Simulated Rainfall Research Articles

Sugarcane leaf return and mixing significantly reduce slope runoff and soil loss

AbstractImproper management of sugarcane cultivation may cause severe soil erosion, especially in lateritic red soil hilly areas. Crop straw return to the field can effectively improve the soil structure, but there is a lack of evaluation studies of the soil and water conservation benefits of sugarcane leaf mixing and return to the field, and the underlying regulatory mechanism has rarely been described. Thus, we conducted a series of simulated rainfall experiments to investigate the impact of returning different mixed sugarcane leaf weights (0, 3, 6, 9, 12 and 15 t/ha) to the field on erodible lateritic red soil slopes that support sugarcane production under various slopes (5°, 10°, 15° and 20°) in different rainfall events (60 and 120 mm/h). The results indicated that returning sugarcane leaves into farmland could effectively regulate the process of runoff and sediment production on lateritic red soil slopes, and the optimal mixing amount was 9 t/ha. Under a low rainfall intensity, the erosion process was mainly affected by the slope, and the benefits of applying the sugarcane leaf mixing treatment to the slope to reduce runoff and sediment could reach 13.37–53.04% and 23.86–77.55%, respectively. However, under a high rainfall intensity, the sugarcane leaf mixing amount was the main influencing factor, the benefits for reducing runoff and sediment could reach 4.64–38.72% and 30.87–93.14%, respectively. The sugarcane leaf mixing amount exhibited a linear relationship with the Reynolds number (R2 > 0.63), whereas the runoff velocity (R2 > 0.96), Froude number (R2 > 0.94) and drag coefficient (R2 > 0.85) exhibited well‐fitting exponential function relationship with it. This study provides a reference for future endeavours regarding the inhibition mechanisms of sugarcane leaves mixed and returned to the field for decreasing slope erosion.

Quantification of water, soil and nutrient losses in the Farinha river basin, Carolina - MA, in the Cerrado biome

Natural resources, such as soil and water, play a crucial role in sustaining life on Earth. When used appropriately, these resources can mitigate environmental impacts. However, inadequate soil management practices can result in negative effects, such as the intensification of erosion processes and significant losses of soil, water and nutrients essential for plant growth. Thus, considering that the Farinha River basin - MA is located in the Cerrado biome and has a large part of its area occupied by highly erodible soils, the aim was to quantify water, soil and nutrient losses using a rainfall simulator. The experimental design adopted was entirely randomised (DIC), in a bifactorial scheme with 5 replications. Factor 1 considered two types of soil management systems (Anthropised Area and Non-Anthropised Area), while factor 2 involved three simulated rainfall intensities (80mm.h-¹, 110mm.h-¹ and 130mm.h-¹). The response variables assessed were losses of water, soil and nutrients and organic matter.The averages were subjected to analysis of variance and, if significant, the Tukey test was applied at 5% probability using Past 4.03 software. The results indicated significant losses of soil, water and nutrients associated with both the soil management system and the rainfall intensities, as well as making it possible to quantify the nutrients lost in runoff water on site. The conclusion is that the combination of inadequate soil management practices and intense rainfall can exacerbate erosion processes and the leaching of macro and micronutrients, resulting in an increasing need to incorporate fertilisers and correctives into agroforestry activities. Furthermore, it is important to emphasise that water erosion also contributes to an increase in soil and nutrient loss, which can lead to adverse environmental impacts, such as contamination of water resources and degradation of soil quality.

Influence of convective parameterization on the simulation of tropical cyclones over the South West Indian Ocean: A case study of tropical cyclone Idai (2019)

