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1.
ABSTRACTThe purpose of this study is to examine local level spatiotemporal rainfall and temperature variability in drought-prone districts of rural Sidama, Central Rift Valley region of Ethiopia. The study used 129 gridded monthly rainfall and temperature data of 32 years (1983–2014). The gridded rainfall and temperature records were encoded into GIS software and evaluated through different statistical and geospatial techniques. Mann-Kendal rank test and F distribution tests were used to test temporal and spatial statistical significance, respectively, of the data. The analysis revealed that Belg and Kiremt are the main rainfall seasons, constituting 81% of the annual rainfall. Although annual, Kiremt, and Belg rainfall amounts appear to have decreased over time, the decreasing trend is statistically significant only for Belg rainfall records. On the other hand, rainfall standard anomaly results indicated seven droughts of different magnitudes: one extreme, two severe, and four moderate. The study also revealed increasing temperature trends over the years under consideration that are statistically significant. The findings of this study on rainfall contradict other findings obtained around the study area. Thus, climate change adaptations need to focus on location-specific climate data analysis so that the intended adaptive interventions can be successful. 相似文献
2.
Cristián Frêne Juan J. Armesto Freddy Véliz Fernando D. Alfaro Kathleen C. Weathers 《水文研究》2021,35(5):e14175
The variability of rainfall-dependent streamflow at catchment scale modulates many ecosystem processes in wet temperate forests. Runoff in small mountain catchments is characterized by a quick response to rainfall pulses which affects biogeochemical fluxes to all downstream systems. In wet-temperate climates, water erosion is the most important natural factor driving downstream soil and nutrient losses from upland ecosystems. Most hydrochemical studies have focused on water flux measurements at hourly scales, along with weekly or monthly samples for water chemistry. Here, we assessed how water and element flows from broad-leaved, evergreen forested catchments in southwestern South America, are influenced by different successional stages, quantifying runoff, sediment transport and nutrient fluxes during hourly rainfall events of different intensities. Hydrograph comparisons among different successional stages indicated that forested catchments differed in their responses to high intensity rainfall, with greater runoff in areas covered by secondary forests (SF), compared to old-growth forest cover (OG) and dense scrub vegetation (CH). Further, throughfall water was greatly nutrient enriched for all forest types. Suspended sediment loads varied between successional stages. SF catchments exported 455 kg of sediments per ha, followed by OG with 91 kg/ha and CH with 14 kg/ha, corresponding to 11 rainfall events measured from December 2013 to April 2014. Total nitrogen (TN) and phosphorus (TP) concentrations in stream water also varied with rainfall intensity. In seven rainfall events sampled during the study period, CH catchments exported less nutrients (46 kg/ha TN and 7 kg/ha TP) than SF catchments (718 kg/ha TN and 107 kg/ha TP), while OG catchments exported intermediate sediment loads (201 kg/ha TN and 23 kg/ha TP). Further, we found significant effects of successional stage attributes (vegetation structure and soil physical properties) and catchment morphometry on runoff and sediment concentrations, and greater nutrients retention in OG and CH catchments. We conclude that in these southern hemisphere, broad-leaved evergreen temperate forests, hydrological processes are driven by multiple interacting phenomena, including climate, vegetation, soils, topography, and disturbance history. 相似文献
3.
