Prediction of Maize Yield and Its Component Factors in Yellow River Irrigation Area of Ningxia under Climate Change

[Objective] The aim was to quantitatively predict the variation trend of maize yield in Yellow River irrigation area of Ningxia under future climate change scenarios.[Method] Based on the data of daily temperature,precipitation and radiation in 25 km × 25 km grid in Ningxia from 2010 to 2100 obtained by regional climate model,maize yield in Yellow River irrigation area of Ningxia in the 21st century was studied by means of corrected CERES-Maize model.[Result] With climate warming,maize yield in Yellow River irrigation area of Ningxia in 2020s and 2050s showed increase trend compared with base years（average in 1961-1990）when current adaptive maize variety and optimum production management measures were adopted,while maize yield went down in 2080s with the further increase of temperature.The grain number per spike and spike grain weight as the yield components of maize also showed the same trend with maize yield.In 2020s and 2050s,the increase of maize yield under B2 scenario was higher than that under A2 scenario,while the decrease of maize yield under B2 scenario was lower than that under A2 scenario in 2080s.[Conclusion] With the increase of temperature,maize yield in Yellow River irrigation area of Ningxia went up firstly and then went down.

Temporal-spatial distribution and variability of cadmium contamination in soils in Shenyang Zhangshi irrigation area,China

Heavy metal contamination in soils has been of wide concern in China in the last several decades. The heavy metal contamination was caused by sewage irrigation, mining and inappropriate utilization of various agrochemicals and pesticides and so on. The Shenyang Zhangshi irrigation area （SZIA） in China is a representative area of heavy metal contamination of soils resulting from sewage irrigation for about 30 years duration. This study investigated the spatial distribution and temporal variation of soil cadmium contamination in the SZIA. The soil samples were collected from the SZIA in 1990 and 2004; Cd of soils was analyzed and then the spatial distribution and temporal variation of Cd in soils was modelled using kriging methods. The kriging map showed that long-term sewage irrigation had caused serious Cd contamination in topsoil and subsoil. In 2004, the Cd mean concentrations were 1.698 and 0.741 mg/kg, and the maxima 10.150 and 7.567 mg/kg in topsoils （0-20 cm） and subsoils （20-40 cm） respectively. These values are markedly more than the Cd levels in the second grade soil standard in China. In 1990, the Cd means were 1.023 and 0.331 mg/kg, and the maxima 9.400 and 3.156 mg/kg, in topsoils and subsoils respectively. The soil area in 1990 with Cd more than 1.5 mg/kg was 2701 and 206.4 hnl2 in topsoils and subsoils respectively; and in 2004, it was 7592 and 1583 hm^2, respectively. Compared with that in 1990, the mean and maximum concentration of Cd, as well as the soil area with Cd more than 1.5 mg/kg had all increased in 2004, both in topsoils and subsoils.

Spatial distribution of Cd and Cu in soils in Shenyang Zhangshi Irrigation Area(SZIA),China

Heavy metal contamination of soils,derived from sewage irrigation,mining and inappropriate utilization of various agrochemicals and pesticides,and so on,has been of wide concern in the last several decades.The Shenyang Zhangshi Irrigation Area(SZIA) in China is a representative area of heavy metal contamination of soils resulting from sewage irrigation for about 30 years.This study investigated the spatial distribution and temporal variation of soil cadmium(Cd) and copper(Cu) contamination in the SZIA.The soil samples were collected from the SZIA in 1990 and 2004;Cd and Cu in soils was analyzed and then the spatial distribution and temporal variation of Cd and Cu in soils were modeled using Kriging methods.The results show that long-term sewage irrigation had caused serious Cd and Cu contamination in soils.The mean and the maximum of soil Cd are markedly higher than the levels in second grade standard soil(LSGSS) in China,and the maximum of soil Cu is close to the LSGSS in China in 2004 and is more than the LSGSS in China in 1990.The contamination magnitude of soil Cd and the soil extent of Cd contamination had evidently increased since sewage irrigation ceased in 1992.The contamination magnitude of soil Cu and the soil extent of Cu contamination had evidently increased in topsoil,but obviously decresed in subsoil.The soil contamination of Cd and Cu was mainly related to Cd and Cu reactivation of contaminated sediments in Shenyang Xi River and the import of Cd and Cu during irrigation.The eluviation of Cd and Cu in contaminated topsoil with rainfall and irrigation water was another factor of temporal-spatial variability of Cd and Cu contamination in soils.

