Simulated Heavy Rainfall Research Articles

Effects of Initial and Boundary Conditions on Heavy Rainfall Simulation over the Yellow Sea and the Korean Peninsula: Comparison of ECMWF and NCEP Analysis Data Effects and Verification with Dropsonde Observation

Effects of Initial and Boundary Conditions on Heavy Rainfall Simulation over the Yellow Sea and the Korean Peninsula: Comparison of ECMWF and NCEP Analysis Data Effects and Verification with Dropsonde Observation

Direct and Indirect Effects of Mountain Heights on Heavy Rainfall in the Hokitika Region of New Zealand

In the Hokitika region, on the west coast of the South Island of New Zealand on 18 June 2015, very heavy stratiform precipitation (>200 mm/per day) occurred under north-westerlies with small CAPE (<25 J/kg). Analyses of model simulations and observations showed that this heavy rainfall was due to cold-front lifting enhanced by orographic lifting over the Southern Alps. At 1.5 km grid-length, the model terrain underestimated the average height of the 103 tallest mountains over the South Island by ~800 m. This led to weaker orographic lifting and mountain blocking, and a faster-moving and stronger cold front in the Hokitika region. As a result, large errors in the heavy rainfall prediction occurred. By increasing either the resolved or the sub-grid mountain heights, the simulated rainfall errors were largely reduced through stronger orographic lifting and mountain blocking, and simulation of the cold front movement and strength was improved. All the experiments have the same “flow-over” regime with mountain waves and/or wave breaking (Fm ranges 0.61–1.21). However, the rainfall amount and distribution on the windward side of the mountains varied significantly. Our new findings were that the Southern Alps can have significant indirect effects on heavy rainfall by altering the speed and strength of the cold front, in addition to the well-known direct dynamical effects (i.e., orographic lifting and mountain blocking). A combination of these direct and indirect effects makes the heavy rainfall simulation sensitive to mountain heights even under the same “flow-over” regime.

Integrating Ensemble Weather Predictions in a Hydrologic-Hydraulic Modelling System for Fine-Resolution Flood Forecasting: The Case of Skala Bridge at Evrotas River, Greece

Ensemble weather forecasting involves the integration of multiple simulations to improve the accuracy of predictions by introducing a probabilistic approach. It is difficult to accurately predict heavy rainfall events that cause flash floods and, thus, ensemble forecasting could be useful to reduce uncertainty in the forecast, thus improving emergency response. In this framework, this study presents the efforts to develop and assess a flash flood forecasting system that combines meteorological, hydrological, and hydraulic modeling, adopting an ensemble approach. The integration of ensemble weather forecasting and, subsequently, ensemble hydrological-hydraulic modeling can improve the accuracy of flash flood predictions, providing useful probabilistic information. The flash flood that occurred on 26 January 2023 in the Evrotas river basin (Greece) is used as a case study. The meteorological model, using 33 different initial and boundary condition datasets, simulated heavy rainfall, the hydrological model, using weather inputs, simulated discharge, and the hydraulic model, using discharge data, estimated water level at a bridge. The results show that the ensemble modeling system results in timely forecasts, while also providing valuable flooding probability information for 1 to 5 days prior, thus facilitating bridge flood warning. The continued refinement of such ensemble multi-model systems will further enhance the effectiveness of flash flood predictions and ultimately save lives and property.

Influence of antecedent soil moisture content and land use on the surface runoff response to heavy rainfall simulation experiments investigated in Alpine catchments

In small Alpine catchments, floods are mostly triggered by surface runoff generation during convective heavy precipitation events. Their magnitude also depends on the antecedent soil moisture content, which was shown in several previous studies. This study aims at understanding (a) which sites change their surface runoff response to rainfall events with high precipitation intensity under very moist pre-conditions to what extent and (b) on which site characteristics this depends on. Therefore, we conducted repeated rainfall simulation experiments (40–80 m2, 1 h, 100 mm h−1) at 20 sites in five Eastern Alpine areas and analyzed their results on the basis of soil-physical parameters derived from collected soil samples.The hay meadow sites reacted with a strong increase in surface runoff to reduced saturation deficits, the pasture sites showed a smaller but visible response. The forest sites had the highest water retention capacities. The change in the surface runoff response is a function of the saturation deficit at the beginning of the initial experiment (r = −0.58). The soil physical parameters, especially the fine pore fraction (r = 0.56), correlate with the difference of the total surface runoff coefficient between the initial and the repeated experiment. The fine pore fraction also shows a high correlation (r = −0.78) with the saturation deficit at the beginning of the initial experiment, although pores of this fraction were saturated during all experiments. (Non-quantifiable) Land use effects, which in turn influence the soil physical parameters, play an important role in explaining how the surface runoff response in the repeated rainfall simulation experiment differs from the initial experiment. The information on land use and soil characteristics allowed the sites to be categorized into four types in terms of surface runoff disposition and the increase in total surface runoff coefficient in the second rainfall simulation experiment.

