Carbon flux changes in farmland ecosystems are mainly caused by crop photosynthesis and respiration in farmland. Accurate assessment of carbon emissions generated from the respiration of maize farmland ecosystems is significant for studying global carbon fluxes in terrestrial ecosystems. This study collected eddy covariance, soil moisture, and air temperature measurements from November 2020 to October 2021 in the maize farmland ecosystem, which is located in Dashanchuan Village, Huining County, Gansu Province. We analyzed the variation of daily ecosystem respiration rate (Reco) and monthly respiratory sensitivity index, explored the response of Reco to temperature, and evaluated different models for Reco simulation. The results showed that the carbon emission rate of maize farmland ecosystem in the semi-arid region was unimodal, and the average daily maximum respiration rate was 11.49 μmol m^-2·s^-1. Compared with the response of respiration rate to air temperature (T_a ) and soil temperature (T_s ) at different depths, soil temperature (T_{s 20}) at 20cm depth has the best year-round fitting effect on Reco in this region. Q₁₀ showed unimodal changes during the growing season, with the maximum value occurring in August (5.52 μmol·m^-2·s^-1). By fitting each model, the annual respiratory carbon emission of maize farmland ecosystem in the Longzhong region ranged from 863.71 to 990.18 g C m^-2. The model that exhibited the most effective fitting (Q ₁₀ model) was chosen. After the Q ₁₀ model was optimized considering the parameter time-variability, the fitting accuracy of the Q ₁₀ model was greatly improved, and the estimated annual carbon emission value increased from 868.57 g C·m^-2 to 1094.48 g C·m^-2, which was closer to the observed value (1 110.28 g C·m^-2). Reco was inhibited when soil moisture was lower than 0.16 m³·m^-3 (during December to February).

Greenhouse can effectively improve the growth process of Solanaceae crops, (including tomato, pepper, eggplant, etc.). Greenhouse environmental control strategy is very important for crops to achieve high efficiency and yield. To make full use of the research achievements at home and abroad and promote the research application of greenhouse control strategy in China, this paper summarizes the research progress of greenhouse environmental control strategies from five aspects: conventional proportional integral derivative control, fuzzy control, artificial intelligence control, greenhouse microclimate model, and crop growth model. Given the problems existing in this field in China, it is suggested to integrate intelligent greenhouse control with a crop growth model, creating an intelligent crop growth model. Additionally, the incorporation of remote sensing technology is recommended for predicting crops in diverse regions. This approach aims to bolster the universality of the model and form a greenhouse environment control strategy with distinctive Chinese characteristics.

In order to investigate the effects of different radios of brackish water (farmland drainage) to fresh water in a "saline first, then fresh" combined irrigation mode on soil bulk density, salt migration, and cotton growth. With fresh water irrigation as control (CK), we established 7 different irrigation treatments combining brackish water and fresh water. The radios of brackish water to fresh water were set as follows: 1∶14 (T1), 2∶13 (T2), 3∶12 (T3), 6∶9 (T4), 9∶6 (T5), 12∶3 (T6). Additionally, the T7 treatment received irrigation with full brackish water. Cotton field trials were conducted from April to September 2022. The results showed that salt accumulation occurred in the soil layer of 0~40 cm due to brackish water irrigation. After the growth period, compared with the fresh water control (CK), the electrical conductivity of T1~T6 in 0~40 cm soil layer increased by 1.16% to 26.61%, while the T7 treatment experienced a substantial increase of 86.40%. Compared with the fresh water control, the bulk density of 0~40 cm soil layer in the combined irrigation increased significantly and the soil porosity decreased, and the bulk density increased by 10.24% in theT7 treatment. Brackish water combined irrigation can effectively improve cotton plant height, leaf area index, and stem diameter. Rational utilization of brackish water combined irrigation can provide a good water-salt environment for cotton growth, improve cotton yield, provide a new irrigation model for rational utilization of brackish water in extreme arid areas, and provide theoretical support for the development of water-saving irrigation and sustainable agricultural development in irrigation areas.

