Assessing the Frequency of Floods in Ice-Covered Rivers under a Changing Climate: Review of Methodology

Ice-influenced hydrologic and hydrodynamic processes often cause floods in cold regions of the globe. These floods are typically associated with ice jams and can have negative socio-economic impacts, while their impacts on riverine ecosystems can be both detrimental and beneficial. Several methods have been proposed for constructing frequency distributions of ice-influenced annual peak stages where historical data are scarce, or for estimating future frequencies under different climate change scenarios. Such methods rely on historical discharge data, which are generally easier to obtain than peak stages. Future discharges can be simulated via hydrological models, driven by climate-model output. Binary sequences of historical flood/no-flood occurrences have been studied using logistic regression on physics-based explanatory variables or exclusively weather-controlled proxies, bypassing the hydrological modelling step in climate change projections. Herein, background material on relevant river ice processes is presented first, followed by descriptions of various proposed methods to quantify flood risk and assess their advantages and disadvantages. Discharge-based methods are more rigorous; however, projections of future flood risk can benefit from improved hydrological simulations of winter and spring discharges. The more convenient proxy-based regressions may not adequately reflect the controlling physics-based variables, while extrapolation of regression results to altered climatic conditions entails further uncertainty.

Influence of Warming and Atmospheric Circulation Changes on Multidecadal European Flood Variability

European flood frequency and intensity change on a multidecadal scale. Floods were more frequent in the 19th (Central Europe) and early 20th century (Western Europe) than during the mid-20th century and again more frequent since the 1970s. The causes of this variability are not well understood and the relation to climate change is unclear. Palaeoclimate studies from the northern Alps suggest that past flood-rich periods coincided with cold periods. In contrast, some studies suggest that more floods might occur in a future, warming world. Here we reconcile the apparent contradiction by addressing and quantifying the contribution of atmospheric processes to multidecadal flood variability. For this, we use long series of annual peak streamflow, daily weather data, reanalyses, and reconstructions. We show that both changes in atmospheric circulation and moisture content affected multidecadal changes of annual peak streamflow in Central and Western Europe over the past two centuries. We find that during the 19th and early 20th century, atmospheric circulation changes led to high peak values of moisture flux convergence. The circulation was more conducive to strong and long-lasting precipitation events than in the mid-20th century. These changes are also partly reflected in the seasonal mean circulation and reproduced in atmospheric model simulations, pointing to a possible role of oceanic variability. For the period after 1980, increasing moisture content in a warming atmosphere led to extremely high moisture flux convergence. Thus, the main atmospheric driver of flood variability changed from atmospheric circulation variability to water vapour increase.

Projections of snow water equivalent using a process-based energy balance snow model in southwestern British Columbia

Information about snow water equivalent in southwestern British Columbia is used for flood management, agriculture, fisheries, and water resource planning. This study evaluates whether a process-based, energy balance snow model supplied with high-resolution statistically downscaled temperature and precipitation data can effectively simulate snow water equivalent (SWE) in the mountainous terrain of this region. Daily values of SWE from 1951 to 2018 are simulated at 1 km resolution and evaluated using a reanalysis SWE product (SNODAS), manual snow survey measurements at 41 sites, and automated snow pillows at six locations in the study region. Simulated SWE matches observed inter-annual variability well (R2 > 0.8 for annual maximum SWE) but peak SWE biases of 20% to 40% occur at some sites in the study domain, and higher biases occur where observed SWE is very low. Modelled SWE displays lower bias compared to SNODAS reanalysis at most manual survey locations. Future projections for the study area are produced using 12 downscaled climate model simulations and used to illustrate the impacts of climate change on SWE at 1°C, 2°C, and 3°C of warming. Model results are used to quantify spring SWE changes at different elevations of the Whistler mountain ski resort, and the sensitivity of annual peak SWE in Metro Vancouver municipal watersheds to moderate temperature increases. The results illustrate both the potential utility of a process-based snow model, and identify areas where the input meteorological variables could be improved.

Fall Waterfowl Use of Bridgeport Reservoir, Mono County, California

Aerial surveys from 2003 to 2019 documented the abundance of waterfowl at Bridgeport Reservoir in Mono County, California, from September through mid-November. Waterfowl totals at Bridgeport Reservoir averaged 33,106 ± 4050 (standard error) in the fall. Annual peak counts averaged 10,474 ± 1349, ranging from a low of 2583 in 2014 to the highest single-day count of 23,150 in 2005. Bridgeport Reservoir is a man-made water body in the intermountain West that waterfowl use primarily a mid-migration stopover site, with peak numbers occurring in September. The dominant waterfowl species, the Northern Shoveler (Spatula clypeata), Gadwall (Mareca strepera), Mallard (Anas platyrhynchos), Northern Pintail (A. acuta), and Green-winged Teal (A. crecca), showed both unimodal and bimodal migration chronologies. Regional drought, as indicated by the Palmer drought severity index, combined with a downward trend in waterfowl numbers explained 61.4% of annual variation in fall waterfowl totals. These data may allow future assessment of change in waterfowl abundance at Bridgeport Reservoir in the context of local or regional conditions, and as influenced by climate change.