Proper configuration of the physical parameterization scheme is important for accurate outcomes of mesoscale weather forecasting model. This study evaluates the performance of four distinct cumulus parameterization schemes: the Kain-Fritsch (KF), Grell 3D ensemble (GR3D), Modified Tiedtke (MTIEDKE) and Modified Kain-Fritsch (MKF) schemes, in simulating Tropical Cyclone (TC) Idai (2019) in the Southern Indian Ocean. Utilizing the Weather Research Forecasting (WRF) model and TC best-track and satellite precipitation datasets, the research assesses the models' efficacy in replicating Idai's observed track and intensity. Results indicate that the KF, MTIEDKE, and MKF schemes reasonably capture Idai's southwestward track, with MKF demonstrating superior accuracy in reproducing observed intensity evolution. Conversely, the GR3D simulation exhibits a northwestward deviation, leading to notable track and intensity errors. Further investigations suggest that the smaller track and intensity differences in the MKF simulation are linked to the more accurate simulation of rainfall in both the surrounding environment and the TC inner-core region. The two factors exert strong influences on the large-scale steering flow and TC secondary circulation, respectively. The findings underscore the importance of selecting appropriate convective parameterization schemes for precise tropical cyclone simulations in the Southern Indian Ocean. This research contributes valuable insights into the intricate interaction between convective processes and atmospheric dynamics, offering implications for enhancing tropical cyclone prediction models in the region.

A Novel Approach to a Multi-Model Ensemble for Climate Change Models: Perspectives on the Representation of Natural Variability and Historical and Future Climate

This study developed a novel approach that integrated climate model selection and multi-model ensemble (MME) construction to effectively represent model uncertainties and, consequently, improve consistency in the evaluation of changes to extreme rainfall in different scenarios. Our focus was to combine 10 regional climate model (RCM) simulations, forced by two global climate models (GCM), especially for estimation of design rainfall in a changing climate. We hypothesized that the natural variability and statistically higher moment attributes in the extreme rainfall simulations from RCMs were not fully preserved. Therefore, the MME approach could be more effective in climate change studies, largely due to the use of multiple climate models. First, an experimental study was proposed to validate the efficacy of the proposed modeling framework approach adopting L-moments to quantify relative importance among climate models and their use for representing natural variability in the MME construction. The proposed approach was then applied to climate change scenarios collected from multiple RCMs for the Han-River watershed during both historical (1981 to 2005) and future (2006 to 2100) periods. The results showed that the climate model selection informed by natural variability demonstrated better performance, representing nearly identical distribution to the observed annual maximum rainfall (AMR) in the Han River watershed. The range of the selected scenario was relatively narrower than that of all the scenarios, and the change rate was more consistent with the limited zero crossing, reflecting improvement in both model performance and consistency over historical and future periods, respectively. The change rate of the MME under RCP8.5 appeared to be an approximately 20% increase for the near (2011∼2040) and far (2071∼2100) future, and the degree of increase in the rate for the mid-future (2041∼2070) was slightly lower than that for the other periods, with increase of approximately 10%.

The effectiveness of different formulations of glyphosate herbicides under simulated rainfall conditions in controlling various weeds

Herbicide effectiveness is affected by herbicide formulation, rainfall, and weed type. Differences in glyphosate salt formulations and 2,4 D amine mixtures may result in variations in the herbicide's ability to wash off the herbicide due to rain. The aim of this study was to assess the effectiveness of different glyphosate herbicide formulations under varying rainfall in controlling various weeds. The experiment took place in a controlled greenhouse environment, utilizing a split plot experimental design with four replications.  The main plot was assigned to six different rainfall timings: 0 hours after application (HAA), 1 HAA, 2 HAA, 3 HAA, 4 HAA, and no rainfall. The subplots involved different herbicide formulations, namely isopropylamine glyphosate (h1), potassium glyphosate (h2), sodium glyphosate (h3) and glyphosate herbicide, IPA herbicide glyphosate + 2,4 D Amine (h4) and without any herbicide application (h0). Various parameters were observed, including weed dry weight and percentage of mortality growth. The results showed that the effectiveness of each herbicide formulation was diffent among weed specie under simulated rainfall conditions. Ageratum conyzoides can be controlled using isopropylamine glyphosate and potassium glyphosate with rainfall at 1 HAA. Axonopus compressus can be controlled by isopropylamine glyphosate and sodium glyphosate with rainfall at 1 HAA, while Borreria alata and Cyperus rotundus were effectively controlled by isopropylamine glyphosate with rainfall at 1 HAA.

