Abstract:Saline-alkali soils in Xinjiang are extensive and diverse.Reclaiming these soils for agricultural production plays a critical role in safeguarding food security in China.Exploring reclamation technologies that align with the arid environmental nature and modern water-saving irrigation techniques unique in the region is crucial for the sustainable use of these saline-alkali soils.This paper reviews the historical development and effectiveness of various saline-alkali soil management techniques in Xinjiang,based on literature review and quantitative evaluation of available data.We analyze the bottlenecks in managing saline-alkali soils under the constraints of limited water resources,providing insight into comprehensive utilization strategies for saline-alkali soils in the context of new challenges faced by the region.Based on the balance between water and soil resources,as well as the characteristics of secondary soil salinization in irrigated farmland,we propose an integrated'prevention,control,and treatment'strategy for soil management in watersheds and irrigation districts in the region.Our recommendations include determining rational water resource allocation for irrigation and ecological maintenance,identifying effective techniques to desalinate specific soil layers in drip-irrigated farmlands,establishing dynamic monitoring systems to monitor soil salinization,and implementing prevention-control measures tailored to different types of salinized soils in different areas in the region.These provide a guidance for policymaking to improve management and utilization of saline-alkali soils in Xinjiang.

Abstract:[Objective]Reducing chemical fertilizer use while increasing organic fertilization has been proposed as a solution to mitigate nonpoint source pollution and soil degradation caused by chemical fertilizers.This paper presents the results of an experimental study on the effects of this approach on yield,nutrient uptake,and nitrogen use efficiency of maize in dryland areas of Shanxi Province.[Method]The experiment was conducted from 2021 to 2023.The fertilization treatments were:100％of chemical fertilization(NPK),reducing chemical fertilization by 40％,30％and 20％combined with an application of biochar organic manure(SWC40,SWC30,SWC30),or an application of organic manure(JZ40,JZ30,JZ20),respectively.The control was no fertilization(CK).During the experiment,we measured the yield,nutrient uptake and nitrogen utilization efficiency of the crop consecutively for three years.[Result]A rational combination of chemical fertilization reduction and organic fertilization not only significantly increased grain yield and aboveground biomass,but also improved nutrient uptake and accumulation,as well as nitrogen use efficiency.Compared with NPK,SWC40 increased grain yield by 14.69％,9.88％and 25.62％in 2021,2022 and 2023,respectively,while no significant differences in these traits were found between JZ30 and NPK.In 2023,the cumulative uptake of nitrogen,phosphorus,and potassium in the grains in SWC40 were 145.64,38.30 and 38.07 kg/hm2,respectively.Compared with NPK,SWC40 increased cumulative uptake of nitrogen,phosphorus,and potassium in the grains by 38.36％,56.14％and 46.59％,cumulative uptake of N,P and K in the aboveground part by 64.08％,84.32％and 84.43％,reaching 311.79 kg/hm2,69.49 kg/hm2 and 204.22 kg/hm2,respectively.The nitrogen agronomic efficiency,nitrogen partial factor productivity,nitrogen contribution rate and nitrogen apparent utilization rate in SWC40 were 6.80 kg/kg,15.64 kg/kg,43.53％and 31.01％,respectively,significantly higher than those in NPK.[Conclusion]Reducing chemical fertilization combined with an application of biochar or organic manure was more effective in improving maize yield and nutrient accumulation than combined with fine organic manure.In particular,reducing chemical fertilization by 40％combined with biochar organic manure application was most effective,followed by reducing 30％of chemical fertilization combined with fine organic manure application.

