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Abstract Levee systems are an important part of California’s water infrastructure, engineered to provide resilience against flooding and reduce flood losses. The growth in California is partly associated with costly infrastructure developments that led to population expansion in the levee protected areas. Therefore, potential changes in the flood hazard could have significant socioeconomic consequences over levee protected areas, especially in the face of a changing climate. In this study, we examine the possible impacts of a warming climate on flood hazard over levee protected land in California. We use gridded maximum daily runoff from global circulation models (GCMs) that represent a wide range of variability among the climate projections, and are recommended by the California’s Fourth Climate Change Assessment Report, to investigate possible climate-induced changes. We also quantify the exposure of several critical infrastructure protected by the levee systems (e.g. roads, electric power transmission lines, natural gas pipelines, petroleum pipelines, and railroads) to flooding. Our results provide a detailed picture of change in flood risk for different levees and the potential societal consequences (e.g. exposure of people and critical infrastructure). Levee systems in the northern part of the Central Valley and coastal counties of Southern California are likely to observe the highest increase in flood hazard relative to the past. The most evident change is projected for the northern region of the Central Valley, including Butte, Glenn, Yuba, Sutter, Sacramento, and San Joaquin counties. In the leveed regions of these counties, based on the model simulations of the future, the historical 100-year runoff can potentially increase up to threefold under RCP8.5. We argue that levee operation and maintenance along with emergency preparation plans should take into account the changes in frequencies and intensities of flood hazard in a changing climate to ensure safety of levee systems and their protected infrastructure.

Abstract Levee systems are an important part of California’s water infrastructure, engineered to provide resilience against flooding and reduce flood losses. The growth in California is partly associated with costly infrastructure developments that led to population expansion in the levee protected areas. Therefore, potential changes in the flood hazard could have significant socioeconomic consequences over levee protected areas, especially in the face of a changing climate. In this study, we examine the possible impacts of a warming climate on flood hazard over levee protected land in California. We use gridded maximum daily runoff from global circulation models (GCMs) that represent a wide range of variability among the climate projections, and are recommended by the California’s Fourth Climate Change Assessment Report, to investigate possible climate-induced changes. We also quantify the exposure of several critical infrastructure protected by the levee systems (e.g. roads, electric power transmission lines, natural gas pipelines, petroleum pipelines, and railroads) to flooding. Our results provide a detailed picture of change in flood risk for different levees and the potential societal consequences (e.g. exposure of people and critical infrastructure). Levee systems in the northern part of the Central Valley and coastal counties of Southern California are likely to observe the highest increase in flood hazard relative to the past. The most evident change is projected for the northern region of the Central Valley, including Butte, Glenn, Yuba, Sutter, Sacramento, and San Joaquin counties. In the leveed regions of these counties, based on the model simulations of the future, the historical 100-year runoff can potentially increase up to threefold under RCP8.5. We argue that levee operation and maintenance along with emergency preparation plans should take into account the changes in frequencies and intensities of flood hazard in a changing climate to ensure safety of levee systems and their protected infrastructure.

Many aquatic species with stylar polymorphisms have the capacity for clonal and sexual reproduction and are sensitive to the balance of the two reproductive modes when there are a limited number of mating morphs within a population. This study asked how the clonal and sexual reproductive modes perform in populations that contain only a single morph and where fitness gain through sexual reproduction is rare. In clonal aquatic Nymphoides montana, polymorphic populations normally contain two mating morphs in equal frequencies. Populations are sexually fertile and appear to be maintained by pollen transfer between the two partners. However, in a monomorphic population of N. montana where mating opportunities are unavailable, female and male function is impaired and clonality maintains the population. Here, the consequences of intraspecific variation in sexuality were explored between monomorphic and polymorphic N. montana populations in eastern Australia.Comparative measurements of male and female fertility, total dry mass and genotypic diversity using ISSR markers were made between populations with variable sexuality.Very few seeds were produced in the monomorphic population under natural and glasshouse conditions due to dysfunctional pollen and ovules. Stigma-anther separation was minimal in the monomorphic population, which may be a consequence of the relaxed selective pressures that regulate the maintenance of sexual function. However, clonal reproduction was favoured at the expense of sexual reproduction in the monomorphic population; this may facilitate the establishment of sterility throughout the population via resource reallocation or pleiotropic effects. The ISSR results showed that the monomorphic population was one large, single genotype, unlike the multi-genotypic fertile polymorphic populations. Evolutionary loss of sex in a clonal population in which a mating morph is absent was evident; under these conditions clonal growth may assure reproduction and expand the population via spreading stolons.

