Widespread changes to forested watersheds affected by the mountain pine beetle (Dendroctonus ponderosae Hopkins) epidemic across western North America raised concerns about the effects of this climate-induced disturba...Widespread changes to forested watersheds affected by the mountain pine beetle (Dendroctonus ponderosae Hopkins) epidemic across western North America raised concerns about the effects of this climate-induced disturbance on drinking water and natural resources. Effective communication and knowledge exchange across scientists and stakeholders (i.e., drinking water managers) is essential for constructively responding to such landscape scale disturbances, providing improved adaptive capacity through knowledge sharing. An assessment of stakeholder knowledge levels, information needs, primary concerns, and suggested communication strategies were conducted via an online elicitation survey and World Science Café workshops. Knowledge levels, assessed via a survey of local water managers and experts, were relatively low with approximately half of the respondents reporting little to no knowledge of the effects of mountain pine beetle on drinking water quality and quantity, thereby indicating limited knowledge exchange between scientists and drinking water stakeholders. Increased accessibility and dissemination of research findings pertinent to the mountain pine beetle epidemic’s effects on drinking water quality and quantity is necessary for natural resource management. Recommendations for improved communication among scientists and drinking water stakeholders in particular and forest health in general include dispersal of non-academic research summaries, information exchange through existing media and community resources, demonstration projects, and information clearinghouses. This information provides a better understanding of the challenges, concerns, and first-hand experience of stakeholders of a landscape disturbance issue to apply this knowledge to enhance land management practice and how researchers on this overall project enhanced science communication efforts.展开更多
Developing regional models using physiographic, climatic, and hydrologic variables is an approach to estimating suspended load yield(SLY)in ungauged watersheds. However, using all the variables might reduce the applic...Developing regional models using physiographic, climatic, and hydrologic variables is an approach to estimating suspended load yield(SLY)in ungauged watersheds. However, using all the variables might reduce the applicability of these models. Therefore, data reduction techniques(DRTs), e.g., principal component analysis(PCA), Gamma test(GT), and stepwise regression(SR), have been used to select the most effective variables. The artificial neural network(ANN) and multiple linear regression(MLR) are also common tools for SLY modeling. We conducted this study(1) to obtain the most effective variables influencing SLY through DRTs including PCA, GT, and SR, and then, to use them as input data for ANN and MLR; and(2) to provide the best SLY models. Accordingly, we used 14 physiographic, climatic, and hydrologic parameters from 42 watersheds in the Hyrcanian forest region(in northern Iran). The most effective variables as determined through DRTs as well as the original data sets were used as the input data for ANN and MLR in order to provide an SLY model. The results indicated that the SLY models provided by ANN performed much better than the MLR models, and the GT-ANN model was the best. The determination of coefficient,relative error, root mean square error, and bias were 99.9%, 26%, 323 t/year, and 6 t/year in the calibration period, and 70%, 43%, 456 t/year, and 407 t/year in the validation period, respectively. Overall, selecting the main factors that influence SLY and using artificial intelligence tools can be useful for water resources managers to quickly determine the behavior of SLY in ungauged watersheds.展开更多
Boundary extraction of watershed is an important step in forest landscape research. The boundary of the upriver wa-tershed of the Hunhe River in the sub-alpine Qingyuan County of eastern Liaoning Province, China was e...Boundary extraction of watershed is an important step in forest landscape research. The boundary of the upriver wa-tershed of the Hunhe River in the sub-alpine Qingyuan County of eastern Liaoning Province, China was extracted by digital elevation modeling (DEM) data in ArcInfo8.1. Remote sensing image of the corresponding region was applied to help modify its copy according to Enhanced Thematic Mapper (ETM) image抯 profuse geomorphological structure information. Both the DEM-dependent boundary and modified copy were overlapped with county map and drainage network map to visually check the effects of result. Overlap of county map suggested a nice