几种碳氢燃料与空气混合物相对爆轰敏感度的测定

利用矩形激波管测定了几种碳氢燃料（丁烷，石脑油，ＪＣ５，戊烯，已烯）直接起爆时形成爆轰所需的临界起爆能，并以化学当量比的乙炔氧气混合物直接起爆形成爆轰的临界起爆能为基准，定义了一个无量纲常数Ｄｈ。再利用这个常数，比较了这几种燃料的相对爆轰敏感度。     

Riparian buffers and potentially unstable ground

The spatial coincidence between riparian buffers of various widths and extents and potentially unstable ground was quantified using a physically based model for shallow landslide initiation and GIS for two watersheds on the Olympic Peninsula, Washington, USA. The proportion of the potentially unstable ground in each watershed within riparian buffers is a function of both buffer width and the extent of the stream channel network being buffered. While current buffers required by Washington State cover less than 5% of the potentially unstable ground, buffering all stream channels in these watersheds with 100-m buffers covered 75%–90% of the potentially unstable areas. Our analyses further show that: (1) riparian buffers are not efficient mechanisms for protecting potentially unstable ground, and (2) identifying potentially unstable ground using a physically based model should prove more effective for designing methods to reduce shallow landsliding hazards than relying on extensive buffer zones along stream channels.     

ESTIMATION OF ENERGY REQUIREMENTS OF MORNING DEW EVAPORATION FROM LEAF SURFACES1

ABSTRACT: Evapotranspiration from vegetation is generally computed without consideration for early morning energy loss involved in drying wet leaf surfaces. In humid areas where dew formation is frequent, estimation of energy requirements for evaporating dew should be of interest. In this study, sensible heat flux (H) was computed from wind and temperature profile measurements over the study site. A leaf wetness sensor was used to measure the duration of evaporation from an exposed leaf surface, and net radiation was measured with a radiometer. The energy flux during the period of wet leaf surface evaporation was integrated over time. A cattail lysimeter situated at the site indicated the time when evapotranspiration started after wet leaves were dry. The energy requirements to dry an exposed wet leaf surface was estimated using energy balance methods. The mean value based on 44 days of observations from mid February to early May of 1993 indicates that the energy required to evaporate dew from openly exposed wet leaves was 5 percent of the total daily evapotranspiration of cattails with a coefficient of variation of 0.72. The mean time required to evaporate dew from exposed leaf surfaces from the onset of positive net radiation was 78 minutes. The mean dew evaporation in a morning from an exposed leaf surface was 0.16 mm with a maximum value of 0.41 mm. The energy required to dry wet leaves is a factor that should be considered when modeling evapotranspiration at hourly or shorter time intervals. Also, physical evapotranspiration models need to account for energy requirements for drying dew and rainfall wetted leaves.     

陕西潼关金矿‘94人工泥石流灾害研究

本文研究了１９９４年７月１１日发生在陕西潼关县西峪金矿区，因暴雨引发的人工泥石流所酿成的特大灾难。通过对形成泥石流的地质、地貌、降雨和人为等其他形成的原因进行了分析。提出了今后应加强的预防措施，这对合理开发金矿资源、预防泥石流灾害，有着十分重要的科学意义。     

Effects of increased wood energy consumption on carbon storage in forests of the United States

Large but feasible increases that have been projected for the production of wood energy in the United States can be expected to significantly alter the current carbon storage patterns in US forest vegetation. The 1976 net wood increment left after forest cutting equals about 136 × 10⁶ tons of carbon/year, with about 60% of the increment found in merchantable trees, and the remainder in nonmerchantable components.Achieving 5–10 quads of wood energy beyond 1976 levels by the year 2010 can significantly change current carbon storage patterns with the magnitude of change dependent on the extent of residue harvest to meet energy goals, and the rate of future forest growth. Complete loss of the apparent net wood increment is a possible outcome.Although the future growth and harvest situation cannot be known now, a range of possible scenarios suggests that US forests in the year 2010 will store much less carbon than today, thus significantly changing their role in the global carbon cycle.     

FLOOD ROUTING THROUGH A FLAT,COMPLEX FLOODPLAIN USING A ONE-DIMENSIONAL UNSTEADY FLOW COMPUTER PROGRAM1

ABSTRACT: The routing of flood waves through the Central Basin of the Passaic River in New Jersey is complex because of flat gradients and flow reversals. The one-dimensional unsteady flow program DWOPER, developed by the National Weather Service, was used to simulate flood wave movement through the Basin. A historical event was used for calibration and two synthetic events were simulated. Boundary conditions consisted of discharge hydrographs at inflow points to the study area, local flow hydrographs at interior points, and a stage discharge relation for flow over the crest of a diversion dam at the basin outlet. Manning's n values were adjusted based on stage and discharge data for the historical event; however, verification data were not available for events comparable in magnitude to the synthetic events. Aspects of the investigation reported include techniques for characterizing the flow system, model calibration, techniques for representing a tunnel diversion, and simulation results.     