Abstract:[Objective]Predicting potential crop yield is critical not only to policy making but also to improving agricultural management to safeguard food production.In this paper,we investigate the feasibility of using unmanned aerial vehicles to predict crop yields.[Method]Spring maize was used as the model plant.The field experiment consisted of five soil moisture treatments by irrigating 50%(W1),75%(W2),100%(W3),125%(W4)and 150%(W5)of estimated evapotranspiration.Multispectral images captured by an unmanned aerial vehicle(UAV)were used to construct the vegetation indices,and the pearson's correlation coefficient method was used to screen the input variables for the yield prediction models.Partial least squares(PLS),random forest regression(RF),and particle swarm optimization(PSO)were used to develop and optimize yield prediction models based on the UAV images obtained at the nodulation,tasseling and filling stages of the maize growth.The grain yield was predicted using both single vegetation index and multi-vegetation indices,with the most accurate model used to generate a yield map of the studied area.[Result]Models using multiple vegetation indices were more accurate than models using single vegetation index.Among all models,the PSO-optimized random forest(PSO-RF)model was most accurate during the tasseling stage.Compared with the measured data,the PSO-RF model based on NDVI achieved an R2 of 0.685,RMSE of 1 792.71 kg/hm2,and RPD of 1.764,when using single index,while when using multi-indices,it achieved an R2 of 0.806,RMSE of 1 485.88 kg/hm2,and RPD of 2.032.The W3 produced the highest grain yield(19 845.25 kg/hm2),while the W1 resulted in the least yield(12 054.52 kg/hm2).[Conclusion]Multispectral UAV imagery combined with PSO-optimized random forest models offers a robust and accurate method for crop yield prediction.This method can serve as a valuable tool to improve agricultural management and optimize resource allocation.

Abstract:[Objective]Microplastics have emerged as a significant contaminant over the past few decades in various ecosystems.While their presence and impacts in other ecosystems have been well documented,their occurrence in soils and potential implications for environmental and ecological functions,as well as food security,remain poorly understood.This paper reviews the occurrence of microplastics in farmlands in China.[Method]The review is based on publications indexed by the Web of Science and CNKI databases.The search results were analyzed using the VOSviewer software,and the microplastics studied in these papers were characterized by their types,abundance,particle diameter,color,and geometric shapes.[Result]The types of microplastics found in farmland soils in China show both similarities and regional variations.Polyethylene and polypropylene,mainly from agricultural use and plastic waste,are the dominant microplastics found across most provinces.Microplastics are most abundant in farmland soils in Inner Mongolia,Xinjiang,Shandong,and Guangxi,with their content exceeding 10 000 particles per kilogram of soil.The diameter of microplastic particles primarily ranges from 0 to 2 mm but varies regionally.For example,in Xinjiang and Guizhou,approximately 85%of microplastic particles have a diameter in the range of 0-0.5 mm and 0-0.1 mm,respectively.Common microplastic colors include transparent,white,black,blue,and yellow,with predominant shapes being fibrous,film,fragment,and foam.Based on these findings,this study proposes strategies for mitigating soil microplastic pollution.[Conclusion]This review provides valuable insights into the occurrence and characteristics of microplastic pollution in farmland soils in China.These findings provide guidance for developing policies and practices to prevent and control soil microplastic pollution to ensure sustainability of agricultural production and environmental health.

Abstract:[Objective]The leaf area index(LAI)is an important trait of plant canopies but challenging to measure accurately at large scales.We studied the feasibility of using multispectral imaging and machine learning to estimate the LAI of spring wheat.[Method]The experiment was conducted in a spring wheat field on the Tumochuan Plain in the Yellow River Basin,Inner Mongolia.Images of the spring wheat at the jointing,booting,and grain-filling stages were acquired using a multispectral camera mounted on a DJI P4M UAV.Selected vegetation indices were subjected to principal component analysis(PCA),and the resulting components were used to estimate LAI.We compared six models:multiple linear regression(MLR),decision tree regression(DTR),backpropagation neural network regression(BPNN),gradient boosting decision tree regression(GBDT),support vector machine regression(SVR),and random forest regression(RFR).LAI was calculated separately for each growth stage using different vegetation indices.[Result]LAI was significantly correlated with the normalized difference vegetation index(NDVI),modified simple ratio(MSR),ratio vegetation index(RVI),difference vegetation index(DVI),soil-adjusted vegetation index(SAVI),and normalized difference red edge index(NDRE).It showed a weak correlation with the renormalized difference vegetation index(RDVI)during the heading and grain-filling stages,with their correlation coefficients being 0.23 and 0.21,respectively.The BPNN model was most accurate during the jointing stage,with R2,RMSE,and MAE being 0.822,0.305,and 0.257,respectively.In contrast,the RFR model performed best during the heading,grain-filling,and entire growth periods,with R2 being 0.613,0.811 and 0.834,RMSE being 0.189,0.150 and 0.174,and MAE being 0.126,0.121 and 0.133,respectively.Additionally,the RFR model constructed using data from all three stages was more accurate than models derived from data at individual growth stages.[Conclusion]Multispectral data acquired via UAV,combined with machine learning algorithms,can accurately estimate the LAI of spring wheat at various growth stages.Models constructed using data from multiple growth stages are more accurate than those based on a single stage.The models are most accurate for the booting stage and least for the heading stage.Overall,the RFR model provided the most accurate LAI estimates across the three growth stages.