extraction of the boundary line since the two layers matched precisely, which indicated the DEM-dependent boundary by program was effective and precise. Further upload of drainage network showed discrepancies between the boundary and the drainage network. Altogether, there were three sections of the extraction result that needed to correct. Compared with this extraction boundary, the modified boundary had a better match to the drainage network as well as to the county map. Comprehensive analysis demonstrated that the program extraction has generally fine precision in position and excels the digitized result by hand. The errors of the DEM-dependant extraction are due to the fact that it is difficult for program to recognize sections of complex landform especially altered by human activities, but these errors are discernable and adjustable because the spatial resolution of ETM image is less than that of DEM. This study result proved that application of remote sensing information could help obtain better result when DEM method is used in extraction of watershed boundary.展开更多
Global nitrogen (N) emission and deposition have been increased rapidly due to massive mobilization of N which may have long- reaching impacts on ecosystems. Many agricultural and forest ecosystems have been identif...Global nitrogen (N) emission and deposition have been increased rapidly due to massive mobilization of N which may have long- reaching impacts on ecosystems. Many agricultural and forest ecosystems have been identified as secondary N sources. In the present study, the input-output budget of inorganic N in a small forested watershed of subtropical China was investigated. Inorganic N wet deposition and discharge by stream water were monitored from March, 2007 to February, 2009. The concentrations and fluxes of inorganic N in wet precipitation and stream water and net retention of N were calculated. Global N input by dry deposition and biological fixation and N output by denitrification for forested watersheds elsewhere were reported as references to evaluate whether the studied forested watershed is a source or a sink for N. The results show that the inorganic N output by the stream water is mainly caused by NO3-N even though the input is dominated by NH4+-N. The mean flux of inorganic N input by wet precipitation and output by stream water is 1.672 and 0.537 g N/(m2.yr), respectively, which indicates that most of inorganic N input is retained in the forested watershed. Net retention of inorganic N reaches 1.135 g N/(m2.yr) considering wet precipitation as the main input and stream water as the main output, ff N input by dry deposition and biological fixation and output by denitlification are taken into account, this subtropical forested watershed currently acts as a considerable sink for N, with a net sink ranging from 1.309 to 1.913 g N/(m2-yr) which may enhance carbon sequestration of the terrestrial ecosystem.展开更多
文摘Widespread changes to forested watersheds affected by the mountain pine beetle (Dendroctonus ponderosae Hopkins) epidemic across western North America raised concerns about the effects of this climate-induced disturbance on drinking water and natural resources. Effective communication and knowledge exchange across scientists and stakeholders (i.e., drinking water managers) is essential for constructively responding to such landscape scale disturbances, providing improved adaptive capacity through knowledge sharing. An assessment of stakeholder knowledge levels, information needs, primary concerns, and suggested communication strategies were conducted via an online elicitation survey and World Science Café workshops. Knowledge levels, assessed via a survey of local water managers and experts, were relatively low with approximately half of the respondents reporting little to no knowledge of the effects of mountain pine beetle on drinking water quality and quantity, thereby indicating limited knowledge exchange between scientists and drinking water stakeholders. Increased accessibility and dissemination of research findings pertinent to the mountain pine beetle epidemic’s effects on drinking water quality and quantity is necessary for natural resource management. Recommendations for improved communication among scientists and drinking water stakeholders in particular and forest health in general include dispersal of non-academic research summaries, information exchange through existing media and community resources, demonstration projects, and information clearinghouses. This information provides a better understanding of the challenges, concerns, and first-hand experience of stakeholders of a landscape disturbance issue to apply this knowledge to enhance land management practice and how researchers on this overall project enhanced science communication efforts.
