Bed Width Research Articles

Plankton and contour algal communities in the Ukrainian section of the Western Bug River and its tributaries

The paper deals with spatial dynamics of cell count, biomass, dominant species complexes, information diversity of planktonic and contour algal communities in the Western Bug River and its tributaries. The trophic state and water quality of the rivers under study have been assessed. The spatial heterogeneity of phytoplankton, microphytobenthos and phytoperiphyton brought about high cell count and biomass values during the low-water summer-autumn season. The cell count and biomass have been shown to increase from the upper reaches downstream, correlating with the river bed width. High quantitative diversity of algal communities was due to Bacillariophyta dominance. Cyanobacteria and Chlorophyta were recorded as subdominants. The trophic state of the aquatic ecosystems under study varied between oligotrophic and eutrophic. The Shannon’s index made up 1.58–4.62 bit/cell and 1.60–4.40 bit/mg. The trophic state and information diversity assessed according to contour algal communities were higher than according to phytoplankton. This is indicative of the clear water regime forming in the rivers under study during the low-water summer-autumn season. The obtained findings differ from the data, published earlier for the Kaniv Water Reservoir, where the primary role belonged to phytoplankton. The spatial heterogeneity of algal communities is related to the dominant complexes structure. As a rule, these are monodominant Bacillariophyta complexes or oligodominant Bacillariophyta – Cyanobacteria or Bacillariophyta – Chlorophyta complexes. The water quality assessment according to the abiotic variables and saprobiologic characteristics has shown that the modal classes of water quality are the 2nd–3rd classes (clean waters – satisfactory clean waters). Therefore, the water quality of the Ukrainian section of the Western Bug River and its tributaries does not pose any substantial hazard to the adjacent European countries.

Agronomical interventions for enhancing seed size tubers in potato (Solanum tuberosum) variety kufri khyati

The present experiment was conducted during 2020–21, 2021–22 and 2022–23 at Regional Station, ICAR-Central Potato Research Institute, Gwalior, Madhya Pradesh to evaluate the best spacing combination and dehaulming time for enhancing the seed size potato (Solanum tuberosum L.) tubers and profitability under north-central plains of India. Experiment was conducted in a split-plot design (SPD) comprised of 5 spacing combinations, viz. S1, Ridge and furrow 60 cm × 20 cm (Control); S2, Ridge and furrow 60 cm × 15 cm; S3, Flatbed paired row 90 cm bed width (two rows at 40 cm × 20 cm plant to plant spacing); S4, Flatbed paired row 90 cm bed width (two rows at 40 cm × 15 cm plant to plant spacing); and S5, Flatbed triple row 90 cm bed width (three rows at 20 cm × 20 cm plant to plant spacing) in main plot and 2 haulm killing dates, viz. 70 and 80 days after planting in sub plots. The treatment S5, Flatbed triple row 90 cm bed width (three rows at 20 cm × 20 cm plant to plant spacing) spacing combination significantly increased the number and weight of seed size tubers, net seed size and total tuber yield when dehaulming was done after 80 days. The highest increase in seed size and total tubers over control reported when dehaulmed at 70 days. However, the treatment S3, Flatbed paired row 90 cm bed width (two rows at 40 cm × 20 cm plant to plant spacing) with 80 days haulm killing recorded highest seed size tuber 58.03% and benefit cost (B:C) ratio of 2.51:1 among all other treatment combinations. Though, treatment S3 i.e. flatbed paired row 90 cm bed width (two rows at 40 cm × 20 cm plant to plant spacing) with 80 days haulm killing combination require higher seed rate but can be an economically viable option for enhancing seed size tuber percent and B:C ratio.

Skeletonization of open-channels networks - New approaches

Due to the complexity of open-channel networks in which a lengthy procedure is required to understand and analyze their behavior. This paper introduces a methodology for the skeletonization of complex tree-shaped open channel systems. The aim is to aggregate separate branches into one equivalent branch, which has a new skeletonization factor. Three different illustrative examples of river systems using two approaches are analyzed. The software package HEC-RAS is employed to simulate the proposed open channel networks as a one-dimensional steady, gradually varied flow state. Results show that there is a strong correlation between the skeletonization factor required for the equivalent branch and the flow rate of the equivalent branch. The skeletonization factor is also significantly affected by an increase in the ratio of the bed width of each branch canal to that of the main channel in Approach A. The water depth along the main channel has increased more significantly in approach B than in approach A, with average increases of 49.5 %, 29.2 %, and 14.1 % for a number of branches equal to 2, 4, and 6, respectively. Finally, the developed skeletonization concept can be used to represent complex open-channels network models.

