Water Utilization Efficiency Research Articles

Regulation of soil water and nitrate by optimizing nitrogen fertilization and the addition of manure based on precipitation: An 8-year field record

Optimizing fertilization strategies to improve water utilization efficiency and obtain higher crop yields and low nitrate leaching is essential for balancing food security and environmental risks in the rain-fed area of the Loess Plateau. The eight consecutive years (2014–2022) field experiment followed a split-plot design, and the experimental factors were nitrogen application rate (N0, N75, N150, N225, and N300) and manure application rate (M0 and M1). In general, (1) the relationships between nitrogen application rate and grain yield (GY), crop N uptake and water utilization efficiency (WUE) followed a quadratic curve. Compared with chemical fertilizer alone (NPK), chemical fertilizer plus manure (MNPK) significantly increased the annual average grain yield by 28.5%, 18.3%, 8.9%, 6.9% and 4.2% at the N application rate of N0, N75, N150, N225 and N300. (2) The nitrate accumulation (SNA) in the same soil layer increased with the nitrogen application rate. The residue nitrate will increase dramatically when the N application rate exceeds 150 kg ha-1. The peaks of SNA gradually moved to the deeper layer with increasing years of fertilization. The total soil nitrate accumulation (TSNA) of NPK was significantly higher than that of MNPK in dry and normal years, but the opposite was true in wet years. The total soil water storage (TSWS) decreased and then increased with the N application rate, and the annual average TSWS of the MNPK treatments was 3.9% less than that of the NPK treatments. (3) The addition of manure significantly increased the annual average moisture storage rate (MSR) during the fallow season by 4.6%. The GY in dry and normal years was more dependent on MSR than that in wet years. In terms of the long-term effects, the MSR contributes more to GY than growing season precipitation (GSP), and the high MSR caused by manure application reduced TSNA and TSWS by promoting crop growth. The results showed that M1N150 could obtain a high grain yield while maintaining low nitrate residue. Taken together, this study emphasized the importance of optimizing nitrogen fertilizer management and cattle manure application in combination with precipitation types to ensure food production and reduce negative environmental effects in the rain-fed area of the Loess Plateau in China.

A new regional cotton growth model based on reference crop evapotranspiration for predicting growth processes

Meteorological conditions and irrigation amounts are key factors that affect crop growth processes. Typically, crop growth and development are modeled as a function of time or growing degree days (GDD). Although the most important component of GDD is temperature, it can vary significantly year to year while also gradually shifting due to climate changes. However, cotton is highly sensitive to various meteorological factors, and reference crop evapotranspiration (ETO) integrates the primary meteorological factors responsible for global dryland extension and aridity changes. This paper constructs a cotton growth model using ETO, which improves the accuracy of crop growth simulation. Two cotton growth models based on the logistic model established using GDD or ETO as independent factors are evaluated in this paper. Additionally, this paper examines mathematical models that relate irrigation amount and irrigation water utilization efficiency (IWUE) to the maximum leaf area index (LAImax) and cotton yield, revealing some key findings. First, the model using cumulative reference crop evapotranspiration (CETO) as the independent variable is more accurate than the one using cumulative growing degree days. To better reflect the effects of meteorological conditions on cotton growth, this paper recommends using CETO as the independent variable to establish cotton growth models. Secondly, the maximum cotton yield is 7171.7 kg/ha when LAImax is 6.043 cm2/cm2, the corresponding required irrigation amount is 518.793 mm, and IWUE is 21.153 kg/(ha·mm). Future studies should consider multiple associated meteorological factors and use ETO crop growth models to simulate and predict crop growth and yield.

Pushing the limits of sodium borohydride hydrolysis for on-board hydrogen generation systems

Sodium borohydride (SBH) is a promising hydrogen (H2) carrier; however, its successful deployment has been limited to unmanned aerial vehicle applications. We reevaluated SBH hydrolysis for on-board vehicular applications from an entirely new perspective using solid-phase SBH hydrolysis with a CO2-derived acid at elevated temperatures and pressures, enabling extremely efficient water utilization. This strategy afforded a high H2 storage density of 6.33 wt%, which could be extended to 10.4 wt% via water recovery from fuel cells. High-purity H2 with carbon monoxide levels below 10 ppm was obtained after methanation. Importantly, an energy-efficient SBH regeneration method using residual NaHCO2 was developed. A 1.2-kWe-level SBH hydrogen generation was evaluated with the fuel-cell operation, and a 20-kWe-level compact system was developed with a system-based volumetric H2 storage density of 25 g-H2/L. This technology will accelerate SBH-based vehicular applications at a level of 50 g-H2/L.