基金supported by the Department of Environmental Science,Urmia Lake Research Institute,Urmia University
文摘Developing regional models using physiographic, climatic, and hydrologic variables is an approach to estimating suspended load yield(SLY)in ungauged watersheds. However, using all the variables might reduce the applicability of these models. Therefore, data reduction techniques(DRTs), e.g., principal component analysis(PCA), Gamma test(GT), and stepwise regression(SR), have been used to select the most effective variables. The artificial neural network(ANN) and multiple linear regression(MLR) are also common tools for SLY modeling. We conducted this study(1) to obtain the most effective variables influencing SLY through DRTs including PCA, GT, and SR, and then, to use them as input data for ANN and MLR; and(2) to provide the best SLY models. Accordingly, we used 14 physiographic, climatic, and hydrologic parameters from 42 watersheds in the Hyrcanian forest region(in northern Iran). The most effective variables as determined through DRTs as well as the original data sets were used as the input data for ANN and MLR in order to provide an SLY model. The results indicated that the SLY models provided by ANN performed much better than the MLR models, and the GT-ANN model was the best. The determination of coefficient,relative error, root mean square error, and bias were 99.9%, 26%, 323 t/year, and 6 t/year in the calibration period, and 70%, 43%, 456 t/year, and 407 t/year in the validation period, respectively. Overall, selecting the main factors that influence SLY and using artificial intelligence tools can be useful for water resources managers to quickly determine the behavior of SLY in ungauged watersheds.
基金This work was supported by Knowledge Innovation Pro-gram Chinese Academy of Sciences (No. KZCX2-SW-320-3 & KZCX3-SW-425).
文摘Boundary extraction of watershed is an important step in forest landscape research. The boundary of the upriver wa-tershed of the Hunhe River in the sub-alpine Qingyuan County of eastern Liaoning Province, China was extracted by digital elevation modeling (DEM) data in ArcInfo8.1. Remote sensing image of the corresponding region was applied to help modify its copy according to Enhanced Thematic Mapper (ETM) image抯 profuse geomorphological structure information. Both the DEM-dependent boundary and modified copy were overlapped with county map and drainage network map to visually check the effects of result. Overlap of county map suggested a nice extraction of the boundary line since the two layers matched precisely, which indicated the DEM-dependent boundary by program was effective and precise. Further upload of drainage network showed discrepancies between the boundary and the drainage network. Altogether, there were three sections of the extraction result that needed to correct. Compared with this extraction boundary, the modified boundary had a better match to the drainage network as well as to the county map. Comprehensive analysis demonstrated that the program extraction has generally fine precision in position and excels the digitized result by hand. The errors of the DEM-dependant extraction are due to the fact that it is difficult for program to recognize sections of complex landform especially altered by human activities, but these errors are discernable and adjustable because the spatial resolution of ETM image is less than that of DEM. This study result proved that application of remote sensing information could help obtain better result when DEM method is used in extraction of watershed boundary.
基金supported by the National Natural Science Foundation of China (No. 41071141,40625001)the International Foundation of Science (No. C/4077-2)the fund from Institute of Soil Science,Chinese Academy of Sciences (No. ISSASIP0704)
文摘Global nitrogen (N) emission and deposition have been increased rapidly due to massive mobilization of N which may have long- reaching impacts on ecosystems. Many agricultural and forest ecosystems have been identified as secondary N sources. In the present study, the input-output budget of inorganic N in a small forested watershed of subtropical China was investigated. Inorganic N wet deposition and discharge by stream water were monitored from March, 2007 to February, 2009. The concentrations and fluxes of inorganic N in wet precipitation and stream water and net retention of N were calculated. Global N input by dry deposition and biological fixation and N output by denitrification for forested watersheds elsewhere were reported as references to evaluate whether the studied forested watershed is a source or a sink for N. The results show that the inorganic N output by the stream water is mainly caused by NO3-N even though the input is dominated by NH4+-N. The mean flux of inorganic N input by wet precipitation and output by stream water is 1.672 and 0.537 g N/(m2.yr), respectively, which indicates that most of inorganic N input is retained in the forested watershed. Net retention of inorganic N reaches 1.135 g N/(m2.yr) considering wet precipitation as the main input and stream water as the main output, ff N input by dry deposition and biological fixation and output by denitlification are taken into account, this subtropical forested watershed currently acts as a considerable sink for N, with a net sink ranging from 1.309 to 1.913 g N/(m2-yr) which may enhance carbon sequestration of the terrestrial ecosystem.