Initial Soil Moisture Research Articles

Prediction model of soil water infiltration under moistube irrigation

AbstractAs a new type of underground water‐saving irrigation method, moistube irrigation has great potential for promotion and development. However, the multi‐factor interaction influence and water infiltration prediction model of soil water infiltration under moistube irrigation need to be improved. This paper aims to obtain soil water infiltration data for different bulk densities (1.2, 1.3 and 1.4 g/cm3) and textures (loam, sandy loam and clay loam) under different pressure heads (1, 1.5 and 2 m) through an indoor moistube irrigation soil water infiltration test. By analysing multiple factors affecting soil water infiltration under moistube irrigation, the calculation method was determined with the initial soil moisture content, pressure head, bulk density and texture as the input variables and the Kostiakov model parameters as the output variables. Finally, the method of optimizing the back propagation (BP) neural network by a genetic algorithm (GA) was used to establish the Kostiakov prediction model of soil moisture in moistube irrigation, and the model was verified with analytics. The results showed that the Kostiakov prediction model based on GA‐BP had high accuracy and good consistency. The research results provide more practical proofs and perfect theoretical supplements for the study of soil water infiltration under moistube irrigation.

Prediction of Specific Fuel Consumption of a Tractor during the Tillage Process Using an Artificial Neural Network Method

In mechanized agricultural activities, fuel is particularly important for tillage operations. In this study, the impact of seven distinct parameters on fuel usage per unit of draft power was examined. The parameters are tractor power, soil texture index, plowing speed, plowing depth, width of implement, and both initial soil moisture content and soil bulk density. This study investigated the construction of an artificial neural network (ANN) model for tractor-specific fuel consumption predictions for two tillage implements: chisel and moldboard plows. The ANN model was created based on the collection of related data from previous research studies, and the validation was performed using actual field experiments in clay soil using a chisel plow. The developed ANN model (9-22-1) was confirmed by graphical assessment; additionally, the root-mean-square error (RMSE) was computed. Based on the RMSE, the results demonstrated a good agreement for specific fuel consumption per draft power between the observed and predicted values, with corresponding RMSE values of 0.08 L/kWh and 0.075 L/kWh for the training and testing datasets, respectively. The novelty of the work presented in this paper is that, for the first time, a farm machinery manager can optimize tractor fuel consumption per draft power by carefully controlling certain parameters, such as initial soil moisture content, tractor power, plowing speed, implement width, and depth of plowing. The results show that the input parameters make a significant contribution to the output over the used data with different percentages. Accordingly, the contribution analysis showed that the implement width had a high impact on tractor-specific fuel consumption for both plows at 30.13%; additionally, the chisel and moldboard plows contributed 4.19% and 4.25% in predicting tractor fuel consumption per draft power. This study concluded that practical useful advice for agricultural production can be achieved through optimizing fuel consumption rate by selecting the proper levels of affecting parameters to reduce fuel costs. Moreover, an ANN model could be used to develop future tractor fuel-planning schemes for tillage operations.

Effects of Freeze–Thaw Cycles on Soil Nitrogen Transformation in Improved Saline Soils from an Irrigated Area in Northeast China

Freeze–thaw cycles (FTCs) occur during the nongrowing season, and residual nitrogen (N) increases the risk of N loss with melting water. To study the effect of FTCs on soil N, rice fields in improved irrigated saline soil in northeast China were selected as the research subjects. Water content (10%, 20%, and 30%), different N fertilizer levels (180 and 220 kg/ha), and multiple FTCs of soil samples were used to clarify the effects of N fertilizer application and water content on N efficiency. The results indicate that, after the third FTC, the soil ammonium nitrogen (NH4+-N) level increased significantly. NH4+-N increased with an increase in the initial soil moisture content and decreased with fertilizer levels. Nitrate nitrogen (NO3−-N) decreases with increasing initial soil moisture. The inorganic N increased significantly compared with that in the unfrozen stage, indicating that FTCs promote soil N mineralization. However, high fertilization rates inhibit mineralization. Analysis of variance showed that NO3−-N is sensitive to the N application rate, water content, and salinity (p < 0.05). FTCs and artificial fertilization are the factors that affect N mineralization (p < 0.05). The research results are significant for preventing nitrate leaching and soil acidification during spring plowing and providing a scientific basis for fertilization systems and water environment pollution in improved saline soils.

