MULTITEMPORAL SCALE HYDROGRAPH PREDICTION USING ARTIFICIAL NEURAL NETWORKS1

Abstract: An artificial neural network (ANN) provides a mathematically flexible structure to identify complex nonlinear relationship between inputs and outputs. A multilayer perceptron ANN technique with an error back propagation algorithm was applied to a multitime-scale prediction of the stage of a hydro-logically closed lake, Devils Lake (DL), and discharge of the Red River of the North at Grand Forks station (RR-GF) in North Dakota. The modeling exercise used 1 year (2002), 5 years (1998–2002), and 27 years (1975–2002) of data for the daily, weekly, and monthly predictions, respectively. The hydrometeorological data (precipitations P_(t), P_(t-1), P_(t-2), P_(t-3), antecedent runoff/lake stage R_(t-1) and air temperature T_(t) were partitioned for training and for testing to predict the current hydro-graph at the selected DL and RR-GF stations. Performance of ANN was evaluated using three combinations of daily datasets (Input I = P_(t)), P_(t-l), P_(t-2), P_(t-3), T_(t) and R_(t-l); Input II = Input-l less P_(t) P_(t-l), P_(t-2), P_(t-3); and Input III = Input-II less T_(t)). Comparison of the model output using Input I data with the observed values showed average testing prediction efficiency (E) of 86 percent for DL basin and 46 percent for RR-GF basin, and higher efficiency for the daily than monthly simulations.     

Global-scale vs. regional-scale scenario assumptions: implications for estimating future water withdrawals in the Elbe River basin

In this paper, we explore how scenarios of future water withdrawals in a river basin are influenced by scale-dependent quantifications of the driving forces for two global-scale storylines. Either global-scale information or region-specific information is used to do the quantifications. In addition, we analyze the impact of including or not some restricted regional-scale information in the employed water use model. To develop scenarios of water withdrawals in the German part of the Elbe River basin, we applied the modules for domestic, thermoelectric power and manufacturing water use of the global water model WaterGAP, using scale-dependent driving forces scenarios and other scale-dependent model input. In the global-scale quantitative interpretations of the storylines of the IPCC SRES scenarios A1 and B2, all major driving forces of water withdrawals in the basin—population, thermoelectric power production and industrial gross domestic product—show vigorous increases between 2000 and 2025, while from the regional perspective, smaller increases but mostly decreases appear to be plausible. These discrepancies are partly due to the fact that for the global-scale interpretations only the historic developments until 1990 were taken into account, and not until 2000 as in the regional case. The resulting scenarios of sectoral water withdrawals in 2025 differ strongly between the two scale-dependent interpretations of the storylines, with the global one leading to much higher absolute water withdrawals and much lower withdrawal decreases between 2000 and 2025. Therefore, for regional assessments of water withdrawals, we recommend to embed the scenario analysis in global-scale storylines by performing regional-scale quantifications of the global qualitative driving forces scenarios, based on a limited amount of region-specific information.     

城市适度人口规模研究

一个城市的适度人口规模既与经济发展水平密切相关,它是由所在地区的资源、环境等因素决定的。秦皇岛市是中国北方极度缺水的城市一,水资源构成了限制城市发展的短板因素。通过调整用水结构和采用节水技术,虽可使城市居民的用水份额适度增加,但总量约束决定了该城市的人口规模要保持在与水资源相适应的限度内。     

硫酸钡锶垢去除研究

通过定性分析得出某油田现场结垢物质为硫酸钡锶垢;采用沉淀重量法,对几种市售除垢剂与自制新型除垢剂QX进行了除垢效果对比实验。结果表明,除垢剂QX是一种理想的硫酸钡锶垢除垢剂。当QX加量为25mg／L、温度为50℃时除垢24h,除垢率可达95％以上。同时,对除垢剂加量、除垢时间、盐类加入和酸洗等影响因素进行了正交实验研究,表明除垢剂加量是影响除垢率的主要因素,而酸洗和加入盐会阻碍除垢效果。     

An occupancy‐based quantification of the highly imperiled status of desert fishes of the southwestern United States

Desert fishes are some of the most imperiled vertebrates worldwide due to their low economic worth and because they compete with humans for water. An ecological complex of fishes, 2 suckers (Catostomus latipinnis, Catostomus discobolus) and a chub (Gila robusta) (collectively managed as the so‐called three species) are endemic to the U.S. Colorado River Basin, are affected by multiple stressors, and have allegedly declined dramatically. We built a series of occupancy models to determine relationships between trends in occupancy, local extinction, and local colonization rates, identify potential limiting factors, and evaluate the suitability of managing the 3 species collectively. For a historical period (1889–2011), top performing models (AICc) included a positive time trend in local extinction probability and a negative trend in local colonization probability. As flood frequency decreased post‐development local extinction probability increased. By the end of the time series, 47% (95% CI 34‐61) and 15% (95% CI 6‐33) of sites remained occupied by the suckers and the chub, respectively, and models with the 2 species of sucker as one group and the chub as the other performed best. For a contemporary period (2001?2011), top performing (based on AIC_c) models included peak annual discharge. As peak discharge increased, local extinction probability decreased and local colonization probability increased. For the contemporary period, results of models that split all 3 species into separate groups were similar to results of models that combined the 2 suckers but not the chub. Collectively, these results confirmed that declines in these fishes were strongly associated with water development and that relative to their historic distribution all 3 species have declined dramatically. Further, the chub was distinct in that it declined the most dramatically and therefore may need to be managed separately. Our modeling approach may be useful in other situations in which targeted data are sparse and conservation status and best management approach for multiple species are uncertain.     

