LI Yiran, ZHANG Xinggang, CHENG Tiantian, ZHANG Yongtao
Optimization of SCS model to estimate runoff in the mid-southern hilly region of Shandong province and evaluation of applying it
[Background] Runoff prediction is the basis of soil and water loss monitoring and prediction, and selecting suitable runoff prediction models for different regions can provide convenience for better soil and water conservation work in the river basin.[Methods] Based on the principle of SCS model, this study discussed the method of forecasting runoff for different land use types in the mid-southern hilly region of Shandong province. This study selected the runoff plots of four land use types (sloping farmland, level terrace, bare land and grassland) in the small watershed as the research object. Based on the data of runoff and rainfall observed in 2012-2015 years in the Yaoxiang small watershed, the initial loss rate and runoff curve number of the standard SCS-CN model and its modified form (MS model) in this area were calibrated by using the particle swarm optimization (PSO), then the optimized parameters were taken into the original model for runoff prediction, and the application results of initial model was compared with the optimized model. The measured runoff and other data in 2016 year were used to verify the models. Then the pass percent of model, the Nash-Sutcliffe efficiency coefficient (NSE), RMSE and the coefficient of determination (R2) were selected for evaluation indicators, and the model evaluation system was established based on the principle of TOPSIS method to quantitatively evaluate the application effect of different models.[Results] The application effect of standard SCS-CN model in four land use types was not applicable, and all evaluation indexes were deviated to a greater degree. The particle swarm optimization in 1stOpt software was used to optimize the standard SCS-CN model and MS model, forming the SCS-CNLes model and MSLes model, and the initial loss rate and runoff curve number in the optimized model had certain validity. In the model rate period and the model validation period, the application results of SCS-CNLes model and MSLes model were all fine, and the evaluation indexes of each model were higher than that of standard SCS-CN model. The TOPSIS comprehensive evaluation system was established for analysis. The result showed that the application effect of the MSLes model in the level terrace was the best, the qualified rate of the model was 100%, the NSE value was 0.70, the coefficient of determination was 0.77, and the RMSE value was 0.87. And followed by was the SCS-CNLes model in the grassland, the qualified rate of the model also was 100%, the NSE value was 0.53, the coefficient of determination was 0.83, and the RMSE value was 1.03.[Conclusions] The results show that MSLes model may be applied to forecast the actual runoff to some extent in the level terrace in the mid-southern hilly region of Shandong province, and relevant results can provide theoretical reference for follow-up research of runoff prediction in this area.
Accuracy analysis of model processing UAV remote sensing data: A case study of soil and water conservation monitoring for the Yellow River-to-Baiyangdian Water Transfer Project
[Background] The Unmanned Aerial Vehicle(UAV)remote sensing technology has provided a new technical mean for soil and water conservation monitoring in construction projects, especially in terms of the calculation of the area and volume of disposal ground, also greatly improved the efficiency and accuracy of monitoring. However, the accuracy of different models processing UAV remote sensing data varies a lot. Based on the Yellow River-to-Baiyangdian Water Transfer Project, this study selected 5 disposal grounds in Puyang, a city located in the plain area, as the research object. Since these 5 disposal grounds are similar in location and natural conditions, it is convenient for conducting comparative experiments and comparing the calculation accuracy of different models processing remote sensing data.[Methods] In this study, PhotoScan and Pix4D were used to process the UAV remote sensing data to obtain DOM and DSM images of each disposal ground. Global Mapper, LocaSpace Viewer and Context Capture were used to extract information from DOM and DSM images to calculate the area and volume of disposal grounds. Then 6 sets of models processing UAV remote sensing data were structured:Pho-Glo, Pho-Loc, Pho-Con, Pix-Glo, Pix-Loc and Pix-Con. Based on the actual value of construction organization, we quantified the errors of the area and volume of each disposal ground calculated by different models.[Results] 1) Using these 6 models:Pho-Glo, Pho-Loc, Pho-Con, Pix-Glo, Pix-Loc and Pix-Con, the calculation errors of disposal area were 5.57%, 5.05%, 4.84%, 1.69%, 3.06% and 1.23% respectively, and the errors of disposal volume were, 9.06%, 10.28%, 4.76%, 5.73%, 6.52% and 2.97% respectively. 2) When calculating the disposal area, using Pix4D for preliminary processing significantly reduced the error. There was no significant difference among Global Mapper, LocaSpace Viewer and Context Capture as for the information extraction. 3) When calculating the disposal volume, using Pix4D for preliminary treatment significantly reduced the error. There was no significant difference between Global Mapper and LocaSpace Viewer to calculate the volume of disposal grounds, while the accuracy of Context Capture was significantly higher than that of the others. 4) PhotoScan processed images more accurately when there was water on the surface and the DSM images were more consistent with the actual situation.[Conclusions] The accuracy of the 6 models are quite different, though all of them meet the requirements of relevant regulations. UAV has a bright application prospect in soil and water conservation monitoring for construction projects, which is more efficient and accurate than traditional monitoring methods when calculating the area and volume of disposal grounds. It is suggested that Pix-Con model processing UAV remote sensing data should be popularized in monitoring of construction projects.