Abstract:[Background]Wheat is the second largest cereal crop after rice in China and is largely grown in arid and semiarid regions in the North.Understanding the impact of water stress on its growth and final yield is important to improve its water use efficiency and safeguard wheat production.We studied this in a field experiment.[Method]The experiment was conducted at Wuwei of Gansu province,using the varieties Longchun 41 and Yongliang No.4 as the model plants.This paper aimed to elucidate how water stress imposed in the jointing and grain-filling stages influence growth,physiology and yields of the crops.The control was sufficient irrigation(CK).There were four deficit irrigation treatments:irrigating 65％of water in the CK during both jointing and grain-filling stages(W1),80％during the joint stage and 65％during the grouting stage(W2),65％during the jointing stage and 80％during the grain-filling stage(W3),80％during both jointing and grain-filling stages(W4).In each treatment,we measured growth indexes,grain yield,leaf photosynthetic traits and chlorophyll fluorescence kinetic traits.[Result]Water stress during the jointing and grain-filling stages significantly reduced plant height,leaf area index,dry matter accumulation,net photosynthetic rate,transpiration rate,and photosynthetic electron transport rate.Sufficient irrigation during the tasseling stage can restore the leaf area index(LAI)of the Longchun 41 variety,positively influencing SPAD values,photosynthetic electron transfer,and transpiration.Increasing water deficit led to a reduction in grain yield.On average,the yield of Longchun No.41 was higher than that of Yongliang No.4.The yield of Longchun No.41 in W4 was not significantly different from that in CK.[Conclusion]Considering water saving and grain yield,the optimal irrigation and cultivation for spring wheat in the studied region is to grow the Longchun No.41 variety and irrigate 80％of water used in sufficient irrigation during both the jointing and grain-filling stages.

Abstract:[Objective]Water shortage is a pressing issue in many regions of China,where significant differences exist in agricultural production conditions and efficiency among provinces,municipalities,and autonomous regions.Assessing the agricultural production efficiency of these regions is essential for identifying developmental bottlenecks and devising strategies to enhance both productivity and water use efficiency.[Method]A Data Envelopment Analysis(DEA)model was used to evaluate the comprehensive efficiency,pure technical efficiency,and scale efficiency of agricultural production in 31 provinces,municipalities,and autonomous regions across China from 2004 to 2022.Additionally,the DEA-Malmquist productivity index was applied to analyze the components of efficiency change and the temporal variation characteristics.[Result]The results indicate that,from 2004 to 2022,eight provinces and municipalities achieved DEA efficiency in agricultural production in all years,12 regions were DEA efficient in some years,and 11 provinces and autonomous regions were consistently non-DEA efficient.Despite total factor productivity indices exceeding 1.000 both nationally and regionally,indicating an overall increase in agricultural production efficiency,the technical efficiency,pure technical efficiency,and scale efficiency remained largely unchanged.Technological progress was identified as the primary driver of the observed increase in efficiency.In regions that are non-DEA efficient,such as Hebei and Shanxi,redundant inputs in agricultural water resources and effective irrigated areas suggest that reducing excessive input or reallocating underutilized inputs could enhance production efficiency and the effectiveness of farmland water conservancy investments.Regions with fluctuating pure technical and scale efficiency indices around 1.000 should focus on optimizing production scale and improving the efficiency of existing technologies.Conversely,regions with low technological progress indices,such as Xinjiang and Yunnan,should prioritize technology optimization,adopt water-saving innovations,and enhance farmland water infrastructure.[Conclusion]Our findings reveal significant regional variations in agricultural production efficiency and total factor productivity across China.Strategies for improving these efficiencies are outlined,providing a basis for targeted interventions to enhance agricultural productivity and water use efficiency in water-scarce regions.

