in its vertical hydrological cycle. In this paper, we compare and analyze the impact upon soil moisture movement and water infiltration after the shift of irrigation method from flood irrigation to mulched drip irrigation under mulch through setting up in-field in-situ observation points and carrying out groundwater depth dynamic observation. The results show that compared with mulched drip irrigation under mulch, flood irrigation has a stronger response to rainfall infiltration and a quicker response time in the rise of underground depth. With the decrease of groundwater level, the effect of rainfall infiltration to replenish groundwater is significantly weakened. In the flood irrigation area, the groundwater depth at about 8 m already has no obvious response to a small amount of rainfall. However, the groundwater depth at 6 m in the area of mulched drip irrigation under mulch already has no response to rainfall. Therefore, when groundwater extraction is carried out in irrigation areas, reasonable groundwater extraction levels should be designated in light of different irrigation methods to maintain the sustainable utilization of groundwater. HIGHLIGHTS Observed rainfall infiltration realized through flood irrigation and mulched drip irrigation under mulch.; Analyze the mechanism of the influence of irrigation conditions on rainfall infiltration.; Analyze the change of soil moisture content.; Analyze their impacts upon rainfall infiltration.; The promotion of mulched drip irrigation under mulch will exert a significant impact on rainfall infiltration.

In an attempt to retrieve soil moisture content (SMC) from remote sensing techniques, this article suggests and evaluates a developed approach that overcomes three of the most fundamental limitatio...

espanolEn los ecosistemas forestales, el balance de energia, el ciclo del agua y el ciclo del carbono se vinculan a traves del proceso de evapotranspiracion. La evapotranspiracion es altamente variable en espacio y tiempo, y esta controlada por numerosos factores biofisicos. El objetivo de este estudio fue analizar la variabilidad estacional de la evapotranspiracion e identificar los principales factores que influyen en dicho proceso. El metodo de eddy covariance se utilizo para medir los flujos de calor sensible y calor latente (equivalente a evapotranspiracion) en un bosque bajo manejo forestal, ubicado en la region forestal de Zacualtipan, Hidalgo. Simultaneamente se midio la radiacion neta, el flujo de calor del suelo, el contenido de agua en el suelo y otros parametros meteorologicos. A lo largo del periodo analizado, la proporcion de la radiacion neta con los flujos de calor latente y calor sensible fue similar la mayor parte del tiempo. La evapotranspiracion total anual observada fue de 980 mm. Esta fue menor en el periodo de “nortes" y no se encontraron diferencias significativas entre el periodo de lluvias y el de secas. La temperatura, humedad del suelo, radiacion neta y deficit de presion de vapor explicaron la mayor parte de la variabilidad de la evapotranspiracion. Se recomienda realizar estudios posteriores que involucren el analisis de la productividad del ecosistema y eficiencia en el uso del agua, para comprender mejor los procesos del ecosistema e identificar practicas apropiadas para el manejo forestal sostenible. EnglishIn forest ecosystems the energy balance, the water cycle and the carbon cycle are linked through the evapotranspiration process. Evapotranspiration is highly variable in space and time since it is controlled by numerous biophysical factors. The objective of this study was to analyze the seasonal variability of evapotranspiration and identify the main factors that influence this process. The eddy covariance technique was used to measure fluxes of sensible heat and latent heat (equivalent to evapotranspiration) in a temperate forest under forest management, located in the region of Zacualtipan, Hidalgo, Mexico. Simultaneously, net radiation, soil heat flux, soil moisture content and other meteorological parameters were measured. During the analyzed period, the proportion of the net radiation with the latent heat and sensible heat fluxes was similar most of the time. The total annual evapotranspiration observed was 980 mm. It was lower in the “cold front” season and no differences were found between the rainy season and the dry season. Temperature, soil moisture, net radiation and vapor pressure deficit explained most of the variability of evapotranspiration. Further studies are necessary to involve the analysis of ecosystem productivity and water use efficiency, to better understand ecosystem processes and identify appropriate sustainable forest management practices.

Drought generally has significant impacts on crops. It is essential to quantitatively evaluate the relationship between crop production and drought degree to provide technical support for drought disaster prevention. In this study, a drought degree index that can reflect the changes in precipitation, evapotranspiration, and soil moisture was developed on the basis of crop yield reduction rate. Four drought scenarios were set up to simulate the effects of meteorological drought on drought degree of crops at different growth stages. A cusp catastrophe model was constructed to analyze the mutation characteristics of the drought degree of maize at different growth stages under different meteorological drought conditions. Xi'an City in China was selected as the study area, and summer maize was selected as the research crop. Precipitation and crop yield data from 1951 to 2010 were used as the fundamental data to investigate drought degree mutation of summer maize. The results show that, under the meteorological drought conditions at the emergence-jointing stage, drought degree may change abruptly, and soil moisture content at the sowing-emergence, jointing-tasseling, and tasseling-mature stages should be kept higher than 39%.