Geostatistical analysis of variations in soil salinity in a typical irrigation area in Xinjiang, northwest China

Characterizing spatial and temporal variability of soil salinity is tremendously important for a variety of agronomic and environmental concerns in arid irrigation areas. This paper reviews the characteristics and spatial and temporal variations of soil salinization in the Ili River Irrigation Area by applying a geostatistical approach. Results showed that: (1) the soil salinity varied widely, with maximum value of 28.10 g/kg and minimum value of 0.10 g/kg, and was distributed mainly at the surface soil layer. Anions were mainly SO42- and Cl-, while cations were mainly Na+ and Ca2+; (2) the abundance of salinity of the root zone soil layer for different land use types was in the following order: grassland > cropland > forestland. The abundance of salinity of root zone soil layers for different periods was in the following order: March > June > September; (3) the spherical model was the most suitable variogram model to describe the salinity of the 0-3 cm and 3-20 cm soil layers in March and June, and the 3-20 cm soil layer in September, while the exponential model was the most suitable variogram model to describe the salinity of the 0-3 cm soil layer in September. Relatively strong spatial and temporal structure existed for soil salinity due to lower nugget effects; and (4) the maps of kriged soil salinity showed that higher soil salinity was distributed in the central parts of the study area and lower soil salinity was distributed in the marginal parts. Soil salinity tended to increase from the marginal parts to the central parts across the study area. Applying the kriging method is very helpful in detecting the problematic areas and is a good tool for soil resources management. Managing efforts on the appropriate use of soil and water resources in such areas is very important for sustainable agriculture, and more attention should be paid to these areas to prevent future problems.

CAS-based Water Resources Optimal Allocation and Dynamic Simulation for Sewage Irrigation Area

Based on the theory of complex adaptive system(CAS),the optimal allocation model of water resources in sewage irrigation areas was established,which provided new ideas and application value for the rational utilization of agricultural production and waste water resources.The results demonstrated that the difference of crop energy capture mainly depended on the development stage.Waste water with a certain concentration was able to promote crop growth,while excessive concentration inhibited crop growth.The correlation between water absorption rate and leaf area index was close(R=0.9498,p<0.01).The amount of bad seeds increased at a speed of 34.7·d^-1,when system irrigated randomly in the seedling stage,while it tended to remain stable at a speed of 0.3·d^-1 after plants entering the mature stage which impacted the total yields of crops.

Green Control Measures of Weeds in Wheat Fields in Hetao Irrigation Area along the Yellow River

This study was conducted to solve the problem of green weed control in wheat fields in Hetao irrigation area among the Yellow River.Based on the observation of the competition between wheat and weeds in areas where weeds occurred seriously in wheat fields in Hetao irrigation area among the Yellow River,we measured the effects of green weed control measures and wheat yield using different wheat varieties,planting densities,different organic fertilizers,different ploughing times,and different mulching methods.The results showed that the emergence of weeds in wheat fields dominated by Chenopodiaceae weeds,grain amaranth and barnyard grass was more than 10 d later than wheat.Weeds were mainly distributed between rows(holes),and the number of plants accounted for 66.6%(drill seeding)and 97.6%(hole seeding),respectively.And the growth of weeds in rows(holes)was weaker,and the fresh weight of individual plants was 39.3%-41.9%lower than that between rows(holes).The ecological weed inhibitory effect was significant in the early stage of wheat growth;and among the green weed control measures,except that different varieties and planting densities caused no significant difference in weed control effect,other measures had obvious weed control effects.Comprehensive comparison showed that the control effects of plant number in black film full-covered hole seeding,conventional film-covered hole seeding,increasing ploughing times,and applying organic fertilizer free of weed seed pollution were 82.3%,71.7%,22.0%,and 8.6%,respectively;the fresh weight control effects of black film full-covered hole seeding,conventional film-covered hole seeding,increasing ploughing times,and applying organic fertilizer free of weed seed pollution were 98.0%,97.1%,23.9%,and 9.6%,respectively;and the fresh weight control effects of black film full-covered hole seeding,conventional film-covered hole seeding and increasing ploughing times increased wheat yield by 69.4%,56.4%and 21.1%,respectively.The technologies in this study can realize the purposes of mechanized green weed control in organic wheat production and low-cost,high-yield,large-scale production.

Prevention and Management of Soil Secondary Salinization in Paddy Field Irrigation Area

By analyzing the process of soil salt accumulation in irrigation area, and discussing the change of irrigation and drainage methods for drought transformed into water, the control scheme of soil secondary salinization in Wujiazi Irrigation Area was analyzed concretely, and the experience was summarized. After in-depth discussion, the importance of irrigation and drainage methods in the prevention and control of soil secondary salinization in irrigation areas was analyzed.