Effects of drip irrigation frequency on the yield and nutrient utilization efficiency of tomato under long-season cultivation in solar greenhouse.

To improve the utilization efficiency of nutrients and water and determine the best drip irrigation frequency for long-season tomato cultivation in solar greenhouses, we cultivated tomato grafted seedlings in soil using an integrated water and fertilizer technology: drip irrigation under mulch. Seedlings drip-irrigated with balanced fertilizer (containing 20% N, 20% P2O5, and 20% K2O) and high-K fertilizer (containing 17% N, 8% P2O5, and 30% K2O) once every 12 days were set as control (CK) and that with water once every 12 days as CK1, while other seedling groups, drip-irrigated with a nutrient solution of Yamazaki (1978) formula for tomato, were set as treatments (T1-T4). There were four drip-irrigation frequencies, i.e., once every 2 days (T1), 4 days (T2), 6 days (T3), or 12 days (T4), who received the same total amounts of fertilizer and water over the 12 experimental days. The results showed that, with the decreases of drip irrigation frequency, tomato yield, the accumulation of N, P and K in plant dry matter, the fertilizer partial productivity, and the nutrient utilization rate first increased and then decreased, peaking at the T2 treatment. Compared with CK, under the T2 treatment, plant dry matter accumulation and the accumulation of N, P and K increased by 4.9%, 8.0%, 8.0%, 16.8%, the partial productivity of fertilizer and the utilization efficiency of water increased by 142.8% and 12.2%, the use efficiency of N, P and K was better than CK by 241.4%, 466.6% and 235.9%, respectively, and the tomato yield increased by 12.2%. Under the experimental conditions, drip irrigation with the Yamazaki nutrient solution at a frequency of 4 days could increase the tomato yield, as well as the use efficiency of nutrients and water. Under long-season cultivation, these trends would result in considerable saving of water and fertilizer. Overall, our findings provided a basis for improving the scientific management of water and fertilizers under long-season tomato cultivation in protected facilities.

Raspberry Pi-Embedded Intelligent Control System for Irrigation and Fertilization Based on deep learning

More than two-thirds of freshwater consumed worldwide are used for irrigation, and the existing control system for irrigation and fertilization is not intelligent and efficient enough. It is necessary to improve the utilization efficiency of irrigation water and fertilizer, and the intelligent level of irrigation and fertilization system. We have built tomato fertilizer deficiency and fertilization decision model based on leaf images and deep learning, this paper develops an Raspberry Pi-embedded intelligent control system for irrigation and fertilization based on previous deep learning models. The system included sensors, image acquisition, control part, control panel and remote control, the type of main hardware and sensors were selected, and the circuit of the system were designed. The C language is used to compile the source code of the deep learning framework, and the Python language is used to compress the deep learning model. The result shows that the compression rate of the deep learning model can reach 36.7% and the decision-making time can be shortened by 36% under the condition of ensuring the model accuracy. The Raspberry Pi-embedded intelligent control system can help farmers improve the utilization efficiency of irrigation and fertilizer.

Research on the impact of China's new urbanization on industrial water utilization efficiency - based on spatial spillover effects and threshold characteristics.

To explore the impact of new urbanization development on industrial water utilization efficiency, the epsilon-based measure model and the entropy method were used to calculate the industrial water utilization efficiency and the development of new urbanization based on the panel data of 30 provincial cities in China from 2011 to 2020. Then the spatial Durbin and the panel threshold models were constructed to explore the spatial spillover and threshold effects of new urbanization development on industrial water utilization efficiency. The results show that there are large regional differences in the development of new urbanization and industrial water utilization efficiency. New urbanization development has a positive spillover effects on the improvement of industrial water efficiency. The promotion effect of new urbanization development on industrial water efficiency is affected by the level of new urbanization development, thus showing different results. According to the findings, it is recommended that local governments at all levels should increase their efforts to build new urbanization. And boost high-level and high-quality development of towns and cities while promoting the rationalization of industrial structure and optimizing resource allocation, thereby improving the efficiency of industrial water utilization.