The sensitivity of the inland wind decay to realistic inland surface roughness lengths and soil moisture contents is evaluated for strong, idealized tropical cyclones (TCs) of category 4 strength making landfall. Results show that the relative sensitivities to roughness and moisture differ throughout the decay process, and are dependent on the strength and size of the vortex. First, within 12 h of landfall, intense winds at the surface decay rapidly in reaction to the sudden change in surface roughness and decreasing enthalpy fluxes. Wind speeds above the boundary layer decay at a slower rate. Differences in soil moisture contents minimally affect intensity during the first 12 h, as the enhancement of latent heat fluxes from high moisture contents is countered by enhanced surface cooling. After TCs decay to tropical storm intensities, weakening slows and the sensitivity of the intensity decay to soil moisture increases. Increased latent heating becomes significant enough to combat surface temperature cooling, resulting in enhanced convection outside of the expanding radius of maximum winds. This supports a slower decay. Additionally, the decay of the radial wind profile by quadrant is highly asymmetric, as the rear and left-of-motion quadrants decay the fastest. Increasing surface roughness accelerates the decay of the strongest winds, while increasing soil moisture slows the decay of the larger TC wind field. Results have implications for inland forecasting of TC winds and understanding the potential for damage.

In urban green spaces, it is important to maintain a suitable soil moisture content, an important indicator of plant growth. The management of urban green spaces faces great challenges in semi-humid areas of China, which are featured by interannual changes in rainfall and the alternation between droughts and floods. This paper aims to select suitable Organic Ground Cover (OGC) materials for urban green spaces in such areas, as the OGC can effectively absorb water and suppress the evaporation of soil moisture. For this purpose, 16 OGC materials were selected for our experiments, and 33 identical holes were dug on a field of silty loam. Next, 16 holes were separately covered by a 5 cm-thick layer of the 16 materials, 16 holes were separately covered by a 10 cm-thick layer of the 16 materials, and 1 hole was taken as the control sample (CK). On this basis, the authors explored how the 16 materials in two different thicknesses affect the soil moisture contents in four different soil depths. The results show that: When the OGC layer was 5 cm thick and 10 cm thick, CK had the lowest soil moisture content at any soil depth. In most cases, the soil moisture content under the same OGC material changed insignificantly with the material thicknesses, except FPB2 and CP. The layer of OGC materials should be 5 cm, if the only purpose is to increase the soil moisture content and enhance the landscape effect, and 10 cm if rainwater absorption is also taken into account. The above results provide a reference for selecting the OGC materials suitable for urban greening.

A laboratory model experiment of step vacuum preloading (SVP) for dredger fills was performed. The soil moisture content and water discharge rate were measured. The seepage mechanism of pore water was analyzed based on the theory of drainage consolidation. The results indicated that the seepage fluid mostly consisted of free water during self-weight sedimentation and under 10 kPa vacuum pressure in the SVP test. The stage corresponding to the application of 20 kPa vacuum pressure was the transitional stage in which both the free water and the loosely bound water participated in the seepage. When higher vacuum pressure was applied, the loosely bound water mostly participated in the seepage. In the SVP test, the complete potential difference channels were established in the test bucket during self-weight sedimentation. The vacuum channels at the center began to form when 10 kPa vacuum pressure was applied, and the free water near the sidewall was discharged through the potential difference channel. With 20 kPa vacuum pressure, the vacuum channel developed continuously from the drainage board to the sidewall of the test bucket, completing the process and ultimately stabilizing as the vacuum pressure increasing. The study of the seepage mechanism of pore water during SVP test is significant for the analysis of pore water seepage under vacuum pressure during the consolidation of soft soil foundation. This study contributes to the existing theory related to vacuum preloading consolidation methods, providing theoretical guidance for the analysis of soil consolidation under drainage conditions.

Soil moisture (SM) or soil water content is a critical variable in the climate system and a key parameter in earth surface processes. This study aimed to assess citizen observatory (CO) data's suitability to develop a method to estimate surface SM distribution using Sentinel-1B and Landsat 8 data; acquired between January 2019 and June 2019. Three approaches were developed and compared using multiple linear regression (MLR), regression-kriging (RK) and cokriging (CK). MLR provided more realistic spatial patterns over the landscape, even in a data-poor environment. RK was found to be a potential tool to refine the results, while CO was found to be less effective. The obtained results showed that CO data harmonised with Sentinel-1B SAR, Landsat 8, and terrain data could estimate and map soil moisture content.