Urban irrigation reduces moist heat stress in Beijing, China

AbstractAlthough urban irrigation can modulate local hydrothermal conditions and mitigate urban heat island effects, its impact on moist heat stress (MHS) is poorly understood. Employing the Weather Research and Forecasting Single-Layer Urban Canopy Model (WRF-SLUCM), we evaluated the effect of urban irrigation on the MHS in Beijing, China, and found that the updated initial soil moisture (SM) field improved the simulation of temperature, relative humidity, and wind speed. Besides, urban irrigation reduced urban and rural MHS, and particularly reduced afternoon and evening MHS by up to 1.2 °C but increased morning MHS by up to 0.4 °C. In addition, the effect of different irrigation times on MHS showed that irrigation at 02 and 20 h increased urban and rural MHS, with the best cooling effect at 00 and 13 h, which reduced the MHS by up to 2.65 °C in urban areas and 0.71 °C in rural areas. The findings highlighted mechanistically the effect of urban irrigation on MHS and shed light on how to mitigate urban heat island effects on urban sustainable development.

The Response of Precipitation to Initial Soil Moisture over the Tibetan Plateau: Respective Effects of Boundary Layer Vertical Heat and Vapor Diffusions

Abstract This study investigates the influences of initial soil moisture over the Tibetan Plateau (TP) on precipitation simulation, and the respective effects of boundary layer vertical diffusion for heat (Kh) and vapor (Kq). Results indicate that the responses of boundary layer vertical diffusion to soil moisture are obvious mainly in the daytime. Wetter land surface corresponds to weaker vertical diffusion, which could strengthen thermal forcing and dynamic lifting in the lower atmosphere, and encourage water vapor saturation near the top of boundary layer to prevent the environmental dry air entrainment/invasion, which would be beneficial to more convection and precipitation. Wetter land surface over the TP could enhance the contrast between the cold in the northwestern TP and the warm in the southeastern TP, which would be conducive to the southeastward propagation of precipitation. The simulation of heat and moisture in the boundary layer could be improved by perturbing the relative intensity of Kh and Kq. From the perspective of heat and moisture, Kh affects atmospheric stability, while Kq affects moisture and its vertical transport in the boundary layer. The Kh and Kq have competitive effects on precipitation intensity by influencing the relative importance of moisture and atmospheric stability conditions in the boundary layer. Adjusting the relative intensity of Kh and Kq would deactivate the competitive effects. Stronger Kh but weaker Kq would alleviate the overestimated precipitation by inhibiting vertical transport of moisture to the top of boundary layer and attenuating convective instability in the boundary layer. Significance Statement The purpose of this study is to better understand the effects of boundary layer vertical heat and moisture diffusion in the response of precipitation to soil moisture. This is important because boundary layer vertical diffusion is a crucial factor influencing the relation between soil moisture and precipitation. Our results reveal the competitive effects of boundary layer vertical diffusion for heat and vapor on the simulation of precipitation. These results point a potential way toward better understanding the response of precipitation to soil moisture.

Effect of bentonite particle sizes on GCL hydration by lateritic soils

Numerous studies have analysed the influence of subgrade on the hydration process of GCLs and have shown that initial soil moisture content, particle sizes and soil mineralogy significantly affect the GCL hydration process. However, recent works have revealed that GCLs structure and bentonite characteristics are also a major variable in this process, affecting the water retention curve (WRC), hydration levels and long-term performance of the GCLs. This study examines the impact of bentonite particle size on the hydration process of a GCL when in contact with lateritic subgrades. The hydration process of three different GCLs was analyzed under isothermal conditions in a closed system. The results indicated an influence of bentonite particle sizes on the GCL hydration processes. GCL with granular bentonite showed difficulty in hydration from lateritic subsoils compared to GCLs with powdered bentonites.

