A Satellite Data-Driven, Client-Server Decision Support Application for Agricultural Water Resources Management

Water cycle extremes such as droughts and floods present a challenge for water managers and for policy makers responsible for the administration of water supplies in agricultural regions. In addition to the inherent uncertainties associated with forecasting extreme weather events, water planners need to anticipate water demands and water user behavior in a typical circumstances. This requires the use decision support systems capable of simulating agricultural water demand with the latest available data. Unfortunately, managers from local and regional agencies often use different datasets of variable quality, which complicates coordinated action. In previous work we have demonstrated novel methodologies to use satellite-based observational technologies, in conjunction with hydro-economic models and state of the art data assimilation methods, to enable robust regional assessment and prediction of drought impacts on agricultural production, water resources, and land allocation. These methods create an opportunity for new, cost-effective analysis tools to support policy and decision-making over large spatial extents. The methods can be driven with information from existing satellite-derived operational products, such as the Satellite Irrigation Management Support system (SIMS) operational over California, the Cropland Data Layer (CDL), and using a modified light-use efficiency algorithm to retrieve crop yield from the synergistic use of MODIS and Landsat imagery. Here we present an integration of this modeling framework in a client-server architecture based on the Hydra platform. Assimilation and processing of resource intensive remote sensing data, as well as hydrologic and other ancillary information occur on the server side. This information is processed and summarized as attributes in water demand nodes that are part of a vector description of the water distribution network. With this architecture, our decision support system becomes a light weight 'app' that connects to the server to retrieve the latest information regarding water demands, land use, yields and hydrologic information required to run different management scenarios. Furthermore, this architecture ensures all agencies and teams involved in water management use the same, up-to-date information in their simulations

Use of Urban Tree Canopy Assessments by Localities in the Chesapeake Bay Watershed

Urban tree canopy (UTC) in the Chesapeake Bay watershed (CBW) provides numerous environmental, economic, and societal benefits. UTC assessments use remote sensing technology to deliver a comprehensive spatial snapshot of a locality’s existing UTC. Because UTC assessments delineate the extent and location of tree canopy cover in the context of other land covers (including plantable space), they are important for establishing tree canopy goals, creating and implementing strategies to achieve those goals, and monitoring progress. Over the past decade, UTC assessments have been completed for numerous localities in the CBW as a result of the Chesapeake Bay Program identifying UTC as a key strategy for Bay restoration. Our research investigated the prevalence of UTC assessments within the CBW and studied how localities are using them. We conducted two surveys: 1) a pilot survey of Virginia localities that received UTC assessments as part of the Virginia UTC project; and 2) a comprehensive survey of all 101 localities in the CBW with populations over 2,500 for which a UTC assessment existed as of May 2013. Surprisingly, 33% of localities in the CBW reported being unaware that a UTC assessment had been performed for their jurisdiction. In general, counties and cities were more likely to be aware of the assessments than were towns (or their jurisdictional equivalent). Most localities that were aware of their assessment were using it in some manner for urban forest planning and management; however, the most frequent activities were also the most basic uses, including: educating officials or citizens about the importance of tree canopy (57%), providing a baseline for evaluating progress toward UTC goals (49%), creating a locality-wide tree canopy goal (47%), planning and prioritizing tree plantings (45%), and informing larger initiatives (43%). All other uses of the assessments (i.e., specialized uses) were reported by 33% or fewer of the CBW localities. Our findings point to the need for outreach to local governments about UTC assessments and their potential uses, particularly in light of increasing emphasis in the CBW on managing urban forests and optimizing UTC as a Bay restoration strategy

A new global river network database for macroscale hydrologic modeling

Coarse-resolution (upscaled) river networks are critical inputs for runoff routing in macroscale hydrologic models. Recently, Wu et al. (2011) developed a hierarchical dominant river tracing (DRT) algorithm for automated extraction and spatial upscaling of river networks using fine-scale hydrography inputs. We applied the DRT algorithms using combined HydroSHEDS and HYDRO1k global fine-scale hydrography inputs and produced a new series of upscaled global river network data at multiple (1/16° to 2°) spatial resolutions. The new upscaled results are internally consistent and congruent with the baseline fine-scale inputs and should facilitate improved regional to global scale hydrologic simulations