Effects of bed width and crop row spacing on barnyardgrass (Echinochloa crus-galli) emergence and seed production in furrow-irrigated rice

Abstract Furrow-irrigated rice (Oryza sativa L.) has become a popular option for rice production in Arkansas. Highly troublesome weeds like barnyardgrass [Echinochloa crus-galli (L.) P. Beauv.] are a major problem for producers in all rice production systems. Cultural tactics should become a priority to enhance crop growth and competitiveness. This research aimed to determine the effects of bed width (irrigation furrow spacing) and crop row spacing manipulation on E. crus-galli emergence and seed production in a furrow-irrigated rice system. Three bed widths (76, 97, and 152 cm) (whole-plot factor) were used, and plots were drill seeded in four crop row spacings (13, 19, 25, and 38 cm) (subplot factor). The widest width of 152 cm had a slight increase in E. crus-galli density in the early rice life cycle but, by the end of the season, did not differ from the narrower bed widths. Conversely, a decrease in E. crus-galli seed production was observed as the bed width increased. Similar rice canopy coverage and yields occurred among all three bed widths. As for crop row spacing, as the width increased, E. crus-galli density also increased. The 13-cm crop row spacing had the lowest preflood E. crus-galli density, preharvest panicle count, and seed production. No effect of crop row spacing was observed on rice canopy coverage; however, the 13-cm crop row spacing produced the greatest rice yield. The 13-cm crop row spacing paired with the 152-cm bed width may be the optimum combination of ecological strategies in furrow-irrigated rice to reduce E. crus-galli seed production while maintaining rice growth and yield.

Computational fluid dynamic simulation of packed bed drying process: impact of particle properties, drying conditions, and lateral edge heating modes on drying kinetics

In this work, a two-dimensional computational fluid dynamic (CFD) model is developed to describe the drying process of a packed bed made of spherical particles. The volumetrical evaporation rate inside the bed is computed from the pressure difference between the particle surface and the airflow. By using the thermal equilibrium assumption, the heat conservation equation is derived. The CFD model is solved in the COMSOL Multiphysics environment. The obtained results indicate remarkable maldistributions of temperature and moisture content. These maldistributions can be explained by the impact of lateral edges on thermo-hydraulic behavior. Additionally, the impact of particle diameter, air velocity, and bed width on the spatial-temporal moisture content and temperature distribution is investigated. It shows that the CFD model can be simplified to the receding front drying model for a bed made of small particles. Furthermore, by changing the thermal boundary conditions at the lateral edges, the influence of the heating mode at the lateral edges on the drying behavior is explored. The results indicate that contact heating at the bed wall can help to accelerate the drying process significantly.

Sediment–vegetation interactions determine the fate of fluvial sediment in the upper reaches of a large estuary

AbstractFeedbacks between sediment and plants in the submersed aquatic vegetation (SAV) beds of the Susquehanna Flats help modulate sediment delivery into the upper Chesapeake Bay from its major tributary (Susquehanna River). Recent modeling work has shown that SAV can steer the river plume, directly controlling sediment transport and fate. However, transport mechanisms likely differ between flood and non‐flood conditions and depend on event timing. An opportunity to evaluate these insights in the field occurred with several flood events in summer 2018. Sediment and biomass samples were collected after the flood in the large, continuous main SAV bed of the Flats and in smaller patches to the west of the main bed to evaluate the effect of SAV bed size (width). Sediment characteristics (grain size, organic content) and deposition rates were compared to previous observations during non‐flood conditions in the main bed in 2014–2015 and in the smaller patches in 2019. Overall, sediment deposition rates could be predicted by an empirical model including sediment load, vegetation biomass, and SAV bed width, reflecting the role of vegetation in steering the Susquehanna River plume and modulating sediment input to the upper Chesapeake Bay. Understanding spatiotemporal patterns of sedimentation is essential for realistic estimates of sediment and nutrient (especially nitrogen and carbon) storage in freshwater SAV systems, which have not received as much attention as their saltwater counterparts.

