Collectively engaging complex socio-ecological systems: re-envisioning science, governance, and the California Delta

We address the future of science and governance for the California Delta, focusing on the CALFED Bay-Delta Program, an interagency, multi-stakeholder effort to understand and manage the Delta for multiple purposes. We portray a Delta history as a coevolutionary process between science, governance and ecosystems. Global integrated environmental assessments (IEA) provide insights into understanding complex, dynamic socio-ecological systems. Many of the discursive stakeholder and scientific activities that have arisen under CALFED are similar to IEA and remain essential to the shared learning needed to effectively interact with a dynamic Delta. More deliberately enmeshing environmental monitoring, analysis, and collective learning into Delta governance will improve outcomes.     

Ingredients in sustainably managing water in semi-arid environments

The lessons learned from CALFED indicate that ingredients important in the long-term resolution of water management issues may not result in short-term “solutions”. The value of this special issue lies in its identification of ingredients that stimulate re-framing of issues, adapting to new knowledge and innovative decisions. But sustainable water management also requires the political patience to sustain those processes as a means of perpetuating the long-term decision-making necessary to anticipate and/or respond to an ever-changing environment.     

Performance of a diesel engine with water emulsified diesel prepared with optimized process parameters

An attempt has been made to produce stable water–diesel emulsion with optimal formulation and process parameters and to evaluate the performance and emission characteristics of diesel engine using this stable water–diesel emulsion. A total of 54 samples were prepared with varying water/diesel ratio, surfactant amount and stirring speed and water separation was recorded after 24 and 48 hr of emulsification. The recorded data were used in artificial neural network (ANN)-particle swarm optimization (PSO) technique to find the optimal parameters to produce water–diesel emulsion for engine testing. The predicted optimal parameters were found as 20% water to diesel ratio, 0.9% surfactant and 2200 rpm of stirrer for a water separation of 14.33% in one day with a variation of 6.54% against the actual value of water separation. Water–diesel emulsion fuel exhibited similar fuel properties as base fuel. The peak cylinder gas pressure, peak pressure rise rate and peak heat release rate for water–diesel were found higher as compared to diesel at medium to full engine loads. The improved air-fuel mixing in water–diesel emulsion enhanced brake thermal efficiency (BTE) of engine. The absorption of heat by water droplets present in water–diesel emulsion led to reduced exhaust gas temperature (EGT). With water–diesel emulsion fuel, the mean carbon monoxide (CO), unburned hydrocarbon and oxides of nitrogen (NO_x) emissions reduced by 8.80, 39.60, and 26.11%, respectively as compared to diesel.     

论"水十条"对中国水体污染防治的意义

2015年4月16日,国务院正式发布《水污染防治行动计划》,《水污染防治行动计划》为了与一年前出台的"大气十条"相对应,故亦简称"水十条".这将是今后很长一段时期中国治理水环境的纲领性文件."水十条"对中国水污染治理工作提出了总体目标,同时作为新环保法的延伸,"水十条"将强调市场机制在治理水体污染中的作用、促进环境需求的多样化.总的来说,"水十条"的发布,标志着中国将对水污染防控治理进行强力监管,铁腕治污将进入"新常态".     

沈阳市大气PM_(10)中水溶性无机阴离子的分布特征研究

2014年7月和12月分别对沈阳市大气污染物PM_(10)(可吸入颗粒物)进行采样分析,采样期内PM_(10)浓度全部超过国家一级标准,最大值超出国家二级标准3.3倍。用离子色谱法分析了PM_(10)中的水溶性无机阴离子,结果表明:4种阴离子浓度之和的变化总趋势为7月12月;各离子浓度的关系为SO_4~(2-)NO_3~-Cl~-F~-,4种离子浓度均为冬季高于夏季;对PM_(10)及4种阴离子进行相关性分析,得出NO_3~-、SO_4~(2-)浓度与PM_(10)浓度呈显著正相关,是PM_(10)的重要组分,并通过NO_3~-与SO_4~(2-)的质量比得出沈阳市大气污染物中水溶性组分主要来自于固定排放源。     

再生水中的Pb对萝卜根际土壤微生物群落结构的影响研究

采用盆栽方法研究再生水、再生水+Pb、清水+Pb处理浇灌萝卜,以清水浇灌为对照对萝卜根际土壤微生物群落的影响进行研究。结果表明:(1)土壤总PLFA含量及各菌群生物量从大到小依次为:再生水再生水+Pb清水清水+Pb。再生水灌溉有利于萝卜根际微生物各类群数量的增加,丰富微生物多样性。用含铅的溶液(再生水+Pb、清水+Pb)浇灌萝卜,可抑制土壤微生物各类群的数量,G-受到的抑制尤为明显。(2)主成分分析表明,再生水灌溉与对照相比,土壤微生物群落结构差异最大。(3)土壤微生物各类群与土壤速效钾、硝酸盐氮含量呈极显著正相关(P0.01),真菌、放线菌与土壤有机质含量,G~+、G~-菌与p H均呈极显著正相关(P0.01)。G~+、G~-与萝卜地下鲜重均呈极显著负相关(P0.01),土壤微生物各类群与地上部分硝酸盐含量、与根冠比呈极显著正相关(P0.01)。     

