Norris Lam

Adjunkt i GIS och geomatik

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Works at Department of Physical Geography
Telephone 08-674 78 69
Visiting address Svante Arrhenius väg 8
Room T 420
Postal address Inst för naturgeografi 106 91 Stockholm

About me

My research focuses on applying close-range remote sensing products for characterizing the Earth's topography. The measurement techniques used in my research include laser scanning (e.g. terrestrial and airborne laser systems), acoustic Doppler current profilers, GNSS/GPS, total station and photogrammetry from drone imagery.


Currently not teaching.

Previous courses

Applied Remote Sensing and GIS for Landscape Analysis (GE7062)

Geographic Analysis and Visualization in GIS (GE7080)

Geografiska informationssystem (GE4027 campus)

Geografiska informationssystem (GE4030 distance)

Information and Modeling Systems for Land and Water Resources (GE7006)

Tellus II - Physical Geography (GE4023)

GIS and remote sensing (GE4012)

How to use Matlab to solve problems in environmental, climatological, and earth science research? (Bolin Center for Climate Research School)


My research focuses on applying close-range remote sensing products for characterizing the Earth's topography. The measurement techniques used in my research include laser scanning (e.g. terrestrial and airborne laser systems), acoustic Doppler current profilers, GNSS/GPS, total station and photogrammetry from drone imagery.


A selection from Stockholm University publication database
  • 2019. Steve W. Lyon (et al.). Water 11 (11)

    Education can help secure inclusive and resilient development around water resources. However, it is difficult to provide the latest science to those managing water resources (both now and in the future). Collectively, we hypothesize that dissemination and promotion of scientific knowledge using students as central agents to transfer theoretical knowledge into practice is an efficient way to address this difficulty. In this study, we test this hypothesis in the Latin America and Caribbean (LAC) region as a representative case study region. First, we use a literature review to map a potential gap in research on education around water resources across the LAC region. We then review potential best practices to address this gap and to better translate water resources education techniques into the LAC region. Integral to these efforts is adopting students as agents for information transfer to help bridge the gap between the global state-of-the science and local water resources management. Our results highlight the need to establish a new standard of higher educational promoting exchange between countries as local populations are vulnerable to future shifts in climate at global scales and changes in land usage at regional scales. The new standard should include peer-to-peer mentoring achieved by jointly exchanging and training students and practitioners in water management techniques, increasing access to water data and pedagogic information across the region, and lowering administration roadblocks that prevent student exchange.

  • 2019. Valentin Mansanarez (et al.). Water resources research 55 (11), 9765-9787

    Establishing reliable streamflow time series is essential for hydrological studies and water-related decisions, but it can be both time-consuming and costly since streamflow is typically calculated from water level using rating curves based on numerous calibration measurements (gaugings). It can take many years of gauging data collection to estimate reliable rating curves, and even then extreme-flow estimates often still depend on rating curve extrapolation. Hydraulically modeled rating curves are a promising alternative to traditional methods as they can be rapidly derived with few concurrent stage-discharge gaugings. We introduce a novel framework for Rating curve Uncertainty estimation using Hydraulic Modelling (RUHM), based on Bayesian inference and physically based hydraulic modeling for estimating stage-discharge rating curves and their associated uncertainty. The framework incorporates information from the river shape, hydraulic configuration, and the control gaugings as well as uncertainties in the gaugings and model parameters. We explored the interaction of uncertainty sources within RUHM by (1) assessing its performance at two Swedish stations, (2) investigating the sensitivity of the results to the number and magnitude of the calibration gaugings, and (3) evaluating the importance of prior information on the model parameters. We found that rating curves with constrained uncertainty could be estimated using only three gaugings for either low or low and medium flows that have a high probability of occurrence, thereby enabling rapid rating curve estimation. Prior information about the water-surface slope-stage relation, obtainable from site surveys, was needed to adequately constrain uncertainty estimates. Plain Language Summary Reliable streamflow time series are essential for water-related decisions. However, it can take several years and numerous measurements to establish a reliable streamflow time series, and these may still be associated with large uncertainty. To address these issues, we developed a novel framework that couples uncertainty assessment with hydraulic modeling of the relation between water level and streamflow at a hydrological monitoring station using information about the physical characteristics of the channel. This relation between water level and streamflow, known as the rating curve, is the basis for calculating streamflow time series from the water level time series measured at hydrological monitoring stations. We explored the interaction of different uncertainty sources on rating curve estimation at two Swedish stations and found that rating curves could be modeled with high confidence (i.e., low uncertainty) using only three observations for either low flows or low and medium flows. Since such flow conditions occur often and are easy to measure (at least relative to the rare and hard-to-measure high flows) our framework has an advantage over traditional approaches by potentially allowing for more rapid rating curve estimation.

  • Norris Lam (et al.).

    Hydraulic models can be useful tools for developing reliable rating curves, however, uncertainties in the input measurements can have implications for the model results. In this study, we investigate the impact of uncertain input field measurements (i.e. stream channel topography, water surface slope, vegetation density, stage, and discharge) on rating curves generated with a physically-based hydraulic model. This is the first-time measurement uncertainties have been assessed with the hydraulic model and we demonstrate the method at a regularly monitored catchment in central Sweden. The results show that the modeling approach, calibrated with three gauging measurements, acquired at low to median flows, was able to generate rating curves with relatively constrained uncertainty for the highest observed stage (i.e. -12% and +46%) when all uncertainty sources were accounted for. These results suggest that this modeling approach could be applied to quickly develop reliable rating curves and simultaneously estimate the uncertainty in the rating curves. 