A modeling study of aerosol effect on summer nocturnal convective precipitation in Beijing

Using the WRF model with chemistry (WRF-Chem), this study investigates the potential contributions of aerosol direct (ADE) and aerosol indirect (AIE) effects on the nocturnal convective precipitation occurred on 9–10 September 2019 in Beijing. It shows that ADE plays a more important role in spatiotemporal changes of heavy precipitation than AIE in urban areas. Further simulation analyses show that ADE suppresses precipitation by inducing greater surface shortwave radiative cooling and stability before 13:00 (UTC, hereafter) on 9 September, which reduces convective available potential energy (CAPE) losses and then increases the later CAPE. The ADE-induced CAPE increase makes updrafts stronger, increasing cloudiness and transporting more cloud water into the upper troposphere. This, in turn, causes greater latent heat release from freezing and then stronger convection, producing higher rain rate during 13:00–21:00. During 12:00–18:00, AIE causes a decrease in CAPE, which weakens updrafts. AIE decreases the snow mixing ratio above 700 hPa except at 15:00–16:00 on 9 September, which can decrease the release of latent heat from freezing, contributing to the decrease in precipitation after 18:00. Due to the greater stability before 10:00 and the longer time required for updrafts to overcome this stability, ADE necessitates 2–3 h to adjust the simulated rainfall time series.

Conducting an in situ evaluation of erodibility in a Mediterranean semi-arid and conventional vineyard in Granada province (Southern Spain) through rainfall simulation experiments

AbstractVineyards in Europe has been fundamental for food, drink and cosmetic production, and job creation; however, in recent decades due to increased cultivation intensity, numerous negative consequences, including erosion, have been observed. Erodibility or susceptibility to erosion is a little-studied parameter in vineyards but is crucial for analyzing the vulnerability of this crop. Therefore, in this research, a small portable rainfall simulator was used as a useful tool for assessing erodibility, combined with other methods such as soil analyses or infiltration measurements in a semi-arid vineyard located in the Granada province (Spain) considering 20 different hotspots at diverse hillslope positions along the inter-rows and close to the traffic roads. The experiments were conducted in spring 2022 under dry soil conditions. Our results display susceptibility to erosion, particularly on steeper parts such as the shoulder and backslopes. In these areas, runoff gained momentum, carrying a significant sediment load, diminishing the effectiveness of stone cover, and occasionally leading to its removal, especially near the roads. Nevertheless, it is observed that increased roughness plays a mitigating role by slowing down runoff. Using linear correlation analysis and Spearman rank coefficient, we observed this effect is linked to factors such as stoniness, vegetation, and moderate tillage. Conversely, in the flatter zones, primarily in lower areas, reduced runoff and delayed onset are primarily influenced by factors such as roughness, type of cover, material composition, and organic matter content. We concluded that this study case can demonstrate that erodibility in vineyards can shed light as an extra parameter to inform farmers, rural inhabitants, and policymakers about the extreme problem of the vulnerable soils of vineyards.

Droplet Injection for Multiphase Rainfall Simulations on Dynamically Refined Mesh for Effective Interface Capturing

This paper presents a volume of fluid (VOF) model for multiphase rainfall simulation that injects rain droplets as a continuous phase alongside the adaptive mesh refinement (AMR) method to resolve air-water interfaces. An approach based on multi-level domains and a pseudo-random algorithm is proposed to determine injection locations in a random and non-intrusive manner with the least bias. Face zones instead of faces are adopted as constituent elements for droplet injection to prevent droplet fragmentation due to a change of face IDs caused by AMR. Correspondingly, a new multi-level address system is introduced to establish the correspondence among subdomains at different levels. The model is applied to multiphase flow VOF simulation for parametric 2-D and 3-D rainfall analysis. The results are verified by the data reported in the literature. It demonstrates that the model can efficiently simulate realistic rainfall phenomena, capture the droplet interface, and preserve droplet injection uniformity.