To further improve the accuracy of estimating regional reference crop evapotranspiration (ET ₀) by Penman-Monteith model, we focused on the main grain producing areas in China. The region was stratified into temperate humid and semi-humid areas (THSZ), temperate arid and semi-arid areas (TASZ), warm temperate and semi-humid areas (WTSZ), and subtropical humid areas (SHZ). Based on the daily meteorological data from 32 meteorological stations spanning the period from 1994 to 2020, a time Convolutional neural network model (TCN) optimized by Cheetah algorithm (CO), Sand Cat algorithm (SCSO) and Wild dog algorithm (DOA) were employed. Additionally, radiation (R_s ) values estimated by 3 kinds of sunshine hours empirical models and 3 kinds of temperature empirical models were merged with the PM model to get an improved PM model. Root mean square error (RMSE), determination coefficient (R ²), mean absolute error (MAE), and efficiency coefficient (E_NS ) were used as precision evaluation systems. The results showed that: the calculation accuracy of the sunshine hours models was better than that of the temperature models. The CO-TCN models showed the highest accuracy in the whole region. The median values of RMSE, MAE, R ², and E_NS in different partitions are 0.099~0.171 mm/d, 0.057~0.111 mm/d, 0.984~0.998, and 0.983~0.997, respectively. The radiation values estimated by the CO-TCN model can be integrated with the PM model as standard values for estimating ET₀ in the main grain-producing areas.

In view of the characteristics of drought-prone and severe drought in Yunnan Province, this paper selects typical hydrological drought years and drought events in the historical period from January 1981 to June 2020, and explores the applicability of GRACE satellite inversion data in monitoring drought in Yunnan Province. The purpose of this paper is to propose a new method to solve the difficulty of drought monitoring in areas with no or less data. Based on the GRACE gravity satellite data inversion, the monthly average water storage changes in five sub-regions of central Yunnan, northeastern Yunnan, southeastern Yunnan, southwestern Yunnan, and northwestern Yunnan were obtained, and the drought and flood index-relative water storage index of each sub-region was calculated. The relative water storage index was used to analyze the drought situation in each sub-region of Yunnan Province, and the drought analysis conclusions of the relative water storage index and the standard precipitation evapotranspiration index SPEI3 were compared from the monthly time scale. The results show that the monitoring results of the relative water storage index based on GRACE gravity satellite data inversion in typical hydrological drought years are basically consistent with the actual drought conditions, and its applicability in central Yunnan is the best. The monitoring accuracy of spring drought is better than that of other seasons, and the inversion data can reflect the drought degree of different regions and seasons in Yunnan Province to a certain extent. Using SPEI3 to monitor the drought in Yunnan Province and different regions, the results are in good agreement with the drought events recorded in the statistical yearbook. The monitoring accuracy in southeastern Yunnan is better than that in other regions, and the accuracy in summer and winter is better than that in spring. Both GRACE and SPEI3 well captured the typical drought years and drought events in the historical period. Among the selected 24 typical drought events, the highest coincidence rate in each partition reached 15/24. Compared with GRACE, SPEI3 is less prone to underreporting. In general, the underreporting rates of the two indices in each sub-region are maintained at a low level, with a maximum of no more than 1/3. Among them, SPEI3 is less likely to be underreported than GRACE, and its minimum underreporting rate is only 1/8. Both indices show good applicability in drought monitoring in the province and each sub-region.

Evapotranspiration plays a vital role in the hydrological cycle, holding significant importance in the analysis of actual evapotranspiration and its influencing factors within irrigation areas. This analysis is crucial for the efficient utilization of water resources and the high-quality development of agriculture. However, the current approach often involves the use of traditional statistical methods that exhibit limited explanatory power in identifying the main factors of evapotranspiration. Furthermore, these methods tend to overlook the spatial correlation between evapotranspiration and its influencing factors during correlation analysis. Therefore, this paper uses the improved random forest model to determine the main influencing factors of actual evapotranspiration and explores the temporal and spatial correlation between actual evapotranspiration and its influencing factors through ridge regression model and geographically weighted regression model. The results show that: ①During the irrigation period, net surface radiation, average air temperature, leaf area index, and actual water vapor pressure are the main influencing factors of actual evapotranspiration; In the non-irrigation period, the net surface radiation, average temperature, wind speed and sunshine time are the main influencing factors of actual evapotranspiration. Actual evapotranspiration serves as a representative measure of crop water consumption within the irrigation area to some extent. Therefore, the influence of crop water consumption in irrigation areas is different between the irrigation period and the non-irrigation period. ②Over time, there is a negative correlation between wind speed and actual evapotranspiration (P<0.05), and other influencing factors exhibit a positive correlation with actual evapotranspiration (P< 0.05). Spatially, apart from the negative correlation between wind speed and actual evapotranspiration in most areas, other influencing factors demonstrate a positive correlation with actual evapotranspiration in most areas. Therefore, excluding wind speed, other influencing factors have a positive effect on crop water consumption in most areas.