Effects of slopes, rainfall intensity and grass cover on runoff loss of mercury from floodplain soil in Oak Ridge TN: A laboratory pilot study

Mercury is recognized as a global pollutant. A large amount of elemental mercury was used in the Manhattan Project in Oak Ridge, TN and Hg is still present in the water-shed surrounding the Y-12 facility and East Fork Poplar Creek. Soil erosion during rainfall-runoff events result in nonpoint source Hg transport from floodplain soils to aquatic ecosystems. This study investigated transport mechanisms of Hg through surface runoff processes from floodplain soils in Oak Ridge, TN into water with a simulated rainfall laboratory pilot scale experiment. The experiments simulated rainfall intensity (50–140 mm/h), the ground grass coverage (5 %-85 %), the soil moisture conditions and the slopes (7.5–16.32 degrees) producing soil runoff erosion processes. Results show that high grass coverage, decreased landscape slope and low rainfall resulted in the decreased Hg concentrations in sediments transported through runoff from the floodplain soil. Hg loss was strongly correlated with and controlled by soil loss. The order of environmental factors on Hg loss was the slope > rainfall intensity > grass cover. As grass cover increased from 5 % to 85 %, Hg in sediment decreased from 124 to 72.3 µg/kg and Hg in penetrating water decreased from 4.7 to 2.8 µg/kg on wet soil condition at the slope 12.560. Hg loss and soil loss significantly increased with the increase of the soil slope. As the slope increased from 7.550 to 12.560, Hg loss increased from 364 to 2905 mg/m2 in the dry soil condition with 5 % grass cover. Meanwhile Hg loss and soil loss significantly decreased with the increase of grass cover. The Hg concentration in sediment increased with increasing initial soil moisture from Dry Soil, to Wet Soil and Very Wet Soil. The roots of grasses stabilized soil Hg and the Hg content in soil rhizosphere were significantly higher than that in non-rhizosphere. This study indicates that rainfall intensity, ground grass coverages, landscape slopes and initial soil moisture content strongly controlled Hg transport from the floodplain ecosystem and its flux into stream water. Mercury associated with sediment was the major Hg input into stream waters from floodplain soils in Oak Ridge, TN. Proper onsite management, such as increasing ground coverages with local low lying grasses and decreasing landscape slopes may significantly reduce potential Hg transport into local stream water in Oak Ridge TN.

Nitric Acid and Organic Acid Mixture Show Less Deviation in Extractability of Potassium Between Field-Moist and Air-Dried Soil

ABSTRACT Air-drying of soils for testing can cause fixation/release of potassium (K), showing a K status different from that of the field. We compared different extractants to find one with the least deviation in K-extractability between field-moist and air-dried soils. We chose two treatments (No-K and 150% of recommended K fertilization) of a field experiment (maize-wheat) for the study. Field-moist soil (0–15 cm) was collected at 3, 4, 5, 6, 7, 8, 23, 24, 25, and 26 days after the irrigation (DAI) from each replicated plot at the flowering stage of the 2018–19 wheat crop. Soil K, before and after air-drying, was extracted with 1 M ammonium acetate (NH4OAc), 0.1 M nitric acid (HNO3), 0.01 M calcium chloride (CaCl2), and 0.01 M organic acid mixture (OAM, mixture of 0.0025 M each of citric acid, malic acid, tartaric acid, and oxalic acid). Air-drying significantly (P < .05) affected the soil K for all methods except HNO3 in plots without K fertilization. However, air-drying’s effect on K release was more pronounced in No-K soils with high initial moisture content (>10%). Averaged over K-fertilization and initial soil moisture, the K-extractability using HNO3 and OAM showed the least deviation (9.6% for both) by air-drying. It was significantly (P < .05) lower than NH4OAc or CaCl2, which showed as high as 21.1–23.0% deviation due to air-drying. Hence, one should use 0.1 M HNO3 or 0.01 M OAM instead of 1 M NH4OAc to get an available K status closer to that in the field.