A field experiment was conducted at the farmer’s field at Ratanpur village of Marshaghai block of Kendrapara, Odisha, India to evaluate effect of different mulching practices on weed population, moisture content in soil and yield of brinjal. The village is an adopted village by Krishi Vigyan Kendra Kendrapara, in which various activities in agriculture are going on under National Innovations on Climate Resilient Agriculture (NICRA) programme to combat the flood-affected area of the locality. The experiment consists of five mulching treatments like Black polythene mulch, Black and silver polythene mulch, Transparent mulch, Organic mulch (rice straw) and No mulch. Results revealed that black with silver colour polythene mulch was recorded with significantly higher yield per plant (2.59 kg) and yield per ha (62.1 t/ha) which was at par with black colour polythene mulch. Organic mulch was found to be next best treatment with respect to yield per plant (2.40 kg) and yield per ha (53.5 t/ha). The same treatment also resulted in the higher gross return (Rs. 434700/ha), net return (Rs. 274150/ha) and B:C ratio (2.71) which was followed by black polythene mulching and organic mulching practices. Weed suppression and moisture retention was higher with black polythene mulch.

Determining and predicting both the spatial and temporal variability of soil moisture content is a critical factor in crop production in semi-arid agricultural systems. The objective of this research was to predict the spatial distribution of soil moisture content using ordinary kriging (OK), regression kriging (RK) and cokriging (CK) models. For that purpose, the soil moisture was monitored in the wet period (March, April and May) and dry period (August, September and October) in Kadinhani district of Konya Province, Turkey. In each monthly sampling period of the study, a total of 278 samples were collected from locations within an area of 29,608.6 ha. The coefficients of variation (CV) of the soil moisture in dry and wet soil conditions were 0.39 and 0.20, respectively. Soil texture, bulk density (BD) and land use were the most important factors influencing soil moisture. In addition, dry soil generally had a smaller nugget effect than wet soil. Overall, CK was able to better estimate the soil moisture content than OK and RK, as evidenced by the smaller mean absolute error (MAE) and mean square error (MSE). RK estimation is more vulnerable to error than CK and OK estimations because the low coefficients of determination in the regression equation lead to increased error and lower confidence in the estimates. The insights generated by the modeling utilized in this study can assist land use planners, land managers and farmers to more efficiently predict, manage and utilize soil moisture content and hence produce larger crops more sustainably.

This study utilised static triaxial and dynamic cone penetration tests to examine the identification of changes in strength in soil materials as a result of an increase in moisture content. The applicability of a light dynamic cone penetrometer device in railway environments was also studied. On a broader scale, the aim was to find an investigation method suited to field locations that identify low-quality or persistently moist materials directly from the structure. The triaxial tests found an apparent increase in shear strength when the water content dropped below 7%. Based on the series of laboratory tests, the dynamic cone penetrometer reacted strongly to material density, but the impact of moisture content was also evident. Furthermore, the results showed that dynamic cone resistance is a reasonably unfeasible metric for assessing the structural quality of materials consisting primarily of sand, due to the number of factors affecting the resistance. In the laboratory tests, the lowest dynamic cone resistances were measured in the material with the highest structural quality. publishedVersion

In the present study, the effect of vertical load, tire inflation pressure and soil moisture content on power loss in tire under controlled soil bin conditions were investigated. Also a finite element model of tire-soil interaction in order to achieve a suitable model for predicting power loss in tire was created. Increasing the vertical load on the tire had a noteworthy impact on increasing the tire contact volume with the soil, reducing the percentage of slip, and increasing the rolling resistance; although, reducing the load on the tire had the opposite effect. At a constant inflation pressure, by increasing the vertical load on the tire, the amount of power loss due to the rolling resistance and the total power loss in the tire increased. Increase in soil moisture content increased the power loss caused by slip. Increasing the inflation pressure at a constant vertical load, also increasing the soil moisture content, led to an increase in the power loss caused by rolling resistance, and increase total power loss. The obtained error for estimating power loss of rolling resistance and total power loss was satisfactory and confirmed the acceptability of the model for power loss estimation.

There are many methods to measure the suction and saturation point of any soil and the most used is Tensiometer. The objective of this research is to investigate a new trend to measure the saturation point and suction by using soil moisture content sensors (SMCS) and compare the procedure with tensiometer for the granular soil. The soil in this study has been prepared at three relative densities (5%, 35% and 75%) used. The results show that the readings of SMCS become stable when the water content is more than 20% with different relative densities. The relative density did not affect the SMCS reading when approximately reaching the saturation point.