Glyphosate-Based Herbicide Formulations with Greater Impact on Earthworms and Water Infiltration than Pure Glyphosate

Glyphosate is the most widely used active ingredient (AI) in thousands of glyphosate-based herbicides (GBHs) worldwide. Short-term impacts of AIs or GBHs on earthworms are well known, but few studies have examined long-term legacy effects >3 months after application. In a pot experiment, we studied both short-term and long-term effects on deep burrowing earthworms (Lumbricus terrestris) and soil functions. Therefore, the cover crop Sinapis alba was grown in soils with either 3.0% or 4.1% soil organic matter content (SOM) and either sprayed with a GBH (Touchdown Quattro, Roundup PowerFlex, or Roundup LB Plus) or the respective glyphosate AI (diammonium-, potassium-, or isopropylamine-salt) or hand weeded (control). Long-term effects showed increased earthworm activity under GBHs even 4 months after application, but similar activity under AIs and control. Another application of the same treatments 5 months after the previous one also increased earthworm activity under GBHs, especially at high SOM levels. Water infiltration after a simulated heavy rainfall was 50% lower, and leaching was 30% higher under GBH than under AI application or hand weeding. Individual GBHs and AIs varied in their effects and were influenced by SOM and soil moisture. Full disclosure of all ingredients in GBH formulations would be necessary to allow a comprehensive assessment of environmental risks.

Sensitivity of cloud microphysics on the simulation of heavy rainfall in WRF- a case study for the 7–10 August 2019 event over Kerala, India

This work investigates the mechanism of the extremely heavy rainfall event during 7–10 August 2019 in Kerala. As the skill of WRF model for simulating the heavy rainfall strongly depends on the choice of cloud microphysics (CMP), sensitivity analysis is performed using cloud resolving WRF simulations with different CMP schemes to assess their performance. Total five sensitivity experiments are conducted by varying CMP schemes namely Thompson, Goddard, WSM6, Kessler and Purdue-Lin. Model results along with the fifth generation European Reanalysis (ERA5) data indicate that the heavy rainfall occurred in association with the monsoon depression, intensification of off-shore trough, and low-level jet (LLJ) phenomena and associated moisture transport and convergence. Our results clearly suggest that the heavy rainfall occurred during 7–10 August 2019 was less intensive compared to the August 2018 event. One of the prime reasons for meagre intensity is the presence of the upper tropospheric cyclonic flow over southeast Arabian Sea off Kerala, which reduced the intensity of low-level westerly flow, moisture transport and convection in 2019 event relative to the 2018 event. Comparison of simulated rainfall against station and gridded rainfall data indicate that the spatial and temporal variations of rainfall could be reproduced except that the model slightly over-estimated rainfall at a few stations in the central parts of Kerala. Out of the five CMP schemes, Thompson scheme simulates large amounts of cloud, rain, and snow during the period of peak rainfall with relatively low amounts of ice. Moreover, Thompson indicates a high warming in the 4–6 km layer due to large snow production while Lin and Goddard configurations exhibit altitude shift in this pattern i.e., more heating in the upper troposphere (9–15 km layer) due to producing more solid hydrometeor distributions and associated freezing processes. Among the CMP schemes, Thompson followed by Goddard better simulated the spatial and temporal distribution of rainfall as they produced the strongest convergence, CAPE and vertical motions compared to WSM6, Lin and Kessler schemes. Moreover, the simulated hydrometeor mixing ratios in the 2019 heavy rainfall event are less by 60–80% as compared to that of 2018 due to differences in the synoptic settings.