Severe convective outbreak in Siberia in May 2020: Event analysis and high-resolution simulation

Western Siberia is exposed to extreme wind events caused by severe convective storms. However, our knowledge on such storms in Siberia is still fragmentary compared to other parts of the world primarily due to the lack of weather radar data. These storms cause substantial damage, which signifies the need for comprehensive assessment of their characteristics and predictability even on the basis of existing data. In this paper, we present a case study analysis of a severe weather outbreak that occurred on 25–26 May 2020 in Western Siberia, during a record six-month heatwave that lasted in Siberia from January to June. The outbreak resulted in six fatalities and substantial economic losses. Using various satellite data and damage reports we found that two consecutive mesoscale convective systems (MCSs) developed within the outbreak having an exceptionally long total track about 2000 km and causing large-scale forest damage with a total area of 64.5 km2. Such an exceptionally long path was supported by a strong mid-tropospheric jet, which settled extremely high values of wind shear that fostered the development of the outbreak. To analyze the accuracy of the forecast of the MCS and three associated windstorms on 26 May, we performed a set of simulations with the COSMO and ICON numerical weather prediction models launched with convection-permitting resolution (2.2 km) with different forecast lead times. Both models successfully predicted the most severe windstorm with the <50 km spatial displacement and the <1.5 h time shift, but COSMO generally simulated more strong wind. However, two other windstorms of that day were predicted with lower accuracy. The simulation results revealed a limited sensitivity of the model to variations in initial soil temperature and moisture. Together with the better performance of the forecast with >24 h lead time, this emphasized the predominant role of large-scale dynamics and the minor role of local factors in the outbreak formation and development. In particular, the intrusion of the upper tropospheric high potential vorticity streamer along the blocking periphery induced strong deep convection and determined the severe character of the outbreak. Specifically, the studied outbreak had an exceptional longevity compared to other long-lived windstorms observed in Northern Eurasia at the blocking periphery.

Effects of freeze-thaw on soil detachment capacity in the black soil region of Northeastern China

Soil detachment capacity (Dc) is an important parameter used to determine erosion intensity in physical-process-based erosion models. Freeze-thaw affects soil detachment processes by altering the mechanical properties of soil; however, due to the compound action of freeze-thaw and runoff on Dc, quantifying the impact of seasonal freeze-thaw on Dc remains challenging. A series of experiments with six freeze-thaw cycles (FTC), six initial soil moisture contents (SMC), three slope gradients, and five flow discharges were conducted to investigate the effect of freeze-thaw and hydrodynamic characteristics on Dc. The results showed that soil shear strength (τm), cohesion (Coh), and internal friction angle (φ) gradually tended to become stable with increasing FTC, indicating that repeated FTC had a cumulative impact on soil mechanical properties, and there was a critical FTC between 5 and 7. When FTC rose from 1 to 15, the reduction in τm, Coh, and φ was 0.03∼23.96%, 2.63∼75.21%, and − 5.70∼19.24%, respectively, which increased with an increasing SMC, suggesting that the deterioration effect of FTC on soil mechanical properties was promoted by increasing SMC. During alternating FTC, the relative range and variation coefficient of Dc were 2.21–2.43 and 67.87–75.72%, respectively, indicating that Dc was highly sensitive to FTC. Furthermore, Dc increased by 2.37–71.22% after 15 FTC. Alternating freeze-thaw weakened the soil resistance to detachment. Moreover, the promoting effect of FTC on Dc intensified with an increasing SMC, indicating that the variation in Dc was strongly affected by SMC during FTC. A prediction model (R2=0.955, RRMSE=14.99%) was established to quantify the influence of freeze-thaw and hydrodynamic characteristics on Dc. The explanation rate of variables in the Dc prediction equation was quantitated: the explanation rate of stream power (64.3%) was higher than that of FTC (10.02%) and SMC (3.92%), suggesting that the impact of freeze-thaw on Dc was covered by hydrodynamic characteristics. Further validation is required for the prediction equations when applied beyond the range of construction conditions.