Implications of WRF model resolutions on resolving rainfall variability with topography over East Africa

There is an increasing need to improve the accuracy of extreme weather forecasts for life-saving applications and in support of various socioeconomic sectors in East Africa, a region with remarkable mesoscale systems due to its complex topography defined by sharp gradients in elevation, inland water bodies, and landuse conversions. This study sought to investigate the impacts of the Weather Research and Forecasting (WRF) model spatial resolution on resolving rainfall variability with topography utilizing nested domains at 12 and 2.4 km resolutions. The model was driven by the National Centers for Environmental Prediction (NCEP)-Global Data Assimilation System (GDAS) Global Forecast System (GFS) final (FNL) reanalysis to simulate the weather patterns over East Africa from 3rd April 2018 to 30th April 2018, which were evaluated against several freely available gridded weather datasets alongside rainfall data from the Kenya Meteorological Department (KMD) stations. The reference datasets and the model outputs revealed that the highlands had more rainfall events and higher maximum daily rainfall intensity compared to the surrounding lowlands, attributed to orographic lifting enhancing convection. Rainfall was inversely proportional to altitude from 500 m to 1,100 m above sea level (ASL) for both coarse and fine resolutions. The convection-permitting setup was superior in three aspects: resolving the inverse altitude-rainfall relationship for altitudes beyond 3000 m ASL, simulating heavy rainfall events over the lowlands, and resolution of the diurnal cycle of low-level wind. Although the coarse resolution setup reasonably simulated rainfall over large mountains, only the convection-permitting configuration could accurately resolve rainfall variability over contrasting topographical features. The study notes that high-resolution modeling systems and topography-sensitive bias correction techniques are critical for improving the quality of operational weather forecasts in East Africa.

Removal effect of pollutants from stormwater runoff in shallow bioretention system with gramineous plants.

The bioretention system is one of the most widely used low impact development (LID) facilities with efficient purification capacity for stormwater, and its planting design has been a hot spot for research at home and abroad. In this paper, ryegrass (Lolium perenne L.), bermuda (Cynodon dactylon Linn.), bahiagrass (Paspalum notatum Flugge), and green grass (Cynodon dactylon × C .transadlensis 'Tifdwarf') were chosen as plant species to construct a shallow bioretention system. The growth traits and nutrient absorption ability of four gramineous plants were analyzed. Their tolerance, enrichment, and transportation capacity were also evaluated to compare plant species and their absorptive capacity of heavy metals (Cu, Pb, and Zn). Results showed that the maximum absorption rate (Imax) ranged from 22.1 to 42.4 μg/(g·h) for P and ranged from 65.4 to 104.8 μg/(g·h) for NH4+-N; ryegrass had the strongest absorption capacity for heavy metals and the maximum removal rates of Cu, Pb, and Zn by four grasses were 78.4, 59.4, and 51.3%, respectively; the bioretention cell with ryegrass (3#) was significantly more effective in purifying than the unplanted bioretention cell (1#) during the simulated rainfall test. Overall, the system parameters were optimized to improve the technical application of gramineous plants in the bioretention system.

Pesticide extraction from soil into runoff in North American and Australian croplands

Context Do some pesticides run off more than others? How does pesticide runoff vary with pesticide properties? Aims Improve understanding of pesticide runoff from croplands. Methods Concentrations in surface soil and in runoff from three Australian rainfall simulation studies and three rainfall simulation and five catchment studies in North American croplands were used. The ratio of event averaged runoff concentrations and the surface soil concentrations is the runoff extraction ratio. Key results Pesticide runoff concentrations were closely related to soil surface concentrations at the start of rainfall. Runoff extraction ratios were not significantly different for 13 pesticides with a wide range of properties, on gentle slopes (0–3%), but were significantly lower for three pesticides. On steeper slopes, runoff extraction was significantly greater for atrazine but lower for glyphosate and metolachlor. Low sloping, furrow irrigated fields had low sediment concentrations and low pesticide runoff concentrations for more tightly sorbed pesticides, but not for less sorbed pesticides. Runoff extraction was not significantly different for simulated and most catchment studies. Conclusions Similar runoff extraction ratios were due to similar hydrology and limited sediment concentrations. Different runoff extraction occurs on bare soil if (a) pesticides are leached from the runoff-mixing layer, requiring sorption coefficients less than two and significant infiltration, and no interflow, (b) sediment concentrations are either low (<2 g L−1) or high (>100 g L−1) and (c) pesticides have different concentration profiles in the runoff-mixing layer. Implications Conditions studied apply for croplands in the North American mid-west on silty soils and for Australian clay soils.