Effects of joint assimilation of FY-4A AGRI and ground-based microwave radiometer on heavy rainfall prediction

As the latest generation of Chinese Geostationary Weather Satellites, Fengyun-4 carries the Advanced Geosynchronous Radiation Imager (AGRI), which has more spectral bands and higher temporal and spatial resolution than the Visible Infrared Spin-Scan Radiometer (VISSR) onboard geostationary satellite FY-2. Direct assimilation of the FY-4A AGRI datasets has been proved to be an efficient way to improve heavy rainfall simulation. We aim to assess the joint assimilation of AGRI infrared radiance and ground-based MWR (Microwave Radiometer) data on short-duration heavy rainfall prediction. RTTOV (Radiative Transfer for the TIROS Operational Vertical Sounder) is used as the observational operator for FY-4A AGRI data assimilation. The data assimilation interface is built in WRFDA 4.3 to achieve direct assimilation of FY4A AGRI radiance. The forecasting effectiveness of the joint assimilation for a typical heavy rainfall event over northern China is analyzed with four simulation experiments. The main conclusions are: 1) Assimilating MWR data can improve the initial humidity condition in the middle-lower layers, while AGRI radiance assimilation favors the initial humidity correction in the middle-upper layers. The joint assimilation of two datasets can remarkably improve the initial humidity condition in the entire column. 2) Data assimilation effectively improves the 6-h accumulated rainfall simulation. The joint assimilation of AGRI radiance and MWR data is superior to assimilating either of them. The joint assimilation significantly improves the rainfall forecast over the Beijing area, where the seven MWRs are distributed. 3) Data assimilation experiments present similar effects on predicted and initial humidity conditions. The MWR_DA experiment (only assimilate MWR data) markedly improves the humidity forecast in the middle-lower layers, while AGRI_DA (only assimilate AGRI data) is effective in the middle-upper layers. The joint assimilation of AGRI radiance and MWR data could skillfully correct the humidity distribution in the entire layers, allowing for more accurate heavy rainfall prediction. This paper provides a valuable basis for further improving the application of FY-4A AGRI radiance in numerical weather models.

Microplastic surface retention and mobility on hiking trails

Hiking and trail running are a source of microplastic (MP) pollution on recreational trails in wilderness and conservation areas; however, the fate of MPs deposited on trails is poorly understood as MP mobility on such surfaces has not yet been examined. In this study, we simulated heavy rainfall (100 mm/h) on trail surfaces with existing MP pollution (in situ MPs) and spiked with 99 ± 2 rubber MPs (100–940 μm). Runoff was collected for 15 min and spiked and in situ MPs were quantified. Hydrological, erosional and microplastic responses were evaluated in relation to slope, bulk density, soil moisture and surface condition indicators, including amounts and types of surface cover and soil physical attributes. The MPs were largely immobile, with 85–100% of spiked MPs retained on trail surfaces. In situ MPs were detected in the trail runoff, with the majority being polyurethane, polypropylene and polyester. Microplastic movement was primarily influenced by hydrological effects, and analysis indicated the main explanatory variable was total runoff volume, followed by soil slaking. Trail sections with at least 15% herbaceous cover or a layer of loose alluvium had higher MP retention. Areas of resource accrual may be preferentially enriched, suggesting MPs from outdoor recreation may be concentrated on and adjacent to recreational trails. Microplastics deposited on trails may have long term implications for biodiversity and ecosystem functioning in wilderness and conservation areas, particularly around the trail corridor.

Spatial and temporal scaling of sub-daily extreme rainfall for data sparse places

Global efforts to upgrade water, drainage, and sanitation services are hampered by hydrometeorological data-scarcity plus uncertainty about climate change. Intensity–duration–frequency (IDF) tables are used routinely to design water infrastructure so offer an entry point for adapting engineering standards. This paper begins with a novel procedure for guiding downscaling predictor variable selection for heavy rainfall simulation using media reports of pluvial flooding. We then present a three-step workflow to: (1) spatially downscale daily rainfall from grid-to-point resolutions; (2) temporally scale from daily series to sub-daily extreme rainfalls and; (3) test methods of temporal scaling of extreme rainfalls within Regional Climate Model (RCM) simulations under changed climate conditions. Critically, we compare the methods of moments and of parameters for temporal scaling annual maximum series of daily rainfall into sub-daily extreme rainfalls, whilst accounting for rainfall intermittency. The methods are applied to Kampala, Uganda and Kisumu, Kenya using the Statistical Downscaling Model (SDSM), two RCM simulations covering East Africa (CP4 and P25), and in hybrid form (RCM-SDSM). We demonstrate that Gumbel parameters (and IDF tables) can be reliably scaled to durations of 3 h within observations and RCMs. Our hybrid RCM-SDSM scaling reduces errors in IDF estimates for the present climate when compared with direct RCM output. Credible parameter scaling relationships are also found within RCM simulations under changed climate conditions. We then discuss the practical aspects of applying such workflows to other city-regions.