Reducing Water, Nutrient, Pesticide, and Carbon Footprints and Costs for Drip-Irrigated Vine Crops with Compact Bed Plasticulture

Highlights Narrower and taller compact beds (CB) were designed to increase the system efficiency of drip-irrigated plasticulture. CB lowered water, fertilizer, plastic, pesticide, and fuel inputs while maintaining watermelon yield. CB reduced GHG emissions and input costs while increasing input productivity. CB are a synergistic and win-win climate-smart design to increase the sustainability of high-intensity plasticulture. Abstract. Raised bed plasticulture, used globally for producing high-value fruits and vegetables, is a high input and high intensity production system. We show that improved water and nutrient efficiency with reduced material inputs, costs, and carbon footprint is achieved with the use of taller and narrower plastic-mulched compact beds [61×30 (width × height in cm), 61×10, 46×30, and 41×30] compared to the wider and shorter conventional bed [76×20] used for growing watermelon. The primary motivation behind the compact bed design is to improve economic and environmental sustainability by reducing the bed width, to increase the fraction of the bed that is wetted by drip irrigation and to reduce the area of farmland covered under plastic. Compact beds were evaluated at two locations in South Florida with different hydrologic settings, using an ensemble of field data (inputs, plant health, yield, soil moisture, and nutrient levels) and a field-verified hydrologic model (HYDRUS). No reduction in yields was observed with compact beds, indicating no production risk for the growers. Compact beds conserve water and reduce deep percolation losses by 6 cm compared to conventional beds, thereby improving water productivity by 20%. Compact beds require less fertilizer (10%-50%) to maintain the same nutrient (N-P-K) concentrations as those in conventional beds because of smaller soil volumes. Reductions in water and fertilizer inputs provide the environmental benefit of reducing nutrient leaching to groundwater, while reduced impervious area reduces runoff losses. Compact beds reduced input (fertilizer, plastic mulch, pesticide, and diesel) costs of the system by US$720/ha and greenhouse gas emissions by 1630 kg CO2e/ha (9%) compared to conventional plasticulture. The annual cost savings create a win-win for farmers to increase profits and/or invest in conservation measures such as precision irrigation. Compact beds offer a climate change mitigation and adaptation strategy for the plasticulture system for watermelon and other similar cucurbit crops (e.g., cucumber, pumpkin, and zucchini). Keywords: Climate-Smart Agriculture, Economics, Greenhouse Gas Emissions, Nutrient Leaching, Sustainable Design, Water Conservation.

Predicting seepage losses from lined irrigation canals using machine learning models

IntroductionEfficient water resource management in irrigation systems relies on the accurate estimation of seepage loss from lined canals. This study utilized machine learning (ML) algorithms to tackle this challenge in seepage loss prediction.MethodsFirstly, seepage flow through irrigation canals was modeled numerically and experimentally using Slide2 and physical models, respectively. Then, the Slide2 model results were compared to the experimental tests. Thus, the model was used to conduct 600 simulation scenarios. A parametric analysis was performed to investigate the effect of canal geometry and liner properties on seepage loss. Based on the conducted scenarios, ML models were developed and evaluated to determine the best predictive model. The ML models included non-ensemble (regression-based, evolutionary, neural network) and ensemble models. Non-ensemble models (adaptive boosting, random forest, gradient boosting). There were four input ratios in these models: bed width to water depth, side slope, liner to soil hydraulic conductivity, and liner thickness to water depth. The output variable was the seepage loss ratio. Seven performance indices and k-fold cross-validation were employed to evaluate reliability and accuracy. Moreover, a sensitivity analysis was conducted to investigate the significance of each input in predicting seepage loss.Results and discussionThe findings revealed that the Artificial Neural Network (ANN) model was the most dependable predictor, achieving the highest determination-coefficient (R2) value of 0.997 and root-mean-square-error (RMSE) of 0.201. The eXtreme Gradient Boosting (XGBoost) followed the ANN model closely, which achieved an R2 of 0.996 and RMSE of 0.246. Sensitivity analysis showed that liner hydraulic conductivity is the most significant parameter, contributing 62% predictive importance, while the side slope has the lowest significance. In conclusion, this study presented efficient and cost-effective models for predicting seepage loss, eliminating the need for resource-intensive experimental or field investigations.