Climatic and stream-flow controls on tree growth in a Western montane riparian forest

Humans have severely impacted riparian ecosystems through water diversions, impoundments, and consumptive uses. Effective management of these important areas is becoming an increasingly high priority of land managers, particularly as municipal, industrial, and recreational demands for water increase. We examined radial tree growth of four riparian tree species (Pinus jeffreyi, Populus trichocarpa, Betula occidentalis, and Pinus monophylla) along Bishop Creek, California, and developed models relating basal area increment (BAI) and relative basal area increment (RBAI) to climatic and stream flow variables. Between years 1995–1999, univariate regression analysis with stream flow explained 29 to 61% of the variation in BAI and RBAI among all species except P. trichocarpa; growth by P. trichocarpa was not significantly related to stream flows over this period. Stepwise linear regression indicated that species responded differently to climatic variables, and models based on these variables explained between 33 to 86% of variation in BAI and RBAI during the decade of the 1990s. We examined branch growth of P. trichocarpa for sensitivity to differences in stream flow regimes and found that annual branch growth did not vary between a high- and low-flow site, but that annual branch growth was significantly higher in wet years with greater stream flows. Our results support the establishment of site-specific management goals by land managers that take into account all of the important tree species present in riparian ecosystems and their differential responses to altered hydrologic condition. Instream flow requirements for maintaining tree growth and vigor are only one of the species-specific responses that need to be evaluated, and these assessments should attempt to separate experimentally stream-flow (managed) controls from climatic (unmanaged) controls on growth.     

COMPARISON OF PROCESS‐BASED AND ARTIFICIAL NEURAL NETWORK APPROACHES FOR STREAMFLOW MODELING IN AN AGRICULTURAL WATERSHED1

ABSTRACT: The performance of the Soil and Water Assessment Tool (SWAT) and artificial neural network (ANN) models in simulating hydrologic response was assessed in an agricultural watershed in southeastern Pennsylvania. All of the performance evaluation measures including Nash‐Sutcliffe coefficient of efficiency (E) and coefficient of determination (R²) suggest that the ANN monthly predictions were closer to the observed flows than the monthly predictions from the SWAT model. More specifically, monthly streamflow E and R² were 0.54 and 0.57, respectively, for the SWAT model calibration period, and 0.71 and 0.75, respectively, for the ANN model training period. For the validation period, these values were ?0.17 and 0.34 for the SWAT and 0.43 and 0.45 for the ANN model. SWAT model performance was affected by snowmelt events during winter months and by the model's inability to adequately simulate base flows. Even though this and other studies using ANN models suggest that these models provide a viable alternative approach for hydrologic and water quality modeling, ANN models in their current form are not spatially distributed watershed modeling systems. However, considering the promising performance of the simple ANN model, this study suggests that the ANN approach warrants further development to explicitly address the spatial distribution of hydrologic/water quality processes within watersheds.     

ANALYTICAL REGRESSION STAGE ANALYSIS FOR DEVILS HOLE,DEATH VALLEY NATIONAL PARK,NEVADA1

ABSTRACT: Devils Hole is a collapse depression connected to the regional carbonate aquifer of the Death Valley ground water flow system. Devils Hole pool is home to an endangered pupfish that was threatened when irrigation pumping in nearby Ash Meadows lowered the pool stage in the 1960s. Pumping at Ash Meadows ultimately ceased, and the stage recovered until 1988, when it began to decline, a trend that continued until at least 2004. Regional ground water pumping and changes in recharge are considered the principal potential stresses causing long term stage changes. A regression was found between pumpage and Devils Hole water levels. Though precipitation in distant mountain ranges is the source of recharge to the flow system, the stage of Devils Hole shows small change in stage from 1937 to 1963, a period during which ground water withdrawals were small and the major stress on stage would have been recharge. Multiple regression analyses, made by including the cumulative departure from normal precipitation with pumpage as independent variables, did not improve the regression. Drawdown at Devils Hole was calculated by the Theis Equation for nearby pumping centers to incorporate time delay and drawdown attenuation. The Theis drawdowns were used as surrogates for pumpage in multiple regression analyses. The model coefficient for the regression, R²= 0.982, indicated that changes in Devils Hole were largely due to effects of pumping at Ash Meadows, Amargosa Desert, and Army 1.