Sensitivity analysis of cumulus and microphysics schemes in the WRF model in simulating Extreme Rainfall Events over the hilly terrain of Nagaland

A comprehensive study is carried out to investigate the sensitivity of various combinations between cumulus (CU) and microphysics (MP) schemes using the Weather Research and Forecasting (WRF) model for simulating Extreme Rainfall Events (EREs) over the hilly terrain of Nagaland (25.1 oN – 27.2 oN; 93.2o – 95.3°E). The study explores fifty-four distinct simulation combinations resulting from six CU and nine MP schemes. The simulated rainfall is compared with ground-based rain gauge network and Global Precipitation Measurement (GPM) satellite observations. The investigation focuses primarily on finding the optimal CU-MP scheme combination based on spatiotemporal precision achieved by the identified schemes. The C14 (New Simplified Arakawa Schubert) cumulus scheme is found to be the optimum individual CU scheme. Similarly, the M14 (WDM5) microphysics scheme performs as the optimum individual MP scheme. The study highlights the significance of evaluating the performance of combined schemes over individual ones. Among the fifty-four combinations, sensitivity analysis identified six top-performing combinations, out of which the C11-M8 (Multiscale Kain Fritsch - New Thompson) combination stands out to be optimum with a robust correlation coefficient (CC) of 0.75, lower standard deviation (STD) of 0.76 mm, and RMSD of 0.51 mm. A variation in lead/lag time is found to vary from (−) 3.2 to (+) 5.0 h, with a median value of (+) 1.3 h, suggesting that, on average, the model tends to predict the occurrence of peak rainfall events slightly earlier than observed one. The absolute difference in latitudes (longitude) of peak rainfall, variation ranges from 0.42o - 0.8o (0 o - 0.51o), with a median value of 0.66o (0.37o), indicating that the model could better represent the longitudinal peak rainfall positions with notable accuracy. The spatial correlation coefficient (SCC) ranges between 0.31 and 0.68 with a median value of 0.50. From the overall analysis, it is also found that double moment MP schemes (New Thompson, Morrison (2 M), WDM5, WDM6) consistently perform better than the single moment MP schemes (Kessler, Lin et al., WSM3, WSM5, WSM6), whether in combination with CU schemes or individually. Spatiotemporal variations observed across different cases underscore the pivotal role of accurate topography representation in complex terrains, emphasizing the significance of terrain data in shaping rainfall patterns.

Exploring optimal deep tunnel sewer systems to enhance urban pluvial flood resilience in the gangnam region, South Korea

Urban pluvial flooding is becoming a global concern, exacerbated by urbanization and climate change, especially in rapidly developing areas where existing sewer systems lag behind growth. In order to minimize a system's functional failures during extreme rainfalls, localized engineering solutions are required for urban areas chronically suffering from pluvial floods. This study critically evaluates the Deep Tunnel Sewer System (DTSS) as a robust grey infrastructure solution for enhancing urban flood resilience, with a case study in the Gangnam region of Seoul, South Korea. To do so, we integrated a one-dimensional sewer model with a rapid flood spreading model to identify optimal routes and conduit diameters for the DTSS, focusing on four flood-related metrics: the total flood volume, the flood duration, the peak flooding rate, and the number of flooded nodes. Results indicate that, had the DTSS been in place, it could have reduced historical flood volumes over the last decade by 50.1–99.3%, depending on the DTSS route. Regarding the conduit diameter, an 8 m diameter was found to be optimal for minimizing all flood-related metrics. Our research also developed the Intensity-Duration-Frequency (IDF) surfaces in three dimensions, providing a correlation between simulated flood-related metrics and design rainfall characteristics to distinguish the effect of DTSS on flood risk reduction. Our findings demonstrate how highly engineered solutions can enhance urban flood resilience, but they may still face challenges during extreme heavy rainfalls with a 80-year frequency or above. This study contributes to rational decision-making and emergency management in the face of increasing urban pluvial flood risks.