Standardized agronomic practices for mechanical harvesting of the single-harvest garden pea in India

The field investigations were conducted at Vegetable Research Farm, Department of vegetable Science, Punjab Agricultural University, Ludhiana with the objective to standarize the agronomic practices for mechical harvesting of garden pea. Therefore, effect of different agronomic traits including time of sowing, spacing and sowing method on yield and its attributing traits were studied on single-harvest garden pea. The experiment was laid out in split-plot design with 30 treatments comprising five dates of sowing in main plots and 2 different planting methods (flat and bed) sown at three different spacing in subplots and replicated three times. The bed size was standardized according to front-loading width of the pea combine. Significant interactions were observed between the date of sowing and spacing for a number of pods per plant, green seeds per pod, green pod yield per plant, green pod yield per plot; date of sowing and sowing method for pod length; spacing and sowing method for plant height. However, for all the traits, there was non-significant 3-way interaction. The late sown (20th December) crop resulted in the least number of pods per plant, green seeds per pod, green pod yield per plant and green pod yield per plot which was due to high temperature and low relative humidity conditions at pod development and filling stage. It is concluded that the garden pea cultivar Punjab-89 sown on 5th November at the spacing of 20 × 7.5 cm on beds (bed width of 1.0 m) resulted in significantly highest green pod yield of 12.75 kg/9 m2 in the single harvest. Therefore, the 3 beds of 1 m width can be harvested together with pea combine (because combine has working front width of 3.1 m) results into maximum yield when pea crops is sown on 5th November @ 20 × 7.5 cm spacing.

Rice cultivation under raised bed conserving irrigation technique: effects of bed width on soil wetness and yield

Rice cultivation under raised bed conserving irrigation technique: effects of bed width on soil wetness and yield

Design of open drains by solving Richards equation and artificial neural networks

The perfect design of open drains requires understanding the effect of the different design parameters on groundwater table. The paper objective is to perform sensitivity analysis to show the effect of the drainage flow rate, the distance between the bed of the open drain and the bottom impervious layer, the drain bed width, the spacing between drains, and the soil type (design parameters) on the maximum height of groundwater table above the open drain bed. HYDRUS software, Dupuit equation, and artificial neural networks (ANNs) are used. Comparison is performed between HYDRUS and Dupuit equation for simulating water flow in unconfined aquifer between two water ways. The predicted groundwater table using HYDRUS is above the other one from Dupuit equation. ANNs were used to predict the maximum height of groundwater table from its design parameters. MATLAB code is written to simply use the previous ANNs to find the best drain design.

Numerical Investigation for Rehabilitation and Lining of a Problematic Canal

Canal lining and rehabilitation aim to distribute water, reduce losses, and ensure that water reaches the ends of the canals. Recognizing the need to improve the management of the irrigation system and maintain the width of strategic adjacent roads to canals, the Western Meleg Canal in Menoufia Governorate, Egypt, was selected as a case study. A reach of 1500–3400 km faces problems that impede the implementation of the lining sector as a result of the proximity of the buildings that could not be removed on the canal banks. Two alternatives, including the contraction of the bed width or coverage of the reach from 1500 km to 3400 km on the Western Meleg Canal, were explored. A coupled one-two dimensional numerical model to replicate the water surface profile and flow velocity was implemented. The total cost of each alternative was approximately estimated. The results show that the contraction of the bed width along the considered reach has a limited effect on the levels and velocities of water along the canal, as water levels increased by 2 to 6 cm from the design levels before the contraction of the width of the bed, and the maximum velocity of the water was 0.72 m/s. In the case of covering the selected reach, the difference in water pressure through the coverage (1500:4000 km) was 74 cm, and the coverage works under free flow. The estimated cost of covering is more than four times the cost of plain concrete lining. The findings of this study may help decision-makers and could be implemented in other such canals.

Towards an automated acquisition and parametrization of debris‐flow prone torrent channel properties based on photogrammetric‐derived uncrewed aerial vehicle data

AbstractDebris flows are a hazard in mountainous regions. Cost‐effective, long‐term studies of debris‐flow torrents, however, are rare, leading to uncertainties in hazard assessment and hazard prevention. Here, we address the question of whether cost‐effective remote sensing techniques can be applied for assessment of mountain torrents and possibly further gather accurate, long‐term information on the evolution of the catchment. Torrents prone to debris flows are often devoid of vegetation in the near channel area and hence can be well captured with photogrammetrically derived methods using uncrewed aerial vehicle (UAV) surveys. The possibility of automatically extracting specific torrent parameters from high‐resolution terrain models, such as cross‐section area or gradient, is investigated. The presented methodology yields continuous and automatically derived geometrical parameters such as torrent bed width, inclination and cross‐section area, which is a major advantage compared with point‐based, often dangerous field surveys. Their cross‐validation with field measurements shows strong agreement. Those parameters are accurate along sharply incised sections with strong limitations along sections with steep adjacent slopes and/or dense vegetation. The information along the torrent allows fast identification of key sections and weak spots which can be precisely evaluated in the field. The study highlights that proper classification of real ground points poses the key challenge. We show that photogrammetric routines to derive a high‐resolution digital terrain model (DTM) are limited in the case of dense vegetation coverage. In such cases, LiDAR surveys have clear advantages even though they are also limited by very dense vegetation. We find that UAV data can be used for an objective method of estimating debris‐flow torrent geometric properties. And the introduced approaches therefore build a stepping stone towards a more comprehensive, reproducible and objective assessment of torrent processes and predispositions. However, ground‐referencing fieldwork remains essential, and further research on remote sensing supported hazard assessment of debris‐flow‐prone torrents is indispensable.