Initial soil moisture prewinter affects the freeze–thaw profile dynamics of a Mollisol in Northeast China

The freeze–thaw characteristics are of great hydrological significance in seasonally frozen agricultural soil and may vary for different initial moisture conditions because of variability in land use, topography, tillage and climate change. However, the initial soil moisture regimes before winter freezing that control the dynamics of profile freeze–thaw cycles remain unclear. This study explored the soil profile freeze–thaw dynamics under different prewinter moisture regimes located in a seasonally frozen Mollisol in China. The high, medium and low soil moisture regimes were simulated by infiltrating different water into the soil profiles before winter freezing. We investigated the soil temperature and water content at five depths from October 2017 to May 2018. Our results revealed that the variation in soil water storage occurred after infiltration before winter freezing and lasted throughout the thawing period. The highest soil water occurred above a depth of 20 cm in the early days of the thawing period under all treatments. During the thawing period, the soil water content was highest above depths of 0–20 cm, 20–40 cm and 40–60 cm under high, medium and low infiltration, respectively. Freezing took longer than thawing from 0 cm to 100 cm soil depths. Freezing started later and thawing ended later under higher soil moisture conditions prewinter. The top 10 cm of soil experienced intense soil temperature rise and fall cycles with an average of 20 cycles during the thawing, and higher moisture conditions reduced the freeze–thaw cycles. The depth of zero amplitude in soil temperature under high, medium and low soil water was estimated as approximately 140, 134 and 160 cm, respectively. Our findings suggest that more attention should be given to the top layers and sidewall layers under the lower prewinter soil moisture conditions. This study provides a very detailed understanding of soil temperature and moisture dynamics over a full winter freeze–thaw cycle and would makes a worthy contribution in seasonally frozen areas where few such comprehensive datasets exist.

Biological denitrification inhibition (BDI) on nine contrasting soils: An unexpected link with the initial soil denitrifying community

Denitrification is considered the major pathway leading to soil gaseous (N) losses, affecting N availability for plants and consequently plant productivity. Biological denitrification inhibition (BDI) in Fallopia spp., a plant species complex with a high level of growth and competitiveness for mineral N, acts through procyanidin production. However, the soil factors governing BDI development are still unknown. Through a mesocosm experiment using two treatments – soil planted with Fallopia japonica and unplanted–, nine biologically and physically contrasting soils were studied with the aim to ascertain how each can affect BDI development. Microbial enzyme activities (respiration - SIR, denitrification - DEA), denitrifying functional gene abundance (nirK, nirS), total bacterial community abundance (rRNA 16S) and soil physicochemical parameters (N mineral forms, soil texture, moisture, pH) were measured before and after plant growth, and the DEA:SIR ratio was used as a BDI proxy. The DEA:SIR ratio decreased for six soils. BDI development is related to a small number of soil factors, mainly initial soil moisture and ammonium concentration, and unexpectedly, with the initial abundance of nirK(in), nirS(in) and rRNA 16S(in). The intensity of this decrease is positively correlated to the level of DEA in unplanted soil: the higher the DEA in unplanted soil, the more intense the BDI under F. japonica. The procyanidin concentration of the F. japonica belowground system was positively correlated to BDI intensity. These results suggest that a procyanidin assay from the plant belowground system could be a new proxy for measuring BDI intensity. Interestingly, this research shows that BDI is not systematic, and that few (a)biotic soil parameters influence its development. More importantly, this research is the first to highlight that biotic factors are relevant in explaining BDI. This paper also presents new perspectives on plant-microorganism interactions in terms of plant awareness of the soil microbial community.