In order to promote the application of Straw-based composite pipe Subsurface Irrigation (SSI) technology, a field experiment was conducted to investigate the impact of SSI on the growth and water use efficiency of winter wheat. The experiment involved a comparison of surface drip irrigation (DI), subsurface drip irrigation (SDI) and no irrigation (CK) . The results showed that compared with the CK, SSI, DI, and SDI all have promoting effect on the growth and yield of winter wheat, and the improvement effect of SSI is the most significant. Compared with DI, SSI significantly improved the plant height, leaf area index, and dry matter yield of winter wheat from the starting stage to the heading stage; The ear length and grain number per spike increased by 5.84% and 9.23%, respectively. The yield increased by 15.55%. The water use efficiency and irrigation water use efficiency increased by 21.88% and 15.55%, respectively. The net income increased by 73.79%. Compared with SDI, SSI improved the plant height, leaf area index, and dry matter yield of winter wheat after the turning green period; The ear length and grain number per spike significantly increased by 5.15% and 9.8%, respectively. The yield increased by 5.11%. The water use efficiency and irrigation water use efficiency increased by 8.81% and 5.11%, respectively. The net income increased by 31.38%. In summary, Straw-based Composite Pipe Subsurface Irrigation (SSI) demonstrates the capability to enhance the growth of winter wheat after the jointing stage, improve its yield and water use efficiency, thereby yielding higher economic benefits. SSI has good prospect in supplementary irrigation areas for densely planted crops.

In order to clarify the water physiological characteristics of the differences in quality formation of alfalfa and to explore irrigation models that are suitable for the local conditions and water-saving and efficient, this article takes the Hexi region as an example. It conducts a comparative analysis of three different irrigation treatments, including conventional border irrigation (M), alternating irrigation (T), and furrow irrigation (G), with no irrigation (CK) as a control. The study aims to assess the effect of different irrigation quantities on the yield and quality of "San Deli" alfalfa, focusing on returning green water and budding water. The results are as follows: ①There is a positive correlation between plant height and irrigation frequency under different irrigation methods, and a negative correlation between branch number and irrigation amount; Under alternating irrigation conditions, the highest average plant height among the three crops reaches 91.92 cm when considering factors such as soil moisture, overwintering water, returning green water, and budding water. ②Under various irrigation modes, the net photosynthetic rate and transpiration rate of alfalfa showed an increasing trend with the increase of irrigation water. Among them, the net photosynthetic rate of alternating irrigation increases by 15.64% with the increase in irrigation quantity, and both are higher than the net photosynthetic rate of conventional border irrigation and furrow irrigation under the same irrigation amount. ③The yield of alfalfa under different treatments increases with the increase of irrigation water. The total yield of alfalfa under flood irrigation treatment is significantly higher than that under alternative irrigation and furrow irrigation under the same irrigation amount. The maximum total yield of alfalfa under the conditions of bottom soil moisture, overwintering water, returning green water, and budding water is 49 447.6 kg/hm². ④ The crude protein content and neutral detergent fiber content of alfalfa under different irrigation treatments are significantly higher than those under non-irrigation (CK) treatment, and they increase to varying degrees with the increase of irrigation amount. The Hexi region is located in arid and semi-arid regions. From the perspective of water-saving irrigation, the alternative irrigation mode of bottom soil moisture, overwintering water, returning green water, and budding water can be chosen to achieve water-saving while ensuring high yield.

