黄土丘陵半干旱区枣林露水量研究

利用2012年和2013年叶片湿度传感器(LWS)、温湿度仪、热扩散式探针(TDP)、中子仪实测的露水强度、冠层温湿度、树干径流、土壤水分及气象站监测的气象因子,分析了枣林生育期内露水量的变化规律,探讨了其与水资源输入、输出项的关系。研究结果表明,2012年和2013年枣林露水量随生育期变化呈现递增趋势,果实成熟期达到最大值。露水总量分别为31.31、37.87 mm,分别占同期降水量、蒸腾量和蒸发量的6.87%、10.00%、17.65%和7.90%、15.00%、17.90%,露水量日平均值分别达0.44、0.47 mm。此外,露水量具有发生频率高、稳定性强、重度露水量(大于0.20 mm)比重大的特点。在枣树全生育期内,露水量作为水资源输入项会引起蒸腾量在果实膨大和成熟期显著降低(P0.05),但对蒸发量无显著影响。研究显示露水是该区枣林重要水源,是水量平衡中不可缺少的输入项。     

Trade-off between wheat yield and drainage under current and climate change conditions in northeast Germany

In the temperate climate of northeast Germany, a trade-off exists between water use in agricultural crop production and groundwater recharge which is important for urban water supply, irrigation, forestry and peat protection. The APSIM-Nwheat model was used to analyze the impact of climate change scenarios on deep drainage (DD), the water loss below the maximum root zone as the main source of groundwater recharge, and wheat production for two main soil types. A linear and a nonlinear climate scenario were used in this study: The linear scenario for 2001–2050 was based on a simple linearly modified historical climate record from 1951 to 2000. The nonlinear scenario used the same 1951–2000 historical climate record but combined it nonlinearly with a Global Circulation Model climate scenario for 2001–2050. Simulation results showed different distributions of deep drainage and grain yield with the linear and nonlinear scenarios, but no difference in the 50-year averages. Hence, a linear manipulation of climate records can be as effective for climate change impact studies on deep drainage and grain yield as nonlinearly manipulated climate data, if long-term average changes are of main interest. The simulation results indicated that a trade-off between deep drainage and grain yields can be potentially controlled through N management. However, such control mechanism was more effective under current climate conditions than under future climate and on a better water-holding silt soil compared to a poorer water-holding loamy sand. It is suggested that areas with poor water-holding soils should be managed extensively for groundwater recharge harvesting while better water-holding soils should be used for high input grain production.     

豫西山区次降雨侵蚀力简化模型的建立

而降雨侵蚀力是定量监测评价一个地区土壤侵蚀状况的重要因子之一,找到适宜简便的计算方法十分重要。本文利用位于豫西山区鲁山县的两个水文站各三年共125次自记降雨过程资料,建立了该区域次降雨侵蚀力计算模型:R次=0.146×Pt×I30-1.189(r=0.992,n=105);并进行了预报效果检验,采取模型有效系数和相对偏差评价模型的的效果,结果表明二者分别为99%和8.8%。本文所创立的次降雨侵蚀力模型简便实用,不仅可以评价区域年R值分布,有效地分析R值的年内分布状况,更重要的是为水土流失定量监测从多年平均监测、年监测提高到次降雨流失量的监测提供了可能,从而实现区域定量监测的精度。     

降雨侵蚀力新算法在豫西山区应用的初步研究

降雨侵蚀力是定量监测评价一个地区土壤侵蚀状况的重要因子之一,找到适宜简便的计算方法十分重要.卜兆宏提出的降雨侵蚀力新算法具有简便易用的优点.本文利用位于豫西山区鲁山县的3个水文雨量站10年185次的自记降雨过程资料,以经典算法年R值为基准,对新算法在该区的适用性进行了分析评价.结果表明:新算法结果与经典值存在高度的一致性,一致性高达90.2%,模型有效系数为96.4%,相对误差为7.7%,说明新算法能够在该区应用,可以采取此法对该区的降雨侵蚀力进行深入的分析研究;并同时对资料摘读时应该注意的问题进行了讨论.     

Development of an appropriate procedure for estimation of RUSLE EI30 index and preparation of erosivity maps for Pulau Penang in Peninsular Malaysia

Pluviographic data at 15 min interval from 6 stations in Pulau Penang of Peninsular Malaysia were used to compute rainfall erosivity factor (R) for the revised universal soil loss equation (RUSLE). Three different modelling procedures were applied for the estimation of monthly rainfall erosivity (EI₃₀) values. While storm rainfall (P) and duration (D) data were used in the first approach, the second approach used monthly rainfall for days with rainfall ≥ 10 mm (rain₁₀) and monthly number of days with rainfall ≥ 10 (days₁₀). The third approach however used the Fournier index as the independent variable. Based on the root mean squared error (RMSE) and the percentage error (PE) criteria, models developed using the Fournier index approach was adjudged the best with an average PE value of 0.92 and an average RMSE value of 164.6. Further, this approach was extended to the development of a regional model. Using data from additional sixteen stations and the Fournier index based regional model, EI₃₀ values were computed for each month. ArcView GIS was used to generate monthly maps of EI₃₀ values and also annual rainfall erosivity (R). The rainfall erosivity factor (R) in the region was estimated to vary from 9000 to 14,000 MJ mm ha^− 1 h^− 1 year^− 1.     

