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.

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.

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.

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.

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.

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.

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.