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【Objective】 Water storage pit is a technology used in arid regions in northwestern China to collect rainwater for irrigation. In this paper, we studied the three-dimensional distribution of water, heat and oxygen in soil in an orchard under water storage pit irrigation using numerical simulation. 【Method】 Water flow was based on the Richard equation and heat transfer and oxygen diffusion in soil were modelled by convection - diffusion equations. These coupled equations were solved using the COMSOL - a Multiphysics software. The model was verified against data measured from a field, and the validated model was then used to analyze the effect of the water storage pit on distribution of water, heat and oxygen in soils in the proximity of the pit. 【Result】 The three-dimensional coupled model is accurate and can reproduce the measured spatiotemporal changes in soil water, temperature and oxygen, with the RMSE for soil water, temperature and oxygen being 0.036 7, 1.609 9 and 0.013 8, respectively. The water storage pit changed the distribution of water, heat and oxygen in the pit wall greatly. As time elapsed, soil water content in the regions proximal to the pit decreased, while oxygen concentration increased. Temperatures in the pit and soil surface were mainly impacted by atmospheric temperature. Spatial water distribution was ellipsoidal around the pit. Soil water content was the highest in the proximity of the pit bottom, while oxygen concentration and temperature in this region were the lowest. The distribution of water, temperature and oxygen tended to uniformize as time elapsed, despite that temperature and oxygen are less sensitive to irrigation than soil water. Oxygen concentration decreased with the distance from the soil surface and pit wall. 【Conclusion】 Water storage pit irrigation increased the interface between soil and water, thereby affecting transport of water, heat and oxygen in the soil. Numerical simulations indicated that the dynamics of water, heat and oxygen in the soil was affected by evaporation, rainfall, atmospheric temperature, atmospheric oxygen concentration and other environmental factors.

【Objective】 Turgor pressure in crops varies with root water uptake as a response to occurrence of water stress. This paper investigates how turgor pressure in the leaf of celery responds to drip irrigation and the factors which affect the pressure variation. 【Method】 The experiment was conducted in a greenhouse. It consists of sufficient irrigation (FI) and deficit irrigation (NI) treatment. Change in leave turgor pressure, characterized by expansion parameters Pp and Pp*, in each treatment was measured using a probe. We also measured the environmental factors and physiological traits of the plant, and analyzed their relationship with Pp/Pp* using multiple regression, path analysis and time warping methods. 【Result】 ① The parameter Pp* maximized at daytime and minimized at night on typical sunny days, regardless of the irrigation treatments and growing stage. However, Pp* started to increase earlier in NI than in FI treatment, with the peak of Pp* in the former being 39.3%~66.7% higher than that in the latter. ② The diurnal change in Pp* was similar to that in the stomatal conductance (Gs) and transpiration rate (Tr). Pp* was positively correlated to Gs and Tr, but negatively to leaf water potential (Ψ). ③ The change in leaf turgor pressure varied with irrigation. The maximum and minimum Pp increased gradually priori to irrigation and decreased rapidly after irrigation, especially in the NI treatment where the change was more profound. ④ Pp* was positively correlated to atmospheric temperature (TA) and vapour pressure deficit (VPD), but negatively to relative humidity (RH) and wind speed (WS). Path analysis showed that the highest correlation between Pp* and TA, and VPD was an indirect factor affecting Pp*. Stepwise regression indicated that WS impacted Pp* significantly only in NI. We also found that the impact of TA on Pp* was not instant but existed a delay, especially in NI where the delay was more than 10~30 min than that in FI. 【Conclusion】 Variation in leaf turgor pressure in greenhouse celery was closely related to irrigation amount and meteorological factors. Insufficient irrigation increased the maximum turgor-pressure variation parameter but delayed the effect of atmospheric temperature on the turgor pressure.