  • 2017. Norris Lam, Jason W. Kean, Steve W. Lyon. Hydrology Research 48 (4), 981-996

    The rating curve enables the translation of water depth into stream discharge through a reference cross-section. This study investigates coupling national scale airborne laser scanning (ALS) and acoustic Doppler current profiler (ADCP) bathymetric survey data for generating stream rating curves. A digital terrain model was defined from these data and applied in a physically based 1-D hydraulic model to generate rating curves for a regularly monitored location in northern Sweden. Analysis of the ALS data showed that overestimation of the streambank elevation could be adjusted with a root mean square error (RMSE) block adjustment using a higher accuracy manual topographic survey. The results of our study demonstrate that the rating curve generated from the vertically corrected ALS data combined with ADCP data had lower errors (RMSE = 0.79 m3/s) than the empirical rating curve (RMSE = 1.13 m3/s) when compared to streamflow measurements. We consider these findings encouraging as hydrometric agencies can potentially leverage national-scale ALS and ADCP instrumentation to reduce the cost and effort required for maintaining and establishing rating curves at gauging station sites similar to the Röån River.

  • 2015. Norris Lam (et al.). Journal of the American Water Resources Association 51 (5), 1211-1220

    This brief pilot study implements a camera-based laser scanning system that potentially offers a viable, cost-effective alternative to traditional terrestrial laser scanning (TLS) and LiDAR equipment. We adapted a low-cost laser ranging system (SICK LSM111) to acquire area scans of the channel and bed for a temporarily diverted stream. The 5mx2m study area was scanned at a 4mm point spacing which resulted in a point cloud density of 5,600 points/m(2). A local maxima search algorithm was applied to the point cloud and a grain size distribution of the stream bed was extracted. The 84th and 90th percentiles of this distribution, which are commonly used to characterize channel roughness, were 90mm and 109mm, respectively. Our example shows the system can resolve both large-scale geometry (e.g., bed slope and channel width) and small-scale roughness elements (e.g., grain sizes between about 30 and 255mm) in an exposed stream channel thereby providing a resolution adequate for the estimation of ecohydraulic roughness parameters such as Manning's n. While more work is necessary to refine our specific field-deployable system's design, these initial results are promising in particular for those working on a limited or fixed budget. This opens up a realm of laser scanning applications and monitoring strategies for water resources that may not have been possible previously due to cost limitations associated with traditional TLS systems.

  • 2015. Steve W. Lyon (et al.). Water 7 (4), 1324-1339

    This pilot study explores the potential of using low-resolution (0.2 points/m(2)) airborne laser scanning (ALS)-derived elevation data to model stream rating curves. Rating curves, which allow the functional translation of stream water depth into discharge, making them integral to water resource monitoring efforts, were modeled using a physics-based approach that captures basic geometric measurements to establish flow resistance due to implicit channel roughness. We tested synthetically thinned high-resolution (more than 2 points/m(2)) ALS data as a proxy for low-resolution data at a point density equivalent to that obtained within most national-scale ALS strategies. Our results show that the errors incurred due to the effect of low-resolution versus high-resolution ALS data were less than those due to flow measurement and empirical rating curve fitting uncertainties. As such, although there likely are scale and technical limitations to consider, it is theoretically possible to generate rating curves in a river network from ALS data of the resolution anticipated within national-scale ALS schemes (at least for rivers with relatively simple geometries). This is promising, since generating rating curves from ALS scans would greatly enhance our ability to monitor streamflow by simplifying the overall effort required.

  • Article Laser vision
    2015. A. A. Harpold (et al.). Hydrology and Earth System Sciences 19 (6), 2881-2897

    Observation and quantification of the Earth's surface is undergoing a revolutionary change due to the increased spatial resolution and extent afforded by light detection and ranging (lidar) technology. As a consequence, lidar-derived information has led to fundamental discoveries within the individual disciplines of geomorphology, hydrology, and ecology. These disciplines form the cornerstones of critical zone (CZ) science, where researchers study how interactions among the geosphere, hydrosphere, and biosphere shape and maintain the 'zone of life', which extends from the top of unweathered bedrock to the top of the vegetation canopy. Fundamental to CZ science is the development of transdisciplinary theories and tools that transcend disciplines and inform other's work, capture new levels of complexity, and create new intellectual outcomes and spaces. Researchers are just beginning to use lidar data sets to answer synergistic, transdisciplinary questions in CZ science, such as how CZ processes co-evolve over long timescales and interact over shorter timescales to create thresholds, shifts in states and fluxes of water, energy, and carbon. The objective of this review is to elucidate the transformative potential of lidar for CZ science to simultaneously allow for quantification of topographic, vegetative, and hydrological processes. A review of 147 peer-reviewed lidar studies highlights a lack of lidar applications for CZ studies as 38 % of the studies were focused in geomorphology, 18 % in hydrology, 32 % in ecology, and the remaining 12 % had an interdisciplinary focus. A handful of exemplar transdisciplinary studies demonstrate lidar data sets that are well-integrated with other observations can lead to fundamental advances in CZ science, such as identification of feedbacks between hydrological and ecological processes over hillslope scales and the synergistic co-evolution of landscape-scale CZ structure due to interactions amongst carbon, energy, and water cycles. We propose that using lidar to its full potential will require numerous advances, including new and more powerful open-source processing tools, exploiting new lidar acquisition technologies, and improved integration with physically based models and complementary in situ and remote-sensing observations. We provide a 5-year vision that advocates for the expanded use of lidar data sets and highlights subsequent potential to advance the state of CZ science.

Show all publications by Norris Lam at Stockholm University

Last updated: December 3, 2020

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