Influence of photovoltaic power station engineering on soil and vegetation: Taking the Gobi Desert Area in the Hexi corridor of Gansu as an example
[Background] During the construction of photovoltaic electric field, the excavation, dumping and rolling of the original surface inevitably destroy the soil and vegetation of the construction area. Through the study on the disturbance of soil environment and vegetation caused by the construction of photovoltaic power station, this paper tried to provide technical support for the ecological protection during the construction of photovoltaic power plant in the Gobi Desert Area in the Hexi corridor of Gansu.[Methods] The study took 6 typical photovoltaic power stations in Wuwei, Zhangye and Jiayuguan cities from east to west in the Gobi Desert Area in the Hexi corridor in Gansu as the research object. The disturbances of photovoltaic power station construction on soil environment and vegetation were studied by using the methods of field observation, inspection, and soil and water conservation monitoring data.[Results] 1) There was little difference in soil pH value, total nitrogen, total phosphorus, total potassium, organic matter and available phosphorus in the disturbed area between photovoltaic panels and the undisturbed area outside the photovoltaic power station, and the disturbance to the influence of soil nutrient was not obvious. 2) During the construction of photovoltaic electric field, the original vegetation and the surface crust were destroyed greatly, and the surface crust was damaged, which aggravated soil erosion and dust, and even caused dust storms. The destruction of vegetation reduced the coverage of vegetation and caused the deterioration of ecological environment and the decrease of plant population diversity. 3) During the operation period, the photovoltaic panel collected rainwater and the abandoned water for cleaning the photovoltaic panel, which increased the soil moisture content of the disturbed land between the photovoltaic panels and was conducive to vegetation restoration.[Conclusions] It is suggested that photovoltaic power station construction should give priority to photovoltaic modules with high photoelectric conversion efficiency, and spiral steel pipe pile foundation should be selected as the support foundation under geological conditions to reduce the disturbance range and intensity to the surface. The consciousness of environmental protection must be established in achieving the civilization construction.
