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.     

Use of Predictive Weather Uncertainties in an Irrigation Scheduling Tool Part II: An Application of Metrics and Adjoints

We apply predictive weather metrics and land model sensitivities to improve the Colorado State University Water Irrigation Scheduler for Efficient Application (WISE). WISE is an irrigation decision aid that integrates environmental and user information for optimizing water use. Rainfall forecasts and verification performance metrics are used to estimate predictive rainfall probabilities that are used as input data within the irrigation decision aid. These input data errors are also used within a land model sensitivity study to diagnose important prognostic water movement behaviors for irrigation tool development purposes simultaneously performing the analysis in space and time. Thus, important questions such as “how long can a crop water application be delayed while maintaining crop yield production?” are addressed by evaluating crop growth stage interactions as a function of soil depth (i.e., space), rainfall events (i.e., time), and their probabilistic uncertainties. Editor’s note : This paper is part of the featured series on Optimizing Ogallala Aquifer Water Use to Sustain Food Systems. See the February 2019 issue for the introduction and background to the series.     

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.     

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.     

Hydrological Controls and Freshening in Meromictic Soap Lake,Washington, 1939-20021

Kallis, Jahn, Leo Bodensteiner, and Anthony Gabriel, 2010. Hydrological Controls and Freshening in Meromictic Soap Lake, Washington, 1939-2002. Journal of the American Water Resources Association (JAWRA) 46(4): 744-756. DOI: 10.1111/j.1752-1688.2010.00446.x Abstract: The chemically stratified layer of naturally formed meromictic lakes exhibits unusual and often extreme physical and chemical conditions that have resulted in the evolution of uniquely adapted species. The Columbia Basin Irrigation Project appears to have had a marked effect on the hydrology of Soap Lake, a meromictic lake in the Grand Coulee of central Washington. The relation of hydrology to salinity was assessed by analyzing water budgets before and after the introduction of the irrigation project. Before irrigation, water gains were balanced by losses; after irrigation began groundwater gains approximately doubled. To manage lake levels and reduce groundwater influx, wells were installed to intercept groundwater. Although the hydrological cycle has been restored to pre-irrigation conditions, the meromictic character of the lake continues to change. Interception wells remove 10 to 16 Mm³ of groundwater annually, but influx continues based on change in the monimolimnion. From 1958 to 2003 the chemocline descended 1.1 m and the volume of the monimolimnion from 698,000 m³ to 114,000 m³. Annual loss of volume is occurring at a rate of 1.9% since 1958. Although groundwater interception wells are maintaining the volume of the entire lake, the recession of the chemocline indicates that conditions that have maintained meromixis at Soap Lake are currently not in equilibrium.     

绿地再生水灌溉土壤微生物量碳及酶活性效应研究

再生水灌溉引起了土壤理化性质的变化,其对土壤生物活性的影响备受关注.以再生水利用较典型的北京为研究区,分层采集了不同再生水灌溉历史的城区公园绿地与城郊农田表层土壤样品,测定并分析了一些常规理化指标、土壤微生物量碳及5种土壤酶（脲酶、碱性磷酸酶、蔗糖酶、脱氢酶和过氧化氢酶）活性,探讨长期再生水灌溉下土壤微生物量碳和酶活性的变化.结果表明,再生水灌溉下公园绿地土壤微生物量碳和酶活性均高于其自来水对照灌区,农田上升不明显.与对照相比,公园绿地与农田再生水灌区0～20 cm土层土壤微生物量碳平均含量分别上升了60.1%和14.2%,公园绿地再生水灌区0～20 cm土层中土壤酶活性平均增幅为36.7%,而农田为7.4%.调查区土壤微生物量碳及酶活性均随土壤深度的增加而降低,其中公园绿地0～10 cm与10～20 cm土层间差异极显著.因此,北京地区城市绿地使用再生水长期灌溉有助于提高土壤生物活性.     