Oscillation, synchrony, and multi-factor patterns between cereal aphids and parasitoid populations in southern Brazil

In different parts of the world, aphid populations and their natural enemies are influenced by landscapes and climate. In the Neotropical region, few long-term studies have been conducted, maintaining a gap for comprehension of the effect of meteorological variables on aphid population patterns and their parasitoids in field conditions. This study describes the general patterns of oscillation in cereal winged aphids and their parasitoids, selecting meteorological variables and evaluating their effects on these insects. Aphids exhibit two annual peaks, one in summer–fall transition and the other in winter-spring transition. For parasitoids, the highest annual peak takes place during winter and a second peak occurs in winter–spring transition. Temperature was the principal meteorological regulator of population fluctuation in winged aphids and parasitoids during the year. The favorable temperature range is not the same for aphids and parasitoids. For aphids, temperature increase resulted in population growth, with maximum positive effect at 25°C. Temperature also positively influenced parasitoid populations, but the growth was asymptotic around 20°C. Although rainfall showed no regulatory function on aphid seasonality, it influenced the final number of insects over the year. The response of aphids and parasitoids to temperature has implications for trophic compatibility and regulation of their populations. Such functions should be taken into account in predictive models.

Inconsistency of Global Vegetation Dynamics Driven by Climate Change: Evidences from Spatial Regression

Global greening over the past 30 years since 1980s has been confirmed by numerous studies. However, a single-dimensional indicator and non-spatial modelling approaches might exacerbate uncertainties in our understanding of global change. Thus, comprehensive monitoring for vegetation’s various properties and spatially explicit models are required. In this study, we used the newest enhanced vegetation index (EVI) products of Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 to detect the inconsistency trend of annual peak and average global vegetation growth using the Mann–Kendall test method. We explored the climatic factors that affect vegetation growth change from 2001 to 2018 using the spatial lag model (SLM), spatial error model (SEM) and geographically weighted regression model (GWR). The results showed that EVImax and EVImean in global vegetated areas consistently showed linear increasing trends during 2001–2018, with the global averaged trend of 0.0022 yr−1 (p < 0.05) and 0.0030 yr−1 (p < 0.05). Greening mainly occurred in the croplands and forests of China, India, North America and Europe, while browning was almost in the grasslands of Brazil and Africa (18.16% vs. 3.08% and 40.73% vs. 2.45%). In addition, 32.47% of the global vegetated area experienced inconsistent trends in EVImax and EVImean. Overall, precipitation and mean temperature had positive impacts on vegetation variation, while potential evapotranspiration and vapour pressure had negative impacts. The GWR revealed that the responses of EVI to climate change were inconsistent in an arid or humid area, in cropland or grassland. Climate change could affect vegetation characteristics by changing plant phenology, consequently rendering the inconsistency between peak and mean greening. In addition, anthropogenic activities, including land cover change and land use management, also could lead to the differences between annual peak and mean vegetation variations.

Analisis Energi Baru Terbarukan Untuk Sistem Kelistrikan Desa

Electricity is a primary need for society. Energy that will never run out of availability is energy from solar radiation. Indonesia is an agricultural country that can utilize alternative energy by utilizing biomass energy, one of which is rice husk and straw waste. Based on data from the BMKG Paloh Station, Sambas Regency has a fairly large intensity of sunlight because it is located just below the equator. The intensity of light in the dry season can reach 6 hours in a period of 8 hours of sunlight, namely from 8.00 - 16.00. The resulting energy conversion is 38.01 mj/m2/day. Meanwhile, for the biomass potential from the BPS data of Sambas Regency in Tebas District, there are 6,730 ha of rice fields, which can produce 403 tons of rice husk and straw waste in one day for 1 year and can produce 5 million Mj/day . The results of the conversion analysis of the optimization of renewable energy for power plants that have an annual peak power of 45kW and daily energy consumption of 330kWh/day obtained the most optimal potential for rice husk and straw waste, which requires an initial capital of $ 67,120 with a total net present minimum cost. Electricity from the system cost is also minimum at US$ 0.005/kWh. And in technical economic analysis, modeling this system requires a payback period of about 11 years without grid bills and 5 years with grid bills. Meanwhile, conversion using PV requires larger capital and longer payback.