Water Level Control Research Articles

IoT-Based Automatic Hydro-Organic Smart Farming System in Greenhouse with Solar Panels for Khok Nong Na

In this research, we propose IoT-Based Automatic Hydro-Organic Smart Farming System (AHOSFS) in Greenhouse with Solar Panels for Khok Nong Na, design and development with Internet of Things and solar energy. Data is collected from sensors for the following factors that affect plant growth: humidity, temperature, light, pH, EC, air quality, water temperature, and water level. The Firebase cloud-based application was used to collect all the data, and it enables farmers to monitor and control the system using their smartphones. The results showed AHOSFS can mix water and nutrient solution, which measure pH of 6.61 and EC of 1.23, control water level and mix nutrient solution in appropriate quantities. Green oak can thrive at pH levels between 6.0 and 7.0, EC levels between 1.1 and 1.7, and humidity level between 75 and 85. The sensor measured temperature value between 18 and 25 °C, which was adequate for the growth of green oak. Sensor also measured water temperature between 25 and 28 °C. The comparative value of cultivation in a hydro-organic system deployed between AB solution, organic fertilizer Formula 1 and Formula 2 found that organic fertilizer formula 1 has an effective and approximate AB solution at 81.64%. The fertilizer formula 2 has AB solution at 89.72%, which was more secure at a comparable level.

Drum boiler system water level control: A study of existing hybrid optimization algorithms

In this research, we use a variety of optimization techniques to perfect the settings of a PID controller that manages the water level in a boiler's drum. In this study, Particle Swarm Optimization (P_S OPTIMIZATION) is used alongside other optimization techniques and compared to each other. Optimization that combines bacterial foraging with Particle swarms (BFP_S) and Hybridising the Gravitational Search Algorithm along with Particle swarm (GSAP_S) seeks to improve search results. The forementioned methods were tested, and their results were compared, utilising metrics such as IS ERROR, IA ERROR, ITA ERROR, and time domain specifications.

Layered Composite Decoupling Control Based on Regional Dynamic Sparrow Search Algorithm

This paper addresses the issues of coupling and disturbances in a dual-tank water level control system within the context of process control in chemical water treatment at industrial facilities. In response to these challenges, a Layered Composite Decoupling Control system based on the Regional Dynamic Sparrow Search Algorithm (RDSSA-LCDC) is proposed. The utilization of an enhanced Regionally Dynamic Sparrow Search Algorithm (RDSSA) addresses the pitfalls of the Sparrow Search Algorithm (SSA), such as susceptibility to local optima and inadequate precision. RDSSA is employed for the parameter tuning of the system’s PID controller. Structurally, it incorporates a Hierarchical Composite Decoupling Control (LCDC) strategy, initially establishing a forward channel to construct an inner-layer decoupling model employing pre-feedback to rectify the lower-level system’s inputs, thereby mitigating inter-branch coupling. Subsequently, it develops an improved disturbance observer model based on pseudo-inverse compensation in the feedback channel, addressing conventional disturbance observer biases, and observing and suppressing system coupling and disturbances. Finally, within the dual-tank water level control system, various control schemes are simulated and compared, affirming the approach’s commendable decoupling, responsiveness, and disturbance rejection performance.

Assessment of greenhouse gas mitigation from rice cultivation using alternate wetting and drying and rice straw biochar in Thailand

The mitigation of greenhouse gas (GHG) emissions and water usage optimization in rice cultivation is challenging for many agricultural countries, including Thailand, who have set goals of reaching net zero emissions and coping with droughts caused by climate change. Alternate wetting and drying (AWD) and biochar application are possible practices for achieving cleaner rice production through reduction of GHG emissions and water consumption. However, these methods’ potential varies by site, especially in areas with limited control of water levels. This study assessed the effects of AWD at different drying levels (10, 15, and 20 cm below the soil surface) and rice straw biochar on GHG emissions, yield production, water use, soil characteristics, and economic aspects. This study was conducted over two rice cultivation seasons: a major season in 2022 and a second season in 2023 at a field in Kalasin Province, northeastern Thailand. Using AWD and biochar reduced annual GHG emissions by 48.2% and 8.01%, respectively. Deeper drying levels of AWD showed greater mitigation potential than shallow levels. The combination of AWD and biochar had additional potential for GHG mitigation, however, this impact did not show statistical change as compared to their separate potentials. The adoption of AWD and biochar could also maintain the amount of rice yield compared to traditional practice. All levels of AWD saved irrigation water consumption by an average of 16.8% per season; the highest potential was observed in AWD at 10 cm below the soil surface. Biochar improved soil health after two seasons by enhancing soil pH and organic carbon sequestration. The combination of AWD and biochar did not additionally augment the capacity in water saving of AWD or soil improvement of biochar. The AWD water regime also did not increase net profits, while biochar decreased net profits due to the required investment in biochar production. Using AWD is a feasible way to mitigate GHG emissions and save water without affecting rice productivity and net profits in northeastern Thailand.