Abstract:[Objective]UlanSuhai Lake,a critical surface water body in the Hetao Irrigation District of Inner Mongolia,plays a vital role in supporting various sectors,including agriculture,industry and local livelihoods.Its ecological health has been influenced by diverse biotic and abiotic factors that have shown significant spatial and temporal variations.This paper is to analyze its ecological health and the underling determinants over recent years.[Method]Ecological health of the lake was analyzed using data measured from 2015 to 2019.Key indicators considered include hydrological dynamics,physical,chemical,biological traits of the lake water,as well as social and ecological services the lake provides.The evaluation was calculated using the hierarchical analysis-entropy weight comprehensive health index.[Result]Ecosystem health of the lake showed a notable improvement over the study period.From 2015 to 2016,ecosystem health of the lake was classified as poor,transitioning to moderate from 2017 to 2018,and showing a marked improvement by 2019.Furthermore,the water quality of the lake has consistently improved over the last decade,now reaching Grade V of the national water quality standards.[Conclusion]The hierarchical analysis-entropy weight comprehensive health index method is reliable and practical for evaluating ecological health of lakes,effectively identifying temporal changes and the underlying influencing factors.These findings provide a valuable baseline for guiding protection,management,and sustainable development of UlanSuhai Lake.

Abstract:[Objective]Winter wheat in Northern China is often rotated with other crops which are expected to have a legacy effect.This paper aims to study the effect of different tillage and preceding crops on soil nutrients,yield and water use efficiency of the winter wheat.[Method]The field experiment consisted of a rotary tillage(RT)and a no-tillage(NT).The preceding crops for each tillage were corn(MW)or soybean(SW).During the experiment,we measured the changes in soil nutrients,soil water content,water and fertilizer use efficiency,and yield of the wheat.[Result]For the same preceding crop,non-tillage increased soil water content compared to rotary tillage;under the same tillage,soil water content with maize as the preceding crop was higher than that with soybean as the preceding crop.In all treatments,soil nutrients decreased with soil depth.In the 0-50 cm soil layer,NTSW increased soil organic carbon,soil total nitrogen and nitrate nitrogen by 4.14% -13.54% ,35.51% -54.44% and 55.75% -1 12% ,respectively,compared to the RTMW.RTMW had the highest available phosphorus and potassium in the 10-50 cm soil layer.The RTSW had the highest ammonium nitrogen in the 0-50 cm soil layer,13.39% -20.64% more than that in the RTMW.The winter wheat in NTSW had the highest spike numbers,spikelet numbers,thousand-grain weight;and its grain yield was 16.62% higher than that of RTMW.The NTSW had the highest water use efficiency,8.67% more than that of RTMW.The NTSW had the highest nitrogen,phosphorus and potassium use efficiency.[Conclusion]The NTSW facilitated nutrient accumulation in the winter wheat field.It had the highest water and fertilizer use efficiency and increased grain yields the most as a result.

Abstract:[Objective]Optimizing water distribution in canal-irrigation districts is a prerequisite to improve irrigation water use efficiency.This paper proposes an optimization method to distribute water in two-level canal-irrigation systems.[Method]The method was based on water supply to irrigation districts;it optimizes volume of water distribution,water distribution flow rate and time for each water use unit.We considered two scenarios.The first one was insufficient irrigation where water supply cannot meet water demand during the growing season of crops,in which the model calculated the allocated water for each water user first using water resource allocation coefficient,and then determined the water distribution using the optimal distribution model.The second was sufficient irrigation where water supply meets water demand;we first ranked the priority of the water distribution to each user,and then determined the volume of optimal water flow and timing.The objective of the optimization in both scenarios was to maximize water flow rate and expedite water distribution.The model was applied to the Bojili Irrigation District.[Result]The model can optimally allocate and distribute water across the canal system.When water supply is ample,the model can optimally determine water distribution sequence based on the allocation coefficient.When water is scarce,the model can optimally allocate water to each user based on the distribution coefficient.In both scenarios,water distribution flow rate in the main and branched canals exceed 80％and 75％of the maximum flow limits in the first and second scenarios,respectively.The water distribution period for the first and second scenarios is 10.90 and 17.84 days,respectively.[Conclusion]The model we developed is effective and provides an improved water allocation method for water management in irrigation districts.

