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21.
Natural Hazards - Flooding constitutes the most predominant natural disaster in India. The degree and causes of vulnerability to flood risk vary by society, geographical region and over time. The... 相似文献
22.
This paper examines how people explain reasons and impacts of environmental change in the low-rain savanna of the central Sudan and mountainous forest lands of northern Thailand. The explanations are analyzed by using the concept of environmental literacy, which refers to the people’s ability to grasp the environment and its interactions. The paper aims to study people’s conceptions of the environment, which compose one factor in directing their behavior. For the study, rural inhabitants in the State of North Kordofan, the Sudan, and the Chiang Mai Province in Thailand were interviewed.It was noted that an individual’s capability to understand the environment is alone insufficient to address environmental problems because the efficient alleviation of the problems requires collective actions at all levels, and because of factors beyond an individual’s control. However, the results supported the assumption that the local people have knowledge of their environment that may help in developing sustainable environmental management practices. The main advantages of using the environmental literacy concept are argued to be its dynamic and synthetic essence, its link to sustainable behavior, and wide applicability in various contexts within heterogeneous communities. 相似文献
23.
Spatial variability and rainfall characteristics of Kerala 总被引:1,自引:0,他引:1
Geographical regions of covariability in precipitation over the Kerala state are exposed using factor analysis. The results
suggest that Kerala can be divided into three unique rainfall regions, each region having a similar covariance structure of
annual rainfall. Stations north of 10‡N (north Kerala) fall into one group and they receive more rainfall than stations south
of 10‡N (south Kerala). Group I stations receive more than 65% of the annual rainfall during the south-west monsoon period,
whereas stations falling in Group II receive 25–30% of annual rainfall during the pre-monsoon and the north-east monsoon periods.
The meteorology of Kerala is profoundly influenced by its orographical features, however it is difficult to make out a direct
relationship between elevation and rainfall. Local features of the state as reflected in the rainfall distribution are also
clearly brought out by the study. 相似文献
24.
Anu Kisand Anna-Liisa Kirsi Kristiina Ehapalu Tiiu Alliksaar Atko Heinsalu Ilmar Tõnno Aina Leeben Peeter Nõges 《Journal of Paleolimnology》2017,58(1):43-56
We studied high-resolution stratigraphy of phosphorus (P) forms in the Holocene sediments of large shallow Lake Peipsi (Estonia/Russia) in order to evaluate the lake ecosystem response to environmental changes and track the lake’s eutrophication history. We distinguished four main periods in the history of Lake Peipsi, each having likely different factors responsible for the distribution pattern of P fractions in the sediment record. We suggest that in the oldest period, from ca. 10.4 up to 7.3 cal ka BP, the sediment composition was mainly determined by rising water level, the second period dated 7.3–2.3 cal ka BP was governed mainly by stable hydrology and P loading, while the third period between 2.3 and 0 cal ka BP was primarily influenced by emerging anthropogenic impact. The sediments from the last period since 1950 are subject of ongoing diagenetic processes but still reflect rapid eutrophication of the lake. Comparison of the results with periods derived from other sediment proxies proved the usability of P fractions stratigraphy in reconstruction of the development of lakes. 相似文献
25.
Seafloor sediment classification based on echo characteristics obtained from single-beam echosounder is very useful in remote
and instant sediment classification. Results of different classification techniques using such data provide robust results
when the acoustic beam has a normal incidence with the seabottom. This may not always be true and show poor classification,
with the data acquired during rough sea periods corresponding to both oblique and normal incidence of the acoustic pulse,
due to roll and pitch motion of the ship. In the present study, an attempt is made to exploit the artificial neural network
(ANN) techniques for better classification with such data. Learning Vector Quantisation (LVQ) is a supervised learning algorithm
of ANN that is found to be an effective tool and show good performance. The input data to the network include the roughness
index (E1) and hardness index (E2) derived from echo characteristics. The network utilizes the competitive learning, a distance
function in the first layer and a linear function in the second layer. The network was tried with a different size of hidden
neurons and training data size to see the influence on classification. It is found that with ten neurons in the first layer
and four neurons in the second layer good performance in classification for the data was achieved. 相似文献
26.
Peeter Nõges Lea Tuvikene Tiina Nõges Anu Kisand 《Aquatic Sciences - Research Across Boundaries》1999,61(2):168-182
27.
