In this study, an integrated simulation-based allocation modeling system (ISAMS) is developed for identifying water resources management strategies in response to climate change. The ISAMS incorporates global climate models (GCMs), a semi-distributed land use-based runoff process (SLURP) model, and a multistage interval-stochastic programming (MISP) approach within a general framework. The ISAMS can not only handle uncertainties expressed as probability distributions and interval values but also reveal climate change impacts on water resources allocation under different projections of GCMs. The ISAMS is then applied to the Kaidu-kongque watershed with cold arid characteristics in the Tarim River Basin (the largest inland watershed basin in China) for demonstrating its efficiency. Results reveal that different climate change models corresponding to various projections (e.g., precipitation and temperature) would lead to changed water resources allocation patterns. Variations in water availability and demand due to uncertainties could result in different water allocation targets and shortages. A variety of decision alternatives about water allocations adaptive to climate change are generated under combinations of different global climate models and ecological water release plans. These findings indicate that understanding the uncertainties in water resources system, building adaptive methods for generating sustainable water allocation patterns, and taking actions for mitigating water shortage problems are key adaptation strategies responding to climate change. 相似文献
Yangtze River Delta(YRD) area is one of the important economic zones in China. However,this area faces increasing environmental problems. In this study, we use ground-based multi-axis differential optical absorption spectroscopy(MAX-DOAS) network in Eastern China to retrieve variations of NO_2, SO_2, and formaldehyde(HCHO) in the YRD area. Three cities of YRD(Hefei, Nanjing, and Shanghai) were selected for long-term observations. This paper presents technical performance and characteristics of instruments, their distribution in YRD, and results of vertical column densities(VCDs) and profiles of NO_2, SO_2, and HCHO.Average diurnal variations of tropospheric NO_2 and SO_2 in different seasons over the three stations yielded minimum values at noon or in the early afternoon, whereas tropospheric HCHO reached the maximum during midday hours. Slight reduction of the pollutants in weekends occurred in all the three sites. In general trace gas concentrations gradually reduced from Shanghai to Hefei. Tropospheric VCDs of NO_2, SO_2, and HCHO were compared with those from Ozone Monitoring Instrument(OMI) satellite observations, resulting in R~2 of 0.606, 0.5432, and 0.5566, respectively. According to analysis of regional transports of pollutants, pollution process happened in YRD under the north wind with the pollution dissipating in the southeast wind. The feature is significant in exploring transport of tropospheric trace gas pollution in YRD, and provides basis for satellite and model validation. 相似文献
This study explored the national hydrogen refueling infrastructure requirement along major United States (US) interstate highway corridors to support the deployment of fuel cell electric trucks (FCETs) for the national long-haul trucking fleet. Given the long-haul trucking shipment demand in 2025 projected by the Freight Analysis Framework, locations and capacities of hydrogen stations were identified for inter-zone freight flows, and the total daily refueling demand was estimated for intra-zone flows for each FAF zone. Based on the infrastructure deployment results, we conducted an economic feasibility analysis of FCETs by evaluating the total ownership cost. We found that when the FCET penetration is relatively high (e.g., 10% penetration), FCETs become more competitive in terms of fuel cost and idling cost and could be economic viable if the incremental vehicle cost is reduced to meet the near-term FCET technology cost targets and the liquefaction cost is reduced to an optimal case. We also observed that the station cost depends on regional factors, particularly regional demand, which is used to determine station capacity. Thus, one possible strategy for station roll-out is to have early investment in target regions where station costs are expected to be relatively low such as the Pacific and West South Central regions.