The water tap design for ablution activities considering cultural influences: a design for sustainability

Water is a vital resource that should be utilized effectively. However, it is overused and squandered on a daily need, including the unrestrained use of water for ablution purposes. This condition can be due to a lack of awareness and the influences of peer cultural values. Therefore, the aim of this study is to develop a water-tap design that takes into consideration the influences of cultural value. Accordingly, confirmatory factor analysis and structural equation modelling (SEM) approach the significant correlation between cultural influences and user preferences on water-tap design by referring at the critical threshold output of each attribute. The result showed that collectivism and uncertainty avoidance dimensions were identified as the influencing cultural dimensions and the automatic water level-control float valve, mechanical water-taps with auto-stop function, and transparent water tanks are the most important considerations for water tap technical specification. Through the assessment of its applicability, the use of the prototype can reduce water usage by 54.6% compared to regular water-taps. Correspondingly, the approach of cultural value in the designing process is expected to give more insights to practices such as product designers when determining design specification while for knowledge, it extends the applicability of Hofstede cultural theory for product design and development.

Water level control on coastal landform distribution and associated processes in a highly fluctuating shallow lake (Gallocanta Lake, NE Spain)

AbstractShallow lakes in semi‐arid environments are very sensitive to hydrological alterations associated with climate change. Their shorelines and geometry can change according to water level fluctuations. Gallocanta Lake (NE Spain) is a typical example of such lacustrine conditions because it is exposed to strong winds parallel to its elongation axis and is located in a semi‐arid Mediterranean environment. In this work, a high‐resolution digital elevation model (DEM) of the area is used to compare the distribution of coastal forms (beaches, barrier islands, deltas, lagoons, etc.) with the frequency at which different water levels are attained. As a result, a clear relationship is obtained between presently active forms and the water levels most frequently reached in the lake. It is deduced that, once formed, the surrounding coastal plains related to these coastal forms control the permanence of water around a given height interval, favouring the development of these morphologies, in a positive feedback mechanism only broken by subsequent climate warming and lake water lowering. The hydrodynamic conditions responsible for activating the coastal forms have been analysed by applying a mathematical model of wind‐driven currents in the lake that predicts the present erosional/progradational trends associated with them. The combination of the different results obtained was used to generate a synthetic map of active coastal processes and trends along the lake shore during high water episodes, with two versions according to the two dominant wind scenarios in the region. The distribution of erosion/sedimentation trends along the lake shores has helped to propose the existence of longitudinal littoral cells, each one recording different shoreline trend (retreat, progradation, and stability), depending on the prevailing wind scenario. This synthetic scheme can be useful for predicting the eco‐morphological trends of the lake shore and adapting the present management practices in this protected area accordingly.

Computational analysis of hybrid grey wolf and particle swarm optimization for water level control in coupled tank

<p><span>Water level control at a precise set point is a major concern in process control systems such as bulk drug production industries. Loss in production at the initial stage is observed until the water level reaches desired level. Pharmaceutical industries can however be benefited if they could maintain the precise water level control at the initial stage of production with the help of the performance optimization using various techniques. To achieve optimized value of the selected performance index, a hybrid of particle swarm optimization (PSO) and grey wolf optimization (GWO) is found to provide the desired performance in the best possible manner. The mathematical model of the coupled tanks is first developed using the state space analysis which can then be converted to transfer function form so as to accomplish the simulation. In this paper, integral square error (ISE) is selected as the performance index for the minimization to improve overall performance of the system. <span>Observations from the hybrid GWO-PSO optimization articulate that overshoot and settling time can be improved as per the industry needs. Performance evaluation of different optimization techniques is discussed in this paper.</span></span></p>

Development and evaluation of the first automated irrigation system for alternate wetting and drying technique in rice cultivation in Bangladesh