Green roofs contribute notably to green building and sustainable city goals. Most studies focused on summer cooling and energy-saving benefits, with little attention on winter warming effect. This study evaluated contributions of the soil component to winter warming with reference to the thickness and moisture content. In subtropical Wuyishan city, Fujian Province, China, we built three houses as experimental green-roof plots. We adjusted soil thickness, measured moisture content, and monitored their impacts on roof outer surface temperature (ROST) in winter. We designated measured outdoor temperature, relative humidity, solar radiation, wind speed, soil thickness and soil moisture content as independent variables, and ROST as dependent variable. The empirical data were enlisted to establish a neural-network prediction model in conjunction with a genetic algorithm to optimize parameter thresholds and weights. The numerical model successfully predicted winter ROST at different combinations of soil thickness and moisture content and identified the best value for energy-saving performance. The model predicted that the maximum ROST of 13.5 °C was achieved at 20 cm soil thickness and 3.9 % moisture content. The choice of deciduous or evergreen plants could fine-tune soil moisture requirement and improve warming service. The study demonstrated the feasibility of optimizing the green-roof design by adjusting controllable soil variables. The neural-network model could reliably predict ROST under different soil conditions to inform design and management.

Considerable progress has been made in understanding the variation rules of the freezing/thawing period and soil water-heat exchange. With the use of meteorological and soil observation data, this study highlighted the importance of vegetation cover and soil moisture for the beginning of the freezing/thawing period, and an improved calculation equation of the soil moisture content was presented, which could be used to simulate the variation in soil moisture during the freezing/thawing period. Our analyses showed that the temperature changes at the beginning of the soil freezing month (December) and the soil thawing month (February) were significantly different from 2009 to 2018. The rate of air temperature increase in December reached 0.38 °C/a. However, the air temperature in February changed little. As a result, the beginning of the soil freezing period was clearly lagged, while the beginning of the soil thawing period fluctuated little. The total soil thawing time increased by 25 days over 10 years. Furthermore, it was shown that the surface vegetation cover and soil moisture affected the beginning of the freezing/thawing time. In general, the soil freezing/thawing state at sites with low vegetation cover and soil moisture content was more likely to change. To further study the freezing/thawing mechanism, the relationship between the soil temperature and soil moisture during the freezing/thawing period was expressed as a fitting function of the relationship between soil water and heat. It was shown that the relationship between the soil moisture and soil temperature followed the new fitting function in both warm and cold years.

Tanah merupakan dasar dari suatu struktur bangunan. Setiap daerah memiliki karakteristik dan sifat-sifat tanah yang bervariasi.Seringkali terdapat beberapa sifat tanah yang buruk dan kurang menguntungkan untuk suatu konstruksi bangunan.Contoh beberapa sifat tanah yang perlu diperhatikan adalah plastisitas yang tinggi, kekuatan geser yang rendah, kemampatan atau perubahan volume dan kembang susut yang besar. Sangat penting untuk mengetahui permasalahan tanah tersebut, serta memberikan upaya untuk memperbaikinya. Pengujian ini bertujuan untuk mengetahui penambahan abu batubara pada tanah,serta mengetahui nilai kadar air tanah dalam pengujian pemadatan tanah (kompaksi proctor) setelah dicampurkan abu batubara. Dari hasil pengujian pemadatan tanah diperoleh, tanah yang di stabilisasi dengan abu batubara pada variasi 0%, 10%, 15%, 20% dan 25% menunjukkan adanya peningkatan nilai kepadatan kering. Pada pengujian pemadatan tanah dengan pencampuran abu batubara nilai kepadatan kering dari variasi 0% sebesar 1,307 terus meningkat hingga 25% sebesar 1,379.

The experiment was conducted at Regional Agricultural Research Station (RARS), Jamalpur, Bangladesh during the period of 2017-18 and 2018-19 with the objectives to evaluate the effect of different mulch on soil temperature, soil moisture conservation and yield attributes of chilli. There were five treatments comprising T1: no mulch, T2: rice straw mulch @ 5 t ha-1, T3: water hyacinth mulch @ 5 t ha-1, T4: black polyethylene mulch and T5: white polyethylene mulch. The results revealed that, all the mulch treatment had higher soil temperature and soil moisture content at 5 cm and 10 cm depth compared to no mulch treatment. Soil temperature was highest in black polyethylene mulch, it increased average soil temperature by about 5.7 oC at 5 cm depth and 5.1 oC at 10 cm depth compared to no mulch treatment at 120 Days. Rice straw mulch treatment recorded highest soil moisture, it increased average soil moisture about 27.87 % at 5 cm depth and 28.57% at 10 cm depth over no mulch treatment. Rice straw mulch treatment produced highest green chilli yield (8.81 t ha-1) which was 26.94 % increased over no mulch treatment (6.94 t ha-1).Considering economic analysis, highest gross return (Tk 352400 ha-1), gross margin (Tk 235400 ha-1) and BCR (3.01) was obtained from same treatment T2 i.e., rice straw mulch treatment.