Abstract:[Background and Objective]Water erosion is a common form of soil degradation,affecting 1.071 4 million km2 of soil in China,accounting for 40.77％of national soil erosion.While the soil surface in most regions in Northeastern China is relatively flat,the black soils are susceptible to water erosion due to their unique environment and unsustainable agricultural practices,threatening food production and ecological security.Tremendous efforts have been made in improving the black soil and water conservation to ameliorate water erosion.This paper reviews the progress made over the past decades.[Method]The review was based on literature and data related to water erosion in sloped black soils and their mitigation technologies,with the focus on the influence of rainfall,topography,vegetation,soil condition and human activities.[Result]The area of soils affected by water erosion was approximately 133 200 km2,accounting for 63.76％of total eroded black soils in the region.Hillslope and gully erosion are the predominant erosion patterns,forming a hillslope-gully system that is a major source of sediment.Key erosion-control technologies included ridge tillage,straw return,ridge planting,hedgerows,terracing,minimal tillage with residue mulching,no-tillage,and gully control.Critical issues in implementing these technologies include a detailed understanding of their underlying mechanisms,effectiveness,optimal configurations,and selection for different regions.Future research should focus on improving understanding of the mechanisms of these technologies,establishing a comprehensive erosion-control system,and developing strategies for regulating runoff and soil consolidation.[Conclusion]Water erosion is a great challenge in sloped black soil farmland in Northeastern China,influenced by both natural factors and human activities.Significant efforts have been made in alleviating water erosion both theoretically and practically.This review serves as a foundation for advancing research and developing strategies to mitigate water erosion in sloped black soils and similar environments.

Abstract:[Objective]Frequent droughts have significantly impacted agricultural productivity and ecological health of the Loess Plateau.This study investigates the characteristics and driving factors of dry-wet evolution in the region.[Method]The analysis was based on meteorological data,including temperature,precipitation,relative humidity,sunshine hours,and wind speed,measured from 1961 to 2020 at 71 weather stations across the Loess Plateau.The changes in wet and dry spells and their underlying determinants were analyzed using standardized precipitation evapotranspiration index(SPEI),Mann Kendall test,and run length theory.[Result]Temporally,temperature showed a significant increase,while wind speed,relative humidity and sunshine hours showed significant decreases from 1961 to 2020.In contrast,precipitation showed a weak decrease,while ET0(reference crop evapotranspiration)exhibited a first increase followed by a decrease during this period.Spatially,the Northwest saw increased precipitation and decreased ET0.Conversely,the Northeast experienced declines in both precipitation and ET0.From 1999 onward,the SPEI showed an initial decrease followed by an increase.The Southeast experienced high drought frequency but with shorter durations and lower severity,extreme drought events in which were rare.In contrast,the Northwest had fewer but more severe and prolonged droughts.Rising temperatures,increasing precipitation and decreasing ET0 were the primary drivers of dry-wet alterations.ET0 had a stronger influence on dryness and wetness patterns than precipitation.The correlation between the mid-latitude westerly belt,sunspot activity,and SPEI was weak,indicating limited influence of large-scale atmospheric and solar factors.[Conclusion]The Loess Plateau showed a warm-drying trend from 1961 to 1999,followed by a warm-wetting trend thereafter.These findings improve our understanding of hydrological changes and help develop mitigating strategies for managing drought and water resources in the region.

Abstract:[Objective]The ecological functions of the Yellow River Basin have undergone significant changes in recent decades due to both natural and anthropogenic influences.In this paper,we analyze the spatiotemporal variation in habitat quality within the Henan Section of the basin from 1990 to 2020 to help ecological restoration and sustainable development in the region.[Method]Habitat quality was assessed using the habitat quality module in the InVEST model and spatial autocorrelation analysis in GIS.Key determinants of spatiotemporal variation were identified using the Geodetector method.[Result]Over the past 30 years,the study area experienced a marked reduction in cultivated land and grassland,alongside a more than twice increase in construction land.The average habitat quality in the Henan Section was moderate,generally higher in the west and lower in the east.From 1990 to 2020,habitat quality exhibited strong spatial clustering,despite year-to-year fluctuations.Land use type was the primary driver of habitat quality change.Interaction effects between land use and variables such as elevation,temperature,NDVI,slope,precipitation,GDP,and population density all had explanatory power exceeding 0.95.[Conclusion]Habitat quality in most parts of the Henan Section of the Yellow River Basin remained low from 1990 to 2020,with the decline closely linked to the expansion of construction land,particularly in urban areas.Science-based land use planning is essential to improving habitat quality and ensuring ecological sustainability of the region.