Effect of Irrigation on Groundwater Dynamic Change in the Typical Irrigated Area of Qinghai Province

Under the influence of the natural and human factors, water table of irri- gated area Changes frequently, but it is mainly affected by irrigation water infiltration replenishment during the irrigation. 5 groundwater observation wells were constructed in experimental plot of the Daxia irrigated area to carry out the experiment of the effect of irrigation on groundwater dynamic change in this research. The results showed that the groundwater stage dynarnic change rule of spring and seedling irri- gation stage in the typical plot was fit to the hydrological geology condition of grade- I terrace of Huangshui river valley. On the whole, lateral canal water direction formed a line effect. The No. 1 and No. 2 observation well were the closest to the lateral canal, which received more supplies, and the water level was the highest; the No, 3 observation well took the second place; The No. 4 and No. 5 observation well accepted least supplies, and the water level was the lowest. The rangeability of water table of spring irrigation period was significantly higher than that of seedling irrigation period, this is mainly due to the difference value of intake water volume and drainage water volume of spring irrigation phase was significantly higher than the seedling irrigation phase.

Distribution of Arsenic in Sewage Irrigation Area of Pearl River Delta,China

The aim of the present work is to investigate the distribution of arsenic（As） in sewage ir-rigation area,to deduce the migration and transformation mechanism of As in soil and groundwater,and to infer the source of As in soil and groundwater.This study is carried out in a sewage irrigation area of the Pearl River Delta,China.Surface water samples,soil samples,and groundwater samples from sewage irrigation area were analyzed for As and other elements.As contents in water samples were analyzed by hydride generation-atomic fluorescence spectroscopy,and As fractionation in soil samples was extracted using a seven-step sequential extraction method according to a seven fraction scheme：water soluble,ion exchangeable,bound to carbonate,weakly bound to organic matter,associ-ated with oxides of iron（Fe） and manganese（Mn）,strongly bound to organic matter,and the residual fraction.Waste water has content of As up to 16.8 μg/L in the study area.Soil has enriched As due to the irrigation of soil with waste water,and the total content of As in soil is about 0.7 times higher than the background value.Sequential extraction method reveals that the mean content of residual fraction in soil is more than 70%,releasable fraction（weakly organic fraction,Fe-Mn oxide fraction,and car-bonate fraction） is about 20%-30%,whereas strongly organic and mobile fractions（water soluble and ion exchangeable） are within 0.2%.In the soil profile,the contents of water soluble,ion exchangeable,and carbonate fraction decrease with the depth,whereas the contents of other fractions are irregular with the depth.Using correlation analysis,it is concluded that water soluble fraction is easy to change into ion exchangeable and carbonate fraction,ion exchangeable fraction is easy to change into carbon-ate and Fe-Mn oxide fraction,and carbonate fraction is easy to change into weakly organic and Fe-Mn oxide fraction in the soil of study area.Organic matter and（hydr）oxides of Fe and aluminium（Al） in soil play an important role in controlling the distribution and mobility of As in soil.As concentrations in groundwater range from 2.8 to 21.0 μg/L,and it is inferred that As from waste water and the release of high As sediment（soil and aquifer medium） are the main sources for high As groundwater in study area.Using cluster analysis,it is concluded that reducing ground-water with slightly alkaline is beneficial to en-richment of As in groundwater,and hydroxides of Fe,Mn,and Al also play a key role for the en-richment of As in groundwater of the study area.

Timely monitoring of soil water-salt dynamics within cropland by hybrid spectral unmixing and machine learning models

Soil salinization and water scarcity are main restrictive factors for irrigated agriculture development in arid regions.Knowing dynamics of soil water and salt content is an important antecedent in remediating salinized soils and optimizing irrigation management.Previous studies mostly used remote sensing technologies to individually monitor water or salt content dynamics in agricultural areas.Their ability to asses different levels of crop water and salt management has been less explored.Therefore,how to extract effective diagnostic features from remote sensing images derived spectral information is crucial for accurately estimating soil water and salt content.In this study,Linear spectral unmixing method(LSU)was used to obtain the contribution of soil water and salt to each band spectrum(abundance),and endmember spectra from Sentinel-2 images.Calculating spectral indices and selecting optimal spectal combination were individually based on soil water and salt endmember spectra.The estimation models were constructed using six machine learning algorithms:BP Neural Network(BPNN),Support Vector Regression(SVR),Partial Least Squares Regression(PLSR),Random Forest Regression(RFR),Gradient Boost Regression Tree(GBRT),and eXtreme Gradient Boosting tree(XGBoost).The results showed that the spectral indices calculated from endmember spectra were able to effectively characterize the response of crop spectral properties to soil water and salt,which circumvent spectral ambiguity induced by water-salt mixing.NDRE spectral index was a reliable indicator for estimating water and salt content,with determination coefficients(R2)being 0.55 and 0.57,respectively.Compared to other models,LSU-XGBoost model achieved the best performance.This model properly reflected the process of soil water-salt dynamics in farmland during crop growth period.This study provided new methods and ideas for soil water-salt estimation in dry irrigated agricultural areas,and provided decision support for gover-nance of salinized land and optimal management of irrigation.