To investigate the hydraulic performance of refractive micro sprinklers and determine their suitable working parameters, the hydraulic performance test of micro sprinklers is carried out to clarify the characteristics of water distribution of individual micro sprinklers under different working conditions and the trend of its flow rate, range, and sprinkler intensity with the change of working pressure and nozzle diameter is analyzed. Under the combination of square and triangle, the influence of working pressure and combination spacing on the uniformity coefficient of sprinkler irrigation CU is investigated. Based on the principal component analysis method, the relevant evaluation indexes are unified to establish a comprehensive evaluation model of refractive micro-sprinkler nozzle working parameters. The results show that: The flow rate of a single sprinkler head, sprinkler irrigation intensity show a positive correlation with the working pressure. However, the impact on the range is not obvious with changes in pressure. The variations in the Coefficient of Uniformity (CU) due to changes in spacing are significantly greater in the case of square and triangular combinations compared to alterations in working pressure and the method of combination. Considering the scores assigned to each condition, the optimal selection for the micro-sprinkler head is determined. The application example results indicate that the ideal working conditions for the refractive micro-spray nozzle involve a positive triangular combination, a working pressure of 0.25 MPa, and a combination spacing of 0.4 m.

To investigate the impact of drip fertigation frequency on growth, N utilization, yield, and quality of flue-cured tobacco, field experiments were conducted. Five treatments were employed: No fertilization (CK), local conventional treatment (CF), DF1 (one time fertigation during each fertilization stage), DF2 (one time fertigation a day for 2 days during each fertilization stage) and DF3 (one time fertigation a day for 3 days during each fertilization stage) over two consecutive years of 2018-2019. The results showed that, compared to CF, each drip fertigation treatment observed equivalent tobacco yield compared to CF (P＜0.05 ). Additionally, there were relatively higher NUE observed across all drip fertigation treatments. However, the performance of tobacco growth varied, contingent upon the specific drip fertigation frequency. As compared with those of DF1 and DF2, the leaf area index at the flourishing stage increased by 7.3%~33.3% and 1.6%~28.7%, respectively, root volume increased by 3.9%~46.6% and 21.2%~40.5%, respectively, the NUE increased by 39.0%~95.0% and 21.5%~34.3%, respectively, leaf nicotine content increased by 17.5%~28.5% and 12.5%~20.0%, respectively. In contrast to middle and low drip fertigation frequency, a high drip fertigation frequency was found to be advantageous for tobacco growth. It facilitated the formation of a good root morphology, improvement in NUE, and promotion of both tobacco leaf yield and quality. This suggests that employing a high drip fertigation frequency is an effective measure to harmonize the efficient utilization of nitrogen fertilizer with the enhancement of tobacco leaf yield and quality.

Drought is one of the important restrictions to agriculture development all over the world, which seriously threatens national food security and ecological sustainable development. Biochar is a kind of biomass regeneration product and it is rich in carbon. As an outstanding soil amendment, it can not only improve the physical and chemical structure of soil, improve the soil water retention, but also alleviate the negative effects of drought stress on crops. This study reviewed the research achievements of biochar in alleviating crop drought stress, including promoting crop growth and development, enhancing crop resistance to drought, improving soil physicochemical and microbiological characteristics, and so on. Moreover, it focused on elucidating the relationship and key mechanisms between biochar characteristics and its role on alleviating drought stress. Finally, it discussed the differences of research at home and abroad as well as areas that need to be strengthened, and also looked forward to the future potential of biochar application in alleviating drought stress, thereby providing theoretical basis and reference for the further promotion and application of biochar.