APPLICATION OF A SIMPLIFIED GREEN-AMPT MODEL TO THE MAGA EARTHFILL DAM UNDER RAINFALL CONDITIONS: A SENSITIVITY ANALYSIS CASE OF AN INFILTRATION MODEL

The present paper applies a simplified Green-Ampt (GA) infiltration model for the numerical modelling of seepage processes within the body of the Maga earth dam, located in the Far-North Cameroon, under rainfall conditions. The parametrization approach makes possible the predictions of infiltrations parameters for various textures that constitute the body of earth dam and its vicinities. The effects of soil texture, permeability coefficient, rain intensity and initial moisture on infiltration rate and cumulative depth are investigated using numerical simulations carried out by running an Excel VBA code. A proposed optimization procedure of the literature is then used to improve the GA model parameters and accuracy of predictions. A case sensitivity analysis of the infiltration model parameters has also been made. Initial and saturated water contents, rain intensity and permeability coefficient at saturation have been identified as the most influents parameters for the model predictions, with obvious interactions between inputs. The contribution of main effects and interactions of above inputs ranges between 68.8% to 90.03% of the total variance. Comparisons of numerical results with the experimental ones obtained from the literature on real cases of simulated rainfall on main sub-Saharan soils have been done. The results show that numerical simulations underestimated 60% and 56.25% of the hydrodynamics parameters respectively for one and four simulated rain-sequence with relative errors (RE) ranging between -76.22% and 300.25%. The most representative results were obtained for 53.13% of the predicted hydrodynamics parameters with RE value ranging between -23.90% and 12.75%. The obtained results proved that, the simplified GA model exhibited an acceptable accuracy in predicting seepage processes for ferruginous and degraded vertic soils. Therefore, the present study contributes to understand the role of numerical simulations tools in modelling and predicting subsurface phenomenon as seepage, for areas with high floods risks in a context of significant climate changes.

Nutrient transport by overland sheet flow on sites containing swine slurry

Nutrients in agricultural runoff may cause offsite environmental impacts. The objective of this investigation was to examine nutrient transport by overland sheet flow on sites containing swine slurry. Data examined in this study was collected during field rainfall simulation tests conducted on cropland sites in southeast Nebraska, USA. Inflow was added to the top of experimental plots in four successive increments to simulate runoff rates occurring at greater downslope distances. Runoff rates on the experimental sites ranged from 2.3 to 21.2 L min−1 and maximum equivalent downslope distances varied from 5 to 108 m. Phosphorus (P) and nitrogen (N) transport rates were found to increase in a linear fashion with runoff rate. Hypothesis testing using the student’s t-test affirmed the prediction that a linear equation, calibrated for site specific conditions, can be used to relate nutrient transport rates to runoff rates. P and N transport rates were thought to be influenced by (a) the quantity of nutrients released by swine slurry at a particular runoff rate and (b) the amount of overland sheet flow available to transport the released nutrients. If nutrient transport rates can be linked to runoff rates, it may be possible to extrapolate experimental results obtained from small plots to greater downslope distances. Existing process-based models used to route overland sheet flow along hillslopes on upland areas could also be modified to include nutrient constituents.

Persistence and relocation of dislodgable herbicide residue from simulated rainfall following glyphosate treatment to dormant zoysiagrass turf