This study was conducted to investigate the effect of level soil bund stabilized with Vetiver grass and soil bund age on selected soil physicochemical properties on Somodo watershed, Jimma Zone, South-western, Ethiopia. A reconnaissance survey was conducted to identify a representative sampling site. From the selected sampling site croplands with level soil bund aged three years, six years and adjacent untreated cropland were identified. A total of 108 composite soil samples (3 treatments * 6 replications * 2 depths * 3 zones) were collected. Soil samples were analyzed following standard laboratory analysis. Ages of level soil bund (LSB) significantly affected SMC (soil moisture content) (p

No-tillage is often suggested as a strategy to reduce greenhouse gas emissions. Modeling tillage effects on nitrous oxide (N2O) emissions is challenging and subject to great uncertainties as the processes producing the emissions are complex and strongly nonlinear. Previous findings have shown deviations between the LPJmL5.0-tillage model (LPJmL: Lund–Potsdam–Jena managed Land) and results from meta-analysis on global estimates of tillage effects on N2O emissions. Here we tested LPJmL5.0-tillage at four different experimental sites across Europe and the USA to verify whether deviations in N2O emissions under different tillage regimes result from a lack of detailed information on agricultural management, the representation of soil water dynamics or both. Model results were compared to observational data and outputs from field-scale DayCent model simulations. DayCent has been successfully applied for the simulation of N2O emissions and provides a richer database for comparison than noncontinuous measurements at experimental sites. We found that adding information on agricultural management improved the simulation of tillage effects on N2O emissions in LPJmL. We also found that LPJmL overestimated N2O emissions and the effects of no-tillage on N2O emissions, whereas DayCent tended to underestimate the emissions of no-tillage treatments. LPJmL showed a general bias to overestimate soil moisture content. Modifications of hydraulic properties in LPJmL in order to match properties assumed in DayCent, as well as of the parameters related to residue cover, improved the overall simulation of soil water and N2O emissions simulated under tillage and no-tillage separately. However, the effects of no-tillage (shifting from tillage to no-tillage) did not improve. Advancing the current state of information on agricultural management and improvements in soil moisture highlights the potential to improve LPJmL5.0-tillage and global estimates of tillage effects on N2O emissions.

Cassava (Manihot esculenta Crantz) yield could be improved by drip irrigation if irrigation scheduling is correctly organized. Soil moisture content is an important factor for controlling irrigatio...

Soil moisture (SM) is a critical variable in energy and water partitioning at the interface between the land surface and atmosphere. In this study, we provided a robust method to retrieve soil mois...

This study is concerned with Collapsible soils which have significant volume decrease suddenly due to an increase in soil moisture content, with or without an increase in the in-situ stress level. Since the collapsible soils contain low levels of moisture content when they are formed naturally, they are considered to be such a problematic type of unsaturated soils. Reliable simple correlations between basic soil properties would be valuable because of the cost and difficulty of performing collapse tests either in the laboratory or in-situ. This study focuses on silty sand and sandy silt types of the collapsible soils. In order to fulfill the study objectives, a large database was developed from different researches works. The database contains information regarding basic soil properties of laboratory and field samples.

The Canadian Forest Fire Danger Rating System (CFFDRS) and the National Forest Fire Danger Rating System (NFFDRS) were exercised under the Mediterranean forest type conditions of Crete Island, Greece in 2008–2009. The CFFDRS shows a high association between the assessed values of the duff moisture content on one hand and the Fine Fuel Moisture Code and the Duff Moisture Code on the other hand. During the designated fire seasons, there was an insignificant association between the Fire Weather Index and the wild forest fires which are contrary associated with wildfire occurrences. Meanwhile, the NFFDRS showed monitoring capabilities but with the insufficient prediction of the daily fire danger in the Mediterranean forests. During the tested forest fire seasons, there was an unstable association between the burnt area and the fire occurrences. Consequently, there was no significant correlation between the CFFDRS and the litter soil content. Although, CFFDRS has a higher prediction accuracy of moisture content of some shallow roots annual plants within the studied area. The findings of the current research emphasized that there is no single system that is adequate enough for both soil moisture content and the annuals moisture content simultaneously.

The goal of this study was to compare wheel-rut development between a conventional 8-wheel forwarder and a 10-wheel forwarder. Two Ponsse Buffalo forwarders with 14 metric ton load capacity were co...

The Standardized Precipitation Index (SPI) and the Standardized Precipitation Evapotranspiration Index (SPEI) are used to monitor and identify different types of drought, including meteorological, hydrological, and agricultural droughts. This study evaluates the accuracy of estimating soil moisture levels using the two indexes. The analysis correlated the SPI and the SPEI over three years (November 2016–October 2019) using Rstudio, with average monthly soil moisture taken using a Soil Moisture Sensor; 3-, 6- and 12-months SPI and SPEI showed a positive correlation for soil moisture (Sig 0.05). In contrast, the 3-, 6-, and 12-months indexes were significant (p-value

Algeria shares similarities with other countries of the world facing destructive floods. The need to understand changes in the intensity, frequency and severity of floods is critical for reducing significant social, economic, and environmental implications. In this study, flood indicators derived from annual maximum series and peak over threshold series were analyzed using Mann−Kendall trend analysis and linear regression analysis. Several studies in northern Algeria found decreasing trends of annual precipitation. However, precipitation could not explain most flood indicator trends found in our study. A general decreasing annual and seasonal trends of flood indicators were detected in the wadi Cheliff Basin. This result is partly due to decreasing precipitation and partly due to the construction of dams which have significantly altered flood processes. Increasing trends were found in the Mina Basin, which could be explained as the result of increases in urban area and decrease in soil moisture content before the occurrence of floods. Conversely, there was no dependency demonstrated between significant changes and spatial scales for these flood indicators. That is to say, human impacts and climate variability likely constitute the main factors causing increasing or decreasing flood trends.