Livelihood vulnerability of smallholder farmers to climate change: A comparative analysis based on irrigation access in South Sulawesi, Indonesia

Bulukumba Regency is one of the major rice-producing areas in South Sulawesi,Indonesia and has experienced frequent climate disasters over the past decade.Several downstream villages within the Bettu River irrigation area have been affected by the drought,culminating in reduced lowland rice production and increasing the vulnerability of farmers’livelihoods.This study aims to evaluate the vulnerability of the livelihood system among rice farmers in the Bettu River irrigation area by classifying the area into two zones based on the distance from the main irrigation canal,namely the upstream area and downstream area.The livelihood vulnerability index(LVI)framework and livelihood vulnerability index-Intergovernmental Panel on Climate Change(LVI-IPCC)approach were applied by selecting geographic and socio-demographic indicators that affected the farmer households,including 8 major components and 26 sup-components.The data for LVI-IPCC estimation were collected by randomly selecting 132 households from villages in the two areas.The empirical results showed that farmers in the downstream area were more vulnerable to climate change than farmers in the upstream area.The major components causing the livelihood vulnerability of the downstream farmers were livelihood strategy,food,water,land,and health,as well as natural disasters and climate variability.In particular,the sub-components of agricultural livelihood diversification,consistent water supply for farming,and drought events were important in the downstream area.Farmers in the upstream area were vulnerable to socio-demographic profile and social network components.The LVI-IPCC findings suggested that the government should prioritize farmers in the downstream area to develop resilience strategies,particularly by increasing irrigation infrastructure and the number of reservoirs and drilling holes.Furthermore,to increase their adaptive capacity in terms of diversification of agricultural livelihood systems,the government and donor agencies need to provide trainings on the development of home food industries for poor farmers and vulnerable households that were affected by disasters.

Vertical Variation Characteristics of Basic Physical Properties in the Daxia Irrigated Area of Qinghai Province

Influenced by climate, biology and soil properties, vertical soil profile showed stratification character in terms of basic physical properties. The research conducted measurement and analysis on basic physical properties of typical field in the Daxia irrigation area in Qinghai Province. The results showed that soil bulk density changed from decreasing to increasing upon soil horizon; the soil horizons in 0-40 and 90-150 cm were high porosity zones, and the others were low porosi- ty area; the saturation moisture capacity, water retention of capillary porosity and field water retention all changed from decreasing to increasing upon soil horizon featured by arithmetic progression. In addition, the research area in Daxia irrigated area showed loose structure in soil horizon of 0-40 cm, compacted in 40-60 cm, and loose again in 60-200 cm vertically.

Quality of terrestrial data derived from UAV photogrammetry:A case study of Hetao irrigation district in northern China

Most crops in northern China are irrigated,but the topography affects the water use,soil erosion,runoff and yields.Technologies for collecting high-resolution topographic data are essential for adequately assessing these effects.Ground surveys and techniques of light detection and ranging have good accuracy,but data acquisition can be time-consuming and expensive for large catchments.Recent rapid technological development has provided new,flexible,high-resolution methods for collecting topographic data,such as photogrammetry using unmanned aerial vehicles(UAVs).The accuracy of UAV photogrammetry for generating high-resolution Digital Elevation Model(DEM)and for determining the width of irrigation channels,however,has not been assessed.A fixed-wing UAV was used for collecting high-resolution(0.15 m)topographic data for the Hetao irrigation district,the third largest irrigation district in China.112 ground checkpoints(GCPs)were surveyed by using a real-time kinematic global positioning system to evaluate the accuracy of the DEMs and channel widths.A comparison of manually measured channel widths with the widths derived from the DEMs indicated that the DEM-derived widths had vertical and horizontal root mean square errors of 13.0 and 7.9 cm,respectively.UAV photogrammetric data can thus be used for land surveying,digital mapping,calculating channel capacity,monitoring crops,and predicting yields,with the advantages of economy,speed and ease.