Investigation of water utility efficiency features: production variables and the DEA model choices

Abstract Data envelopment analysis (DEA) has been used for decades to investigate utility efficiency- and management-specific features. DEA has been extended in various industries with different models that consume different types of production variables to meet industry-specific efficiencies. However, the discernment of production variables and proper DEA models is still a problem in the water industry. Ratio information has been used in DEA for absolute data to assess utility efficiency- and management-specific features; using ratios in DEA for absolute data produces wrong efficiency results because the convexity axiom of DEA for absolute data is not satisfied. This study presents a collection of information and an assessment of DEA for absolute and ratio data to identify the strengths of the production variables and the DEA model that are appropriate for assessing utility efficiency- and management-specific features. The analysis shows that the use of ratio variables in DEA for ratios improves utility economics, the working environment, and the social trust dimension.

Demonstration and experimental characteristics of a water-vapor Hall thruster

Water is an attractive candidate for condensable propellants owing to its availability, handleability, and sustainability. This study proposes the use of water vapor as a propellant for a low-power Hall thruster, and experimentally demonstrates the feasibility of this proposal. Based on the performance estimation from the plume diagnostics, a thrust-to-power ratio of 19 mN/kW, specific impulse of 550–860 s, and anode efficiency of 5–8 % were obtained at an anode power of 233–358 W. From further efficiency analysis, the mass utilization efficiency of water was found to be the most deteriorated among the internal efficiencies compared to the conventional xenon propellant, which was consistent with the expectations from a small discharge current oscillation, large beam divergence, and increase in low-energy ions. Moreover, additional power loss via reactions unique to polyatomic molecules was indicated by evaluation of the ionization cost. In this experiment, the mass utilization efficiency was improved with an increase in the anode voltage from 200 to 240 V without degradation of the power utilization. This suggests that operating at a higher voltage is more suitable for a water-vapor Hall thruster.

Estimating the Effects of Deficit Irrigation on Water Absorption and Utilization of Tomatoes Grown in Greenhouse with Hydrus-1D Model

Quantitative analysis of tomato root water uptake and soil water utilization in the root zone under deficit irrigation is an important tool to improve agricultural water utilization efficiency. In this study, three different deficit irrigation levels were set at the flowering and fruit development stage (Stage I) and the fruit-ripening stage (Stage II), respectively. The Hydrus-1D model and field data were used to analyze the effects of deficit irrigation on tomato root growth, soil water uptake and utilization in the root zone. The results showed that deficit irrigation could reduce the total root length density of water-absorbed roots but increase the water-absorbed root length density of the underlying soil (30–60 cm). Moderate and severe water deficits at Stage II increased the water-absorbed root length density of the underlying soil by 0.10–6.26% and 2.12–11.71% compared with a mild water deficit. Considering tomato root growth, the Hydrus-1D model can improve the accuracy of soil moisture simulation. The main water absorption zone of tomato roots was 0–30 cm. Compared with full irrigation, the ratio of water absorption by the underlying root system (30–60 cm) to the total water absorption of the profile (0–60 cm) increased by 2.16–2.82% and 5.34–6.34% due to mild and moderate water deficits at Stage I. At Stage I and Stage II, a water deficit could reduce soil evaporation. T3 had the highest water use efficiency in two years, which was 24.07% (T9) and 20.47% (T8) higher than the lowest value, respectively. The optimal deficit irrigation scheme under this experiment condition is as follows: the soil water content was 70–90% θf (field capacity) at Stage I and was 40–60% θf at Stage II (T3).

Attapulgite application improves maize yield, water, and fertilizer utilization efficiency in newly cultivated sandy farmland in northwestern China

We determined the effects of attapulgite clay additions to sandy soils on maize yield and water-fertilizer use efficiency to evaluate a new method for enhancing productivity in newly-reclaimed farmlands in the oasis. The 2-year field trial included six treatments: no fertilizer, single fertilizer application (N–P2O5–K2O at 320–240–200 kg·ha−1), and combined applications of different amounts of attapulgite clay and fertilizer (attapulgite powder at 1500, 3000, 6000 kg·ha−1), 20% fertilizer reduction (256–192–160 kg·ha−1) and attapulgite powder at 6000 kg·ha−1. The results showed that maize yield increased by 4.9–14.9% and above-ground biomass increased by 6.1–32.3% with the application of 1500, 3000, and 6000 kg·ha−1 of attapulgite powder compared with the single application of fertilizer. With a combined application of a 20% reduction in fertilizer and 6000 kg·ha−1 attapulgite powder, maize yield increased by another 6.6%. Maize irrigation-water productivity (MIWP) increased by 0.03–0.13 kg·m−3, and nitrogen use efficiency (NUE), agronomic efficiency (AEN) and partial productivity factor of nitrogen (PFPN) increased by 10.8–54.0, 15.5–49.5, and 4.6–14.8%, respectively, compared with no attapulgite application. The contribution rate of fertilizer to maize yield increment improved by 10.0–30.1% with attapulgite application. The attapulgite clay application increased the field water capacity of sandy soils, nutrient retention in the 0–40 cm soil layer, and reduced nutrient leaching losses to deeper soils, thus improving water-fertilizer use efficiency. In Linze County, the abundant reserves of attapulgite clay may be used as a regular application in sandy farmlands in newly-reclaimed oases for a new promising way to rapidly improve sandy soil structure, enhance water-fertilizer use efficiency, and increase crop yields.