Exploring an intelligent adaptation method of hydrological model parameters for flood simulations based on the light gradient-boosting machine

Traditional hydrological modeling methods use a set of parameters to simulate flood processes with complex causes and variable intensity, which can easily lead to parameter instability. To address the problem of parameter instability, this study proposes an approach integrating the hydrological model with Intelligent Adaptation Parameters (IAP), whose intelligent adaptation relationship is established by the light gradient-boosting machine (LightGBM) based on individual calibration parameters by each flood event and flood characteristics including flood-caused rainstorm information and initial soil moisture. A widely used hydrological model, Xin 'anjiang (XAJ) model, is chosen to be integrated with IAP (XAJ-IAP) in this study, which has a relatively complex structure and a total of 15 model parameters. The obtained findings demonstrate that: (1) recalibrating the sensitive runoff concentration and separation parameters with a single flood leads to a notable enhancement in simulation accuracy, while simultaneously considering the model's physical significance; (2) the XAJ overestimates large floods and underestimates small floods. Compared with the XAJ, the XAJ-IAP has a better rain-flood response relationship and simulation accuracy for floods of different magnitudes, solving the problem of parameter instability that exists in XAJ; and (3) evaluated in terms of information gain, sensitive parameters contribute the most to the establishment of the intelligent adaptation relationship in the LightGBM compared to flood-caused rainstorm information and initial soil moisture, indicating that sensitive parameters are the most important input features of the LightGBM. It can be concluded that the intelligent adaptation system can not only solve the problem of parameter instability that exists when traditional hydrological models simulate complex and changeable floods, but also further reveal the relationship between the model and floods.

Determining the Stabilised Subfoudation Soil Deformation Modulus According to the Plate Load Tests and Geotechnical Monitoring Data

Introduction. The subsiding soils, which are widely spread in the south of Russia, create a number of problems and hazards due to the high probability of subfoundations subsidence in case of exceeding the values of initial soil moisture and initial pressure for subsidence. This is an important phenomenon to be considered at all life cycle stages of a building or structure, especially at the stage of design, when the scientifically justified design and technological solutions must be developed to ensure the reliable operation of facilities in the complicated engineering and geological conditions being studied hereby. The present article analyses the acting federal and regional regulatory and technical documentation in the field of buildings and structures design on the subsiding soils. Based on the numerical experiment, the incorrectness of the results sometimes received upon following the normative methodology is shown. A new calculating methodology based on determining the stabilised subfoudation soil deformation modulus according to the plate load tests and geotechnical monitoring data is proposed.Materials and Methods. The research comprised:– analysis of the existing approaches and methodologies for the subfoundations and foundations design on the subsiding soils;– numerical experiments, including calculations according to the normative methodology, which implied variation of the original data of both the initial properties of soils and technological parameters of stabilisation, as well as statistical processing of the results;– analysis of the carried out earlier by the authors geotechnical monitoring results of the buildings built on the stabilized soils and experimental study of the deformation properties using a patented device;– determining the main factors having influence on the design solutions for the subfoudation soils and building foundations strengthening under a complicated set of operational loads and establishing a new dependence of the stabilised soil deformation modulus on the initial soil deformation modulus and percentage of soil reinforcement.Research results. It has been established that the existing methodologies for calculating the stabilised subfoudation soils are not enough precise for determining the forecastable subsidence of buildings and structures, and the obtained design values do not always correspond to the factual deformations of subfoundations and foundations. The dependence of the stabilised subfoudation soil deformation modulus on the initial soil deformation modulus and percentage of soil reinforcement with the cement-sand mortar has been traced. A new calculating methodology has been developed based on determining the stabilised subgrade soil deformation modulus according to the data of the plate load tests using a patented device and geotechnical monitoring.Discussion and conclusion. It has been established that the deformation modulus of the soil mass stabilised by the cementation method depends non-linearly on percentage of soil reinforcement with the cement-sand mortar and the initial soil deformation modulus, and this dependence is described by a second-order surface equation of a general form. It is recommended to apply the discovered dependencies for designing the technological parameters of the subsiding soils stabilisation in the Rostov region conditions.