Erosion resistance of virgin chernozem and chernozem with classical and No-Till types of cultivation under the conditions of simulated heavy rainfall

Erosion resistance of virgin chernozem and chernozem with classical and No-Till types of cultivation under the conditions of simulated heavy rainfall

Atmospheric–hydrological modeling for Beijing's sub-center based on WRF and SWMM

The combination of intense climate change and rapid urbanization means that urban storms and floods capable of causing substantial economic losses are becoming one of the principal disasters that threaten sustainable urban development. Therefore, atmospheric–hydrological modeling, which could effectively extend the forecast period and support related research in regions lacking precipitation data, has received increasing attention in relation to urban hydrology. In this study, considering more comprehensive optimization of the physical parameterization schemes of the Weather Research and Forecasting (WRF) model, an atmospheric–hydrological modeling system based on the WRF model and Storm Water Management Model (SWMM) was proposed and applied to Beijing's sub-center. Results showed that the cumulus parameterization scheme has greatest impact on simulation of heavy rainfall. Overall, the combination of the WRF Single-Moment 5-class scheme, Grell–Freitas scheme, Yonsei University scheme, the newer version of the Rapid Radiative Transfer Model, Revised MM5 Monin–Obukhov scheme, Noah land surface model, and the Urban canopy model produced the best performance. Application of the proposed system demonstrated the feasibility of simulating urban storms and floods via WRF–SWMM system, which can represent the entire process from the rainfall produced by atmospheric movements to the formation of the urban floods.

Peanut Response to Flumioxazin and S-Metolachlor Under High Moisture Conditions

ABSTRACT Georgia produces nearly 51% of the United States peanut (Arachis hypogaea L.) crop. To combat and prevent weed infestations, herbicide programs containing flumioxazin and S-metolachlor are often applied preemergence (PRE). Despite herbicide effectiveness for weed control, peanut injury following heavy rainfall can be problematic. The objective of this study was to evaluate the impact of injury from flumioxazin and S-metolachlor after simulated heavy rainfall events on peanut growth and yield. Plots were planted at the University of Georgia Ponder Research Farm located near Ty Ty, Georgia using conventional tillage practices and twin-row spacing. Treatments included PRE applications of flumioxazin at 0, 0.11 and 0.22 kg ai/ha alone or in combination with S-metolachlor at 0, 1.07, 1.40, 2.80 kg ai/ha and were applied using a CO2-pressurized backpack sprayer. Irrigation and rainfall were ≥20 cm in the 30 days after planting (DAP) to simulate heavy rainfalls. Flumioxazin at 0.22 kg ai/ha caused the greatest visual injury (>60%) and most whole-plant fresh weight/m reductions at 21 DAP compared to other treatments. Peanut density was not impacted by flumioxazin or S-metolachlor. Neither flumioxazin nor S-metolachlor affected J-rooting. Yield was not reduced by any rate of flumioxazin. However, S-metolachlor at 2.80 kg/ha, (2.6X field rate), reduced yields by 8.9% compared to plots where no S-metolachlor or recommended field rates were applied.

Effects of glyphosate-based herbicides and their active ingredients on earthworms, water infiltration and glyphosate leaching are influenced by soil properties