AbstractThe severity of herbicide injury to dormant zoysiagrass (Zoysia spp.) increases with increasing green leaves at treatment time, but injury also occurs following treatment to fully dormant zoysiagrass, especially when treatment precedes rapid shoot emergence. Research was conducted to determine the persistence of radio‐labeled glyphosate or glufosinate on dormant zoysiagrass leaves, to assess how simulated raindrop quantity affects relocation of glyphosate plus colorant to subcanopy areas, and to evaluate the response of post‐dormant zoysiagrass to glyphosate dislodged and relocated from dormant leaves via simulated rainfall, dew, or disturbance during post‐dormancy growth. When dormant zoysiagrass leaves were treated with 14C‐glufosinate or 14C‐glyphosate, 69% and 57%, respectively, of the herbicides were water extractable for 21 days. Increasing the number of simulated raindrops 0.5 cm−2 from 1 to 20 removed >95% of the applied colorant from treated dormant zoysiagrass leaves, with concomitant relocation of residue to underlying filter paper. Maximum exposure of a single subtending green shoot occurred at five simulated raindrops 0.5 cm−2, which would approximate a rainfall of 3.35 mm. Subsequently, glyphosate applied to dormant zoysiagrass plugs followed by 3 mm simulated rainfall or dew and wiping 7–9 days later, when turf had reached 15% green cover, reduced zoysiagrass clipping biomass by 35% and 72%, respectively. Glyphosate applied to dormant zoysiagrass can dislodge and injure newly developing green shoots during transition. This injury can be mitigated by irrigating 1 day after glyphosate treatment to dormant turf or ensuring that the first irrigation or rainfall following treatment is at least 12 mm.

Optimizing Straw Mulching Methods to Control Soil and Water Losses on Loess Sloped Farmland

Straw mulching is a key method for controlling soil and water losses. Mulching costs may be reduced by applying it in strips rather than over entire areas. However, the effect of different straw mulching methods on the effectiveness of reducing soil erosion is unclear. In this study, the effects of straw mulching strip length (covering 1/4, 1/2, 3/4, and 4/4 of the slope length) and coverage rate (0.2, 0.5, and 0.8 kg m−2) on interception, infiltration, runoff, and soil erosion were investigated at the plot scale using rainfall simulation experiments. The further complex correlations between these variables were analyzed using structural equation modeling (SEM). Bare slopes were used as a control group. The rainfall intensity was chosen to be 60 mm h−1. The results showed that (1) the modified Merriam interception model can describe the change in interception with time under straw mulching conditions well (R2 > 0.91, NSE > 0.75). (2) A total of 35.39–78.79% of the rainwater is converted into infiltration on straw-covered slopes, while this proportion is 36.75% on bare slopes. The proportion of rainwater converted to infiltration was greatest (78.79%) when the straw covered 3/4 of the slope length at a coverage rate of 0.5 kg m−2, which was the most conducive to rainwater harvesting on the slope. (3) Straw mulching protects the topsoil from the impact of raindrops and directly affects the sediment yield (direct effect = −0.44). Straw mulching can also indirectly affect sediment yield by increasing interception, reducing runoff, and decreasing the sediment carrying capacity of runoff (indirect effect = −0.83). Compared with bare slopes, straw covering at least 1/2 of the slope length can significantly reduce runoff yield, but straw covering only 1/4 of the slope length can significantly reduce sediment yield. Moreover, once the straw mulch slope length reaches 3/4 and the coverage rate reaches 0.5 kg m−2, further increases in mulch slope length and coverage rate will not significantly reduce the runoff and sediment yields. These results assessed the effectiveness of different straw mulching methods in controlling soil and water losses on sloping farmland.

Evaluating the effect of geocell with vegetation and gravel on changes in the effective parameters of runoff using a rainfall simulator (case study: Iran)

Permeable pavements can reduce the negative effects of flooding in urban areas. This research seeks to study and compare the performance of the impervious surface as a control (O), sandy loam (SL), gravel (G), gravel with geocell layer (GGE), rosemary (R), rosemary with geocell layer (RRE), turf (T), and turf with geocell layer (TGE) in reducing runoff volume (RV), time to start runoff (TR), runoff coefficient (C), time to end runoff (TER), peak flowrate (PF), time to peak (TP), and time base (TB) under six different rainfall intensities (i) and two different slopes (s) using a rainfall simulator. For this purpose, 96 physical models were considered at the laboratory level. For the dependent variables TR, TER, PF, TP, and TB, there was a significant difference between the data at the level of 5% in all cases. Based on the results, changes in rainfall intensity, slope, and type of treatment could make a significant difference in the results of the C parameter. All treatments were able to reduce runoff volume in all test conditions. Rosemary had a better performance in controlling runoff and parameters affecting it compared to turf. The maximum and minimum cumulative runoff volumes observed for treatment GGE are 85.4 and 2 L, respectively. Finally, the results revealed that GGE could perform better in reducing runoff and cumulative volume in all cases compared to the rest of the test groups. The highest percentage of runoff volume reduction in GGE treatment was 96.5%.