A Novel Analytical Solution for Ponded Infiltration With Consideration of a Developing Saturated Zone

AbstractPonding at the soil surface exerts profound impacts on infiltration. However, the effects of ponding depth on infiltration, especially the development of a saturated zone below the soil surface, have yet to be considered in present infiltration models. A new general Green‐Ampt model solution (GAMS) was derived for a one‐dimensional vertical infiltration problem under a uniform initial moisture distribution with ponding on its surface. An expression was included in the new solution for simulating the saturated layer developed below the soil surface as long as the pressure head at the surface is sufficiently high to saturate the soil. The GAMS simulates the infiltration processes closer to the numerical solution by HYDRUS‐1D than the traditional and the recently improved Green‐Ampt model. Moreover, an inversion method to improve the estimates of soil hydraulic parameters from one‐dimensional vertical infiltration experiments that is based on the GAMS was suggested. The effect of ponding depth (hp), initial soil moisture content, soil texture, and hydraulic soil properties (saturated hydraulic conductivity Ks, water‐entry suction hd and shape coefficient n of soil water retention curve) in the saturated zone was also evaluated. The results indicate that the saturated zone length increased at a comparable rate with the unsaturated wetted zone length during infiltration. Generally, a larger saturated zone was found for soils with higher initial soil moisture contents, coarser texture, higher Ks values, greater n, and lower −hd. Our findings reveal that including the saturated zone in the infiltration model yields a better estimate of the soil hydraulic parameters. The proposed GAMS model can improve irrigation design and rainfall‐runoff simulations.

The Soil Moisture–Surface Flux Relationship as a Factor for Extreme Heat Predictability in Subseasonal to Seasonal Forecasts

Abstract Thresholds of soil moisture exist below which the atmosphere becomes hypersensitive to land surface drying, inducing thermal feedbacks that can exacerbate heatwaves. Realistic representation of threshold transitions in forecast models could improve extreme heat predictability and understanding of the role of land–atmosphere coupling. This study evaluates the performance of several forecast models from the Subseasonal Experiment (SubX) and several prototype versions of the Unified Forecast System (UFS) in their representation of threshold transitions by validation against reanalysis data. A metric of skill (true skill score) is applied to soil moisture breakpoint values, which mark the transition to heatwave hypersensitivity for drying soils. Forecast models have poor skill at being initialized on the correct side of the breakpoint, but show improvement when normalized to account for deficiencies in their soil moisture climatologies. Regionally, models performed best in the U.S. Northwest and worst in the Southwest. They effectively capture the tendency of western regions to spend more summer days in the hypersensitive regime than the eastern United States. Models represent well extreme heat as a consequence of atmospheric initial state for the first week of the forecast, but struggle to represent the soil moisture feedback regime. Forecast models generally perform better at extreme heat prediction when they are already dry and in the hypersensitive regime, even when erroneously so, implying that errors or biases exist in model parameterizations. Nevertheless, composite analysis shows encouraging model performance of the “hit” category, suggesting that an improvement in soil moisture initialization could further improve extreme heat forecast skill.

Evaluating The Effect of Initial Soil Moisture Content on Infiltration Characteristics Using Empirical and Hydrus 1D Models

Evaluating The Effect of Initial Soil Moisture Content on Infiltration Characteristics Using Empirical and Hydrus 1D Models