Rice stands as one of the most water-intensive crops in agriculture, demanding a substantial volume of water annually for cultivation in Bangladesh. To address this considerable water requirement, the International Rice Research Institute (IRRI) introduced the alternate wetting and drying (AWD) irrigation method. This approach necessitates consistent manual oversight to maintain the desired water levels in the field. In pursuit of reducing this manual effort, a study was conducted at Bangabandhu Sheikh Mujibur Rahman Agricultural University. The study aimed to develop an automated version of the AWD irrigation system, assess its impact on plant growth and yield-contributing factors, and investigate water use efficiency through using that automated system. The automated AWD system incorporated water level controllers, solenoid valves, and water level detection probes to regulate water levels in the paddy field. The experiment followed a Randomized Complete Block Design (RCBD) with three treatments: T1 (Conventional Irrigation - CI), T2 (AWD), and T3 (Automated Alternate Wetting and Drying - AAWD), each replicated four times. The findings indicated minimal variation in growth and development parameters of the rice plants between the CI and AWD treatments. Likewise, yield components demonstrated no significant differences among the various treatments. Notably, the treatment with automated alternate wetting and drying (AAWD), namely T3, displayed the highest water use efficiency (WUE) at 65.20 kg/ha/cm, while the lowest WUE of 52.56 kg/ha/cm was observed in the conventional irrigation (CI) treatment T1. The results underscore the clear advantage of adopting an automated AWD system, yielding a 20% reduction in irrigation water usage compared to the conventional approach. This transition also minimizes the need for labor-intensive interventions in the paddy fields of Bangladesh, illustrating the potential for more efficient and sustainable rice cultivation practices.

Water-Level Fluctuation Control of the Trophic Structure of a Yangtze River Oxbow.

Seasonal water-level fluctuations can profoundly impact nutrient dynamics in aquatic ecosystems, influencing trophic structures and overall ecosystem functions. The Tian-e-Zhou Oxbow of the Yangtze River is China's first ex situ reserve and the world's first successful case of ex situ conservation for cetaceans. In order to better protect the Yangtze finless porpoise, the effects of water-level fluctuations on the trophic structure in this oxbow cannot be ignored. Therefore, we employed stable isotope analysis to investigate the changes in the trophic position, trophic niche, and contribution of basal food sources to fish during the wet and dry seasons of 2021-2022. The research results indicate that based on stable isotope analysis of the trophic levels of different dietary fish species, fish trophic levels during the wet season were generally higher than those during the dry season, but the difference was not significant (p > 0.05). Fish communities in the Tian-e-Zhou Oxbow exhibited broader trophic niche space and lower trophic redundancy during the wet season (p < 0.05), indicating a more complex and stable food web structure. In both the wet and dry seasons, fish in the oxbow primarily relied on endogenous carbon sources, but there were significant differences in the way they were utilized between the two seasons (p < 0.05). In light of the changes in the trophic structure of the fish during the wet and dry seasons, and to ensure the stable development of the Yangtze finless porpoise population, we recommend strengthening the connectivity between the Tian-e-Zhou Oxbow and the Yangtze River.

An Intelligent Water Monitoring IoT System for Ecological Environment and Smart Cities.

Global precipitation is becoming increasingly intense due to the extreme climate. Therefore, creating new technology to manage water resources is crucial. To create a sustainable urban and ecological environment, a water level and water quality control system implementing artificial intelligence is presented in this research. The proposed smart monitoring system consists of four sensors (two different liquid level sensors, a turbidity and pH sensor, and a water oxygen sensor), a control module (an MCU, a motor, a pump, and a drain), and a power and communication system (a solar panel, a battery, and a wireless communication module). The system focuses on low-cost Internet of Things (IoT) devices along with low power consumption and high precision. This proposal collects rainfall from the preceding 10 years in the application region as well as the region's meteorological bureau's weekly weather report and uses artificial intelligence to compute the appropriate water level. More importantly, the adoption of dynamic adjustment systems can reserve and modify water resources in the application region more efficiently. Compared to existing technologies, the measurement approach utilized in this study not only achieves cost savings exceeding 60% but also enhances water level measurement accuracy by over 15% through the successful implementation of water level calibration decisions utilizing multiple distinct sensors. Of greater significance, the dynamic adjustment systems proposed in this research offer the potential for conserving water resources by more than 15% in an effective manner. As a result, the adoption of this technology may efficiently reserve and distribute water resources for smart cities as well as reduce substantial losses caused by anomalous water resources, such as floods, droughts, and ecological concerns.