To investigate the spatial distribution of soil pH, salinity, fast-acting nutrients, and trace elements in the Korla pear orchard, and to comprehend the comprehensive fertility level of balsam pear orchards, this paper designates the Korla fragrant pear planting area as its study domain. A total of 50 representative Korla fragrant pear orchards are selected for the deployment of sample point and subsequent soil sample collection. Classical and geostatistical methods are used to study the spatial variability of soil nutrient and trace element indicators in the top layer (0-40 cm) of pear orchards, and the soil fertility status of pear orchards are investigated as well. In classical statistical analysis, it is observed that the coefficient of variation for pH is 0.02, indicating a weak variation. Conversely, the coefficient of variation for conductivity is 1.03, showing strong variability. The coefficients of variation for organic matter, alkali-dissolved nitrogen, fast-acting phosphorus, fast-acting potassium, effective manganese, effective copper, effective zinc, and effective iron are 0.37, 0.53, 0.99, 0.59, 0.45, 0.25, 0.24, and 0.48, respectively, suggesting a moderate degree of variability in these parameters. The integrated soil fertility index (IFI) values within the study area range from 0.37 to 0.80, with a mean value of 0.58. Geostatistical analysis shows that the nugget coefficients for soil organic matter, alkaline dissolved nitrogen, and fast-acting potassium are all greater than 75%, indicating a weak spatial autocorrelation for these parameters. The nugget gold coefficients for pH, conductivity, fast-acting phosphorus, effective manganese, effective copper, effective zinc, and effective iron are all in the range of 25%~75%, suggesting moderately strong spatial autocorrelation for these metrics. The proportion of Ⅰ (Optimal), Ⅱ (Well), Ⅲ (Medium), Ⅳ (Poor) and Ⅴ (Worse) soils in Korla pear orchards are 2.72%, 10.54%, 61.80%, 24.87%, and 2.77%, respectively. The spatial distribution of integrated soil fertility exhibits a patchy pattern. The more fertile class I is dispersed in the northern region, while Class II shows a patchy distribution in both the northern and western areas. Class III is mainly located in both the northern and southern area. The less fertile classes IV and V are mainly concentrated in the central area. Overall, the soil fertility of balsam pear orchards in Korla City is of medium level. Soil properties are more spatially heterogeneous. Effective manganese and effective iron are the major limiting factors for soil fertility. Orchards should be managed differently. Orchards should be supplemented with manganese, and iron micronutrient fertilizer, and the central region should also focus on supplementing nitrogen fertilizer, phosphate fertilizer, and organic fertilizer.

To address the challenge of multiple scattering between the canopy and the surface during soil moisture retrieval using drone remote sensing under high corn plant height (>1.5 m), we searched for an appropriate retrieval method. In this study, we used fused unmanned aerial vehicle (UAV) multispectral and thermal infrared data, Sentinel-1A synthetic aperture radar (SAR) satellite data, and field-measured data to investigate the soil moisture retrieval and accuracy verification under vegetation coverage. We employed three methods: temperature vegetation drought index (TVDI), water cloud model (WCM), and an improved WCM method that introduces MIMICS model parameters. The TVDI method had a retrieval accuracy of R ² = 0.50 (10 cm) and 0.42 (20 cm) during the jointing stage period, and R ² = 0.49 (10 cm) and 0.46 (20 cm) during the milk-ripe period. The WCM method had a retrieval accuracy of R ² = 0.53 (10 cm) and 0.44 (20 cm) during the jointing stage period, and R ² = 0.18 (10 cm) and 0.02 (20 cm) during the milk-ripe period. The improved WCM method had a retrieval accuracy of R ² = 0.76 (10 cm) and 0.69 (20 cm) during the jointing stage period, and R ² = 0.78 (10 cm) and 0.74 (20 cm) during the milk-ripe period. The improved WCM method using MIMICS model parameters outperformed both the WCM method and the TVDI method in both growth stages. The retrieval accuracy of all three methods was higher at 10 cm than at 20 cm in both growth stages. Therefore, the improved WCM method with MIMICS model parameters is more suitable for soil moisture retrieval at a depth of 10 cm under high corn plant height conditions.

Sugarcane, a major crop in Guangxi and Yunnan, is highly susceptible to drought. Soil moisture content is an important indicator for assessing the impact of drought on sugarcane. In this study, the focus of the research was the soil moisture content in sugarcane fields, and unmanned aerial vehicle (UAV) thermal infrared and multispectral sensor data were used to calculate temperature and RDVI vegetation indices for the sugarcane canopy. The UAV monitoring data were calibrated and validated using a method of manual measurement, and a temperature vegetation drought index (TVDI) model for sugarcane was developed. The results showed that TVDI calculated using multispectral and thermal infrared sensors had a high correlation with soil moisture content during the seedling, tillering, elongation, and mature stages of sugarcane, with determination coefficients (R ²) of 0.906 6, 0.819 0, 0.852 9, and 0.916 0, respectively. Therefore, the TVDI model proves to be the most suitable for monitoring drought in both seedlings and mature stages of sugarcane.