Prediction and monitoring model for farmland environmental system using soil sensor and neural network algorithm

Abstract In this study, data fusion algorithm is used to classify the soil species and calibrate the soil humidity sensor, and by using edge computing and a wireless sensor network, farmland environment monitoring system with a two-stage calibration function of frequency domain reflectometer (FDR) is established. Edge computing is used in system nodes, including the saturation value of the soil humidity sensor, the calculated soil hardness, the calculation process of the neural network, and the model of soil classification. A bagged tree is adopted to avoid over-fitting to reduce the prediction variance of the decision tree. A decision tree model is established on each training set, and the C4.5 algorithm is adopted to construct each decision tree. After primary calibration, the root mean squared error (RMSE) between the measured and standard values is reduced to less than 0.0849%. The mean squared error (MSE) and mean absolute error (MAE) are reduced to less than 0.7208 and 0.6929%. The bagged tree model and backpropagation neural network are used to classify the soil and train the dynamic soil dataset. The output of the trained neural network is closer to the actual soil humidity than that of the FDR soil humidity sensor. The MAE, the MSE, and the RMSE decrease by 1.37%, 3.79, and 1.86%. With accurate measurements of soil humidity, this research shows an important guiding significance for improving the utilization efficiency of agricultural water, saving agricultural water, and formulating the crop irrigation process.

A Review on Regulation of Irrigation Management on Wheat Physiology, Grain Yield, and Quality.

Irrigation has been pivotal in sustaining wheat as a major food crop in the world and is increasingly important as an adaptation response to climate change. In the context of agricultural production responding to climate change, improved irrigation management plays a significant role in increasing water productivity (WP) and maintaining the sustainable development of water resources. Considering that wheat is a major crop cultivated in arid and semi-arid regions, which consumes high amounts of irrigation water, developing wheat irrigation management with high efficiency is urgently required. Both irrigation scheduling and irrigation methods intricately influence wheat physiology, affect plant growth and development, and regulate grain yield and quality. In this frame, this review aims to provide a critical analysis of the regulation mechanism of irrigation management on wheat physiology, plant growth and yield formation, and grain quality. Considering the key traits involved in wheat water uptake and utilization efficiency, we suggest a series of future perspectives that could enhance the irrigation efficiency of wheat.

Grass-legume mixture and nitrogen application improve yield, quality, and water and nitrogen utilization efficiency of grazed pastures in the loess plateau.

Grazing on cultivated grassland is a green agricultural model. However, in China's Loess Plateau, the type of cultivated grassland suitable for grazing and the amount of nitrogen application is still unclear, which has led to the failure of this model to be widely implemented. In this context, we set up an experiment using three grass planting types, including monoculture of alfalfa (Medicago sativa L.), monoculture of brome (Bromus inermis L.), and mixed planting of the two forages. Under each planting type, there were six management measures: grazing and no nitrogen application (GN1), grazing and 80 kg ha-1 nitrogen application (GN2), grazing and 160 kg ha-1 nitrogen application (GN3), cutting and no nitrogen application (MN1), cutting and 80 kg ha-1 nitrogen application (MN2), and cutting and 160 kg ha-1 nitrogen application (MN3). To explore the impacts of these treatments on pastures, we studied the effects on the yield, quality, and water use efficiency of the three cultivated grasslands. Results showed that alfalfa monoculture and alfalfa-brome mixed sowing grassland resulted in significantly higher hay yield, crude protein yield, water use efficiency (WUE), precipitation use efficiency (PUE), nitrogen use efficiency (NUE), and agronomic efficiency of nitrogen (AEN) as compared to brome monoculture grassland. In addition, the crude protein, ether extract, and crude ash content of alfalfa monoculture and alfalfa-brome mixture were increased significantly while the contents of neutral detergent fiber (NDF) were reduced, thereby increasing the relative feed value (RFV) during the two years. The forage hay yield, crude protein yield, ether extract, crude ash content, RFV, PUE, and WUE were significantly higher with GN1, GN2, and GN3 treatments than that with MN1 treatment. In contrast, the NDF and acid detergent fiber (ADF) content was significantly lower than the MN1 treatment. Furthermore, the fresh forage yield, crude protein yield, PUE, and WUE of GN3 treatment were significantly higher than that of GN1 and GN2 treatments in both years, while the NUE and AEN were significantly higher in GN2 and GN3 treatments than that of MN3 treatment. Based on these results, alfalfa-brome mixed cropping with the application of 160 kg ha-1 nitrogen under grazing conditions is an appropriate management practice for improving the forage yield, quality, and water- and nitrogen utilization efficiency of cultivated grassland in the Loess Plateau of China. This integrated management model is applicable to the cultivation and utilization of mixed grassland on nutrient-poor land in the Loess Plateau.