Abstract:[Background and Objective]In 2023,Xinjiang initiated a project to cultivate 66 700 hectares of spring soybeans.Due to its arid and semi-arid climate,soybean production in Xinjiang depends heavily on irrigation and fertilization.Understanding the combined effects of water and nitrogen under mulched subsurface drip irrigation is critical for optimizing the use efficiency of these inputs and providing technical guidance for soybean production.[Method]A field experiment was conducted using the soybean variety Yongnong 3 in a split-plot design.The experiment included three irrigation amounts:3 600 m3/hm2(W1),4 500 m3/hm2(W2),and 5 400 m3/hm2(W3).Each irrigation treatment was paired with four nitrogen applications:no nitrogen(N0),138 kg/hm2(N1),207 kg/hm2(N2),and 276 kg/hm2(N3).During the experiment,we measured and analyzed crop growth,yield and grain quality.[Result]① Increasing irrigation amount significantly promoted crop growth.Dry matter accumulation over time followed a logistic growth curve,with rapid accumulation observed between the pod-setting and grain-filling stages.② Irrigation and nitrogen application had significant effects on crop growth and yield components.Dry matter accumulation,yield,and yield components increased with irrigation amount.Among all nitrogen treatments,138 kg/hm2(N1)resulted in the highest dry matter accumulation and yield.③ The highest dry matter accumulation(11 233.53 kg/hm2)and grain yield(5 685 kg/hm2)were achieved with 5 400 m3/hm2 of irrigation(W3)and 138 kg/hm2 of nitrogen application(N1).Compared to W1N0,this combination increased grain yield by 132.04%,pods per plant by 164.57%,grains per plant by 134.13%,grain weight per plant by 227.22%,main stem node count by 25.06%,and 100-grain weight by 24.31%.④ While increasing irrigation did not significantly affect protein and fat content,nitrogen application increased protein content but reduced fat accumulation.[Conclusion]In the arid and semi-arid regions of Xinjiang,effective irrigation and nitrogen management are crucial for optimizing soybean growth and yield.Increasing irrigation amount and applying nitrogen at 138 kg/hm2 can significantly enhance spring soybean productivity,improving sustainable agricultural development and profitability in the region.

Abstract:[Objective]Brackish groundwater can be used as a complementary irrigation resource to safeguard crop production in regions lacking freshwater resources.The purpose of this paper is to study the effect of the salinity of brackish water and soil water content on spatiotemporal variations in soil enzymatic activities,as well as growth and yield of cucumber.[Method]The experiment was conducted in an greenhouse,with the cucumber irrigated by brackish waters with salt concentrations of 5(E1),3.5(E2),2.5(E3),0.5 g/L(E4),respectively.We measured soil matric potential at the depth of 20 cm underneath the drip emitter,such that irrigation was resumed when the matric potential decreased to-15 kPa(L1),-25 kPa(L2)or-35 kPa(L3),respectively.In each treatment,we measured the spatiotemporal changes in activities of urease,alkaline phosphatase and sucrase in the soil,as well as growth and yield of the cucumber.[Result]The activities of all three enzymes decreased vertically with the soil depth and horizontally with the distance from the drip emitters.The three enzymes were most active in the top 0-20 cm soil layer,0-15 cm away horizontally from the drip emitters.Irrigation with water at salt concentration of 0.5-2.5 g/L improved the alkaline phosphatase activity,with limited effect on the activities of urease and sucrase.Increasing water salinity to 3.5-5 g/L suppressed the activities of all three enzymes.With the decrease in soil matric potential used for irrigation control,the activity of sucrase increased steadily,while the activities of urease and alkaline phosphatase increased first followed by a decrease.Irrigation with water at salt concentration of 3.5-5 g/L significantly inhibited the growth and development of the cucumber,while reducing the soil matric potential used for irrigation control to-35--25 kPa improved the cucumber growth and yield.[Conclusion]Irrigating greenhouse cucumber using brackish water with salt concentration of 0.5-2.5 g/L and resuming irrigation whenever the soil matric potential at the depth of 20 cm underneath the drip emitters decreased to-35--25 kPa can improve cucumber production without resulting in noticeable soil quality deterioration.

