污水直接膜过滤用于农灌可行性试验

本试验尝试用膜直接截留污水中对人体健康有害的细菌病毒,而保留水中对作物有益的氮、磷等营养元素,以期实现水、肥双成分资源化。试验结果表明,无论是微滤膜还是超滤膜均对细菌及粪大肠菌有很高的截留率(99.9%～99.999%),污水中有机物、氮与磷的保留率分别为32%～67%、72%～78%和60%～62%。用渗滤液灌溉的小麦较之清水灌溉和常规灌溉的小麦,麦穗单重分别提高13%和7.5%。     

桂林市某蔬菜种植基地重金属污染调查及分析

通过对桂林市某蔬菜种植基地灌溉水、土壤与蔬菜中重金属的测定,结合国家农灌水、土壤和食品卫生标准,分析了该区Cu、Pb、Zn、Cd污染状况。经测定分析,该区灌溉水质达到了国家三类水质标准;土壤中重金属含量普遍超过背景值,但达到了国家土壤环境质量标准;蔬菜中的重金属含量符合国家无公害蔬菜的标准。结果表明,该区尚未受到重金属污染,符合无公害食品种植基地要求。     

Treated wastewater irrigation effect on soil, crop and environment： Wastewater recycling in the loess area of China

A study was carried out at the Loess Plateau in Dongzhi,China,to test the feasibility of using secondary treatment sewage effluent and to determine whether the water quality would then meet the recommended irrigation norm.Seven crops,including celery,wheat, maize,millet,apples,rapeseed and yellow beans,were tested in the study.Physical and chemical properties of the soil,crop yield and quality and leachate at different soil depths were measured.In most cases,the quality of the crops that made use of treated sewage was not distinctively different from those that did not use treated sewage.However,yields for the former were much higher than they were for the latter.Leachates at different soil depths were analyzed and the results did not show alarming levels of constituents.For a period of approximately 14 months,the treated sewage irrigation had no significant effect on the loess soil and no cases of illness resulting from contact with the treated sewage were reported.With treated sewage irrigation,a slight increase in the organic content of the soil was observed.     

Characterizing Drought in Irrigated Agricultural Systems: The Surface Water Delivery Index (SWDI)

Quantifying surface water shortages in arid and semiarid agricultural regions is challenging because limited water supplies are distributed over long distances based on complex water management systems constrained by legal, economic, and social frameworks that evolve with time. In such regions, the water supply is often derived in a climate dramatically different from where the water is diverted to meet agricultural demand. The existing drought indices which rely on local climate do not portray the complexities of the economic and legal constraints on water delivery. Nor do these indices quantify the shortages that occur in drought. Therefore, this research proposes a methodological approach to define surface water shortages in irrigated agricultural systems using a newly developed index termed the Surface Water Delivery Index (SWDI). The SWDI can be used to uniformly quantify surface water deficits/shortages at the end of the irrigation season. Results from the SWDI clearly illustrate how water shortages in droughts identified by the existing indices (e.g., SPI and PDSI) vary strongly both within and between basins. Some surface water entities are much more prone to water shortages than other entities based both on their source of water supply and water right portfolios.     

Irrigation Water Allocation Using an Inexact Two‐Stage Quadratic Programming with Fuzzy Input under Climate Change

Agricultural irrigation accounts for nearly 70% of the total water use around the world. Uncertainties and climate change together exacerbate the complexity of optimal allocation of water resources for irrigation. An interval‐fuzzy two‐stage stochastic quadratic programming model is developed for determining the plans for water allocation for irrigation with maximum benefits. The model is shown to be applicable when inputs are expressed as discrete, fuzzy or random. In order to reflect the effect of marginal utility on benefit and cost, the model can also deal with nonlinearities in the objective function. Results from applying the model to a case study in the middle reaches of the Heihe River basin, China, show schemes for water allocation for irrigation of different crops in every month of the crop growth period under various flow levels are effective for achieving high economic benefits. Different climate change scenarios are used to analyze the impact of changing water requirement and water availability on irrigation water allocation. The proposed model can aid the decision maker in formulating desired irrigation water management policies in the wake of uncertainties and changing environment.     

Impact of untreated wastewater irrigation on soils and crops in Shiraz suburban area, SW Iran

In this study an assessment is made of the negative impacts of wastewater irrigation on soils and crops sampled along the Khoshk River channel in suburban area of Shiraz City, SW Iran. For this purpose, samples of soil profiles (0–60 cm in depth) and crops were collected from two wastewater irrigated sites and a tube well-irrigated (control) site. Total concentrations of the five heavy metals (Ni, Pb, Cd, Zn and Cr) and their phytoavailable contents were determined. The Pollution Load Indexes (PLIs) and Contamination Factors (CFs) for soils and Hazard quotients (ΣHQ) for some vegetables were also calculated. The results showed the use of untreated wastewater has caused the following changes as compared to control site: (1) a 20–30% increase in organic matter content of soil; (2) increase in pH by 2–3 units; (3) significant concentration increase in Ex-Ca especially in top layers of soil resulting in high CEC; (4) build up of heavy metals (notably Pb and Ni) in topsoil above Maximum Permissible Limits (MPLs) indicating a moderate contamination (PLI > 1, CF > 2.5); (5) contamination of some vegetables (spinach and lettuce) with Cd due to its high phytoavailability in topsoil causing a HQ > 1; (6) excessive accumulation of Ni and Pb in wheat due to continual addition of heavy metals through long-term wastewater application. The study concludes that strict protection measures, stringent guidelines and an integrated system for the treatment and recycling of wastewater are needed to minimize the negative impacts of wastewater irrigation in the study area.     