River flood routing using artificial neural networks

Flood routing through rivers is very important for the design of protection measures. Sensitivity analysis was performed using HEC-RAS 1D to show the effect of Manning’s coefficient, reach length, peak inflow hydrograph, base time of the inflow hydrograph, channel bed slope, channel side slope, and channel bed width on the peak discharge and the shape of the downstream hydrograph. About 1,600 synthetic realizations were generated using HEC-RAS 1D to train, validate, and test the artificial neural networks (ANNs). The network was trained to estimate the peak discharge from river reach and inflow hydrograph parameters. Testing this network shows a very good agreement between the predicted and actual peak discharges. Another network is trained to predict the whole outflow hydrograph from inflow hydrograph for a certain reach. Hence, flood routing through rivers can be performed using ANNs easily, accurately and quickly.

COMPATIBILITY BETWEEN FOREST SPECIES, SOIL AREA, AND ACCESSIBILITY ON SIDEWALKS

The compatibility between the built environment and trees is also a challenge for urban planning. However, there are few guidelines related to the space for tree growth on sidewalks. This research aimed to analyze the space occupied by trees on sidewalks in the city of Frederico Westphalen, RS, Brazil. We used data from 400 trees of 10 species (dendrometric and qualitative variables) and from the urban structure (width of sidewalks and tree bed area) to analyze the relationship between the species according to the soil capacity and pedestrian’s accessibility. It was found that 90.25% of the trees are in places where the sidewalks promote accessibility to pedestrians and that 60.25% of them tree bed areas with adequate capacity, being possible to increase their size to improve the development of the trees in 39.75% of the cases. Regarding the amount of soil required for each tree, it was found that most species (72.25%) would not have an adequate amount of soil, (Situation 1 – sidewalk width x 4). For Situation 2 (tree bed width x 1), 100% of the individuals would not have an adequate amount of soil. We concluded that the method to evaluate the compatibility between soil area and sidewalk accessibility is easy to replicate and helpful for studies on urban trees and urban planning.

Modeling of scour depth and length of a diversion channel flow system with soft computing techniques

Abstract This study employed soft computing techniques, namely, support vector machine (SVM) and Gaussian process regression (GPR) techniques, to predict the properties of a scour hole [depth (ds) and length (Ls)] in a diversion channel flow system. The study considered different geometries of diversion channels (angles and bed widths) and different hydraulic conditions. Four kernel function models for each technique (polynomial kernel function, normalized polynomial kernel function, radial basis kernel, and the Pearson VII function kernel) were evaluated in this investigation. Root mean square error (RMSE) values are 8.3949 for training datasets and 11.6922 for testing datasets, confirming that the normalized polynomial kernel function-based GP outperformed other models in predicting Ls. Regarding predicting ds, the polynomial kernel function-based SVM outperforms other models, recording RMSE of 0.5175 for training datasets and 0.6019 for testing datasets. The sensitivity investigation of input parameters shows that the diversion angle had a major influence in predicting Ls and ds.

Online sequential, outlier robust, and parallel layer perceptron extreme learning machine models for sediment transport in sewer pipes.