Laura Duncanson Wenli Huang Kristofer Johnson Anu Swatantran Ronald E. McRoberts Ralph Dubayah 《Carbon balance and management》2017,12(1):18
Background
Carbon accounting in forests remains a large area of uncertainty in the global carbon cycle. Forest aboveground biomass is therefore an attribute of great interest for the forest management community, but the accuracy of aboveground biomass maps depends on the accuracy of the underlying field estimates used to calibrate models. These field estimates depend on the application of allometric models, which often have unknown and unreported uncertainties outside of the size class or environment in which they were developed.Results
Here, we test three popular allometric approaches to field biomass estimation, and explore the implications of allometric model selection for county-level biomass mapping in Sonoma County, California. We test three allometric models: Jenkins et al. (For Sci 49(1): 12–35, 2003), Chojnacky et al. (Forestry 87(1): 129–151, 2014) and the US Forest Service’s Component Ratio Method (CRM). We found that Jenkins and Chojnacky models perform comparably, but that at both a field plot level and a total county level there was a ~ 20% difference between these estimates and the CRM estimates. Further, we show that discrepancies are greater in high biomass areas with high canopy covers and relatively moderate heights (25–45 m). The CRM models, although on average ~ 20% lower than Jenkins and Chojnacky, produce higher estimates in the tallest forests samples (> 60 m), while Jenkins generally produces higher estimates of biomass in forests < 50 m tall. Discrepancies do not continually increase with increasing forest height, suggesting that inclusion of height in allometric models is not primarily driving discrepancies. Models developed using all three allometric models underestimate high biomass and overestimate low biomass, as expected with random forest biomass modeling. However, these deviations were generally larger using the Jenkins and Chojnacky allometries, suggesting that the CRM approach may be more appropriate for biomass mapping with lidar.Conclusions
These results confirm that allometric model selection considerably impacts biomass maps and estimates, and that allometric model errors remain poorly understood. Our findings that allometric model discrepancies are not explained by lidar heights suggests that allometric model form does not drive these discrepancies. A better understanding of the sources of allometric model errors, particularly in high biomass systems, is essential for improved forest biomass mapping.28.
29.
P. V. Joseph Anu Simon Venu G. Nair Aype Thomas 《Journal of Earth System Science》2004,113(2):139-150
Time series of daily averaged rainfall of about 40 rain gauge stations of south Kerala, situated at the southern-most part
of peninsular India between latitudes about 8‡N and 10‡N were subjected to Wavelet Analysis to study the Intra Seasonal Oscillation
(ISO) in the rainfall and its inter-annual variability. Of the 128 days, 29th May to 3rd October of each of the 95 years 1901-1995
were analysed. We find that the period of ISO does not vary during a monsoon season in most of the years, but it has large
inter-annual variability in the range 23 to 64 days. Period-wise, the years cluster into two groups of ISO, the SHORT consisting
of periods 23, 27 and 32 days and the LONG with a single period of 64 days, both the sets at a significance level of 99%.
During the 95 years at this level of significance there are 44 years with SHORT and 20 years with LONG periods. 11 years have
no ISO even at the 90% level of significance.
We composited NCEP SST anomalies of the summer monsoon season June to September for two groups of years during the period
1965–1993. The first group is of 5 years with a LONG ISO period of 64 days for south Kerala rainfall at significance level
of 99% and the second group is of 12 years with SHORT ISO periods of 23, 27 and 32 days at the same level of significance.
The SST anomaly for the LONG (SHORT) ISO resembles that for an El Nino (La Nina). 相似文献
30.
This study presents a multiproxy record of Holocene environmental change in the region East of the Pechora Delta. A peat plateau profile (Ortino II) is analyzed for plant macrofossils, sediment type, loss on ignition, and radiocarbon dating. A paleosol profile (Ortino III) is described and radiocarbon dated. A previously published peat plateau profile (Ortino I) was analyzed for pollen and conifer stomata, loss on ignition, and radiocarbon dating. The interpretation of the latter site is reassessed in view of new evidence. Spruce immigrated to the study area at about 8900 14C yr B.P. Peatland development started at approximately the same time. During the Early Holocene Hypsithermal taiga forests occupied most of the present East-European tundra and peatlands were permafrost free. Cooling started after 5000 14C yr B.P., resulting in a retreat of forests and permafrost aggradation. Remaining forests disappeared from the study area around 3000 14C yr B.P., coinciding with more permafrost aggradation. The retreat of forests resulted in landscape instability and the redistribution of sand by eolian activity. The displacement of the Arctic forest line and permafrost zones indicates a warming of at least 2–3°C in mean July and annual temperatures during the Early Holocene. At least two cooling periods can be recognized for the second half of the Holocene, starting at about 4800 and 3000 14C yr B.P. 相似文献