Precision irrigation relies on accurate perception of plant water statue. Plant-based sensors is a potential method to online monitor change in plant water statues due to its convenience , automaton and being able to measure water in both leaf stomata and other plant organs simultaneously. Among all available sensor, the non-invasive and in-situ leaf patch clamp pressure probe (LPCP) technology is a promising one as it allows continuous monitoring of plant leaf turgor pressure over at predefined interval. The principle of the LPCP is to measure the attenuated pressure of a leaf patch in response to a constant clamp pressure, and it has become a new versatile method to diagnose plant water status with high precision and sensitivity. LPCP has been applied in plant stomatal physiology to measure water status, and it can also help irrigation scheduling and has thus received increased interest over the recent years. We review in this paper its principle for plant water status diagnosis, installation and derivative parameters selection. Combined with leaf turgor measured by it for celery under drip irrigation, we analyzed the relationship between the change in turgor, environmental factors and plant water physiological parameters to explain the application of the device. We also outlined its pitfalls and the ways to improve it. We concluded that further studies on its application to canopy, predicting the impact of multi-environmental factors and evaluation of multi-source continuous indicators were needed. The research focus should be shifted from exploring the mechanism of plant physiological feedback to developing rational irrigation strategies.

【Background】Tomato is an important economic crop planted widely in both north and south of China. In addition to its effect in antioxidant and anti-cancer, tomato is also nutritious and rich in VC, lycopene and other nutrients. Water and nutrients are two abiotic factors determining tomato growth. Irrational irrigation and fertilization, especially when they are used excessively, not only waste resources and contaminate groundwater, but could also compromise crop yield and quality. Understanding how water and nutrients combine to modulate tomato growth is hence critical to its sustainable production. 【Objective】The overall objective of this paper is to determine the production functions of water and nitrogen of greenhouse tomato in response to water-nitrogen coupling under mulched drip irrigation. We can therefore find its key water-demand stages and provide guidelines for efficient use of water and nitrogen fertilizer in tomato production. 【Method】The experiment considered four factors and three levels, with all designed using the orthogonal test to study how yield of the tomato responds to change in water and nitrogen coupling. The Jensen model was used to describe the change in tomato yield with water and nitrogen applications. 【Result】The tomato yield calculated by the model was consistent with the measurements, with the squared sum of the model fitting residuals being 0.01 and the determination coefficient being 0.793. The root mean square error, average relative error and average absolute error between the calculated and the measured yield were 2.98 t/hm2, 2.53% and 2.39 t/hm2, respectively. The water sensitive index at each growth stage was ranked in the descending order as flowering stage (λ2=0.200) > seedling stage (λ1=0.096) > ripening stage (λ3=0.059). The water sensitive index calculated from the cumulative curve of the water sensitive index agreed well with the estimate from the Jensen model. The factors that impacted tomato yield was ranked in the following descending order based on their significance: irrigation at flowering stage>irrigation at seedling stage>nitrogen application>irrigation at maturity stage, with the effect of irrigation at flowering stage being significant (P

The study delves into the prevailing focal points and developmental trends within the international sphere of crop root research under drip irrigation. It leverages the Web of Science core database and employs VOSviewer for a systematic review of the literature spanning 2001 to 2022. The analysis encompasses publication counts, publishing journals, contributing authors, research institutions, and keywords. Findings indicate that research on root systems under drip irrigation has become a notable area of interest in the field of irrigation, attracting global scholarly attention. There is a marked upward trend in publication output, with institutions in China and the United States taking on central roles. Journals like Agricultural Water Management and Acta Horticulturae are key publication venues, with Vadose Zone Journal being notable for high-impact articles. The research primarily involves agronomy, water resources, and horticulture, focusing on yield enhancement through drip irrigation, root distribution under various techniques, crop quality in response to partial root-zone drying, and irrigation scheduling model development. Scholars like Jiri Simunek and Yaohu Kang have made substantial contributions. The field's established framework calls for continued international collaboration to drive further innovation. The identified trends and parameters can be a valuable reference for researchers, policymakers, and practitioners, guiding efforts to optimize agricultural productivity and resource use. [ABSTRACT FROM AUTHOR]

Hydrological forecasting in semi-arid and semi-arid areas is always the focus problem for hydrologists, and the watershed hydrological model is an effective tool for simulating and forecasting hydrological processes. The double excess watershed model (DEWM) was proposed by the Chinese hydrologists in Shanxi Province and was widely used in local reservoirs. Practical application of reservoirs for many years shows that there exist certain problems in the structure of model. Therefore, we modify the structure from three aspects: 1.Employ new infiltration formulas, 2.Simplify filling container structure and proposes a curve of the underground infiltration capacity, 3.Modify the evaporation simulation. Floods of Zhangfeng reservoir are used to verify the applicability of the modified model (MDEWM). Use the SCE algorithm to calibrate the model parameters, and compare the flow processes of calibration period and validation period with the measured values respectively. The flood peak pass rate are 83.3% and 91.7% in calibration period, and peak current are 50% and 100% in validation period of MDEWM, which results are better than DEWM or equal to it. The research of this article can provide a certain theoretical significance and practical value for flood forecasting, reservoir scheduling and water management in semi-arid and semi-humid areas. [ABSTRACT FROM AUTHOR]