Review on the off-site erosion effect of up-slope runoff and sediment
[Background] Up-slope runoff and sediment play an important role in energy deliver and sediment transport between the adjacent section. The change of up-slope runoff and sediment will affect the soil erosion process of down-slope. Thus, it is the vital content of soil erosion to study the up-slope runoff and sediment. However, previous studies mainly focused on the sediment sources of small watershed and the off-site depositional effects of up-slope runoff and sediment, while less studies focused on the off-site erosional effect of up-slope runoff and sediment.[Methods] This paper reviewed the study methods of the off-site erosional effect of up-slope runoff and sediment. Based on the previous research, the "off-site erosion" was firstly proposed in this paper. And then, it summarized the research achievements of predecessors. In terms of the characteristics of off-site runoff and sediment yield, the paper summarized the off-site erosional effect of up-slope runoff and sediment on the bare slope, and the research progress of the influence of soil and water conservation on the off-site erosional effect. Furthermore, it discussed the hotspots, challenges, and the future research directions of the off-site erosional effect.[Results] "Off-site erosion" refers to the change of downslope runoff characteristics and the sediment yield caused by up-slope runoff and sediment. The up-slope runoff and sediment joined into the down-slope and increased the runoff energy of down-slope. Besides, the runoff velocity, hydraulic radius, Reynolds number and Froude number increased, while resistance coefficient decreased. Based on the analysis of observed data and simulation experiments, the up-slope runoff and sediment would increase the sediment yield of down-slope. However, when the sediment concentration of runoff came to the sediment carrying capacity of runoff, the runoff with sediment couldn't erosive the down-slope soil, and even to deposit. The soil and water conservation measures on slope decreased runoff amount and sediment yield entering the down-slope. Some scholars thought soil and water conservation on slope decreased the off-site sediment yield, while others drew the opposite conclusion. Engineering measures, such as dams, drastically cut the runoff erosional energy, thus they had the decreased effect on off-site.[Conclusions] "Off-site erosion" is a relatively spatial concept, but how to reasonably define the up-slope and down-slope regions, there is still no clear definition. Up-slope runoff and sediment, erosion pattern evolution process and erosion process interacted with each other. Meantime, off-site erosional effect of up-slope runoff and sediment would be impacted by the dynamic change, such as rainfall intensity, underlying surface, sediment concentration and sediment carrying capacity. Further research of the off-site erosional effect of up-slope runoff and sediment could be conducted in confirming the concept of "off-site erosion", exploring the influence factors and mechanism of off-site erosion, illuminating the transfer characteristics of sediment and runoff energy during the off-site erosional process of up-slope runoff and sediment, as well as quantitating the off-site less erosional effect of soil and water conservation.
Research advances in spatial variability of soil aggregate by using geostatistics
[Background] Soil aggregate is to soil what cell is to organism. They have profoundly impacts on soil fertility and plant growth, and play important roles in soil resistance to erosion, soil remediation, and global carbon cycling, etc. The aim of this review is to find out the main issues in current researches, and provide an outlook of the potential for GIS and geostatistics application in spatial variability of soil aggregate.[Methods] We collected all relevant literature for this review. Based on these references, we reviewed the current development of spatial variability of soil aggregates by using GIS and geostatistics, analyzed spatial quantification methods and scale effects, summarized the factors influencing the spatial variation of soil aggregate, and the modeling of spatial variability prediction of aggregate stability.[Results] Current researches about geostatistics have made some progress in the spatial variability of soil aggregate. However, due to the spatio-temporal variability of soil properties, climate, topography, vegetation and human activities, the relevant researches need to be further studied. 1) At different spatial scales, the contribution of soil properties, natural factors, and human activities to the spatial variability of aggregate stability are unclear. 2) Some studies have used remote sensing data, DEM and other readily available data for spatial prediction of aggregate stability. The low spatial resolution cannot reflect the spatial variation in detail. Therefore, it is necessary to further improve the resolution of remote sensing data and predict the spatial variability of aggregate stability with a higher precision.[Conclusions] Previous studies placed emphasis on the formation process and stabilization mechanisms of soil aggregates at micro-scale. However, these micro-scale analyses cannot fully reveal the roles and functions of soil aggregates in ecosystems due to the fact that the eco-role of soil aggregate is affected by a combination of factors, such as soil properties, natural environment, and human activities, etc. In addition, the spatial heterogeneity in the aggregate structure and stability raises the difficulty in deriving the spatial pattern of soil aggregates with traditional classical statistics under real conditions, which makes geostatistics gradually be introduced in soil aggregates analysis. A large number of new methods and the continuous improvement of geostatistics are being applied to soil science. We should try to introduce the new analytical methods and models to analyze the spatial variability of soil aggregate. It is of great significance to study the formation process of aggregate, the influence factors of aggregate stability and the contribution of influence factors to aggregate stability, to understand the formation mechanism of aggregate, and to accurately explore the factors affecting the formation and stability of soil aggregate.
