Influence of vegetation parameters on runoff and sediment characteristics in patterned Artemisia capillaris plots

Vegetation patterns are important in the regulation of earth surface hydrological processes in arid and semi-arid areas. Laboratory-simulated rainfall experiments were used at the State Key Laboratory of Soil Erosion and Dryland Farming on the Loess Plateau, Yangling, northwestern China, to quantify the effects of Artemisia capillaris patterns on runoff and soil loss. The quantitative relationships between runoff/sediment yield and vegetation parameters were also thoroughly analyzed using the path analysis method for identifying the reduction mechanism of vegetation on soil erosion. A simulated rainfall intensity of 90 mm/h was applied on a control plot without vegetation （Co） and on the other three different vegetation distribution patterns： a checkerboard pattern （CP）, a banded pattern perpendicular to the slope direction （BP）, and a single long strip parallel to the slope direction （LP）. Each patterned plot received two sets of experiments, i.e. intact plants and roots only, respectively. All treatments had three replicates. The results showed that all the three other different patterns （CP, BP and LP） of A. capillaris could effectively reduce the runoff and sediment yield. Compared with Co, the other three intact plant plots had a 12%-25% less runoff and 58%-92% less sediment. Roots contributed more to sediment reduction （46%-70%）, whereas shoots contributed more to runoff reduction （57%-81%）. BP and CP exhibited preferable controlling effects on soil erosion compared with LP. Path analysis indicated that root length density and plant number were key parameters influencing runoff rate, while root surface area density and root weight density were central indicators affecting sediment rate. The results indicated that an appropriate increase of sowing density has practical significance in conserving soil and water.

Application of Inorganic and Organic Manure Fertilizers as Means of Conserving Plectranthus esculentus N.E.Br in Mid-Altitude Zone of Rwanda

Plectranthus esculentus N.E.Br, locally known as “Impombo” is an important indigenous food crop in Rwanda which is currently endangered. One major factor that causes disappearance of this species, is the lower agronomic recommendations developed for growers and lack of information about nutrients contents leading to loss of interest in its cultivation. The objective of this study was to evaluate the response of living stone potato to inorganic manure fertilizers as an attempt to conserve and evaluate the potential of the crop food security crop, source of income, and its adaptation in the mid-altitude zone of Rwanda. The performance of the crop was evaluated under application of NPK (17:17:17) and farm yard manure fertilisers. These fertilizers were evaluated using a Randomized Completely Block Design (RCBD) with three replications. Analyse of variance showed that significant at (p < 0.01) was recorded in stem height, number of leaves but not high in stem diameter. The results indicated that vegetative growth and yield of plants in control plots were lower than what was obtained in treated plots. Production of living stone potato on large under application NPK (17.17.17) and organic fertlizer will ensure the conservation of genetic resources, food security, agricultural development and financial benefit to local farmers.

Identification of Contamination Information of Vegetation in Coal Mines Based on Hyperspectral Remote Sensing Data

The development and application of the hyper-spectral remote sensing (HRS) in the environment investiga-tion and evaluation of coal mines have been discussed in detail. By using Hyperion HRS technology and field spectrummeasuring and integrating traditional geological method as well as laboratory chemical measurement, the absorptionspectrum features and the spectral variation rules of vegetation caused by coal mine waste piles were studied. Based onthe spectral modeling methods and Vegetation Red Edge Parameter (VREP), the diagnose spectra information andspectral variation parameter were extracted, and the mapping methods of VREP were researched. The spatial distribu-tions of contaminative vegetation have been quickly found out.This study has provided technical supports for the envi-ronment investigation and pollution management of coal mines.

The Effects of Flexible Vegetation on Forces with a Keulegan- Carpenter Number in Relation to Structures Due to Long Waves

Extreme coastal events require careful prediction of wave forces. Recent tsunamis have resulted in extensive damage of coastal structures. Such scenarios are the result of the action of long waves on structures. In this paper, the efficiency of vegetation as a buffer system in attenuating the incident ocean waves was studied through a well controlled experimental program. The study focused on the measurement of forces resulting from cnoidal waves on a model building mounted over a slope in the presence and absence of vegetation. The vegetative parameters, along with the width of the green belt, its position from the reference line, the diameter of the individual stems as well as the spacing between them, and their rigidity are varied so as to obtain a holistic view of the wave-vegetation interaction problem. The effect of vegetation on variations of dimensional forces with a Keulegan-Carpenter number （KC） was discussed in this paper. It has been shown that when vegetal patches are present in front of structure, the forces could be limited to within F＊≤I, by a percentile of 92%, 90%, 55%, and 96%, respectively for gap ratios of 0.0, 0.5, 1.0, and 1.5. The force is at its maximum for the gap ratio of 1.0 and beyond which the forces start to diminish.

Measurement of vegetation parameters and error analysis based on Monte Carlo method

In this paper we bring up a Monte Carlo theory based method to measure the ground vegetation parameters,and make quantitative description of the error.The leaf area index is used as the example in the study.Its mean and variance stability at different scales or in different time is verified using both the computer simulation and the statistics of remotely sensed images.And the error of Monte Carlo sampling method is analyzed based on the normal distribution theory and the central-limit theorem.The results show that the variance of leaf area index in the same area is stable at certain scales or in the same time of different years.The difference between experimental results and theoretical ones is small.The sig-nificance of this study is to establish a measurement procedure of ground vegetation pa-rameters with an error control system.

A new global land productivity dynamic product based on the consistency of various vegetation biophysical indicators

Changes in land productivity have been endorsed by the Inter Agency Expert Group on Sustainable Development Goals(IAEGSDGs)as key indicators for monitoring SDG 15.3.1.Multiple vegeta-tion parameters from optical remote sensing techniques have been widely utilized across different land productivity decline processes and scales.However,there is no consensus on indicator selection and their effectiveness at representing land productivity declining at different scales.This study proposes a fusion framework that incorporates the trends and consistencies within the four com-monly used remote sensing-based vegetation indicators.We ana-lyzed the differences among the four vegetation parameters in different land cover and climate zones,finally producing a new global land productivity dynamics(LPD)product with confidence level degrees.The LPD classes indicated by the four vegetation indicators(VIs)showed that all three levels(low,medium,and high confidence)of increasing area account for 23.99%of the global vegetated area and declining area account for 7.00%.The Increase high-confidence(HC)area accounted for 2.77%of the total area,and the Decline-HC accounted for 0.35%of the total area.This study demonstrates the accuracy of the high-confidence(HC)area for the evaluation of land productivity decline and increase.The“forest”landcover type and“humid”climate zone had the largest increasing and declining area but had the lowest high-confidence proportion.The data product provides an important and optional reference for the assessment of SDG 15.3.1 at global and regional scales according to the specific application target.