Mapping Outlets of Iowa Flood Center and National Water Center River Networks for Hydrologic Model Comparison

River networks based on Digital Elevation Model (DEM) data differ depending on the DEM resolution, accuracy, and algorithms used for network extraction. As spatial scale increases, the differences diminish. This study explores methods that identify the scale where networks obtained by different methods agree within some margin of error. The problem is relevant for comparing hydrologic models built around the two networks. An example is the need to compare streamflow prediction from the Hillslope Link Model (HLM) operated by the Iowa Flood Center (IFC) and the National Water Model (NWM) operated by the National Water Center of the National Oceanic and Atmospheric Administration. The HLM uses landscape decomposition into hillslopes and channel links while the NWM uses the NHDPlus dataset as its basic spatial support. While the HLM resolves the scale of the NHDPlus, the outlets of the latter do not necessarily correspond to the nodes of the HLM model. The authors evaluated two methods to map the outlets of NHDPlus to outlets on the IFC network. The methods compare the upstream areas of the channels and their spatial location. Both methods displayed similar performance and identified matches for about 80% of the outlets with a tolerance of 10% in errors in the upstream area. As the aggregation scale increases, the number of matches also increases. At the scale of 100 km², 90% of the outlets have matches with tolerance of 5%. The authors recommend this scale for comparing the HLM and NWM streamflow predictions.     

A Water Allocation Decision‐Support Model and Tool for Predictions in Ungauged Basins in Northeast British Columbia,Canada

Pressures on water resources due to changing climate, increasing demands, and enhanced recognition of environmental flow needs result in the need for hydrology information to support informed water allocation decisions. However, the absence of hydrometric measurements and limited access to hydrology information in many areas impairs water allocation decision‐making. This paper describes a water balance‐based modeling approach and an innovative web‐based decision‐support hydrology tool developed to address this need. Using high‐resolution climate, vegetation, and watershed data, a simple gridded water balance model, adjusted to account for locational variability, was developed and calibrated against gauged watersheds, to model mean annual runoff. Mean monthly runoff was modeled empirically, using multivariate regression. The modeled annual runoff results are within 20% of the observed mean annual discharge for 78% of the calibration watersheds, with a mean absolute error of 16%. Modeled monthly runoff corresponds well to observed monthly runoff, with a median Nash–Sutcliffe statistic of 0.92 and a median Spearman rank correlation statistic of 0.98. Monthly and annual flow estimates produced from the model are incorporated into a map‐ and watershed‐based decision‐support system referred to as the Northeast Water Tool, to provide critical information to decision makers and others on natural water supply, existing allocations, and the needs of the environment.     

Challenges and Opportunities for Creating Intelligent Hazard Alerts: The “FloodHippo” Prototype

Disasters evolving from hazards are a persistent and deadly occurrence in the United States. Despite this, hazard alerts have remained spatially vague, temporally imprecise, and lack actionable information. These deficiencies indicate a divide between the status quo and what is possible given modern environmental models, geographic information systems (GIS), and smartphone capabilities. This work describes an alternative, prototype system, “FloodHippo,” which integrates operational model outputs, cloud‐based GIS, and expanded communication channels to provide personal and interactive disaster alerts for floods. The precepts and methods underpinning FloodHippo apply equally to other disasters that evolve over space and time, presenting the opportunity for a more intelligent disaster response system. The development of such a system would not only minimize current shortcomings in disaster alerts but also improve resilience through individual action, along with community, academic, and federal cooperation.     

Water Nakba in Palestine: Sustainable Development Goal 6 versus Israeli hydro-hegemony

This Viewpoint article argues that Sustainable Development Goal 6, which aims to ensure the availability and sustainable management of water and sanitation for all, cannot be achieved for the Palestinian people under the current political situation of Israeli occupation. Through the practice of hydro-hegemony, Israel controls all water resources in Israel and the Occupied Palestinian Territory, thus denying water sovereignty to the Palestinians. This is demonstrated through three case studies: The Jordan Valley; the West Bank settlements; and Gaza. The politics of water in Israel and the Occupied Palestinian Territory is best understood as part of the dynamics of settler colonialism, in which ethnic cleansing is achieved through the dispossession of essential resources. The authors discuss what role the international scientific community can play in supporting Palestinian water sovereignty and therefore SDG 6.