Advancements in web‐mapping tools for land use and marine spatial planning

Land use and marine spatial planning processes are increasingly supported by systematic assessment techniques, particularly by multi‐criteria spatial analysis methods. This has been facilitated by the growing release and uptake of web‐mapping tools, which contribute to transparent, consistent, and informed planning processes and decisions. This article reviews the usability, functionality, and applicability of contemporary planning web‐mapping tools to identify the state‐of‐the‐art and future prospects. The review reveals that interfaces are increasingly available and intuitively applicable by non‐specialized users. Basic map navigation and data querying functionality is being expanded to incorporate advanced map‐making and online data geoprocessing capabilities that enable deriving new data and insights. However, the majority of published planning web tools are one‐off solutions, and a disconnect between research and practice is rendering many of these inaccessible or obsolete. Despite the significant progress made in advancing their provision in the last decade, there is a need for developing transferable interfaces that are maintained beyond project end dates, for them to effectively and consistently support planning processes.     

Zonal versus meridional velocity variance in satellite observations and realistic and idealized ocean circulation models

Global, high-quality, satellite-based observation of oceanic currents over the past 13 years has revealed ubiquitous quasi-horizontal eddies in the mesoscale (tens to hundreds of kilometers), confirming the view of a highly turbulent ocean suggested by observational programs in the 1970s. Idealized quasigeostrophic turbulence models suggest mesoscale turbulent flow can vary between isotropic, and highly anisotropic zonal jets. Here we compare the zonal and meridional velocity variance from satellite altimetry. We find that, for an unexplained reason and despite the chaotic nature of turbulence, the surface flow is organized into mesoscale patches where either zonal or meridional velocity variance dominates. The patches persist over 13 years, much longer than the turbulent timescale of a few months. Implications include potentially highly anisotropic redistribution of tracers by the mesoscale flow. Zonally averaged velocity variances reveal a slight preference for meridional over zonal velocity variance. Realistic primitive equation models succeed in reproducing both the patchy structure in local preference for either zonal or meridional velocity variance, and the zonally averaged preference for meridional variance. Idealized models of fully developed, quasigeostrophic turbulence fail in both regards.     

Adequacy of satellite derived rainfall data for stream flow modeling

Floods are the most common and widespread climate-related hazard on Earth. Flood forecasting can reduce the death toll associated with floods. Satellites offer effective and economical means for calculating areal rainfall estimates in sparsely gauged regions. However, satellite-based rainfall estimates have had limited use in flood forecasting and hydrologic stream flow modeling because the rainfall estimates were considered to be unreliable. In this study we present the calibration and validation results from a spatially distributed hydrologic model driven by daily satellite-based estimates of rainfall for sub-basins of the Nile and Mekong Rivers. The results demonstrate the usefulness of remotely sensed precipitation data for hydrologic modeling when the hydrologic model is calibrated with such data. However, the remotely sensed rainfall estimates cannot be used confidently with hydrologic models that are calibrated with rain gauge measured rainfall, unless the model is recalibrated. G. Artan, J. L. Smith and K. Asante – work performed under USGS contract 03CRCN0001.     

Intercomparison and validation of snow albedo parameterization schemes in climate models

Snow albedo is known to be crucial for heat exchange at high latitudes and high altitudes, and is also an important parameter in General Circulation Models (GCMs) because of its strong positive feedback properties. In this study, seven GCM snow albedo schemes and a multiple linear regression model were intercompared and validated against 59 years of in situ data from Svalbard, the French Alps and six stations in the former Soviet Union. For each site, the significant meteorological parameters for modeling the snow albedo were identified by constructing the 95% confidence intervals. The significant parameters were found to be: temperature, snow depth, positive degree day and a dummy of snow depth, and the multiple linear regression model was constructed to include these. Overall, the intercomparison showed that the modeled snow albedo varied more than the observed albedo for all models, and that the albedo was often underestimated. In addition, for several of the models, the snow albedo decreased at a faster rate or by a greater magnitude during the winter snow metamorphosis than the observed albedo. Both the temperature dependent schemes and the prognostic schemes showed shortcomings.     

Are spatial patterns of soil moisture at plot scales generalisable across catchments,climates, and other characteristics? A synthesis of synoptic soil moisture across the Mid-Atlantic

The spatial variation of soil moisture over very small areas (<100 m²) can have nonlinear impacts on cycling and flux rates resulting in bias if it is not considered, but measuring this variation is difficult over extensive temporal and spatial scales. Most studies examining spatial variation of soil moisture were conducted at hillslope (0.01 km²) to multi-catchment spatial scales (1000 km²). They found the greatest variation at mid wetness levels and the smallest variation at wet and dry wetness levels forming a concave down relationship. There is growing evidence that concave down relationships formed between spatial variation of soil moisture and average soil moisture are consistent across spatial scales spanning several orders of magnitude, but more research is needed at very small, plot scales (<100 m²). The goal of this study was to characterise spatial variation in shallow soil moisture at the plot scale by relating the mean of measurements collected in a plot to the standard deviation (SD). We combined data from a previous study with thousands of new soil moisture measurements from 212 plots in eight catchments distributed across the US Mid-Atlantic Region to (1) test for a generalisable mean–SD relationship at plot scales, (2) characterise how landcover, land use, season, and hillslope position contribute to differences in mean–SD relationships, and (3) use these generalised mean–SD relationships to quantify their impacts on catchment scale nitrification and denitrification potential. Our study found that 98% of all measurements formed a generalised mean–SD relationship like those observed at hillslope and catchment spatial scales. The remaining 2% of data comprised a mean–SD relationship with greater spatial variation that originated from two riparian plots reported in a previous study. Incorporating the generalised mean–SD relationship into estimates of nitrification and denitrification potential revealed strong bias that was even greater when incorporating mean–SD observations from the two riparian plots with significantly greater spatial variation.     

The impact of wildfire on baseflow recession rates in California

The effect of wildfire on peak streamflow and annual water yield has been investigated empirically in numerous studies. The effect of wildfire on baseflow recession rates, in contrast, is not well documented. The objective of this paper was to quantify the effect of wildfire on baseflow recession rates in California for both individual watersheds and for all the study watersheds collectively. Two additional variables, antecedent groundwater storage and potential evapotranspiration, were also investigated for their effect on baseflow recession rates and postfire baseflow recession rate response. Differences between prefire and postfire baseflow recession rates were modeled statistically in 8 watersheds using a mixed statistical model that accounted for fixed and random effects. For the all‐watershed model, antecedent groundwater storage, potential evapotranspiration, and wildfire were each found to be significant controls on baseflow recession rates. Wildfire decreased baseflow recession rates 52.5% (37.6% to 66.0%), implying that postfire reductions in above‐ground vegetation (e.g., decreased interception, decreased evapotranspiration) were a stronger control on baseflow recession rate change than hydrophobicity. At an individual watershed scale, baseflow recession rate response to wildfire was found to be sensitive to intraannual differences in antecedent groundwater storage in 2 watersheds, with the effect of wildfire on baseflow recession rates being greater with lower levels of antecedent groundwater storage. Examination of burn severity for a subset of the study watersheds pointed to riparian zone burn severity as a potential primary control on postfire recession rate change. This study demonstrates that wildfire may have a substantial impact on fluxes to and from groundwater storages, altering the rate at which baseflow recedes.