Research on Multi-Objective Optimization Model of Foundation Pit Dewatering Based on NSGA-II Algorithm

This study focuses on optimizing the foundation pit dewatering scheme using the foundation pit dewatering theory and the principles of multi-objective optimization. It explores the development of a multi-objective optimization model and efficient solution technology for foundation pit dewatering. This research focuses on the foundation pit dewatering project at the inverted siphon section of Xixiayuan canal head, specifically from pile number XZ0+326 to XZ0+500. It establishes an optimized mathematical model for foundation pit dewatering that incorporates three objectives. Additionally, a dewatering optimization program is developed by utilizing the MATLAB optimization toolbox and the multi-objective optimization algorithm program based on the NSGA-II algorithm (Gamultiobj). The multi-objective optimization mathematical model is solved, and a Pareto-optimal solution set with uniform distribution is obtained. The multi-objective optimization evaluation system based on AHP is constructed from the three aspects of dewatering cost, the impact of settlement on the environment, and the safety and stability of the foundation pit. The optimization scheme of the Pareto-optimal solution set is selected as the decision result to provide multiple feasible schemes for the dewatering construction of foundation pits. The optimization scheme is verified by using the GMS software. The simulation results demonstrate that the optimization scheme fulfills the requirements for water level and settlement control. Moreover, the developed optimization program efficiently solves the multi-objective optimization problem associated with foundation pit dewatering. Lastly, an evaluation system incorporating the NSGA-II algorithm and AHP is developed and utilized in the context of dewatering engineering in order to offer multiple viable optimal dewatering schemes.

The potential of a coordinated system of gates for flood irrigation management in paddy rice farm

Rice is one of the most important staple foods in the world. In Europe, Italy is the main producer of rice, with almost all production concentrated in the northeast of the country. Traditionally, rice is grown in fields that are flooded from before planting until just before harvest. This water management technique requires a great deal of labour for farmers who have to manually adjust the inlet and outlet gates to maintain a constant ponding water level in the fields, especially when there is fluctuation of water supply at the farm inlet, for example as a result of rainfall. In addition, the practice of flood irrigation is very water-intensive. New technologies based on remotely and automatically controlled gates are being studied to increase the efficiency of this irrigation method. The objective of this work is to explore the potential of a coordinated and intelligent system of gates for efficient farm irrigation management and ponding water level maintenance. Based on information and measurements from a real case study consisting of a 40-hectare paddy rice farm located in northern Italy, where automatic gates and water level sensors were placed at strategic points of the farm canals and fields, respectively, a proportional-integral (PI) and a non-linear model predictive control (NMPC) of water levels were implemented and compared through modelling and simulation experiments. The results show that the proportional-integral control reproduces the actions that the farmer uses when faced with situations of surplus of water in the fields or a shortage of water in the farm canal. In particular, the general coordination of the gates is lost, and the individual binomial field-gate prevails as an independent system in the farmer's operation. Conversely, non-linear predictive control coordinates the gate operation to obtain a uniform ponding water level in the fields when there is a shortage of water, or significant water conservation when there is an excess of water as a result of rainfall. In conclusion, a nonlinear predictive control model seems to be a suitable strategy to advance irrigation management in rice farms, allowing rice farmers to continue the tradition of flooding while increasing its performance.

Mathematical Modeling of coupled tank interacting system for controlling water level using GWO and PSO optimization

In bulk drug production industries water level control at a precisepoint is a major dispute. Loss in production at the initial stageis observed until the water level reaches desired level. Pharmaceuticalindustries can however earn more profit if they could maintainprecise water level control at the initial stage of production. To synchronizethe water level precisely having best performance parameters,this work introduces Particle Swarm Optimization (PSO) and GreyWolf Optimization (GWO). By determining the mathematical model,the method for water proportion (level) control in the bridged tanksfor the MIMO system may be accomplished. The prior step for systemidentification is by observing the open-loop response of the system.This can be processed by analyzing the actual parameters of the coupledtank. State-space analysis of coupled tanks is explained in detailalong with its conversion into transfer function. In this paper, theinherent parameters required for the calculation are discussed. MATLABis used as the platform for observing the responses. Observationsfrom the PID controller articulate that, there is a need for a better controllerto enhance the performance. Performance analysis along withits discussion is conferred in this paper.