BackgroundGlyphosate-based herbicides (GBHs) are among the most often used pesticides. The hundreds of GBHs used worldwide consist of the active ingredient (AI) glyphosate in form of different salts, possibly other AIs, and various mostly undisclosed co-formulants. Pesticide risk assessments are commonly performed using single AIs or GBHs at standard soil conditions without vegetation. In a greenhouse experiment, we established a weed population with common amaranth (Amaranthus retroflexus) to examine the effects of three GBHs (Roundup LB Plus, Roundup PowerFlex, Touchdown Quattro) and their corresponding AIs (salts of glyphosate isopropylammonium, potassium, diammonium) on the activity and physiological biomarkers (glutathione S-transferase, GST; acetylcholine esterase, AChE) of an ecologically relevant earthworm species (Lumbricus terrestris). GBHs and AIs were applied at recommended doses; hand weeding served as control. Experiments were established with two soil types differing in organic matter content (SOM; 3.0% vs. 4.1%) and other properties.ResultsEarthworm activity (casting and movement activity) decreased after application of glyphosate formulations or active ingredients compared to hand weeding. We found no consistent pattern that formulations had either higher or lower effects on earthworm activity than their active ingredients; rather, differences were substance-specific. Earthworm activity was little affected by soil organic matter levels. Biomarkers remained unaffected by weed control types; GST but not AChE was decreased under high SOM. Water infiltration after a simulated heavy rainfall was interactively affected by weed control types and SOM. Leachate amount was higher after application of formulations than active ingredients and was higher under low SOM. Glyphosate concentrations in soil and leachate were strongly affected by application of formulations or active ingredients and varied with SOM (significant weed control type x SOM interaction).ConclusionsWe found that both commercial formulations and pure active ingredients can influence earthworms with consequences on important soil functions. Glyphosate products showed increased, reduced or similar effects than pure glyphosate on particular soil functions; soil properties can substantially alter this. Especially at lower SOM, heavy rainfalls could lead to more glyphosate leaching into water bodies. A full disclosure of co-formulants would be necessary to further decipher their specific contributions to these inconsistent effects.

Improvement of an Extreme Heavy Rainfall Simulation Using Nudging Assimilation

From 21 to 22 July 2012, Beijing and its surrounding areas suffered from an extreme precipitation event that was unprecedented relative to the past 61 years, and the event caused 79 deaths and reported direct economic losses of 11.64 billion Yuan. However, current models have difficulty to simulate the spatial and temporal distribution characteristics of such events. Therefore, improved simulations of these extreme precipitation processes are needed. In this study, nudging methods, including grid nudging (GN) and spectral nudging (SN), and more accurate surface type data retrieved from remote sensing were used in the Weather Research and Forecasting (WRF) model to simulate this extreme precipitation case. When the default city underlay surface of the WRF model was replaced by a more accurate urban surface (NU), the precipitation intensity could be better simulated, but the peak moment of precipitation seriously lagged. Although the peak precipitation intensity simulated by the GN experiment was weak, the simulated precipitation time was basically consistent with the observations. Using GN in only the outside domain could better simulate precipitation peaks, while using GN in both the inside and outside domains could better simulate the spatial distribution characteristics of precipitation. Additionally, the precipitation from GN could be better simulated than that from SN. Overall, the two nudging methods could contribute to better simulations of this case because the nudging methods could improve the simulations of 500-hPa geopotential height, 850-hPa water vapor transport, and low-level weather systems, which are the key factors in adjusting the spatial and temporal distributions of precipitation. This study is the basis for the investigation of the mechanism and attribution of extreme precipitation processes, and the results are of great significance for promoting understanding of and mitigating disasters caused by extreme precipitation.

Arbuscular mycorrhizal fungus–induced decrease in phosphorus loss due to leaching in red soils under simulated heavy rainfall

Phosphorus (P) loss from the soil due to leaching is affected by plant roots and arbuscular mycorrhizal fungi (AMF). This paper aimed to (i) analyze the effects of plant roots and AMF on P concentrations in interflow and P loss from the soil due to leaching and (ii) explain whether there were interaction effects between plant roots and AMF on the loss of P from soils due to leaching. In this study, samples of red soil were collected from wasteland, farmland, and slopeland on the Yunnan Plateau. As a host plant, maize was cultivated in a dual-compartment cultivation system. There were mycorrhizal and hyphal compartments for the arbuscular mycorrhizal fungal inoculation treatment and root and soil compartments for the non-inoculation treatment. The maize biomass and P uptake, P concentrations in interflow within two soil layers (0–20 and 20–40 cm), and P losses due to leaching under simulated heavy rainfall (40 and 80 mm/h) were analyzed. Arbuscular mycorrhizal fungal inoculation significantly enhanced the biomass and P uptake of maize, but had little effect on P concentration in the interflow under 40 mm/h rainfall. In addition, Arbuscular mycorrhizal fungal inoculation resulted in a decrease of 37–65% in P concentration in interflow under 80 mm/h rainfall, and a decrease of 21–39% in the P loss from soils due to leaching under heavy rainfall (40 and 80 mm/h). Moreover, significant or highly significant positive correlations were observed between P concentrations in the interflow and the loss of P due to leaching from the red soil. Two-way analysis of variance indicated that AMF significantly or highly significantly decreased P concentrations in the interflow and decreased P loss from red soils due to leaching, whereas the root effects were insignificant. In addition, there was no interaction between AMF and maize roots. Our study indicated that the arbuscular mycorrhizal fungus–induced decreases in the loss of P due to leaching from red soils were caused by decreased P concentrations in the interflow. The potential for AMF to reduce P leaching from soils is an important ecological function.