The spatial and temporal distribution of crop water demand is the basis for the scientific formulation of irrigation water quotas in different regions. As an important commercial grain base in China, Heilongjiang Province has been ranked in the middle of the country in terms of irrigation water use efficiency for many years. Therefore, it is of great significance to reasonably calculate and analyse crop water demand to improve irrigation water use efficiency and grain yield. Based on the meteorological data of 28 stations in Heilongjiang Province from 1961 to 2020, we employed the Penman-Monteith formula recommended by FAO. Our analysis focused on three key perspectives: annual water demand of maize, water demand of each fertility period, and water demand of each fertility period in different eras. We utilized statistical methods, including the Mann-Kendall test, the sliding t-test, and the climatic tendency rate, to identify trends, mutations, and other characteristics. Spatial distribution maps were created using ArcGIS to study the spatial-temporal evolution of the water demand of maize at each fertility period in depth. The results showed that, over the past 60 years, the average annual water demand of maize in Heilongjiang Province stood at 477.47 mm. The climatic tendency rate ranged between -23.11 and 5.62 mm/(10 a), indicating an overall decreasing trend in the annual demand. Notably, there was a sequence mutated in 2008. The average value of water demand of maize in each fertility period in the past 60 years was 13.96, 77.72, 74.64, 44.60, 204.46, and 62.38 mm, and its sequence mutated at different points; the maximum value of water demand of maize in each fertility period mainly appeared in the 1970s, and its sequence mutated at different points. The average values of water demand in each fertility period of maize in the past 60 years were 13.96, 77.72, 74.64, 44.60, 204.46, and 62.38 mm, with different points of sequence mutation; the maximum values of water demand in each fertility period of maize mainly appeared in the 1970s, and the minimum values appeared in the early2000s and 2010s; the maximum upward trend of water demand in each fertility period mainly appeared in the 1970s and 1990s, and the maximum downward trend appeared in the 1970s and 1990s. The greatest upward trend of water demand in each fertility period occurred mainly in the 1970s and 1990s, whereas the greatest downward trend occurred mainly in the early 2000s. The water demand of maize from different perspectives showed a general trend of decreasing and then increasing from west to east, in which the staminate-milk ripening period is the critical period of maize water demand.

Clarifying the spatio-temporal characteristics of the irrigation water requirements in Yuncheng will provide basic parameters for the scientific allocation of irrigation water requirements of this city in the future. Based on the long-term observation data of 13 meteorological stations in Yuncheng, the reference crop water requirement was determined by Penman-Monteith formula. Combined with the parameters of effective rainfall and crop coefficient, the irrigation water requirement of winter wheat and summer maize in Yuncheng in the past 50 years and its spatio-temporal variation were calculated and analyzed. During the investigated period, the annual irrigation water requirements for winter wheat and summer maize experienced a trend of fluctuation reduction, with change rates of -0.7 and -2.1 mm/(10 a), respectively. Winter wheat has higher irrigation water requirements in April and May, reaching 80.5 mm and 108.4 mm, respectively. In contrast, for summer maize, the peak irrigation water requirements occurs in August, approximately 85.3 mm. The spatial characteristics of average irrigation water requirements for winter wheat and summer maize show a gradual increase from east to west. The range of spatial irrigation water requirements is 283.6~336.8 mm for winter wheat, while it is only 165.4~253.9 mm for summer maize. The result of correlation analysis indicates that vapor pressure deficit and solar radiation have a significant influence on the irrigation water requirements of winter wheat and summer maize in Yuncheng. The irrigation water requirements for winter wheat and summer maize in Yuncheng have shown a fluctuating decreasing trend, it increases from east to west. The fluctuations in temperature and precipitation indicate a trend of warming and humidification in the climate in Yuncheng. This evolving climate scenario should be thoroughly taken into account when formulation and optimization of irrigation schemes in the future.