PDE‐constrained model predictive control of open‐channel systems

AbstractA PDE‐constrained model predictive control (MPC) algorithm for open‐channel systems based on the Saint‐Vevant(S‐V) equations is investigated in this paper. The S‐V equations, which precisely model the dynamics of open‐channel systems, are quasi‐linear hyperbolic partial differential equations (PDEs) without analytical solutions. Directly applying the S‐V equations to an MPC controller design becomes sophisticated. In this work, the calculus of variation is used to obtain the adjoint equations and the adjoint analysis method is utilized to deduce the gradients of the MPC optimization problem. Particularly, the physical constraints involving both the state and control variables are also considered. A gradient‐based optimization algorithm in combination with the numerical computation of Preissmann implicit scheme is proposed to solve the constrained MPC optimization problem. The control performances of the developed PDE‐constrained MPC algorithm with respect to the controlled water levels and gate openings are compared with those of the MPC controller designed for the linearized model. All the simulation tests are carried out on an aqueduct reach in Yehe Irrigation District in Hebei Province, China. The results show that the proposed PDE‐constrained MPC algorithm is a promising method in dealing with the constraints in terms of hyperbolic PDEs, control variables and state variables simultaneously.

Micro-pressure promotes endogenous phosphorus release in a deep reservoir by favouring microbial phosphate mineralisation and solubilisation coupled with sulphate reduction

Deep reservoirs vary in their hydrostatic pressure owing to artificial water level control. The potential migration of phosphorus (P) in reservoir sediments raises the risk of harmful algal blooms. To ascertain the mechanisms of endogenous P release in reservoirs, we characterised aquatic microbial communities associated with coupled iron (Fe), P and sulphur (S) cycling at the sediment–water interface. The responses of microbial communities to hydrostatic pressures of 0.2–0.7 mega pascals (MPa; that is, micro-pressures) were investigated through a 30-day simulation experiment. Our findings unravelled a potential mechanism that micro-pressure enhanced the solubilisation of Fe/aluminium (Al)-bound P caused by microbially-driven sulphate reduction, leading to endogenous P release in the deep reservoir. Although the vertical distribution of labile Fe was not affected by pressure changes, we did observe Fe resupply at sediment depths of 2–5 cm. Metagenomic analysis revealed increased abundances of functional genes for P mineralisation (phoD, phoA), P solubilisation (pqqC, ppx-gppA) and sulphate reduction (cysD, cysC) in sediments subjected to micro-pressure, which contrasted with the pattern of S oxidation gene (soxB). There was a tight connection between P and S cycling-related microbial communities, based on significant positive correlations between labile element (P and S) concentrations and functional gene (phoD, cysD) abundances. This provided strong support that Fe–P–S coupling processes were governed by micro-pressure through modulation of P and S cycling-related microbial functions. Key taxa involved in P and S cycling (for example, Bradyrhizobium, Methyloceanibacter) positively responded to micro-pressure and as such, indirectly drove P release from sediments by facilitating P mineralisation and solubilisation coupled with sulphate reduction.

Application of Simple Crested Weirs to Control Outflows from Tiles Drainage

Triangular sharp-crested weirs are commonly used to measure low-flow measurements in open channels. The flow over such a V-notch is proportional to the height of water above the weir on the upstream side. Therefore, it is relatively easy to calculate the flow from standard equations by using only recordings of water levels. Thus, these types of weirs can provide inexpensive measurements of flow volumes and resulting nutrient loads from subsurface drainage systems and associated conservation practices. The objective of this study was to develop appropriate weir equations for a 22.5° V-notch weir developed for a new tubular water level control structure in a controlled drainage system (CD). Analyses using this weir, with three typical slope angles of 30°, 45°, and 60°, were also conducted. There were no significant differences in the fitted parameters across the three analyzed slope angles. The coefficient of determination (R2) values were 0.9955, 0.9981, and 0.9980, respectively. However, the best-fitted equation for a 22.5° V-notch weir was for a slope angle of 45°. The flow equation was Q = 0.2235H2.4182, with Q in liters per minute and H in centimeters. This equation can be used for measuring flow through tubular-controlled drainage structures.

PERANCANGAN ALAT SISTEM KONTROL KETINGGIAN AIR DENGAN MENGGUNAKAN METODE PROTOTYPE BERBASIS ARDUINO

Making a water level control system using the Arduino-based prototyping method means making a tool to regulate the water level of the pool automatically. The Arduino platform is used to develop the system, which serves as the main regulator that can control various related components and sensors. The prototype design process enables rapid development of iterative control systems. The system was developed and upgraded to meet the desired performance requirements by using Arduino modules, water pump actuators, water level sensors, and additional components such as LCDs, ultrasonic sensors, buzzers, and relays. At first, the water level sensor is used to measure the water level in the tank. The data from the sensor is processed by the Arduino, and a corresponding control signal is generated. This control signal regulates the water pump to discharge water from the tank according to the set point. When developing this prototype, an important factor to consider is the accuracy and reliability of the control system. When designing this tool, scalability and ease of use were also considered. It is expected that this water level control system tool can provide efficient water level regulation solutions for various applications, such as agricultural irrigation, automatic irrigation systems, water level control storage tanks, and others, using an Arduino-based tool approach.