Incorporating nonrevenue water in the efficiency assessment of water supply utilities: A parametric enhanced hyperbolic distance function

This study assesses the technical efficiency of water utilities incorporating an undesirable output, nonrevenue water, and allowing a proportional input reduction. A parametric enhanced hyperbolic distance function was applied to Malaysia's 14 state water utilities from 2000 to 2017. Overall, Malaysia's water utilities can increase the water volume delivered while decreasing nonrevenue water and making further input reductions. Water utilities, on average, experienced higher technical efficiency after the regulatory reform. Network density and regulatory reform significantly influenced the technical inefficiency of water utilities in Malaysia.

Response of Plant Species Diversity to Flood Irrigation in the Tarim River Basin, Northwest China

This study quantitatively analyzes the effects of flooding on the growth and species diversity of riparian forests along the Yarkant River and the Tarim River, Xinjiang, in northwest China, and provides important information for the efficient utilization of water and water resource management in arid regions. Monitoring of species diversity of riparian forests was conducted every year from 2016 to 2019 in the Xiamale forest district in the lower reaches of the Yarkant River, and in the Shaya forest district and the lunnan forest district in the upper and middle reaches of the Tarim River. The Pielou index, Shannon–Wiener index, Simpson index, and importance value were used to analyze the influence of flooding. The results showed the following: (1) After three years of flooding, indices for the lower reaches of the Yarkant River and Tarim River were significantly increased and 11 new plant species appeared. (2) With increasing distance from the river channel, plant density and species diversity decreased. Flooding trends are the main factors affecting the distribution of plant species and water is the main restricting factor that influences plant growth in arid areas; thus, desert riparian forests improved significantly after flooding. (3) Flooding increases the regeneration capacity and species diversity of plant communities in desert riparian forests. In order to maintain the current trend of ecological improvement, flooding irrigation must continue.

Comprehensive evaluation of the optimal rates of irrigation and potassium application for strawberry

Accurate and effective management of irrigation and fertilization is essential for efficient greenhouse strawberry production. Here, the effects of the combined application of water and potassium on strawberry growth were evaluated by experimenting with 12 treatments, including four transpiration (ETC)-based irrigation levels (W1: 100% ETC, W2: 85% ETC, W3: 70% ETC, and W4: 55% ETC) and three potassium levels according to the target yield (K1: 369.5 kg/hm2, K2: 307.9 kg/hm2, and K3: 246.3 kg/hm2). Various indexes of strawberry yield, fruit quality, water and fertilizer utilization efficiency, and soil nutrient residues were measured. Irrigation and potassium application had significant effects on strawberry production. Higher irrigation levels increased yield (Y), and moderate water and potassium application increased single fruit weight (SFW), water utilization efficiency (WUE), total soluble sugar (TSSC), and the sugar-acid ratio (SAR). While low-application of potassium increased the soluble protein content (SP), partial factor productivity of potassium (PFPK), and reduce nutrient residues in soil effectively. A comprehensive system for evaluating strawberry growth and its benefits to the soil environment was developed. The FAHP and CRITIC methods were used to calculate the subjective weight and objective weight of each index, respectively. The largest subjective weight was observed for Y (0.200), and the largest objective weight was observed for soil-available potassium (0.101). The final weight was determined using Game theory; Y had the highest weight (0.185), and free amino acids (FAA) had the lowest weight (0.047). Grey relational analysis (GRA) was used to evaluate the optimal irrigation and potassium scheme for accomplishing multiple objectives. The response of the comprehensive score of strawberries to irrigation and potassium exhibited a negative parabolic relationship, and the effect of irrigation was greater than the effect of potassium application. There was a significant interaction between irrigation and potassium application, and an irrigation amount of 2053-2525 m3/hm2 with a potassium application rate of 288.1-334.2 kg/hm2 was optimal for promoting strawberry yield, fruit quality, and efficiency and reducing soil nutrient residues. The results of this study provide new insights that could aid the development of sustainable approaches for enhancing agricultural production. Keywords: strawberry, irrigation, potassium, FAHP, CRITIC, nutrient residues DOI: 10.25165/j.ijabe.20231602.7591 Citation: Yang X Q, Du R C, Zhang M C, Feng H W, Wang Z Q, Zhang Z. Comprehensive evaluation of the optimal rates of irrigation and potassium application for strawberry. Int J Agric & Biol Eng, 2023; 16(2): 65-72.