A new algorithm, parameter adaptive DE mixed algorithm, is presented based on the standard differential evolution algorithm. In the process of adjusting the scaling factor and the crossover factor, the comparison judgment of individual fitness is added into the algorithm to improve the convergence speed of the algorithm. At the same time, after the differential evolution algorithm reaches the iterative number, the optimal solution of the differential evolution algorithm is used as the starting point of the trust region reflection to perform secondary optimization andform a mixed differential evolution algorithm finally. Six standard test functions were adopted to test the performance of the parameter adaptive DE mixed algorithm. The test result shows that the new algorithm can greatly improve the convergence of the algorithm. In order to verify the solution quality of the parameter adaptive DE mixed algorithm, 18 historical floods of Zhangfeng Reservoir were taken as study case in this paper, by using this new algorithm and the commonly used SCE-UA algorithm in hydrological model parameters optimization to calibrate the parameters of hydrological model. The results show that the pass rate of the flood peak is 83.3%, and the pass rate of the peak time is 91.7% during the calibrated period, the pass rate of the flood peak and peak time are 66.7% and 83.3% during the tested period by the new algorithm. Compared with the SCE-UA algorithm, the proposed parameter adaptive DE mixed algorithm can more effectively approximate the measured flow process, it indicatesit is feasible that the algorithm can be applied to the parameters calibration of the hydrological model. [ABSTRACT FROM AUTHOR]

The traditional qualitative analysis of the individual factors on the kinetic and thermodynamic parameters cannot sufficiently reveal the mechanism underlying ammonia volatilization in soil. This study aimed to determine the effects of temperature, moisture content, and their interaction on the kinetic and thermodynamic parameters, which revealed the key control mechanism underlying ammonia volatilization, modified the traditional Arrhenius model, and established a quantitative prediction model of cumulative NH3-N loss (CNL). Laboratory culture experiments were conducted under different temperatures (T) (15°C, 20°C, 25°C and 35°C) and moisture contents (θ) (60%, 80%, and 100% field capacities). Soil ammonia volatilization was also measured every 2 d. Results showed that the effects of individual factors and their interaction on the values of reaction rate (KN), Activation free energy (ΔG), and activation entropy (ΔS) followed the descending order of T>θ>T·θ, whereas those of activation enthalpy (ΔH) and activation degree (lgN) followed the descending order of θ>T>T·θ. The interaction showed significant effect on KN value and insignificant effect on all the thermodynamic parameters. The effects of water and temperature were mainly observed during the preparatory stage and the most critical transition state stage of the chemical reaction, respectively. Given that ΔH > 0, ΔG > 0, and ΔS > 0, ammonia volatilization is found to be an endothermic reaction controlled by enthalpy. The new KN(T)-2 model with the determination coefficient (R²) of 0.999 was more accurate than the traditional Arrhenius model with the R² of 0.936. The new NH3(T, θ) model with the mean absolute percentage error (MAPE) of 4.17% was more accurate than the traditional NH3(T) model with the MAPE of 7.11%. These results supplemented the control mechanism underlying ammonia volatilization in soil fertilized with urea and improved the prediction accuracy of CNL. [ABSTRACT FROM AUTHOR]

A field experiment using PVC growth tubes was conducted in the Loess Plateau of China to determine the effective root depth (ERD) of winter wheat and its relationship with root distributions and soil water conditions. The water stable isotopes technique was used to estimate the water uptake contributions of different root depths during the growth stages. On the basis of IsoSource and the Romero-Saltos model, the ERD was 0-40 cm in the majority of the growth stage. However, in the heading and filling stages, the ERD could reach 60%-75% of the maximum root depth. Furthermore, the contributions to water uptake of different root depths were correlated with variations in soil water and root length density (r=0.395 and 0.368, respectively; p<0.05). However, by path analysis, the low decisive coefficient indicated that root distribution and soil water content did not always follow the same trend as water uptake. The conclusions of this study can help with understanding winter wheat water uptake mechanisms in arid and semi-arid regions and increasing water use efficiency. [ABSTRACT FROM AUTHOR]