Water level control of small-scale recirculating aquaculture system with protein skimmer using fuzzy logic controller

The recirculating aquaculture system (RAS) is a land-based aquaculture facility, either open-air or indoors, that minimizes water consumption by filtering, adapting, and reusing water. Solid organic matter from fish waste and food waste directly becomes waste that needs to be eliminated because it is a source of increasing total ammonia nitrogen (TAN), total suspended solids (TSS), total dissolved solids (TDS), and also has an impact on reducing dissolved oxygen (DO). RAS requires a water level control system so the fish tank does not experience water shortages or floods, disrupting the aquatic aquaculture ecosystem. In this study, small-scale RAS is modeled using a 3-coupled tanks system approach with a tank configuration that follows the most straightforward RAS water recirculation process (fish tank, mechanic filter, biofilter). Clean water from the reservoir flows into the fish tank through a protein skimmer. This study applies the fuzzy logic controller (FLC) to control the water level in the protein skimmer and biofilter tanks by controlling the position of several valves where the placement positions of the valves have been determined according to system requirements. The study results show that the tuned single-input FLC has the best average output response characteristics with t&lt;sub&gt;s&lt;/sub&gt;=50, h&lt;sub&gt;1ss&lt;/sub&gt;=49.98, e&lt;sub&gt;ss&lt;/sub&gt;=0.02 in protein skimmer and t&lt;sub&gt;s&lt;/sub&gt;=4700, h&lt;sub&gt;1ss&lt;/sub&gt;=39.75, e&lt;sub&gt;ss&lt;/sub&gt;=0.25 in the tank system.

Development of dam controller technology water level and alert system using Arduino UNO

Recently, various water level detection monitoring systems integrations were implemented to various places such as rivers and reservoirs to avoid floods. Thus, it is determined to construct a project primarily focused on water level management, named dam controller technology (DCOTech). DCOTech is a system that controls the amount of water in a reservoir using a microcontroller ATMEGA328p and several functions to prevent flash floods. Water sustainability requires proper monitoring via sensors and a controller. Moreover, a buzzer is used in DCOTech to give a warning signal to the people around and the residents. The water level sensor was constructed with a metal plate attached at both the bottom and top edges of the reservoir. The results obtained met expectations; whenever the sensor detects the water level is low, the green light emitting diode (LED) is turned on; otherwise, when the sensor detects the water level is high, the drain valve is opened, and simultaneously, turned on the buzzer to alert the surrounding. The goal of this project is to integrate a control system into an autonomous water level controller. This study aims to provide a solution to unexpected floods and to notify inhabitants when the water level is dangerously high.

A PROPOSED TECHNIQUE FOR IMPROVING THE ACCURACY OF TIDAL MODELING OF RIVER NETWORKS CONNECTING TO THE DADAHUP IRRIGATION AREA

Optimizing the operational management of tidal irrigation networks is a significant factor in the reactivation program of the swamp irrigation areas in Central Kalimantan Province. Appropriate water level and flow rate control in a tidal environment would provide a better solution for this effort. Monitoring water parameters and hydraulic modeling is an intelligent technique for evaluating irrigation canals' gate system operations. This paper focuses on providing more accurate hydraulic modeling that requires proper boundary conditions and calibration of the canal roughness coefficient. This study aims to obtain a more precise downstream boundary condition data calibration method with an appropriate river cross-sectional roughness coefficient value to improve the overall hydraulic modeling accuracy of the river network connecting to the Dadahup Irrigation Area. The hydraulic modeling utilized the HEC-RAS Software, where input data preparation used geometric data derived from the National Geospatial Agency's DEM in the form of river channel network chain, cross-section, and long-section data. Boundary condition data evaluation compared and selected data generated from references and the Tides Application Software. The results show that the tide prediction from the Tides Application Software provides the slightest difference between the predicted tide and the measured ones. The river network's channel roughness coefficient calibration utilized the generated boundary condition tide and simultaneously measured water level data at several locations. The results show that the most minor Root Mean Squared Error (RMSE) of the Manning roughness coefficient differences of the river channel network can reach 0.04 with a minimum RMSE value of 0.027.