Future Decreases in Freezing Days across North America

This study used air temperatures from a suite of regional climate models participating in the North American Climate Change Assessment Program (NARCCAP) together with two atmospheric reanalysis datasets to investigate changes in freezing days (defined as days with daily average temperature below freezing) likely to occur between 30-yr baseline (1971–2000) and midcentury (2041–70) periods across most of North America. Changes in NARCCAP ensemble mean winter temperature show a strong gradient with latitude, with warming of over 4°C near Hudson Bay. The decline in freezing days ranges from less than 10 days across north-central Canada to nearly 90 days in the warmest areas of the continent that currently undergo seasonally freezing conditions. The area experiencing freezing days contracts by 0.9–1.0 × 106 km2 (5.7%–6.4% of the total area). Areas with mean annual temperature between 2° and 6°C and a relatively low rate of change in climatological daily temperatures (−) near the time of spring thaw will encounter the greatest decreases in freezing days. Advances in the timing of spring thaw will exceed the delay in fall freeze across much of the United States, with the reverse pattern likely over most of Canada

Projected Climate Change Impacts on the Hydrology and Temperature of Pacific Northwest Rivers

A dominant river-tracing-based streamflow and temperature (DRTT) model was developed by coupling stream thermal dynamics with a source-sink routing model. The DRTT model was applied using 1/16 degree (similar to 6 km) resolution gridded daily surface meteorology inputs over a similar to 988,000 km(2) Pacific Northwest (PNW) domain to produce regional daily streamflow and temperature simulations from 1996 to 2005. The DRTT results showed favorable performance for simulation of daily stream temperature (mean R-2 = 0.72 and root-mean-square error = 2.35 degrees C) and discharge (mean R-2 = 0.52 and annual relative error 14%) against observations from 12 PNW streams. The DRTT was then applied with a macroscale hydrologic model to predict streamflow and temperature changes under historical (1980s) and future (2020s, 2040s, and 2080s) climate change scenarios (IPCC AR4) as they may affect current and future patterns of freshwater salmon habitat and associated productivity of PNW streams. The model projected a 3.5% decrease in mean annual streamflow for the 2020s and 0.6% and 5.5% increases for the 2040s and 2080s, respectively, with projected increase in mean annual stream temperatures from 0.55 degrees C (2020s) to 1.68 degrees C (2080s). However, summer streamflow decreased from 19.3% (2020s) to 30.3% (2080s), while mean summer stream temperatures warmed from 0.92 degrees C to 2.10 degrees C. The simulations indicate that projected climate change will have greater impacts on snow dominant streams, with lower summer streamflows and warmer summer stream temperature changes relative to transient and rain dominant regimes. Lower summer flows combined with warmer stream temperatures suggest a future with widespread increased summertime thermal stress for coldwater fish in the PNW region

Comparison of boreal ecosystem model sensitivity to variability in climate and forest site parameters

Ecosystem models are useful tools for evaluating environmental controls on carbon and water cycles under past or future conditions. In this paper we compare annual carbon and water fluxes from nine boreal spruce forest ecosystem models in a series of sensitivity simulations. For each comparison, a single climate driver or forest site parameter was altered in a separate sensitivity run. Driver and parameter changes were prescribed principally to be large enough to identify and isolate any major differences in model responses, while also remaining within the range of variability that the boreal forest biome may be exposed to over a time period of several decades. The models simulated plant production, autotrophic and heterotrophic respiration, and evapotranspiration (ET) for a black spruce site in the boreal forest of central Canada (56°N). Results revealed that there were common model responses in gross primary production, plant respiration, and ET fluxes to prescribed changes in air temperature or surface irradiance and to decreased precipitation amounts. The models were also similar in their responses to variations in canopy leaf area, leaf nitrogen content, and surface organic layer thickness. The models had different sensitivities to certain parameters, namely the net primary production response to increased CO2 levels, and the response of soil microbial respiration to precipitation inputs and soil wetness. These differences can be explained by the type (or absence) of photosynthesis-CO2 response curves in the models and by response algorithms of litter and humus decomposition to drying effects in organic soils of the boreal spruce ecosystem. Differences in the couplings of photosynthesis and soil respiration to nitrogen availability may also explain divergent model responses. Sensitivity comparisons imply that past conditions of the ecosystem represented in the models\u27 initial standing wood and soil carbon pools, including historical climate patterns and the time since the last major disturbance, can be as important as potential climatic changes to prediction of the annual ecosystem carbon balance in this boreal spruce forest

Reducing Interanalyst Variability in Photovoltaic Degradation Rate Assessments

The economic return on investment of a commercial photovoltaic system depends greatly on its performance over the long term and, hence, its degradation rate. Many methods have been proposed for assessing system degradation rates from outdoor performance data. However, comparing reported values from one analyst and research group to another requires a common baseline of performance; consistency between methods and analysts can be a challenge. An interlaboratory study was conducted involving different volunteer analysts reporting on the same photovoltaic performance data using different methodologies. Initial variability of the reported degradation rates was so high that analysts could not come to a consensus whether a system degraded or not. More consistent values are received when written guidance is provided to each analyst. Further improvements in analyst variance was accomplished by using the free open-source software RdTools, allowing a reduction in variance between analysts by more than two orders of magnitude over the first round, where multiple analysis methods are allowed. This article highlights many pitfalls in conducting 'routine' degradation analysis, and it addresses some of the factors that must be considered when comparing degradation results reported by different analysts or methods