This study evaluates the effect of soil moisture content on mineralization process of composted and pelletized chicken manure on pH, nitrate and ammonium contents at a sandy soil. To establish the mineralisation rate of the composted chicken manure in the soil a short soil incubation method was used. The objectives of the study were: (1) To assess the effects of three types of composted chicken manure on soil pH at different moisture contents conditions, (2) To assess the effects of the three types of composted poultry manure on soil easily soluble mineralised N forms (nitrate and ammonium) at different moisture contents. For study of mineralisation rate of composted and admixtured chicken manure pellet a short soil incubation experiment was set up. Beside the control three treatments, each containing 12 pots (three replicates for soil samples with four different moisture content; 40 %, 50 %, 60 % and 70 %) were used. The pH value and nitrate and ammonium contents and their changing were assessed after the first, second, third and fourth weeks respectively. In each of the four experiment blocks, the soil samples were subjected to four treatments: control, P+K, P+K “C”, and Humin Plus. Statistical analysis of the data showed that the three manure types had significant impact on the soil nitrate and ammonium levels at different soil moisture conditions. No significant effect on soil pH was identified during the experiment period. This implies that in order to achieve optimum benefits from application of chicken manure on the farm, it is necessary to do soil testing to assess the nitrate and ammonium status of the soil first. This can provide a basis to make a well-informed decision on which manure is the best in the supply of either nitrate and ammonium to the soil depending on the soil amendment needs.

This study assesses the effect of some soil physical properties on the thermal diffusivity and soil heat flux over Ayadi in Ondo State, Nigeria. Physical properties of the soil at different depths were determined using laboratory techniques. In-situ measurement of air temperature and surface soil temperature were carried out. The phase lag method was used to determine the thermal diffusivity of the soil, while the subsoil heat flux was determined from values obtained for the thermal diffusivity. The result showed that the subsoil heat flux values during the dry season ranged between 0.58 and 52.84 W/m2, while that of the wet season ranged between -0.77 and 98.50 W/m2. The average thermal diffusivity values at the different depths had values between 0.74 × 10-7 and 238.7 × 10-7 m2/s for the dry season, while the wet season had a range of 1.97 × 10-7 to 238.7 × 10-7 m2/s. Keywords: soil moisture content, air temperature, soil temperature, soil heat flux, thermal diffusivity.

Relationships between stem growth and climatic and edaphic factors, notably air temperatures and soil moisture for different slopes, are not completely understood. Stem radial variations were monitored at the bottom and top slope positions in a Larix principis-rupprechtii plantation during the 2017 and 2018 growing seasons. Total precipitation during the growing season in 2017 and 2018 was 566 mm and 728 mm, respectively. Stem contractions typically occurred after mid-morning followed by swelling in the late afternoon in both plots, reflecting the diurnal cycle of water uptake and loss. Trees at the two locations showed the same growth initiation (mid-May) because of the small differences in air and soil temperatures. There were no significant differences in cumulative stem radial growth between the bottom plot (1.57 ± 0.34 mm) and the top plot (1.55 ± 0.26 mm) in 2018. However, in 2017, the main growth period of the bottom plot ceased 17 days earlier than in the top plot, while cumulative seasonal growth of the bottom plot (1.08 ± 0.25 mm) was significantly less than the top plot (1.54 ± 0.43 mm). Maximum daily stem shrinkage was positively correlated with air and soil temperatures, solar radiation, vapor pressure deficits, and negatively correlated with volumetric soil moisture content. The maximum daily shrinkage reflected transpiration rates as affected by environmental factors. Daily radial stem increment was correlated with precipitation and volumetric soil moisture in both years, but with air temperatures only in 2017. The seasonal growth of L. principis-rupprechtii Mayr thus shows interannual dynamics, while precipitation constitutes a key driving factor.