Arbuscular mycorrhizal fungus-induced decrease in nitrogen concentration in pore water and nitrogen leaching loss from red soil under simulated heavy rainfall.

Arbuscular mycorrhizal fungus (AMF) is generally colonized in plant roots and influences the migration of mineral elements such as nitrogen (N) in soils. However, its effect on N leaching loss in red soils is limited. In the present study, red soils were collected from wasteland, farmland, and slopeland in the Yunnan Plateau. Maize, as a host plant, was cultured in a dual-compartment cultivation system. There were mycorrhizal and hyphal compartments for the AMF inoculation treatment and root and soil compartments for the non-inoculation treatment. The N concentration and uptake in maize, N concentration in pore water within two depth (0-20 and 20-40 cm), and N leaching losses from soil under simulated heavy rainfall (40 and 80 mm/h) were analyzed. Results showed that AMF inoculation significantly enhanced the biomass and N uptake in maize. Compared with the root and soil compartments, the N concentrations in pore water and their leaching losses from the mycorrhizal and hyphal compartments were decreased by 48-77% and 51-74%, respectively. Moreover, significant or extremely significantly positive correlations were observed between the N concentrations in pore water with the N leaching losses from soil. The three-way ANOVA showed that AMF highly significantly decreased N concentrations in pore water and their leaching losses from wasteland, farmland, and slopeland; rainfall intensity had strong influences on the N concentration in pore water from farmland and N leaching losses from wasteland and farmland, whereas the maize root's effect was insignificant. The study indicated that the AMF-induced decreases in the N leaching loss from red soils were caused by increased N uptake by maize and decreased N concentrations in pore water. These results have implications for reducing nutrient leaching loss through the management of beneficial microorganisms in soils.

Arbuscular mycorrhizal fungi reduce cadmium leaching from polluted soils under simulated heavy rainfall

Cadmium (Cd)-polluted soils were collected from wasteland, farmland, and slopeland surrounding a lead–zinc mine in Yunnan Province, Southwest China. Maize plants (the host) were inoculated with arbuscular mycorrhizal fungi (AMF) in a dual-compartment cultivation system that included mycorrhizal and hyphal compartments as part of an AMF inoculation treatment and root and soil compartments as part of a the non-inoculation treatment. The effects of AMF on maize biomass and Cd uptake, soil aggregate composition, and Cd concentration in the interflow within two soil layers (0–20 and 20–40 cm) as well as the Cd leaching from these three Cd-polluted soils under simulated heavy rainfall (40 and 80 mm/h) were investigated. The results demonstrated that AMF led to increased maize biomass and Cd uptake. There were greater contents of total glomalin-related soil protein (T-GRSP) and >2.0 mm aggregates and lower Cd concentrations in the interflow and lower dissolved Cd leaching in the mycorrhizal and hyphal compartments than in the soil compartment. A two-way analysis of variance revealed that AMF significantly increased the contents of T-GRSP and >2.0 mm aggregates and reduced both Cd concentrations in the interflow and dissolved Cd leaching. Moreover, AMF interacted extensively with the roots and affected soil aggregate composition and Cd concentrations in the interflow. Under 40 mm/h of rainfall, the contents of T-GRSP and >2.0 mm aggregates were significantly negatively correlated with both Cd concentrations in the interflow and dissolved Cd leaching. In addition, the Cd concentrations in the interflow were significantly positively correlated with the amount of dissolved Cd leaching. Therefore, both AMF-reduced Cd concentrations in the interflow and Cd leaching from Cd-polluted soils were closely related to increased T-GRSP contents and macroaggregate proportion in the soils.