Long-term variability of the carbon balance in a large irrigated area along the lower Yellow River from 1984 to 2006

The irrigated areas in the northern region of China are important food production areas. Therefore, studies on the variability of the carbon balance in these agro-ecosystems are fundamental for the management of carbon sequestration. This paper simulated the long-term variability of the carbon balance in a typical irrigated area along the lower Yellow River from 1984 to 2006, using a process-based ecosystem model called the Simple Biosphere Model, version 2. The mean annual gross primary production (GPP), mean annual net assimilation rate (NAR), mean annual soil respiration (Rs ), and mean annual net ecosystem exchange (NEE) were 1733, 1642, 1304, and 338g C m-2 a-1 , respectively. A significant increasing trend in the seasonal total NAR during the wheat growing season, and a significant decreasing trend in the seasonal total NAR during the maize growing season were detected. However, no significant trend was found in the annual NAR, R s , and NEE. The average carbon sequestration was 1.93 Tg C a-1 when the grain harvest was not taken into account, and the carbon sequestration amount during the maize season was higher than that during the wheat season. However, the agro-ecosystem was a weak carbon source with a value of 0.23 Tg C a-1 , when the carbon in the grain was assumed emitted into the atmosphere.

Copper Residue in Animal Manures and the Potential Pollution Risk in Northeast China

A total of 224 animal manures and feeds, randomly sampled from different sizes of intensive farms in three northeastern provinces, were analyzed to determine Cu concentration. At the same time, the load of animal manure Cu on farmlands and loss to rivers in sewage irrigation areas of Liaoning Province was estimated. The results showed that the mean Cu concentrations in pig, cattle, and chicken feeds were 179.8, 16.6 and 20.8 mg kg-1, respectively. Cu concentrations in manures ranged from 1.5 to 1521.2 mg kg-1. The mean value of 642.1 mg kg-1 in pig manure was higher than the mean values of 65.6 mg kg-1 and 31.1 mg kg-1 in chicken and cattle manures, respectively. The load of animal manure Cu on farmland in the study area ranged from 12.3-35.4 kg km-2 annually. In particular, the Xiaolinghe area received a higher level than the other areas. The possible amount of manure Cu entering river water as a result of soil erosion was lower than 0.76 kg km-2. The highest loss rates were found in the south of Anshan and the west of Jinzhou. It is suggested that animal manures contain a high level of Cu. Long-term agricultural application of animal manure may increase the potential risk of Cu pollution in soil and surface water.

Modeling of hydrological processes in arid agricultural regions

Understanding of hydrological processes,including consideration of interactions between vegetation growth and water transfer in the root zone,underpins efficient use of water resources in arid-zone agriculture.Water transfers take place in the soil-plant-atmosphere continuum,and include groundwater dynamics,unsaturated zone flow,evaporation/transpiration from vegetated/bare soil and surface water,agricultural canal/surface water flow and seepage,and well pumping.Models can be categorized into three classes:(1)regional distributed hydrological models with various land uses,(2)groundwater-soil-plant-atmosphere continuum models that neglect lateral water fluxes,and(3)coupled models with groundwater flow and unsaturated zone water dynamics.This review highlights,in addition,future research challenges in modeling arid-zone agricultural systems,e.g.,to effectively assimilate data from remote sensing,and to fully reflect climate change effects at various model scales.

Evaluation of Landsat 8 image pansharpening in estimating soil organic matter using multiple linear regression and artificial neural networks

In agricultural systems,the regular monitoring of Soil Organic Matter(SOM)dynamics is essential.This task is costly and time-consuming when using the conventional method,especially in a very fragmented area and with intensive agricultural activity,such as the area of Sidi Bennour.The study area is located in the Doukkala irrigated perimeter in Morocco.Satellite data can provide an alternative and fill this gap at a low cost.Models to predict SOM from a satellite image,whether linear or nonlinear,have shown considerable interest.This study aims to compare SOM prediction using Multiple Linear Regression(MLR)and Artificial Neural Networks(ANN).A total of 368 points were collected at a depth of 0-30 cm and analyzed in the laboratory.An image at 15 m resolution(MSPAN)was produced from a 30 m resolution(MS)Landsat-8 image using image pansharpening processing and panchromatic band(15 m).The results obtained show that the MLR models predicted the SOM with(training/validation)R^(2)values of 0.62/0.63 and 0.64/0.65 and RMSE values of 0.23/0.22 and 0.22/0.21 for the MS and MSPAN images,respectively.In contrast,the ANN models predicted SOM with R2 values of 0.65/0.66 and 0.69/0.71 and RMSE values of 0.22/0.10 and 0.21/0.18 for the MS and MSPAN images,respectively.Image pansharpening improved the prediction accuracy by 2.60%and 4.30%and reduced the estimation error by 0.80%and 1.30%for the MLR and ANN models,respectively.