Abstract:The rapid advancement in science,technology,and information over the past decades has led to a wide application of intelligent irrigation technologies worldwide.Using the multi-faceted approach,we analyze the past trajectory and future perspective of intelligent irrigation technologies by depth-examination of theoretical and engineering research as well as the granted patent applications over the past decades.The data used in the analysis were based on the publications indexed by Science Citation Index of Web of Science and Engineering Index(EI)of Scopus,as well as granted patents indexed in Derwent Innovations.This paper focused on performance index,competitiveness,research hotspots,and developing trend of intelligent irrigation.The results show that intelligent irrigation has well steadily established worldwide in terms of its perception,control,decision-making and management.In addition,six research areas have emerged over the past decades:irrigation technologies under drought stress,field experiments and water and fertilizer use efficiency,monitoring soil and water,intelligent irrigation systems,sustainable development and water-saving irrigation,and water balance and irrigation water management.Technologically,there are two active research areas in intelligent irrigation:real-time irrigation control and developing water-saving intelligent irrigation devices.Looking ahead,research in intelligent irrigation is expected to be in sustainability and scalability,as well as its combinations with other technologies.It has potential to safeguard food security and revitalize rural regions worldwide.

Abstract:[Objective]Forage maize is a crop cultivated in the Yinda Irrigation District in Gansu province,China.This paper investigates the influence of planting density on its growth,yield and quality.[Method]The variety of Long Silage No.1 was used as the model plant.The field experiments compared five planting densities:5.6x 104 plants/hm2(M1),6.8×104 plants/hm2(M2),8.0×104 plants/hm2(M3),9.2×104 plants/hm2(M4),and 10.4×104 plants/hm2(M5).In each treatment,we measured plant traits,yield and quality of the plant at its maturity stage.[Result]① Plant height and stem thickness both varied with planting density parabolically.With the increase in planting density,cob length,cob thickness,fresh cob weight,the number of rows of grains and the number of rows in cobs all increased first and then decreased when planting density exceeded 8.0×104 plants/hm2.② With the increase in planting density,fresh grass,hay and kernel yields increased to 182 146.72 kg/hm2,91 054.35 kg/hm2,and 24 278.68 kg/hm2,respectively,when planting density was 8.0× 104 plants/hm2,and then decreased after planting density exceeded 8.0×104 plants/hm2.③ Compared with M4 and M5,M3 increased the crude protein by 8.31％and 12.49％,the crude starch by 10.58％and 15.71％,and the fat contents by 10.38 and 19.71％,respectively.It was found that the neutral washing fiber was the highest in M5 and the least in M3.Compared to M3,M5 increased the neutral detergent fiber by 7.78％.[Conclusion]A planting density of 8.0×104 plants/hm2 is optimal for yield and quality of forage maize cultivated in the Yinda Irrigation District.

Abstract:[Objective]Mulched drip irrigation is a widely used technique in Northwestern China.This paper investigates the combined effects of mulched drip irrigation and nitrogen fertilization on the growth and yield of summer maize.[Method]The experiment was conducted in a maize field in Southern Xinjiang and included a mulched drip irrigation(MD)treatment and a conventional drip irrigation treatment without mulching(LD).Each irrigation treatment had five nitrogen applications:0 kg/hm2(N0),224.6 kg/hm2(N1),278.4 kg/hm2(N2),368.9 kg/hm2(N3),and 464.0 kg/hm2(N4).The control was flood irrigation with a nitrogen application of 278.4 kg/hm2.For each treatment,we measured growth traits and grain yield of the maize.[Result]① With increasing nitrogen application,the SPAD value,leaf area index(LAI),and aboveground dry biomass initially increased before plateauing;these metrics were 18.67％,10.39％,and 10.41％higher in the MD treatment compared to the LD treatment,respectively.② The relationship between dry matter accumulation and nitrogen application fit a logistic model,with the accumulation plateauing when the nitrogen application was 368.9 kg/hm2.Compared to LD,MD prolonged the period of rapid growth by 7-18 days and delayed its onset by 1-6 days.③ The yield in the MD treatment was 1 027.52-2 023.04 kg/hm2 higher than that in LD;nitrogen application increased grain yield by 29.41％-84.46％.The combination of MD and nitrogen application increased yield by 52.17％-106.61％.Nonlinear regression indicated an asymptotic increase in maize yield with nitrogen application.The grain yield in MD and LD plateaued to 362.75 kg/hm2 and 364.14 kg/hm2,when their associated nitrogen application exceeded 267.69 kg/hm2 and 274.11 kg/hm2,respectively.④ In both irrigation treatments,applying 278.4 kg/hm2 of nitrogen fertilizer produced yields comparable to the control,while saving 256.5 mm of water.[Conclusion]Mulched drip irrigation combined with a nitrogen application of 278.4 kg/hm2 is optimal for promoting the growth and yield of summer maize in Southern Xinjiang.