Runoff and sediment losses from rough and smooth soil surfaces in a laboratory experiment

Soil surface roughness may significantly impact runoff and erosion under rainfall. A common perception is that runoff and erosion are decreased as a function of roughness because of surface ponding and increased hydraulic roughness that reduces effective flow shear stress. The objective of this study was to measure the effects of initial surface roughness on runoff and erosion under controlled laboratory conditions. Initially, rough and smooth surfaces were exposed to five simulated rainfall applications at 5% and 20% slopes. In all cases, runoff was delayed for the case of the initially rough surface; however, this effect was temporary. Overall, no statistical differences in either total runoff or erosion were measured on the 20% slope. At 5% slope, runoff was less on the rough surface for the first rainfall application but greater on the final three, probably due to the formation of a depositional seal in that case. This resulted in an overall insignificant difference in runoff for the sum of the five rainfall applications. Erosion was greater on the rougher slope at 5% steepness, probably due to concentration of flow as it moved around the roughness elements on the rougher slope. These results indicate that commonly held perceptions of the impact of soil surface roughness on runoff and erosion may not be entirely correct in all cases.     

Orographic enhancement of wet deposition in the United Kingdom: case studies and modelling

Two field experiments to observe the detailed response of wet deposition to orography in a polluted environment are reported. Rain events were classed as frontal, convective or mixed on the basis of meteorological data. Analysis of the deposition enhancement and cap cloud composition confirmed that for the frontal events the seeder-feeder effect (scavenging of cap cloud by rain drops) dominates. The greater concentration of ions in the water scavenged from the cap cloud than in the rain means that deposition is enhanced for all ions. For marine ions the scavenged water was found to be between five and six times as concentrated as the rain and for anthropogenically produced ions it was about twice as concentrated.A computational model of rainfall incorporating the seeder-feeder effect has been broadly successful in predicting enhancement although some details of the observed pattern remain to be explained.     

兴安落叶松原始林区降水化学输入的特征研究

对寒温带大兴安岭根河落叶松原始林区降雨、林内雨化学因子观测研究结果表明,兴安落叶松原始林区输入的大量元素均低于国内其他重要林区,而微量元素含量接近平均水平。降雨通过林冠形成林内雨时表现出兴安落叶松林冠层对Na、Ca、Cu、Fe有一定的吸附作用,其中Ca的吸附作用表现明显。降雨通过林冠时淋溶出K、Mg、Zn、Mn、P,其中K淋溶量最高。生长季中降雨除Ca的变化较大外,其他大量元素和微量元素的月际变化均较小,5～9月份林内雨多数元素养分含量月际变化曲线呈“U”字型。     

Estimation of rainfall erosivity using 5- to 60-minute fixed-interval rainfall data from China

The 30-min rainfall erosivity index (EI₃₀) is commonly used in the Universal Soil Loss Equation for predicting soil loss from agricultural hillslopes. EI₃₀ is calculated from the total kinetic energy and the maximum 30-min rainfall intensity of a storm. Normally, EI₃₀ values are calculated from breakpoint rainfall information taken from continuous recording rain gauge charts, however, in many places in China and other parts of the world the detailed chart-recorded rain gauge data relative to storm intensities are not readily available, while hourly rainfall is readily available. The objective of this study was to assess the accuracy of EI₃₀ estimations based on 5-, 10-, 15-, 30-, and 60-min time-resolution rainfall data as compared to EI₃₀ estimations from breakpoint rainfall information. 456 storm events from five soil conservation stations in eastern China were used. The values of EI₃₀ based on the fixed-time-interval data were less than those calculated from breakpoint data. The average conversion factors (ratio of values calculated from the breakpoint data to those from the fixed-interval data) for the five stations decreased from 1.105 to 1.009 for the estimation of E values, from 1.668 to 1.007 for I₃₀ values, and from 1.730 to 1.014 for EI₃₀ values as the time resolution increased from 60 to 5 min. The maximum 30-min rainfall intensity was the major source of error in estimating EI₃₀ for 60-min fixed-interval data, while storm kinetic energy played a proportionately more significant role as the fixed-interval data decreased from 60 to 5 min.     

Gully erosion and environmental change: importance and research needs

Assessing the impacts of climatic and, in particular, land use changes on rates of soil erosion by water is the objective of many national and international research projects. However, over the last decades, most research dealing with soil erosion by water has concentrated on sheet (interrill) and rill erosion processes operating at the (runoff) plot scale. Relatively few studies have been conducted on gully erosion operating at larger spatial scales.Recent studies indicate that (1) gully erosion represents an important sediment source in a range of environments and (2) gullies are effective links for transferring runoff and sediment from uplands to valley bottoms and permanent channels where they aggravate off site effects of water erosion. In other words, once gullies develop, they increase the connectivity in the landscape. Many cases of damage (sediment and chemical) to watercourses and properties by runoff from agricultural land relate to (ephemeral) gullying. Consequently, there is a need for monitoring, experimental and modelling studies of gully erosion as a basis for predicting the effects of environmental change (climatic and land use changes) on gully erosion rates.In this respect, various research questions can be identified. The most important ones are:

What is the contribution of gully erosion to overall soil loss and sediment production at various temporal and spatial scales and under different climatic and land use conditions?

What are appropriate measuring techniques for monitoring and experimental studies of the initiation and development of various gully types at various temporal and spatial scales?

Can we identify critical thresholds for the initiation, development and infilling of gullies in different environments in terms of flow hydraulics, rain, topography, soils and land use?

How does gully erosion interact with hydrological processes as well as with other soil degradation processes?

What are appropriate models of gully erosion, capable of predicting (a) erosion rates at various temporal and spatial scales and (b) the impact of gully development on hydrology, sediment yield and landscape evolution?

What are efficient gully prevention and gully control measures? What can be learned from failures and successes of gully erosion control programmes?

These questions need to be answered first if we want to improve our insights into the impacts of environmental change on gully erosion. This paper highlights some of these issues by reviewing recent examples taken from various environments.