An assessment on the recycling opportunities of wastes emanating from scrap metal processing in Mauritius

This paper presents an assessment on the wastes namely slag, dust, mill scale and sludge resulting from scrap metal processing. The aim of this study is to demonstrate that there are various ways via which scrap metal processing wastes can be reused or recycled in other applications instead of simply diverting them to the landfill. These wastes are briefly described and an overview on the different areas of applications is presented. Based on the results obtained, the waste generation factor developed was 349.3 kg per ton of steel produced and it was reported that slag represents 72% of the total wastes emanating from the iron and steel industry in Mauritius. Finally the suitability of the different treatment and valorisation options in the context of Mauritius is examined.     

Anaerobic co-digestion of kitchen waste and fruit/vegetable waste: Lab-scale and pilot-scale studies

The anaerobic digestion performances of kitchen waste (KW) and fruit/vegetable waste (FVW) were investigated for establishing engineering digestion system. The study was conducted from lab-scale to pilot-scale, including batch, single-phase and two-phase experiments. The lab-scale experimental results showed that the ratio of FVW to KW at 5:8 presented higher methane productivity (0.725 L CH₄/g VS), and thereby was recommended. Two-phase digestion appeared to have higher treatment capacity and better buffer ability for high organic loading rate (OLR) (up to 5.0 g (VS) L^?1 d^?1), compared with the low OLR of 3.5 g (VS) L^?1 d^?1 for single-phase system. For two-phase digestion, the pilot-scale system showed similar performances to those of lab-scale one, except slightly lower maximum OLR of 4.5 g (VS) L^?1 d^?1 was allowed. The pilot-scale system proved to be profitable with a net profit of 10.173 $/ton as higher OLR (?3.0 g (VS) L^?1 d^?1) was used.     

Representation of critical natural capital in China

Traditional means of assessing representativeness of conservation value in protected areas depend on measures of structural biodiversity. The effectiveness of priority conservation areas at representing critical natural capital (CNC) (i.e., an essential and renewable subset of natural capital) remains largely unknown. We analyzed the representativeness of CNC‐conservation priority areas in national nature reserves (i.e., nature reserves under jurisdiction of the central government with large spatial distribution across the provinces) in China with a new biophysical‐based composite indicator approach. With this approach, we integrated the net primary production of vegetation, topography, soil, and climate variables to map and rank terrestrial ecosystems capacities to generate CNC. National nature reserves accounted for 6.7% of CNC‐conservation priority areas across China. Considerable gaps (35.2%) existed between overall (or potential) CNC representativeness nationally and CNC representation in national reserves, and there was significant spatial heterogeneity of representativeness in CNC‐conservation priority areas at the regional and provincial levels. For example, the best and worst representations were, respectively, 13.0% and 1.6% regionally and 28.9% and 0.0% provincially. Policy in China is transitioning toward the goal of an ecologically sustainable civilization. We identified CNC‐conservation priority areas and conservation gaps and thus contribute to the policy goals of optimization of the national nature reserve network and the demarcation of areas critical to improving the representativeness and conservation of highly functioning areas of natural capital. Moreover, our method for assessing representation of CNC can be easily adapted to other large‐scale networks of conservation areas because few data are needed, and our model is relatively simple.     

The Grain of Spatially Referenced Economic Cost and Biodiversity Benefit Data and the Effectiveness of a Cost Targeting Strategy

Facing tight resource constraints, conservation organizations must allocate funds available for habitat protection as effectively as possible. Often, they combine spatially referenced economic and biodiversity data to prioritize land for protection. We tested how sensitive these prioritizations could be to differences in the spatial grain of these data by demonstrating how the conclusion of a classic debate in conservation planning between cost and benefit targeting was altered based on the available information. As a case study, we determined parcel‐level acquisition costs and biodiversity benefits of land transactions recently undertaken by a nonprofit conservation organization that seeks to protect forests in the eastern United States. Then, we used hypothetical conservation plans to simulate the types of ex ante priorities that an organization could use to prioritize areas for protection. We found the apparent effectiveness of cost and benefit targeting depended on the spatial grain of the data used when prioritizing parcels based on local species richness. However, when accounting for complementarity, benefit targeting consistently was more efficient than a cost targeting strategy regardless of the spatial grain of the data involved. More pertinently for other studies, we found that combining data collected over different spatial grains inflated the apparent effectiveness of a cost targeting strategy and led to overestimation of the efficiency gain offered by adopting a more integrative return‐on‐investment approach.     

顾及尺度效应的多源遥感数据“源”“汇”景观的大气霾效应

以武汉市为例,利用多源遥感数据研究城市"源""汇"景观格局与大气霾污染的相关关系.首先,基于武汉市Landsat8数据的地表覆盖分类结果,计算不同尺度下地表覆盖的整体异质性景观指数,选择异质性最大的尺度作为"源""汇"景观分析的最优尺度;在此基础上,用MODIS数据的气溶胶光学厚度(AOD)产品作为大气霾污染程度的度量,基于自相关性较小的"类别层"景观指数,使用地理加权回归分析模型对"源""汇"景观与AOD进行局部回归分析,并在工业区、商业区和居民区3种功能区内分析建筑物对大气霾污染影响的差异.结果表明:6 km是本文分析的最优尺度;大气霾污染的"源"景观为建筑物,"汇"景观为灌木和林地;减小"源"景观面积所占比例、增大其破碎化程度、"源""汇"穿插均匀分布,可以有效减小气溶胶光学厚度,降低大气霾污染;对于武汉市来说,其大气霾污染的主要来源为中心城区的商业区和居民区,即来自于市民生活.针对中心城区要发挥其经济、交通等功能,已有的建设用地不宜大面积改动这一现状,可以采取小幅度优化措施,而对于非建成区可采取建前合理规划"源""汇"景观空间分布的措施.