Improved simulation of very heavy rainfall events by incorporating WUDAPT urban land use/land cover in WRF

A World Urban Data Analysis and Portal Tool (WUDAPT) based Local Climate Zone (LCZ) classification and mapping is done for Mumbai, India. Prior WUDAPT-based urban studies have primarily focused on urban heat island (UHI) assessment, and this is the first study to assess the impact on rainfall simulations. Accordingly, in this study, the impact of incorporating the LCZ map in the Weather Research and Forecasting (WRF) model for simulating very heavy rainfall events over Mumbai is assessed. The classified LCZ map is incorporated in the WRF model, and the model performance is compared against the Control, for four recent very heavy rain events. Comparing the results from paired simulations reveals that the rainfall amount and spatial variability is significantly different when the LCZ framework is used. Implementation of WUDAPT data, introduces heterogeneity in the morphological characteristics of the city, which contributes to microscale feedbacks that appear to organize and impact the mesoscale convergence/divergence and convection fields in the WRF model. The study results show variability within the cases highlighting the need for additional investigations in different cities. Overall, the incorporation of WUDAPT LCZs in WRF results in notably improving the model performance for heavy rainfall simulation in urban areas.

Numerical simulation of heavy rainfall in August 2014 over Japan under Pseudo Global Warming Conditions

Climate change as a consequence of global warming may enhance severe precipitation events. This study investigated the impact of global warming on summertime heavy rainfall using the Weather Research and Forecasting model with the pseudo global warming (PGW) method. WRF simulations were conducted for August 2014 over a domain covering Japan, in which two big typhoons attacked Japan and rain fronts frequently passed over, in a baseline and two PGW (RCP4.5 and RCP8.5) conditions. The analysis showed that the future climate led to a larger amount of precipitation than the past climate during the study period in Japan. The mean increase rate of upward moisture supply from the surface of the entire modelling domain was 2.8% K−1 in RCP4.5 condition and 3.3% K−1 RCP8.5 condition. The mean increase rate of 2-m specific humidity was 6.7% K−1 in both RCP4.5 and RCP8.5 conditions, which is comparable to the Clausius-Clapeyron relationship. Therefore, the water supply from the lateral boundaries contributed to the increase in humidity largely and precipitation subsequently. The increases in precipitation related to typhoons were larger than rain fronts, in particular, the changes were remarkable over the paths of typhoons. These results show global warming will significantly increase the summertime heavy precipitation over Japan in the future.

Research on the Application of Palm Mat Geotextiles for Sand Fixation in the Hobq Desert

Traditional sand fixation measures have many limitations. For example, engineering sand fixation measures using barriers cannot completely stabilize sand dunes. Biological sand fixation measures utilizing planted vegetation are very difficult to build during the early stages of desertification control. Chemical sand fixation measures spray chemically bonded materials on sand dunes to form a consolidated layer to prevent sand flow, but the cost of the materials used is relatively high. Therefore, new sand fixation technologies and methods urgently need to be developed. This study demonstrates a new sand fixation method, which uses palm mat geotextiles to stabilize sand dunes and to plant grass. We investigated the physical properties of these palm mat geotextiles in the laboratory and observed vegetation growth in the Hobq Desert. The results showed the following: (1) Palm mat geotextiles are lighter and tougher than common straw mat geotextiles. The average weight, thickness, and tensile strength of palm mat geotextiles are 2023 g/m2, 20.14 mm, and 842–860 kPa, respectively. After a year of field observations, the tensile strength decreased by only 2%. (2) Palm mat geotextiles have excellent water retention capacity and scouring resistance; the maximum water content reached 227%, and the substrate lost 2.9% after laboratory simulation of heavy rainfall for three hours with a rainfall intensity of 30 mm h−1. (3) Palm mat geotextiles significantly decreased the soil temperature and increased moisture in summer. The results showed that the palm mat geotextiles had the largest influence on soil temperature in the upper 5 cm of soil and the largest influence on soil moisture in the upper 10 cm of soil. (4) The field experimental results showed that, by the end of the experiment, the vegetation coverage and the biomass of the palm mat geotextiles with dimensions of 2 × 2 m were 3.9 times and 4.1 times that of the control group and 1.7 times and 1.8 times that of the group of high-banded Salix psammophila sand barriers, which are widely used in the Hobq Desert at present. Palm mat geotextiles are a promising material for sand fixation in the Hobq Desert.