Estimating Green and Blue Water Footprint of Major Cereal and Vegetable Crops in Salale Zone, Oromia, Ethiopia

To attain effective utilization of water in different sectors, understanding and applying the new concept of water management tools like water footprint analysis is mandatory. Hence, this study aims to estimate green and blue water footprint for selected major cereal and vegetable crops in Salale Zone. Ten year (2011–2020) climatic, crop yield, and cultivated area data were collected. Green and blue water footprints (m3/ton), average water footprint per-kilogram of each crops product (m3/kg), and their Zonal level total water footprints (m3/ton) were estimated. The results indicated that both green and blue water footprint was greater than benchmark value for each considered crops though blue water was highly utilized in the Zone for production of vegetable crops than cereal. At Zonal level, average total water footprint for the major crops was estimated to 14,417.35 m3/ton from which 86% accounts for cereal. From the comparison of average Zonal water footprint with the benchmark, the estimated values for each crop was higher than the benchmark which indicated less efficient utilization of green and blue water. Hence, for effective management and utilization of water, applying the concept of water footprint is essential to account water use in production of a given crop.

The coupling and coordination assessment of food-water-energy systems in China based on sustainable development goals

Food, water and energy are essential to sustainable development and their security greatly affects the achievement of sustainable development goals (SDGs). This study analyzes the interactions among food system, water system and energy system in China based on SDG 2, SDG 6 and SDG 7, which is beneficial to promote coordinated development of resources and the attainment of SDGs at nation level. After establishing a comprehensive evaluation indicator system, the paper integrates the entropy method with the hierarchical analysis process to assign weight to indicators, and then uses the coupling coordination model to quantitatively evaluate the coordinated development level of SDG 2 on food system, SDG 6 on water system and SDG 7 on energy system. The results show that: (1) In general, the comprehensive evaluation index of 2010–2020 shows an increasing trend over time and the coupling degree maintains a high level. (2) The coupling coordination degree also maintains a good trend, and transitions from primary coordination to good coordination. (3) The development level of SDG 6 on water system and SDG 7 on energy system still lags behind that of SDG 2 on food system, therefore improving the utilization efficiency of water and energy contributes to promoting sustainable development.

Evaluating the impact of water resource fee-to-tax reform pilot on total factor water utilization efficiency: empirical evidence from Hebei Province, China

Evaluating the impact of water resource fee-to-tax reform pilot on total factor water utilization efficiency: empirical evidence from Hebei Province, China

An Adaptive Predictive Control Algorithm for Comprehensive Dendritic Canal Systems

Automatic canal control is essential to improve water utilization efficiency in irrigation districts. Water level error in the model used by the control algorithm significantly impacts performance. The integrator delay model, which has a linear structure, is widely used in multi-input/multioutput control algorithms, including linear-quadratic control and model predictive control. However, the integrator delay model is suboptimal for large irrigation districts; the canals are long, the flows are large, there are many scattered offtakes, and the operating conditions vary. We developed an adaptive predictive control mode for the Qinhan Canal in Ningxia Province, China. We used a segment integrator delay model for this large irrigation district and employed a differential evolution algorithm for online system identification; this minimizes error. We analyzed and controlled for various uncertainties (i.e., flow observation noise, geometric and hydraulic parameter errors, and accidental interference with the automatic control system). Simulations indicated that the water level fitting errors were significantly reduced compared with the original model, and water level regulation was significantly improved, especially in terms of the maximum absolute error. Adaptive predictive control was better than linear-quadratic control and model predictive control approach for water level. Adaptive predictive control coped well with several uncertainties. The main factors affecting water level control were the flow observation and gate opening control accuracy, and the extent of real-time data coverage. These features require careful attention when automating and modernizing irrigation districts.