In this study, the seed drill with double disk furrow openers was developed to suit planting in wet soil (Heraty sowing) by adding an auxiliary furrow opener, disk cleaning blade and soil firming roller. The performance of the developed seed drill was evaluated at different planting forward speeds of 1.8, 2.3, 3.1, and 4.2 km/h; different sowing depth of 5, 6 and 7 cm; and two different soil moisture content of 34.5 and 31.1% (d.b.). The emergence ratio, emergence period, seed scattering, slippage ratio were measured, and also the required power, consumed energy and total cost were estimated. The obtained results revealed that the developed seed drill can used for sowing in wet soil (Heraty sowing) at planting forward speed not exceed a limit of 2.3 km/h, sowing depth ranged between 5 - 6 cm and soil moisture content not exceed 31.1% (d.b.).

Evidence shows that soil moisture (SM) anomalies (deficits or excesses) are the key factor affecting crop yield in rain-fed agriculture. Over last decades, Poland has faced several major droughts and at least one major soil moisture excess event leading to severe crop losses. This study aims to simulate the multi-annual variability of SM anomalies in Poland, using a process-based SWAT model and to assess the effect of climate change on future extreme SM conditions, potentially affecting crop yields in Poland. A crop-specific indicator based on simulated daily soil moisture content for the critical development stages of investigated crops (winter cereals, spring cereals, potato and maize) was designed, evaluated for past conditions against empirical crop-weather indices (CWIs), and applied for studying future climate conditions. The study used an ensemble of nine bias-corrected EURO-CORDEX projections for two future horizons: 2021–2050 and 2071–2100 under two Representative Concentration Pathways: RCP4.5 and 8.5. Historical simulation results showed that SWAT was capable of capturing major SM deficit and excess episodes for different crops in Poland. For spring cereals, potato and maize, despite a large model spread, projections generally showed increase of severity of soil moisture deficits, as well as of total area affected by them. Ensemble median fraction of land with extreme soil moisture deficits, occupied by each of these crops, is projected to at least double in size. The signals of change in soil moisture excesses for potato and maize were more dependent on selection of RCP and future horizon.

Conversion of tropical peat swamp forests to increase and agricultural production has generated substantial peat carbon loss in the Asia-Pacific region. Different land-uses and management practices oxidize the tropical peat at diverse rates due mainly to different water table levels. In recent years, several studies have measured soil carbon dioxide emissions in-situ; however, only few studies have evaluated the effect of moisture on carbon dioxide fluxes in incubation experiments. Here, we present the dataset of an incubation performed with 360 intact peat cores from three different land-uses (i.e. 120 from intact peat swamp forest; 120 from drained logged peat forest; and 120 from oil palm plantation) collected on the peat dome of Jambi Sumatra Indonesia. Different moisture levels in the intact cores were set by either drying the intact peat cores for short period of time or by adding extra water before the incubation. Dynamic dark aerobic incubation in airtight containers coupled with carbon dioxide measurement with an infrared gas analyser and the gas fluxes was used to measure to gas fluxes. The average carbon dioxide fluxes were 5.38 ± 0.91, 4.15 ± 0.35 and 1.55 ± 0.13 µg CO2-C g−1 h−1 for the intact peat swamp forest, drained logged peat forest and oil palm plantation, respectively.

Internal erosion is widely perceived as contributing to the failure of earthen dams. To reduce the failure risk, timely monitoring of internal erosion is an effective method in observing their internal structure evolution. A set of earthen dam model experiments were conducted. Under an applied voltage, the response potential differences (PD) at the slope of the dam models were collected before and after the impoundment of the upstream reservoir. The discrepancy among the four dam models, the influence of soil moisture content on PD, and the impact of internal erosion on PD were studied. The results show that it is acceptable to employ different dam models to simulate the development of internal erosion, although the discrepancy among the models is inevitable. The moisture content of the soil significantly affects the PD response to applied voltage. The PD increases with an increase in soil moisture content until the soil is saturated. The change in PD is correlated with the development of internal erosion. With the progression of internal erosion, the starting position for the steep increase in PD distribution continues to move toward the dam toe. In addition, the electrode stability is noted to have an effect on measured PD, which requires further studies to be clarified. This study sets the stage for the PD-based monitoring method in observing the evolution of internal erosion in earthen dams.

Increases in extreme hydro-meteorological events due to climate change and decreases in soil permeability and infiltration due to urbanization have increased the risk of flooding, particularly in cities. The limitation of the expansion of conventional drainage systems to manage excess stormwater leads to the application of nature-based solutions (NBS) to control flooding. This study explores potential of green roof NBS for rainfall-fed flood reduction, which can utilize existing roof space for deployment. A detailed literature survey using systematic literature-search procedures was conducted to investigate the performance of extensive/intensive green roofs in runoff reduction using monitoring/modeling approaches. Since limited studies have explored the use of semi-intensive green roofs for flood management, a new simulation study has been developed to compare the effectiveness of semi-intensive green roofs. The performance of different types of vegetation used on green roofs in runoff reduction was investigated using a simulation study, which was validated using a real-world green roof deployed in Dublin.