Sediment transport is a noteworthy task in the design and operation of sewer pipes. Decreasing sewer pipe hydraulic capacity and transport of pollution are the main consequences of continuous sedimentation. Among different design approaches, the non-deposition with deposited bed (NDB) method can be used for the design of large sewer pipes; however, existing models are established on limited data ranges and mostly applied conventional regression methods. The current study improves the NDB sediment transport modeling by utilizing wide data ranges, and furthermore, applying robust machine learning techniques. In the present study, the conventional extreme learning machine (ELM) technique and its advanced versions, namely the online sequential-extreme learning machine (OS-ELM), outlier robust-extreme learning machine (OR-ELM), and parallel layer perceptron-extreme learning machine (PLP-ELM) are used for the modeling. In the studies conducted in the literature, sediment deposited bed thickness (ts) or deposited bed width (Wb) was used in the model structure as a deposited sediment variable, and therefore, different parameters in terms of ts and Wb can be incorporated into the model structure. However, an uncertainty arises in the selection of the appropriate parameter among Wb/Y, ts/Y, Wb/D, and ts/D (Y is flow depth and D circular pipe diameter). In order to define the most appropriate parameter to best describe the impact of deposited sediment at the channel bottom in the modeling procedure, four various scenarios using four different parameters that incorporate deposited sediment variables at their structures as Wb/Y, ts/Y, W/D, and ts/D are considered for model development. It is found that models that incorporate sediment bed thickness (ts) provide better results than those whichuse deposited bed width (Wb) in their structures. Among four different scenarios, models that utilized ts/D dimensionless parameter, give superior results in contrast to their alternatives. Based on the outcomes, the OR-ELM approach outperformed ELM, OS-ELM, and PLP-ELM techniques. The results obtained from applied methods are compared to their corresponding models in the literature, indicating the superiority of the OR-ELM model. It is figured out that the thickness of the deposited bed is an effective variable in modeling NDB sediment transport in sewer pipes.

Optimizing Irrigation Scheduling and Land Configurations of Furrow Irrigated Aerobic Rice

Field experiments were conducted during pishanam 2015 and 2016 at Central Farm, Agricultural College and Research Institute, Killikulam. The experiment was laid out in a factorial randomized block design with three replications. Experimental treatments comprised of three irrigation scheduling and three bed widths. Rice crop was raised under furrow furrow-irrigated raised bed system (FIRB) system. Response of the crop to the different treatments indicated that growth parameters viz., plant height and Dry Matter Production (DMP) were highest in crop raised in bed width of 1.0 m accommodating five rows per bed and irrigating the crop daily. Raised bed of 1.0 m bed width accommodating five rows per bed and irrigating crop daily resulted in higher grain yield (3874 and 3789 kg ha-1 during 2015 and 2016, respectively) and Water use Efficiency (4.39 and 4.24 kg ha-1 mm-1 during 2015 and 2016, respectively) than other irrigation scheduling and land configurations

Development of statistical relationship for the potential assessment of hydrokinetic energy

Instream technology is attaining great focus with enhancement in research from model to prototype testing for the extraction of hydropower energy. The major constraint of instream technology is the potential assessment of hydrokinetic energy. Therefore, the main aim of the study is to develop a model for the potential assessment of hydrokinetic energy available in the vast channel network. Three-dimensional transient numerical simulations have been carried out by incorporating two phase modelling to consider free surface effect. Numerical simulations have been carried out on actual dimensions of rotor and channel to analyse the impact of hydrokinetic rotor's operation on the hydraulic behaviour of channel under different flow velocities. It is noticed that the impact of turbine operation is limited to a certain flow volume. The determination of the impacted distance led to the development of three statistical relationships which provides minimum bed width required for operation, minimum depth essential for submergence and wake recovery distance. The developed statistical relationships defining the longitudinal and lateral spacing between two units are the functions of flow velocity and turbine diameter. Further, the developed statistical relationships is applied on an irrigation channel and assessed that 54122920 kWh/km energy can be generated per year.

Characteristics of Gas–Solid Flow in an Intermittent Countercurrent Moving Bed

The calculation equations of pressure drop and solid flow rate are given in an intermittent countercurrent moving bed with multiple optimized structures. The flow fields are investigated by experimental methods under different conditions, e.g., ratio of position of the gas distributor to the bed width (rp = 0.5~1.5), gas superficial velocity (ug = 0~0.1591 m/s), solid outlet diameter (Do = 5~25 mm) and cone angle (α = 0~60°). It is found that when rp ≥ 1.0, the flow field in the bed is little affected by rp. Flow patterns are divided into three modes: continuous discharging, intermittent discharging (synchronous, asynchronous) and particle bridging. During continuous discharging, the calculation formula of the solid flow rate, which is closely related to Do and gas–solid slip velocity vslip, is established by referring to the modified De Jong and Beverloo formulas, and its error ≤ ±12.5%. The pressure drop of the total bed consists of the pressure drops of the granular bed and the solid outlets, which are affected by Do, vslip and α; it is built by referring to the Ergun formula, and its error ≤ ±17.0%. As the solid flow rate and pressure drop influence each other through vslip, an iterative algorithm is proposed to enhance the computation accuracy.