Costijn Zwart Niels C. Munksgaard Alain Protat Naoyuki Kurita Dionisia Lambrinidis Michael I. Bird 《水文研究》2018,32(15):2296-2303
This work provides a comprehensive physically based framework for the interpretation of the north Australian rainfall stable isotope record (δ18O and δ2H). Until now, interpretations mainly relied on statistical relationships between rainfall amount and isotopic values on monthly timescales. Here, we use multiseason daily rainfall stable isotope and high resolution (10 min) ground‐based C‐band polarimetric radar data and show that the five weather types (monsoon regimes) that constitute the Australian wet season each have a characteristic isotope ratio. The data suggest that this is not only due to changes in regional rainfall amount during these regimes but, more importantly, is due to different rain and cloud types that are associated with the large scale circulation regimes. Negative (positive) isotope anomalies occurred when stratiform rainfall fractions were large (small) and the horizontal extent of raining areas were largest (smallest). Intense, yet isolated, convective conditions were associated with enriched isotope values whereas more depleted isotope values were observed when convection was widespread but less intense. This means that isotopic proxy records may record the frequency of which these typical wet season regimes occur. Positive anomalies in paleoclimatic records are most likely associated with periods where continental convection dominates and convection is sea‐breeze forced. Negative anomalies may be interpreted as periods when the monsoon trough is active, convection is of the oceanic type, less electric, and stratiform areas are wide spread. This connection between variability of rainfall isotope anomalies and the intrinsic properties of convection and its large‐scale environment has important implications for all fields of research that use rainfall stable isotopes. 相似文献
4.
Peng Yue Fan Gao Boyi Shangguan Zheren Yan 《International journal of geographical information science》2020,34(11):2243-2274
ABSTRACT High performance computing is required for fast geoprocessing of geospatial big data. Using spatial domains to represent computational intensity (CIT) and domain decomposition for parallelism are prominent strategies when designing parallel geoprocessing applications. Traditional domain decomposition is limited in evaluating the computational intensity, which often results in load imbalance and poor parallel performance. From the data science perspective, machine learning from Artificial Intelligence (AI) shows promise for better CIT evaluation. This paper proposes a machine learning approach for predicting computational intensity, followed by an optimized domain decomposition, which divides the spatial domain into balanced subdivisions based on the predicted CIT to achieve better parallel performance. The approach provides a reference framework on how various machine learning methods including feature selection and model training can be used in predicting computational intensity and optimizing parallel geoprocessing against different cases. Some comparative experiments between the approach and traditional methods were performed using the two cases, DEM generation from point clouds and spatial intersection on vector data. The results not only demonstrate the advantage of the approach, but also provide hints on how traditional GIS computation can be improved by the AI machine learning. 相似文献
5.
《Astroparticle Physics》2002,16(4):183-386
Frequency distributions of local muon densities in high-energy extensive air showers (EAS) are presented as signature of the primary cosmic ray energy spectrum in the knee region. Together with the gross shower variables like shower core position, angle of incidence, and the shower sizes, the KASCADE experiment is able to measure local muon densities for two different muon energy thresholds. The spectra have been reconstructed for various core distances, as well as for particular subsamples, classified on the basis of the shower size ratio Nμ/Ne. The measured density spectra of the total sample exhibit clear kinks reflecting the knee of the primary energy spectrum. While relatively sharp changes of the slopes are observed in the spectrum of EAS with small values of the shower size ratio, no such feature is detected at EAS of large Nμ/Ne ratio in the energy range of 1–10 PeV. Comparing the spectra for various thresholds and core distances with detailed Monte Carlo simulations the validity of EAS simulations is discussed. 相似文献
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The kinetics of the reactions of C2H radical with ethane (k1), propane (k2), and n-butane (k3) are studied over the temperature range of T = 96-296 K with a pulsed Laval nozzle apparatus that utilizes a pulsed laser photolysis-chemiluminescence technique. The C2H decay profiles in the presence of both the alkane reactant and O2 are monitored by the CH(A2Δ) chemiluminescence tracer method. The results, together with available literature data, yield the following Arrhenius expressions: k1(T) = (0.51 ± 0.06) × 10−10 exp[(−76 ± 30)K/T] cm3 molecule−1 s−1 (T = 96-800 K), k2(T) = (0.98 ± 0.32) × 10−10exp[(−71 ± 60)K/T] cm3 molecule−1 s−1 (T = 96-361 K), and k3(T) = (1.23 ± 0.26) × 10−10 cm3 molecule−1 s−1 (T = 96-297 K). At T = 296 K, k1 is measured as a function of total pressure and has little or no pressure dependence. The results from this work support a direct hydrogen abstraction mechanism for the title reactions. Implications to the atmospheric chemistry of Titan are discussed. 相似文献