Abstract:[Objective]The Huaibei Plain in central China is a major agricultural production area where winter wheat often experiences drought during its growing season.This study analyses the spatiotemporal variation in drought during the winter wheat growing season in this region.[Method]The analysis was based on meteorological data measured from 1957 to 2018.We used the crop water deficit index(CWDI)during the wheat growing season as a proxy for drought,analysing its inter-annual variation,spatial distribution,fluctuation patterns,occurrence rates,and spatial frequency distribution across different areas in the region.[Result]① Throughout the wheat growing season,ten-day water demand and water supply both showed an initial decrease followed by an increase.Effective precipitation per ten-day period was less than 10 mm,while soil-surface evaporation increased by 260％from mid-March to late May.② During the growing season,water supply and demand were balanced in Fuyang,Bengbu,and Mengcheng,but not in Dangshan,Bozhou,and Suzhou.Suzhou had the greatest fluctuation in CWDI,while Bengbu had the least.③ From 1957 to 2018,drought occurrence during the winter wheat growing season increased by approximately 1.5 times,with 2010 experiencing the most widespread and severe droughts.④ Spatially,drought severity increased from the South to the North,with Dangshan,characterized by fluvo-aquic soil,experiencing more severe droughts than areas with Shajiang Mollisol.Over time,the center with high-frequency of moderate drought shifted northward toward Bozhou and Suzhou.Extreme droughts were rare in this region.[Conclusion]Drought severity during the winter wheat growing season in the Huaibei Plain has increased from 1957 to 2018.Water supply and demand are imbalanced in regions such as Dangshan and Suzhou,where supplemental irrigation is needed.

Abstract:[Background and Objective]The Yellow River Basin is the second largest river basin in China.Over the past 60 years,precipitation patterns in the basin have undergone both spatial and temporal changes due to the impact of climate change.This paper analyzes the precipitation characteristics and spatiotemporal alterations in dry-wet patterns in the basin.[Method]The study was based on meteorological data measured from 1960 to 2022 at weather stations across the basin.Spatiotemporal changes in precipitation,dry and wet spells were analyzed using regression analysis,correlation analysis,frequency percentage method,and the Mann-Kendall nonparametric statistical method.[Result]① No significant change in total annual precipitation was identified in the basin from 1960 to 2022.However,a notable decrease in annual precipitation events(-1.95%per decade)and a significant increase in average precipitation intensity(+2.67%per decade)were observed.A sudden change in annual precipitation frequency occurred in 1978,while a shift in precipitation intensity happened in 1990.Since 1990,annual precipitation frequency has decreased markedly,while precipitation intensity has increased significantly.Regionally,the upper basin has become wetter,while the middle and lower reaches of the basin have become drier.Across the basin,light,moderate and medium-intensive rainfall events have declined,while heavy and extreme rainfall events have increased.Extreme rainfall event have become increasingly common,particularly in the middle and lower reaches of the basin.② The risk of drought has increased in the upper and middle reaches of the basin,although drought intensity has decreased.Meanwhile,the likelihood and severity of drought in the lower reach has risen.Wet spells have shown heightened precipitation intensity during the wet season,corresponding to an increase in extreme precipitation events across the basin.The coexistence of drought and flooding highlights vulnerability of the basin to extreme weather events.③ Changes in annual precipitation are primarily driven by intensive precipitation events,while changes in precipitation frequency ware influenced by low-intensive precipitation events.The distribution of wet days is affected by low-intensive precipitation,whereas wet-season precipitation is driven by high-intensive precipitation events.[Conclusion]In the context of climate change,the Yellow River Basin is increasingly vulnerable to both droughts and floods.The reduction in low-intensive precipitation events has prolonged dry periods,increasing drought risk.Simultaneously,the increase in precipitation intensity and extreme events during wet seasons raises flood risk.These findings underscore the urgent need for developing integrated water resource managements and new strategies to mitigate the impact of climate change.