Climate, Hydrologic Disturbance, and Succession: Drivers of Floodplain Pattern

Floodplains are among the world\u27s most threatened ecosystems due to the pervasiveness of dams, levee systems, and other modi. cations to rivers. Few unaltered floodplains remain where we may examine their dynamics over decadal time scales. Our study provides a detailed examination of landscape change over a 60-year period ( 1945 - 2004) on the Nyack floodplain of the Middle Fork of the Flathead River, a free-flowing, gravel-bed river in northwest Montana, USA. We used historical aerial photographs and airborne and satellite imagery to delineate habitats ( i.e., mature forest, regenerative forest, water, cobble) within the. oodplain. We related changes in the distribution and size of these habitats to hydrologic disturbance and regional climate. Results show a relationship between changes in. oodplain habitats and annual flood magnitude, as well as between hydrology and the cooling and warming phases of the Pacific Decadal Oscillation (PDO). Large magnitude floods and greater frequency of moderate floods were associated with the cooling phases of the PDO, resulting in a floodplain environment dominated by extensive restructuring and regeneration of floodplain habitats. Conversely, warming phases of the PDO corresponded with decreases in magnitude, duration, and frequency of critical flows, creating a floodplain environment dominated by late successional vegetation and low levels of physical restructuring. Over the 60-year time series, habitat change was widespread throughout the floodplain, though the relative abundances of the habitats did not change greatly. We conclude that the long- and short-term interactions of climate, floods, and plant succession produce a shifting habitat mosaic that is a fundamental attribute of natural. oodplain ecosystems

Boreal forest CO2 exchange and evapotranspiration predicted by nine ecosystem process models: Intermodel comparisons and relationships to field measurements

Nine ecosystem process models were used to predict CO2 and water vapor exchanges by a 150-year-old black spruce forest in central Canada during 1994–1996 to evaluate and improve the models. Three models had hourly time steps, five had daily time steps, and one had monthly time steps. Model input included site ecosystem characteristics and meteorology. Model predictions were compared to eddy covariance (EC) measurements of whole-ecosystem CO2exchange and evapotranspiration, to chamber measurements of nighttime moss-surface CO2release, and to ground-based estimates of annual gross primary production, net primary production, net ecosystem production (NEP), plant respiration, and decomposition. Model-model differences were apparent for all variables. Model-measurement agreement was good in some cases but poor in others. Modeled annual NEP ranged from −11 g C m−2 (weak CO2source) to 85 g C m−2 (moderate CO2 sink). The models generally predicted greater annual CO2sink activity than measured by EC, a discrepancy consistent with the fact that model parameterizations represented the more productive fraction of the EC tower “footprint.” At hourly to monthly timescales, predictions bracketed EC measurements so median predictions were similar to measurements, but there were quantitatively important model-measurement discrepancies found for all models at subannual timescales. For these models and input data, hourly time steps (and greater complexity) compared to daily time steps tended to improve model-measurement agreement for daily scale CO2 exchange and evapotranspiration (as judged by root-mean-squared error). Model time step and complexity played only small roles in monthly to annual predictions

Terrestrial hydrological controls on land surface phenology of African savannas and woodlands

This paper presents a continental-scale phenological analysis of African savannas and woodlands. We apply an array of synergistic vegetation and hydrological data records from satellite remote sensing and model simulations to explore the influence of rainy season timing and duration on regional land surface phenology and ecosystem structure. We find that (i) the rainy season onset precedes and is an effective predictor of the growing season onset in African grasslands. (ii) African woodlands generally have early green-up before rainy season onset and have a variable delayed senescence period after the rainy season, with this delay correlated nonlinearly with tree fraction. These woodland responses suggest their complex water use mechanisms (either from potential groundwater use by relatively deep roots or stem-water reserve) to maintain dry season activity. (iii) We empirically find that the rainy season length has strong nonlinear impacts on tree fractional cover in the annual rainfall range from 600 to 1800 mm/yr, which may lend some support to the previous modeling study that given the same amount of total rainfall to the tree fraction may first increase with the lengthening of rainy season until reaching an “optimal rainy season length,” after which tree fraction decreases with the further lengthening of rainy season. This nonlinear response is resulted from compound mechanisms of hydrological cycle, fire, and other factors. We conclude that African savannas and deciduous woodlands have distinctive responses in their phenology and ecosystem functioning to rainy season. Further research is needed to address interaction between groundwater and tropical woodland as well as to explicitly consider the ecological significance of rainy season length under climate change