Does century-old biochar affect soil interrill erodibility on cropland soils? A study on pre-industrial kiln sites

Adding biochar to soils is being advocated to mitigate soil erosion. However, given biochar aging and persistency in soils, the effects of biochar on soil in the long-term are important to investigate yet remain largely unknown. The objective was therefore to determine the long-term effect of biochar on interrill erosion on cropland soils. Experiments were conducted using topsoil from three fields of different textures (silt loam, loam and sandy loam). Each field was characterized by the presence of kiln sites containing century-old charcoal used as proxy to investigate the long-term impact of biochar. Aggregate stability was measured using the method of Le Bissonnais (1996), whereas interrill erosion was studied using two successive (24-h apart) rainfall simulation experiments (84 mm h−1, 90 min.). The presence of historical charcoal in kiln sites did not affect soil aggregate stability, irrespective of charcoal-C content or soil type. For the first rainfall simulation only, the century-old charcoal reduced both the final runoff and soil loss rates by, respectively, 15.4 mm h−1 and 12.1 g m−2 h−1 for each percent increase in charcoal-C content. As a result, Meyer’s interrill erodibility decreased with increasing charcoal-C content. However, because the final runoff and soil loss rates decreased to a similar extent with increasing charcoal-C content, Kinnell’s interrill erodibility was unaffected by charcoal-C content. These effects on interrill erosion parameters were independent of soil type and could not be related to changes in soil chemical properties. The measured reduction in runoff and soil loss were attributed to delayed crust development, which could be related to increasing proportions of clods in the soil samples with increasing charcoal-C content. Further research may be needed to confirm the observed trends and underlying mechanisms over a wider range of soil types.

Computational Design for Multi-Optimized Geometry of Sustainable Flood-Resilient Urban Design Habitats in Indonesia

Unfortunately, flooding is a major worldwide problem that especially affects low-lying cities like Semarang, Indonesia. Therefore, this study focuses on the flood-prone areas of Semarang, where recurring high tides and surges from severe precipitation cause havoc. In order to create water-resistant dwelling topologies, the paper explores the early incorporation of computational design approaches. Ultimately, the objective is to explore the strategic application of generative design techniques to support the development of a highly adaptive urban environment using optimization-based data-driven design approaches. With careful consideration, advanced computational methods were used to find concepts that may manage and lessen possible consequences in an efficient manner, increasing the urban landscape’s overall flexibility. Achieving the best possible solutions, which consider issues like feasibility, sustainability, durability, adaptability, and user comfort, requires the application of computational studies such as microclimatic, rainfall, energy performance, and fluid simulations. Consequently, promising advances in water retention and trajectory control features are shown by evaluations that concentrate on wind dynamics and energy considerations. One such example is GEN_8, the most optimal typology produced by additive massing approaches. In addition to showing less water retention than usual building typologies, GEN_8 optimizes energy performance to improve user experience overall. Accordingly, the computationally created geometry GEN_8’s shaded areas and facades effectively account for between 191.4 and 957 kWh/m2 of yearly solar radiation. In contrast, average building typologies show higher amounts of annual solar radiation, with a minimum of 574.32 kWh/m2 and a maximum of 1148.65 kWh/m2. This paper’s comprehensive approach not only addresses worldwide issues but also highlights how computational design techniques may be used to construct, assess, and validate workable solutions for flood-prone locations within a flexible framework that has been painstakingly designed. As a result, the research also highlights the significance of technological advancements and computational tools in assessing, producing, and validating workable solutions for flood-prone locations by carefully curating a flexible framework that ensures efficiency, comfort, and design optimization.