PENGARUH DURASI IRIGASI TETES TERHADAP REDUKSI LENGAS TANAH PADA LAHAN POLYBAG

Soil moisture is an important factor needed by plants for growth, and therefore the amount of soil moisture that can be stored depends on the type of soil or the composition of the soil-forming materials. Compost is one of the nutrients that is often used in the manufacture of planting media on land in the form of polybags, and the amount of compost composition on the soil is thought to greatly affect the ability to store water in the media, both the size and duration of storage. This study aims to examine the effect of using compost on storage of irrigation water in the form of soil moisture and how long it can be stored. in three-storey drip irrigation. The main data analyzed is soil moisture data (w) and the results of the analysis and discussion and conclusions are drawn descriptively. The results of the analysis show that the initial soil moisture content in the range of 19% -25%, can be given additional soil moisture by irrigation of about 12%. The average daily decrease in soil moisture that occurs in soil variation 1 (70%: 30% ) is 3% -4.4% and in soil variation 2 (50%: 50%), the average moisture reduction is around 3% -6%, soil moisture reduction in variation 2 is greater than soil variation 1 for all floors.

Effect of Different Irrigation Managements on Infiltration Equations and Their Coefficients

The main aim of this paper was to analyze the sensitivity of the five infiltration equations (Kostiakov, Kostiakov–Lewis, Philip, Horton and SCS) and their coefficients to various ponding depths and initial soil moisture under different irrigation managements. The treatments included three qualities of water (electrical conductivity = 6, 3 and 0.6 dS/m), two managements of irrigation (intermittent irrigation and daily irrigation) and three irrigation periods (100, 45 and 8 days). The HYDRUS-1D model was calibrated to simulate infiltration in various initial soil moistures and ponding depths. Evaluating the performance of infiltration equations showed that the Horton and Kostiakov–Lewis had better accuracy and Kostiakov and SCS had less accuracy than the other equations. The empirical coefficients of SCS and Kostiakov had the most and least sensitivities, respectively. Furthermore, Horton was the most sensitive equation, while SCS was the least sensitive one. The output parameters under daily management were the most sensitive to variations in infiltration coefficients, especially when the salinity and sodium contents of water and soil were higher. The results also showed that the effect of the initial soil moisture on the infiltration coefficient in high permeable soil (arising from daily management) was greater; but in low permeable soil (arising from intermittent management), the ponding depth was more effective. It is concluded that the infiltration equations (specifically the SCS equation) and their coefficients (specifically coefficient c) should be calibrated relative to the initial soil moisture, ponding depth, soil solution and water irrigation quality. Particularly in areas with high permeable soil (in the daily management), the calibration of the infiltration equation should be conducted with the initial soil moisture. In these areas, the irrigation period should be controlled. In areas with low permeable soil (in intermittent management), calibration should be carried out relative to the ponding depth. In these areas, the inflow rate should be controlled.

Experimental analysis to assess the hydrological efficiency and the nutrient leaching behavior of a new green wall system

Green Walls represent a sustainable solution to mitigate the effects due to climate change and urbanization. However, although they have been widely investigated in different fields of science, studies on the potential of these systems to manage urban stormwater are still few. Moreover, even if these systems provide multiple benefits, as other nature-based solutions, they leach nutrients due to growing media, decomposed vegetation, and the possibility of fertilizer use. In this regard, several studies have evaluated the nutrient concentrations in the runoff from green roofs, while studies that have analyzed the nutrient-leaching behavior of green walls are still limited. To bridge these scientific gaps, this study presents experimental findings on the hydrological efficiency and nutrient-leaching behavior of an innovative modular living wall system. Some rainfall-runoff tests were carried out to assess the hydrological response of a new green wall system in retaining stormwater. To evaluate the concentration of the nutrients, the collected outflow was analyzed by spectrophotometer UV–visible. The findings show that the developed green wall panel presents good retention capacity by considering different simulated rainfalls and varying the initial soil moisture conditions. The results in terms of nutrient concentrations highlight that the vegetation life cycle and the fertilizer uses affect the quality of the water released from the green wall panel. The concentration of the analyzed nutrients is influenced by the simulated rainfall's hydrological characteristics and the days between the planting phase and the test. However, the overall results show that the concentrations of each analyzed nutrient are low, except after the fertilizer use, highlighting that the choice of vegetation that does not need external nutrients should be preferred during the design of a green wall.