再生水灌溉利用的生态风险研究进展

污水再生回用因其具有显著的社会、经济及生态效益,已成为缓解水资源危机的一项重要举措.城市绿地和农业灌溉作为再生水的主要利用途径之一,在国内外已经得到广泛推广实践.为了解国内外在再生水灌溉利用风险方面的研究进展,本文围绕再生水典型污染物包括盐、氮、重金属和新型污染物、病原菌等,从对土壤质量、植物生长、地下水质量和公众健康等几方面,对再生水灌溉利用的生态风险进行了系统分析.结果表明,盐分及盐离子是再生水灌溉利用的主要风险,灌溉利用导致疾病传播的风险始终存在,而新型污染物的生态风险是科学研究热点.借鉴国外经验,分别就城市绿地和农业的灌溉提出了风险管理措施.最后,提出了加强长期定位研究和模型研究,建立再生水水质、灌溉管理与生态风险的有机关联,进行再生水灌溉土壤承载力评价和建立风险管理体系等5项建议,以促进再生水安全利用.     

模型模拟土壤性质和植被种类对再生水灌溉水盐运移的影响

为推动再生水安全灌溉,本研究运用ENVIRO-GRO模型模拟了不同土壤性质、植被条件下土壤盐分的分布规律及累积趋势,探讨了土壤性质和植被种类对再生水灌溉水盐运移的影响.研究发现,不同土壤初始含盐量下,经多年重复模拟后最终达到统一的平衡状态;而不同土壤质地下,随着灌溉年份的增加,壤土、黏壤土中的土壤ECe年均值逐渐增加直到平衡,砂壤土中的土壤ECe年均值逐渐减少直到平衡,平衡时土层中的ECe值砂壤土〈壤土〈黏壤土.3种植被下,大叶黄杨、油松的土壤ECe值增加量小于早熟禾;土壤盐分在土层中的空间、时间分布也均有所不同.此外,不同模拟情景下,土壤盐分累积都不会影响植被的生长（黏壤土除外）,但均出现轻度盐渍化（砂壤土除外）.     

模型模拟再生水灌溉对土壤水盐运动的影响

随着水资源供需矛盾日益尖锐,污水再生利用成为了缓解北京水资源紧缺的重要举措.为推动北京再生水安全灌溉,本研究运用ENVIRO-GRO模型模拟缺水城市北京再生水灌溉土壤水盐运动规律,并对土壤盐分累积进行预测,探讨了不同灌溉措施对土壤水盐运动规律和盐分累积的影响.结果表明,高水量、常规、低水量灌溉,平衡时土壤含盐量（ECe）年均值分别增加了29.5%、97.2%、197.8%;灌溉频率对土壤水盐运动规律影响不大,但低频灌溉下土壤中盐分的累积有减少的趋势;灌溉水含盐量（ECw）为0.6、1.2、2.4 dS.m-1灌溉条件下,平衡时ECe的年均值分别增加了23.7%、97.2%、208.5%,自来水灌溉下土壤盐分虽有增加,但土壤未出现盐渍化.总的来说,目前北京常规再生水灌溉,平衡时土壤盐分累积不会影响早熟禾的生长,但土壤会出现轻度盐渍化.     

河套灌区土壤水和地下水动态变化及水平衡研究

为探究田间土壤水及地下水在不同作物种植区、不同灌期等情况下的动态变化规律与水平衡特征,以春小麦、玉米、向日葵为典型作物,在河套灌区选取4块2亩的试验田,于2009年4-11月采集田间土壤及地下水样品进行研究.结果表明,不同作物地块间土壤含水率的变化差别主要集中在5-9月的作物生长期.夏灌灌水量不足,土壤含水率呈下降趋势,田间土壤水分变化属于“蒸腾蒸发消耗型”;秋浇期内水量充足,各地块各土层含水率均明显增加,田间土壤水分呈“入渗补给型”.各地块地下水埋深月均变化趋势基本一致,由于优先流的存在,地下水对灌溉降水响应快.本文定量研究了区域土壤水和地下水的变化规律,揭示了灌区水平衡要素间的相互转换关系,可为灌区科学合理的水资源管理提供理论依据.