Droughts are recognized as a natural disaster that is caused by the extreme and continuous shortage of precipitation. Drought indices assist in a number of tasks, including their early warning and monitoring by computing severity levels and proclaiming the start and end of droughts. Various drought indices were formulated for the forecasting and prediction of spatiotemporal drought characteristics using various hydrological variables, such as precipitation, evapotranspiration, runoff and soil moisture content. Due to anthropogenic global warming and the increase of temperature, evapotranspiration-based drought indices have become an interest in recent years in drought assessment. This paper attempts to provide more information on drought indices which incorporates Evapotranspiration. The study used Standardized Precipitation Evapotranspiration Index (SPEI), based on evapotranspiration to understand the drought variability at various time scales. This study adopted the Hargreaves model to calculate Potential Evapotranspiration. The SPEI index can also be used to study the wet and dry periods including Evapotranspiration along with precipitation. The study used SPEI to understand the dry and wet years over an urban semi-arid region, Hyderabad, capital and the biggest city of the southern Indian state of Telangana for the years 1965–2015. The years 1965, 1966, 1972, 1973, 1985, 1993 and 2012 were noted as dry years with SPEI values −1.35, −1.06, −1.43, −1.31, −1.05, −1.22 and −1.51 sequentially and year 2006 as the severe wet year with an SPEI value +1.65. The characterization of dry and wet years as demonstrated in the present study will enhance better urban water resources management.

Volatile organic compounds (VOCs) produced by plants are essential indicators of their physiological response to environmental conditions. But evidence of natural variation in VOC emissions and their contributing factors is still limited, especially for non-cultivated species. Here we explored the natural volatile emissions of Dracophyllum subulatum Hook.f., an endemic shrub to the North Island Central Plateau of New Zealand, and determined some environmental factors driving the plant’s emissions. Volatile emissions of D. subulatum were measured on four separate occasions from December 2017 to September 2018 using the “push-pull” headspace sampling technique and analyzed using gas chromatography-mass spectrometry (GC-MS). D. subulatum was classified based on the volatiles measured on each sampling occasion using linear discriminant analysis (LDA). On each sampling occasion, we also recorded and compared ambient air temperature, herbivory damage, total soil nitrogen (N), available phosphorus (P), potassium (K), and soil moisture content. The relationship between environmental variables that differed significantly between sampling occasions and volatile emissions were estimated using generalized linear models (GLMs). Based on VOCs measured on each sampling occasion, we were able to distinguish different chemical profiles. Overall, we found that total emission and the relative proportions of all major chemical classes released by D. subulatum were significantly higher during summer. The GLMs reveal that differences in environmental factors between the four sampling occasions are highly associated with changing emissions. Higher temperatures in summer had a consistently strong positive relationship with emissions, while the impacts of soil moisture content, P and K were variable and depended on the chemical class. These results are discussed, particularly how high temperature (warming) may shape volatile emissions and plants’ ecology.

In oil palm crop, soil fertility is less important than the physical soil characteristics. It is important to have a balance and sufficient soil moisture to sustain high yields in oil palm plantations. However, conventional methods of soil moisture determination are laborious and time-consuming with limited coverage and accuracy. In this research, we evaluated synthetic aperture radar (SAR) and in-situ observations at an oil palm plantation to determine SAR signal sensitivity to oil palm crop by means of water cloud model (WCM) inversion for retrieving soil moisture from L-band HH and HV polarized data. The effects of vegetation on backscattering coefficients were evaluated by comparing Leaf Area Index (LAI), Leaf Water Area Index (LWAI) and Normalized Plant Water Content (NPWC). The results showed that HV polarization effectively simulated backscatter coefficient as compared to HH polarization where the best fit was obtained by taking the LAI as a vegetation descriptor. The HV polarization with the LAI indicator was able to retrieve soil moisture content with an accuracy of at least 80%.

Open burning is often used to remove crop residue during the harvest season. Despite a series of regulations by the Chinese government, the open burning of crop residue still frequently occurs in China, and the monitoring and forecasting crop fires have become a topic of active research. In this paper, crop fires in Northeastern China were forecasted using an artificial neural network (ANN) based on moderate-resolution imaging spectroradiometer (MODIS) satellite fire data from 2013–2020. Both natural factors (meteorological, soil moisture content, harvest date) and anthropogenic factors were considered. The model’s forecasting accuracy under natural factors reached 77.01% during 2013–2017. When considering the influence of anthropogenic management and control policies, such as the straw open burning prohibition areas in Jilin Province, the accuracy of the forecast results for 2020 was reduced to 60%. Although the forecasting accuracy was lower than for natural factors, the relative error between the observed fire points and the back propagation neural network (BPNN) forecasting results was acceptable. In terms of influencing factors, air pressure, the change in soil moisture content in a 24 h period and the daily soil moisture content were significantly correlated with open burning. The results of this study improve our ability to forecast agricultural fires and provide a scientific framework for regional prevention and control of crop residue burning.