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\"affiliation_03\": \"University of California, Berkeley\", 
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\"affiliation_03\": \"University of California, Berkeley\", 
            
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  "funding": "[{\"grant_number\": \"\", \"institution\": \"ETH 
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Zurich\", \"institution_url\": \"\"}]",
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  "license_title": "Creative Commons Attribution Share-Alike 
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(CC-BY-SA)",
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(CC-BY-SA)",
            
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  "name": "impulse_response_function_script",
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  "name": "impulse_response_function_script",
            
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  "notes": "The R script IRFnnhs.R, which efficiently estimates 
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  "notes": "The R script IRFnnhs.R, which efficiently estimates 
            
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impulse response functions for environmental systems that are 
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impulse response functions for environmental systems that are 
            
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nonlinear, nonstationary, or heterogeneous, based on their input and 
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nonlinear, nonstationary, or heterogeneous, based on their input and 
            
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output time series.  \r\n\r\nScripts and results for a series of 
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output time series.  \r\n\r\nScripts and results for a series of 
            
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benchmark tests are also provided, to accompany Kirchner, J.W., 
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benchmark tests are also provided, to accompany Kirchner, J.W., 
            
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Impulse response functions for heterogeneous, nonstationary, and 
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Impulse response functions for heterogeneous, nonstationary, and 
            
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nonlinear systems, estimated by deconvolution and demixing of noisy 
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nonlinear systems, estimated by deconvolution and demixing of noisy 
            
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time series, _Sensors_, 22(9), 3291, 
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time series, _Sensors_, 22(9), 3291, 
            
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https://doi.org/10.3390/s22093291, 2022.  ",
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https://doi.org/10.3390/s22093291, 2022.  ",
            
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  "organization": {
            
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    "approval_status": "approved",
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    "approval_status": "approved",
            
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    "created": "2019-08-21T09:46:01.602326",
            
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    "description": "Our research explores environmental systems, often 
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    "description": "Our research explores environmental systems, often 
            
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using approaches developed in physics.  Environmental systems often 
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using approaches developed in physics.  Environmental systems often 
            
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encompass physical processes and material properties that are complex, 
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encompass physical processes and material properties that are complex, 
            
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heterogeneous on all scales, and poorly characterized by direct 
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heterogeneous on all scales, and poorly characterized by direct 
            
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measurement.  Thus we often need to try to understand these systems by 
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measurement.  Thus we often need to try to understand these systems by 
            
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cleverly analyzing how they behave, and by probing their inner 
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cleverly analyzing how they behave, and by probing their inner 
            
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workings using carefully designed experiments.  The spatial 
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workings using carefully designed experiments.  The spatial 
            
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heterogeneity and process complexity of environmental systems imply 
50
heterogeneity and process complexity of environmental systems imply 
            
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that any feasible theory will inevitably involve substantial 
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that any feasible theory will inevitably involve substantial 
            
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simplifications and generalizations. The essential question in 
52
simplifications and generalizations. The essential question in 
            
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environmental science is which simplifications and generalizations are 
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environmental science is which simplifications and generalizations are 
            
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the right ones.  We seek to answer questions such as:\r\n\r\n- How 
54
the right ones.  We seek to answer questions such as:\r\n\r\n- How 
            
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does rainfall become runoff?\r\n- How is the chemistry of natural 
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does rainfall become runoff?\r\n- How is the chemistry of natural 
            
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waters shaped by subsurface transport and mixing, by chemical 
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waters shaped by subsurface transport and mixing, by chemical 
            
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reactions with soils and rocks, and by biological processes?\r\n- 
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reactions with soils and rocks, and by biological processes?\r\n- 
            
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Conversely, what can we learn about these processes at the scale of 
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Conversely, what can we learn about these processes at the scale of 
            
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the whole landscape, by observing the signals that they impart to 
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the whole landscape, by observing the signals that they impart to 
            
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streams?\r\n- What processes control rates and patterns of physical 
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streams?\r\n- What processes control rates and patterns of physical 
            
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erosion and chemical weathering? And how do they, in turn, regulate 
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erosion and chemical weathering? And how do they, in turn, regulate 
            
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the topographic evolution of mountains and valleys, as well as the 
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the topographic evolution of mountains and valleys, as well as the 
            
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physical and chemical environment in which we (and all other 
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physical and chemical environment in which we (and all other 
            
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organisms) live?\r\n\r\nWe explore connections between terrestrial and 
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organisms) live?\r\n\r\nWe explore connections between terrestrial and 
            
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aquatic environments, and linkages between physical, chemical, and 
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aquatic environments, and linkages between physical, chemical, and 
            
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biological processes. Our work typically combines field observations, 
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biological processes. Our work typically combines field observations, 
            
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simple mathematical models, and novel analyses of environmental data. 
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simple mathematical models, and novel analyses of environmental data. 
            
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  "related_publications": "*Kirchner, J.W., Impulse response functions 
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for heterogeneous, nonstationary, and nonlinear systems, estimated by 
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for heterogeneous, nonstationary, and nonlinear systems, estimated by 
            
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deconvolution and demixing of noisy time series, _Sensors_, 22(9), 
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deconvolution and demixing of noisy time series, _Sensors_, 22(9), 
            
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3291, https://doi.org/10.3390/s22093291, 2022. ",
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3291, https://doi.org/10.3390/s22093291, 2022. ",
            
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