Many aquatic species with stylar polymorphisms have the capacity for clonal and sexual reproduction and are sensitive to the balance of the two reproductive modes when there are a limited number of mating morphs within a population. This study asked how the clonal and sexual reproductive modes perform in populations that contain only a single morph and where fitness gain through sexual reproduction is rare. In clonal aquatic Nymphoides montana, polymorphic populations normally contain two mating morphs in equal frequencies. Populations are sexually fertile and appear to be maintained by pollen transfer between the two partners. However, in a monomorphic population of N. montana where mating opportunities are unavailable, female and male function is impaired and clonality maintains the population. Here, the consequences of intraspecific variation in sexuality were explored between monomorphic and polymorphic N. montana populations in eastern Australia.Comparative measurements of male and female fertility, total dry mass and genotypic diversity using ISSR markers were made between populations with variable sexuality.Very few seeds were produced in the monomorphic population under natural and glasshouse conditions due to dysfunctional pollen and ovules. Stigma-anther separation was minimal in the monomorphic population, which may be a consequence of the relaxed selective pressures that regulate the maintenance of sexual function. However, clonal reproduction was favoured at the expense of sexual reproduction in the monomorphic population; this may facilitate the establishment of sterility throughout the population via resource reallocation or pleiotropic effects. The ISSR results showed that the monomorphic population was one large, single genotype, unlike the multi-genotypic fertile polymorphic populations. Evolutionary loss of sex in a clonal population in which a mating morph is absent was evident; under these conditions clonal growth may assure reproduction and expand the population via spreading stolons.

Given the considerable scale of distribution networks in urban and rural areas, as well as the lack of management records, adjustments of switches during the distribution system operation are poorly documented. Such deficiency results in the inaccuracy of models stored in the distribution network automation system, and thus misleads the state estimation. With the emergence of information and communication technology, a large number of the feeder and residential smart meter data are accumulated. Such data can help recognize the operation modes of distribution networks by analyzing the relationships between the on/off states of switches and the voltage correlations among buses. However, the limited quantity and quality of the sampling data restrict the implementation of data-driven recognition. In this paper, a physical-probabilistic-network (PPN) model applied for inferring overall operation mode of distribution networks is proposed. Based on which, a belief propagation-based algorithm is proposed for the inference even under situations when there are only partial bus voltages data available. Meanwhile, the required variable for inference can be reduced from the active trail analysis. Experiment results are used to compare its performance with classic methods and to prove its effectiveness and advantages.

Given the considerable scale of distribution networks in urban and rural areas, as well as the lack of management records, adjustments of switches during the distribution system operation are poorly documented. Such deficiency results in the inaccuracy of models stored in the distribution network automation system, and thus misleads the state estimation. With the emergence of information and communication technology, a large number of the feeder and residential smart meter data are accumulated. Such data can help recognize the operation modes of distribution networks by analyzing the relationships between the on/off states of switches and the voltage correlations among buses. However, the limited quantity and quality of the sampling data restrict the implementation of data-driven recognition. In this paper, a physical-probabilistic-network (PPN) model applied for inferring overall operation mode of distribution networks is proposed. Based on which, a belief propagation-based algorithm is proposed for the inference even under situations when there are only partial bus voltages data available. Meanwhile, the required variable for inference can be reduced from the active trail analysis. Experiment results are used to compare its performance with classic methods and to prove its effectiveness and advantages.

This article examines land-use, market and welfare implications of lignocellulosic bioethanol production in Hawaii to satisfy 10% and 20% of the State's gasoline demand in line with the State's ethanol blending mandate and Alternative Fuels Standard (AFS). A static computable general equilibrium (CGE) model is used to evaluate four alternative support mechanisms for bioethanol. Namely: (i) a federal blending tax credit, (ii) a long-term purchase contract, (iii) a state production subsidy financed by a lump-sum tax and (iv) a state production subsidy financed by an ad valorem gasoline tax. We find that because Hawaii-produced bioethanol is relatively costly, all scenarios are welfare reducing for Hawaii residents: estimated between -0.14% and -0.32%. Unsurprisingly, Hawaii.s economy and its residents fair best under the federal blending tax credit scenario, with a positive impact to gross state product of $49 million. Otherwise, impacts to gross state product are negative (up to -$63 million). We additionally find that Hawaii-based bioethanol is not likely to offer substantial greenhouse gas emissions savings in comparison to imported biofuel, and as such the policy cost per tonne of emissions displaced ranges between $130 to $2,100/tonne of CO2e. The policies serve to increase the value of agricultural lands, where we estimate that the value of pasture land could increase as much as 150% in the 20% AFS scenario.

This article examines land-use, market and welfare implications of lignocellulosic bioethanol production in Hawaii to satisfy 10% and 20% of the State's gasoline demand in line with the State's ethanol blending mandate and Alternative Fuels Standard (AFS). A static computable general equilibrium (CGE) model is used to evaluate four alternative support mechanisms for bioethanol. Namely: (i) a federal blending tax credit, (ii) a long-term purchase contract, (iii) a state production subsidy financed by a lump-sum tax and (iv) a state production subsidy financed by an ad valorem gasoline tax. We find that because Hawaii-produced bioethanol is relatively costly, all scenarios are welfare reducing for Hawaii residents: estimated between -0.14% and -0.32%. Unsurprisingly, Hawaii.s economy and its residents fair best under the federal blending tax credit scenario, with a positive impact to gross state product of $49 million. Otherwise, impacts to gross state product are negative (up to -$63 million). We additionally find that Hawaii-based bioethanol is not likely to offer substantial greenhouse gas emissions savings in comparison to imported biofuel, and as such the policy cost per tonne of emissions displaced ranges between $130 to $2,100/tonne of CO2e. The policies serve to increase the value of agricultural lands, where we estimate that the value of pasture land could increase as much as 150% in the 20% AFS scenario.