Hydrologic–Economic Model for Managing Irrigation Intensity in Irrigation Areas under Watertable and Soil Salinity Targets

This paper gives mathematical details and sample applications of SWAGMAN Farm (SWAGMAN, Salt Water and Groundwater Management), a farm-scale hydrologic economic model that integrates agronomic, climatic, irrigation, hydrogeological and economic aspects of irrigated agriculture. The model is capable of determining optimum mix of land use to keep watertable and soil salinity within acceptable limits while maximising the economic returns. Alternatively, the model can simulate water and salt balance and economics of a given cropping preference. Web-based and Geographic Information Systems versions of the model are available for integration with the environmental reporting systems of the irrigation areas.     

Cluster analysis and quality assessment of logged water at an irrigation project, eastern Saudi Arabia

A multivariate statistical technique, cluster analysis, was used to assess the logged surface water quality at an irrigation project at Al-Fadhley, Eastern Province, Saudi Arabia. The principal idea behind using the technique was to utilize all available hydrochemical variables in the quality assessment including trace elements and other ions which are not considered in conventional techniques for water quality assessments like Stiff and Piper diagrams. Furthermore, the area belongs to an irrigation project where water contamination associated with the use of fertilizers, insecticides and pesticides is expected. This quality assessment study was carried out on a total of 34 surface/logged water samples. To gain a greater insight in terms of the seasonal variation of water quality, 17 samples were collected from both summer and winter seasons. The collected samples were analyzed for a total of 23 water quality parameters including pH, TDS, conductivity, alkalinity, sulfate, chloride, bicarbonate, nitrate, phosphate, bromide, fluoride, calcium, magnesium, sodium, potassium, arsenic, boron, copper, cobalt, iron, lithium, manganese, molybdenum, nickel, selenium, mercury and zinc. Cluster analysis in both Q and R modes was used. Q-mode analysis resulted in three distinct water types for both the summer and winter seasons. Q-mode analysis also showed the spatial as well as temporal variation in water quality. R-mode cluster analysis led to the conclusion that there are two major sources of contamination for the surface/shallow groundwater in the area: fertilizers, micronutrients, pesticides, and insecticides used in agricultural activities, and non-point natural sources.     

Detection of Class I and II integrons for the assessment of antibiotic and multidrug resistance among Escherichia coli isolates from agricultural irrigation waters in Bulacan,Philippines

Contaminated irrigation water may greatly affect not only the quality of produce but also the people exposed to it. In this study, agricultural irrigation waters in Bulacan, Philippines were assessed and found to be contaminated with Escherichia coli (E. coli) ranging from 0.58 to 4.51 log₁₀ CFU/mL. A total of 79 isolates of E. coli were confirmed through polymerase chain reaction (PCR) amplifying the uidA gene and were tested for phenotypic resistance using 10 antimicrobials through the Kirby–Bauer disc diffusion method. Forty-six isolates (58.22%) were noted to be multidrug resistant (MDR) with high resistance rate to cephalothin, tetracycline, streptomycin, ampicillin, trimethoprim, nalidixic acid, and chloramphenicol. Moreover, this study also examined the prevalence of Class I and II integrons accounting to 67.39% and 17.39%, respectively, of the MDR E. coli strains using multiplex PCR. The results imply that the agricultural water used in Bulacan is contaminated with the fecal material of man or other animals present in the area, and the presence of MDR bacteria, which pose a potential threat to individuals in these areas, is alarming. In addition, detection of integrons could be a good marker for the identification of MDR isolates. Lastly, this study could develop strategies for the proper management of farming sites leading to the detection of food-borne pathogens and prevention of infectious diseases.     

Predicting Satisfaction with Smart Irrigation Controllers and Their Long‐Term Use among Homeowners in Central Florida

Studies throughout Florida have shown smart controllers can substantially reduce irrigation under residential high‐water use conditions. However, successful promotion requires understanding the link between controller performance and the mechanisms by which they are adopted. This article compares irrigation water‐use and survey data collected from households installed with soil moisture sensor and evapotranspiration controllers. The study investigated whether the relative change in irrigation use between two years preceding and two years following installation was a reliable predictor of a homeowner's satisfaction with the device and likelihood of continuing to use it. Results indicated relative changes in irrigation use were only significantly associated with the quality of controller programming. Satisfaction with the controller was largely attributable to satisfaction with the appearance of the landscape and the perceived water‐saving effectiveness of the controller whereas the likelihood of its continued use was only significantly predicted by the level of technical knowledge regarding its functioning and whether or not challenges were experienced with it. Targeting homeowners with supplemental user‐friendly information may best support their long‐term adoption of smart controllers while providing irrigation contractors with training in implementation techniques would represent an integrated strategy for added reductions in residential outdoor water use.